Transcriptional analysis reveals a markedly reduced expression of the voltage-dependent calcium channel α2δ1 subunit in canine prostate cancer compared to benign prostatic hyperplasia

Transcriptional analysis reveals a markedly reduced expression of the voltage-dependent calcium channel α2δ1 subunit in canine prostate cancer compared to benign prostatic hyperplasia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Transcriptional analysis reveals a markedly reduced expression of the voltage-dependent calcium channel α2δ1 subunit in canine prostate cancer compared to benign prostatic hyperplasia Maciej Zacharski, Maciej Ugorski, Przemysław Prządka, Stanisław Dzimira, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6719203/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Oct, 2025 Read the published version in BMC Veterinary Research → Version 1 posted 3 You are reading this latest preprint version Abstract Background Despite its low incidence, the aggressive nature and high metastatic potential of canine prostate cancer (PC) make it a serious problem in veterinary medicine. However, knowledge of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC is still limited. Using high-throughput methods, many PC-related genes have been identified by comparing gene expression profiles in malignant and non-malignant prostate tissues. In these studies, the reference group containing both normal and hyperplastic prostate tissues specimens was compared to the group composed of cancerous tissues specimens. However, this approach does not allow the exclusion of inflammation-related genes from those directly involved in PC development and progression. Furthermore, the RNA-Seq and microarray data were not validated by additional analyses, including immunohistochemistry (IHC). Therefore, to identify PC-specific genes, a comparative analysis of gene expression profiles in PC and benign prostate hyperplasia (BPH) tissue samples was performed using RNA-Seq, and the results were validated by Nanostring technology, Western blotting (WB) and IHC. Results Using the NanoString assay, significant differences were identified for 12 genes, of which ASPM, CLU, TOP2A, TSPAN8/TM4SF3 and HELLS were overexpressed in PC compared to BPH, while ATP6V0A4, CACNA2D1, CLDN10, GOLGA4, KLK2, NKX3.1 and SERPINB6 were downregulated in PC. Validation of the differentially expressed genes (DEGs) at the protein level using WB and IHC revealed a highly decreased expression of the voltage-gated calcium channel subunit alpha-2 delta-1 (α2δ1), encoded by the CACNA2D1 gene, in PC samples compared to BPH. Conclusions Our findings make α2δ1 protein a novel and promising diagnostic biomarker to differentiate PC from BPH. canine prostate cancer benign prostate hyperplasia gene-expression profiling calcium channel subunit α2δ1 CACNA2D1 Figures Figure 1 Figure 2 Figure 3 1. Background Dogs are one of the few species, other than humans, that develop spontaneous prostate cancer (PC) [ 1 ]. However, unlike in humans, canine PC is a rare disease, affecting only 0.2–0.6% of dogs [ 2 – 4 ]. It is characterized by late onset, androgen independence, and is generally highly aggressive and metastatic, with the bones and lungs being the primary sites of metastasis [ 5 – 9 ], making it comparable to human castration-resistant prostate cancer (CRPC) [ 10 ]. Therefore, given the range of similarities between prostate cancer in dogs and humans, dog represent a relevant model for the human disease [ 6 , 11 ], and preclinical studies of new diagnostic and therapeutic approaches in dogs may benefit both species affected by prostate cancer. To date, our knowledge of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC is very limited. Using IHC and the data on differential gene expression between tumor and non-tumor tissues in human PC, only a few changes in the expression of specific markers/proteins have so far been reported in canine PC compared to normal and hyperplastic canine prostate. Similar to findings in humans, decresed expression of Nkx3.1 and overexpression of C-MYC [ 12 , 13 ], reduced expression of PTEN, p53, and the androgen receptor (AR), as well as increased expression of MDM2 [ 14 , 15 ], have been observed. Likewise, elevated levels of HER-2, mTOR, and eIF4E proteins have been detected in canine PC compared with normal prostate [ 16 – 18 ]. In addition, loss of membranous E-cadherin, together with cytoplasmic and nuclear β-catenin staining, suggests that activation of the WNT/β-catenin pathway may play a role in the pathogenesis of canine PC. Despite the advantages of this approach, which strongly support the usefulness of canine PC as a model for studying human PC, these studies have a major limitation in that they cannot identify genes specifically involved in the development and progression of canine PC. Such limitations can be overcome using high-throughput methods such as whole-transcriptome RNA sequencing (RNA-Seq) or microarray profiling, which provide information on the expression of thousands of genes simultaneously. RNA-Seq revealed clear differences in gene expression profiles between non-malignant and malignant canine prostate tissue samples [ 19 , 20 ]. Furthermore, most of these DEGs were mapped to at least one of 49 biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), suggesting that these pathways are deregulated in canine PC. Based on these data, the DEGs were grouped into five super-pathways named Inflammatory Response and Cytokines, Regulation of Immune System and Cell Death, Cell Cycle, Phagosome and Autophagy, and Cell Surface and PI3K Signaling. With this approach, a set of 16 DEGs representing the most interesting potential biomarkers was proposed, half of which have already been found to be associated with PC [ 20 ]. Similarly, using the microarray technique, 33 genes with significantly different expressions between PC and benign prostate tissues were identified [ 21 ]. According to this data, AR-regulated genes and neuroendocrine-associated genes were downregulated in cancerous tissues. However, most previous reports lacked specific information on DEGs between PC and BPH tissues, as in these studies both normal and hyperplastic prostatic tissues were combined in the single control group. In the present study, only BPH tissue samples were used for comparison. This approach, aimed at identifying PC-specific genes, has a major advantage: it enables the exclusion of inflammation-related genes. Inflammation is one of the hallmarks of cancer [ 22 , 23 ], and multiple lines of evidence link the pathogenesis of BPH with prostatic inflammation [ 24 , 25 ]. Here, we compared the transcriptomes of canine BPH and PC to identify genes and their protein products that may serve as candidate diagnostic biomarkers for distinguishing between these two conditions. As noted above, the current understanding of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC remains limited and is still at an early exploratory stage, particularly in comparison with human PC. Consequently, the identification of canine PC-specific genes presents new opportunities to advance the field through the integration of molecular and cell biology approaches. 2. Methods 2.1. Tissue specimens and histochemistry The study was conducted on prostate specimens collected from 15 dogs with PC and 7 dogs with BPH between 2017 and 2023. Dogs underwent surgery (prostate coagulation, prostatectomy, prostate biopsy, n=12) or euthanasia (n=6) at the Department and Clinic of Surgery, Faculty of Veterinary Medicine, University of Environmental and Life Sciences, Wroclaw, Poland. The remaining samples (n=4) were collected during the necropsy of animals performed within 24 hours of the animals’ demise. All owners agreed to the necropsy. Dogs undergoing surgical treatment or euthanasia underwent computed tomography (CT) of the thorax and abdomen to assess the presence of metastatic lesions. According to owner reports, these dogs had no history of chronic systemic diseases and were not receiving any treatment prior to sample collection. Breed, age, neutering status. and TNM classification are presented in Table 1 . For the dogs from which material was collected post-mortem, information on neutering status and health history was unavailable, which is a limitation of the study . Table 1. Specimen characteristics Sample ID Breed Age (years) Neutering Status Collection Procedure HPDx TNM classification Measurements performed RNA-Seq Nanostring WB IHC Dog 1 N/A N/A N/A necropsy BPH N/A No Yes Yes Yes Dog 2 N/A N/A N/A necropsy BPH N/A No Yes No Yes Dog 3 N/A N/A N/A necropsy BPH N/A Yes Yes Yes Yes Dog 4 N/A N/A N/A necropsy BPH N/A Yes Yes Yes No Dog 5 Mixed 12 No surgery BPH T0N0M0 Yes Yes Yes Yes Dog 6 Mixed 8 No surgery BPH T0N0M0 No Yes Yes No Dog 7 Entlebucher Mount. Dog 7 No surgery BPH T0N0M0 No Yes Yes Yes Dog 8 Mixed 12 Yes surgery PC T2N1M0 No Yes No No Dog 9 Mixed 13 Yes surgery PC T1N0M0 No Yes Yes Yes Dog 10 Mixed 15 Yes euthanasia PC T2N1M1 Yes Yes Yes No Dog 11 Mixed - Yes euthanasia PC T3N1M1 No Yes Yes No Dog 12 French Bulldog 8 No euthanasia PC T2N1M1 No Yes Yes Yes Dog 13 Labrador Retriever 10 No surgery PC T2N1M0 No Yes No No Dog 14 Maltese Dog 10 Yes surgery PC T3N1M1 No Yes Yes No Dog 15 Mixed 8 Yes surgery PC T1N0M0 No Yes Yes Yes Dog 16 Mixed 12.5 Yes surgery PC T3N1M0 No Yes No Yes Dog 17 Mixed 12.5 No euthanasia PC T3N1M0 No Yes No Yes Dog 18 Staffordshire Bull Terrier 8 No surgery PC T1N0M0 Yes Yes No Yes Dog 19 Boxer 8 No surgery PC T1N0M0 No Yes No Yes Dog 20 Mixed - No euthanasia PC T3N1M0 No Yes No Yes Dog 21 Poodle 13 Yes euthanasia PC T3N1M1 No Yes No Yes Dog 22 Mixed 5,5 Yes surgery PC T1N0M0 No No Yes Yes HPDx - Histopathological Diagnosis, WB – Western blotting, IHC – immunohistochemistry, TNM – TNM Classification of Malignant Tumors For the histochemistry, the material was fixed in buffered 7% formalin and embedded in paraffin. The 3-µm-thick cut sections were mounted on Superfrost Plus slides, deparaffinized in xylene, and rehydrated to distilled water. The samples were then incubated in Mayer’s hematoxylin for 3 minutes and washed with three changes of tap water or until blue stopped coming off the slides. Following this, the slides were counterstained in alcoholic eosin for 10 seconds without rinsing, dehydrated through two changes of 95% ethanol, two changes of 100% ethanol, two changes of acetone, and cleared in two changes of xylene (10 seconds each). Finally, the slides were mounted with cover slides [26]. 2.2. RNA isolation Total RNA was purified from 30 milligrams of tissue using the RNeasy Fibrous Tissue Mini Kit (Qiagen) according to the manufacturer’s instructions. The protocol included on-column DNase digestion to remove genomic DNA. The purity and concentration of the RNA were assessed using a DS-11 FX spectrophotometer (Denovix), and its quality was assessed by Experion microchip electrophoresis (Biorad). All RNA samples met the quality control thresholds required for downstream analysis. Samples used for RNA-Seq had a mean RNA Integrity Number (RIN) of 8.4 (range: 7.6–9.9) and a mean concentration of 723 µg/µl (range: 188–1182 µg/µl). For the Nanostring assay, the mean RIN was 8.0 (range: 5.4–9.6) with a mean concentration of 1064.4 µg/µl (range: 118–2063 µg/µl) ( Additional file 1. Supplementary Figure 1 ). 2.3. RNA sequencing The library was prepared using 350 ng of total RNA and the QuantSeq 3’ mRNA library preparation FWD kit (Lexogen) according to the manufacturer’s instructions. Briefly, the first strand of cDNA was synthesized, RNA was removed, and the second strand was synthesized using Unique Molecular Identifiers (UMI). Library preparation encompassed 13 cycles of PCR enrichment (initial denaturation: 98 °C, 30 sec.; 13 cycles of 98 °C for 10 sec, 65 °C for 20 sec, 72 °C for 30 sec; final elongation: 72 °C, 1 min) followed by purification of the amplified product. Subsequent to this, a quality control assessment of the libraries was conducted using the Bioanalyser High Sensitivity DNA chip (Agilent Technologies). Thereafter, the libraries were quantitatively assessed by qPCR in accordance with the Illumina protocol. This facilitated the equimolar pooling of the libraries, which were subsequently sequenced on the NextSeq500 (Illumina) instrument using single reads of 75 base pairs on a high-output configuration. Reads trimmed and filtered with Trimmomatic [27] were mapped to the C. lupus familiaris genome version CanFam3.1, annotation release 101, (GeneBank accession: GCF_000002285.3) using STAR v2.7.6a aligner [28]. RSEM v1.2.28 [29] was used to calculate gene count with –rsem-calculate-expression option. The gene counts were made into a count table in R, where genes with no count and low count genes were filtered out. EdgeR v3.30.3 [30] package was used for normalization, calculating dispersion and testing for differential expression. 2.4. Targeted mRNA profiling To evaluate the transcriptomic profiles custom NanoString CodeSet (NanoString Technologies) was utilized. Total RNA was extracted from fresh frozen samples using the RNeasy Fibrous Tissue Mini Kit (Qiagen). RNA samples were prepared by hybridization (65°C) to nCounter Reporter and Capture probes according to the manufacturer protocol. Subsequent to the automated sample cleanup, reporter capture, and alignment on the cartridge by the nCounter Prep Station, the RNA samples were deemed ready for analysis. The sample cartridges were then placed in the nCounter Digital Analyzer for data collection. The study incorporated 555 field-of-view readings, and nSolver 4.0.7 analysis software (NanoString) was employed for data analysis. This software included background correction (20 counts were designated as the background threshold) and normalization using both positive control and five reference (housekeeping) genes. P -values were adjusted to account for multiple testing using the Benjamini-Hochberg false discovery rate (FDR) method and adjusted p-value ≤0.05 was considered significant. The threshold value for significance was set at a fold change (FC) of ≥1.5 to identify DEGs. The Nanostring normalized data were calculated using the Rosalind web-based software with the settings described above for nSolver 4.0.7 analysis software (NanoString). For the calculation of the Z-values and creation of the gene expression heatmap, normalized expression data and the Heatmapper web-based tool was used [31]. The genes and samples were clustered using average linkage and Pearson Distance Measurement Method. 2.5. Western Blotting Tissue samples, weighing 30 milligrams, were homogenized in 350 microliters of ice-cold RIPA buffer (50 mM Tris-HCl, 150 mM NaCl, 1.0% NP-40, pH 8.0). The resulting mixture was then subjected to a 30-minute incubation on ice. Subsequently, the samples were subjected to a centrifugal process at 16,000 × g for 20 minutes at a temperature of 4°C. The resultant clear upper layer was collected and stored on ice. Protein quantification was performed using the BCA assay (Pierce) according to the manufacturer’s instructions. Protein samples (30 μg) were prepared by mixing with 5x Laemmli buffer (containing 15% 2-mercaptoethanol) and subsequently denatured at 95°C for five minutes. Following this step, the samples were allowed to cool on ice, and then loaded onto mini-gels prepared with 7.5% or 12% TGX Stain-free Fast Cast Kit (Bio-Rad). Electrophoresis was conducted at 120 V. After 45 seconds UV-activation of the gel’s Stain-free chemistry, proteins were transferred to a PVDF membrane at 350 mA for 60 minutes, blocked for 1 hour in blocking buffer (5% skimmed milk, 0.05% Tween-20 in PBS) and then incubated with primary antibodies diluted in the blocking buffer (mouse-raised monoclonal antibody anti- voltage-gated calcium channel subunit α2δ1, Thermo-Fisher, cat.no MA3-921; rabbit monoclonal antibody anti-TOP2A, CST, cat. no. 12286T; rabbit polyclonal antibody anti-GOLGA4, CST, cat. no. 79145S; rabbit polyclonal antibodies anti-CLDN10, Abclonal, cat. no. A9853) overnight at 4 °C. The following day, the membrane was washed, and incubated for 1 hour at room temperature with anti-mouse HRP-conjugated antibody (Jackson ImmunoResearch, cat. no. 115-035-003, diluted 10000x) for α2δ1 detection, or with a goat polyclonal anti-rabbit HRP-conjugated antibody (DAKO, cat.no P044801-2, diluted 5000x) for detection of the remaining targets. Secondary antibodies were diluted in the blocking buffer. Following a thorough washing step, total protein was subjected to visualization through the implementation of the Stain-free chemistry method. The subsequent imaging of target-specific bioluminescent signals was conducted utilizing the SuperSignal West Femto ECL substrate (Pierce) and the Chemidoc Touch (Bio-Rad) imaging system. The densitometry analysis was performed by normalizing the bioluminescent signals against the total protein stain-free signal from the corresponding lane of the blot. 2.6. Immunohistochemistry For IHC, FFPE tissues were freshly cut into 3-µm-thick sections and mounted on Superfrost Plus slides (Menzel Gläser). Staining was then performed on a LEICA BOND-MAX (Leica Biosystems) according to the following protocol. Initially, the tissues were deparaffinized using Bond Dewax Solution (Leica Biosystems) and then pre-treated with Bond Epitope Retrieval Solution 1 (Leica Biosystems) for a period of 20 minutes. The activity of the endogenous peroxidase was blocked by Peroxide Block using the BOND Polymer Refine Detection System (Leica Biosystems). Rabbit polyclonal antibodies against α2δ1 were purchased from ABclonal (cat.no A15260). The antibodies were diluted 1:100 with Bond Primary Antibody Diluent (Leica Biosystems) and sections were incubated with primary antibodies for 15 minutes at RT. The samples were then incubated with post-primary and polymer using the BOND Polymer Refine Detection System (Leica Biosystems). The reaction substrate was 3,3’-diaminobenzidine (DAB chromogen) and all sections were counterstained with hematoxylin (BOND Polymer Refine Detection System, Leica Biosystems). Control experiments were performed in the absence of primary antibody. The results of the immunohistochemical reaction were scored within each sample using a semiquantitative scoring system (0 - no staining, + (1) - low, ++ (2) - moderate, +++ (3) - high), taking into account the intensity of cell staining. 2.7. Statistical analysis Statistical analysis of the RNA-Seq and Nanostring data is described in their respective sections of the Methods. Data normality was assessed using the Shapiro-Wilk test. To evaluate differences in mean values for the Western Blot densitometry and IHC data between the BPH and PC groups, the Mann-Whitney U test was used. A P -value < 0.05 was considered statistically significant. 2.8. Availability of data and materials RNA-Seq and Nanostring data were deposited into the Gene Expression Omnibus database under accession numbers GSE299084 and GSE299093, respectively. These data are available at the following URLs: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299084, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299093. The remaining data supporting the conclusions of this article are included within the article, and additional files, and are available from the corresponding author upon reasonable request. 3. Results Each tissue specimen was divided into three parts: fresh-frozen, RNA-later-treated-frozen and formalin fixed paraffin embedded (FFPE). RNA-later–treated frozen tissue samples from dogs 3, 4, 5, 10, and 18 were used for RNA-seq, and all such samples, except one, were used for Nanostring; fresh frozen tissue samples from 13 dogs (1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 14, 15, 22) were used for WB; FFPE sections from 15 dogs (1, 2, 3, 5, 7, 9, 12, 15–22) were used for IHC (Table 1). Sample selection criteria differed between the initial transcriptomic profiling and subsequent experiments. For the RNA-Seq analysis, conducted on a preliminary set of samples, specimens with the highest RIN were chosen. Following the completion of sample collection, tissues for Nanostring, WB, and IHC validation were selected based on availability. 3.1. Comparative molecular profiling of prostate carcinoma and benign prostate hyperplasia RNA-Seq data from two PC tissues and three BPH tissues subjected to bioinformatic analysis revealed 2923 DEGs out of a total of 12 185 genes identified in the studied samples ( Additional file 1, Supplementary Figure 2 ). After subjecting the RNA-Seq data to principal component analysis (PCA), it was established that the substantial disparities (65%) in transcriptomic profiles between PC and BPH samples were in congruence with the histopathological evaluation of the corresponding tissue specimens ( Fig. 1A ). Nevertheless, PCA also revealed heightened heterogenicity between PC samples as opposed to BPH samples. Among the DEGs exhibiting at least a minimum expression level in both groups, 114 genes demonstrated significant upregulation, while 92 genes exhibited significant downregulation in the PC samples compared to the BPH specimens. These genes were selected based on a log 2 -fold change (log 2 FC) less than -2 or greater than 2, the FDR less than 0.05, and a mean normalized counts per million (CPM) greater than 10 in each group ( Fig. 1B; Additional file 2. Supplementary Table 1 ). In the next step, 19 upregulated and 7 downregulated DEGs were selected to validate the RNA-Seq data using the Nanostring technology on a larger (n = 14 PC, n = 7 BPH) patient cohort ( Figure 1B ; Additional file 2, Supplementary Table 1 ). In most cases, this selection was based on the highest FC, but based on the literature data some of the genes were excluded ( SELP , RGS4 , MATN2 , MATN4 , CHAF1A , NUP107 , ATF3 ), and some, with lower FC, were added to the validation set ( CLU , GOLGA4 , SERPINB6 ). The total RNA isolated from fresh frozen tissue samples was subjected to PCR-free targeted mRNA profiling by Direct Digital Detection. The complete results are presented as a heatmap of normalized gene expression ( Figure 2A ). The cluster consisting of PC overexpressed genes was further divided into two subclusters. The three genes highly upregulated in PC samples compared to BPH, TSPAN8 , CLU and CHI3L1 , represented the first sub-cluster. Whereas the remaining genes ( ASPM, TOP2A, HELLS, COL6A3, IGFBP2, MSH6, SULF2, MSH2, IGFBP5, SMOC2, FBN2, SGO2, CENPF, GLI1 ), representing the second sub-cluster, did not show such robust differences between the study groups. The cluster of PC underexpressed genes contained 8 genes (NKX3.1, CLDN10, ATP6V0A4, KLK2, CD303 , GOLGA4A , CACNA2D1 and SERPINB6 ), among which the last three showed the most similar expression pattern. Based on NanoString assay, we found statistically significant differences in the expression of the following 12 genes: ASPM, ATP6V0A4, CACNA2D1 , CLDN10 , CLU, GOLGA4 , HELLS , KLK2, NKX3.1 , SERPINB6 , TOP2A , and TSPAN8 ( Figure 2B, Table 2 ). Five of these genes: TSPAN8 , ASPM , CLU , TOP2A , and HELLS were overexpressed in PC compared to BPH, while the remaining were downregulated in PC. Table 2. Results of Nanostring gene expression analysis for PC vs BPH group. Gene Log 2 FC p-value adj. P-value ASPM 4.63 0.0001 0.0001 TSPAN8 4.59 0.0001 0.0001 TOP2A 2.65 0.0001 0.0001 CLU 2.18 0.0013 0.0026 HELLS 1.69 0.0026 0.0050 COL6A3 1.38 0.0359 0.0643 CHI3L1 1.26 0.0877 0.1176 IGFBP2 1.25 0.0603 0.0932 MSH6 1.21 0.0727 0.1075 SULF2 1.18 0.0553 0.0895 MSH2 1.12 0.0899 0.1176 IGFBP5 0.70 0.3107 0.3522 SMOC2 0.32 0.6420 0.6615 FBN2 0.30 0.7353 0.7353 SGO2 -0.26 0.5242 0.5570 CENPF -0.42 0.4012 0.4400 CD302 -0.96 0.0871 0.1176 NPTX1 -1.71 0.1296 0.1632 GOLGA4 -2.40 0.0001 0.0002 GLI1 -2.56 0.0380 0.0646 SERPINB6 -2.61 0.0001 0.0001 CACNA2D1 -6.09 0.0001 0.0001 ATP6V0A4 -7.86 0.0001 0.0001 CLDN10 -8.02 0.0001 0.0003 NKX3-1 -8.22 0.0001 0.0001 KLK2 -12.73 0.0001 0.0001 Bolded font marks genes showing statistically significant differential expression. 3.2. Validation of selected DEG expression on the protein level In order to provide further validation of the data on protein level, the expression of DEGs was analyzed employing WB and IHC. The targets for protein-level validation via immunochemical methods were selected from the set of Nanostring-confirmed DEGs based on the commercial availability of antibodies. The qualified antibodies were directed against human antigenic epitopes which share over 90% sequence homology with canine epitopes and preferably were monoclonal. Therefore, the following DEGs were subjected to analysis by WB: TOP2 , GOLGA4 , CLDN10 , and CACNA2D1 . Despite the availability of antibodies, the NKX3.1 protein and kallikrein-related peptidase 2 (encoded by the KLK2 gene) were excluded from WB analysis due to their well-documented association with PC. WB analysis using mouse monoclonal antibodies directed against voltage-dependent α2δ1 revealed the presence of an intense band with an apparent molecular mass of approximately 150 kDa in tissue lysates from BPH, which was barely detectable PC protein extracts ( Figure 3A ). Densitometric analysis showed that the mean normalized volume of the α2δ1 band is 11 times lower in PC than in BPH and the difference is statistically significant. Spearman’s correlation analysis shows a strong significant positive correlation between the expression of α2δ1 protein and mRNA (r s = 0.81; p = 0.0014) ( Figure 3A ). These findings were further confirmed by IHC. The expression of α2δ1 in paraffin sections of PC and BPH tissue samples was analyzed using the rabbit polyclonal antibodies. On average, PC samples stained weaker with the anti-α2δ1 antibody than the BPH samples ( Figure 3B, Table 3 ). No binding to canine proteins was observed in the case of antibodies directed against DNA topoisomerase IIα (coded by TOP2A ), Golgin subfamily A member/GOLGA4 protein (coded by GOLGA4 ), and claudin-10 (coded by CLDN10 ). Table 3. A summary of the semiquantitative assessment of α2δ1 immunohistochemical labeling in the canine prostate gland with prostate cancer (PC) and benign prostatic hyperplasia (BPH) Sample ID Histopathological diagnosis Distribution Staining intensity Dog 1 BPH absent 0 Dog 2 BPH very low + Dog 3 BPH absent 0 Dog 5 BPH moderate +++ Dog 7 BPH moderate ++ Dog 9 PC very low + Dog 12 PC very low 0/+ Dog 15 PC absent 0 Dog 16 PC absent 0 Dog 17 PC low +/++ Dog 18 PC very low + Dog 19 PC absent 0 Dog 20 PC very low + Dog 21 PC absent 0 Dog 22 PC absent 0 Samples were grouped in 6 categories based on the number of cells positive for α2δ1 expression: absent (0% labelled cells), very low (1-5% labelled cells), low (6-20% labelled cells), moderate (21-50% labelled cells), high (51-60% labelled cells), very high (>60% labelled cells). Staining intensity: (0) absent, (+) weak, (++) moderate, (+++) intense. 4. Discussion In the case of canine PC, knowledge of its molecular mechanisms and regulatory networks is mostly derived from comparative studies and is limited to changes in the expression of a few genes/proteins known from studies of human PC pathogenesis [32]. These limitations could be overcome using high-throughput methods, but screening of PC tissue versus benign prostate tissue using such an approach, involving the analysis of thousands of genes, has only been performed a few times, and none of these reports supported their findings with a protein-level data. Thiemeyer et al. [33] used RNA-Seq to compare gene expression profiles in malignant and non-malignant prostate tissues to identify potential biomarkers associated with the development and progression of canine PC. As many as 4098 DEGs were found between PC and benign prostate samples, and 688 proteins encoded by these genes were associated with specific biological processes, such as inflammatory response and cytokines, regulation of the immune system and cell death, cell cycle, phagosome and autophagy, and cell surface and PI3K signaling, which are known to be highly deregulated in cancer in general. These cellular processes were described by the authors as “hallmarks of canine PC”. Taking into account their own RNA-Seq data and information from databases and literature on PC-associated genes, the following 16 DEGs were selected as the most promising potential biomarkers of canine PC: AR, CDKN1A, CTNNB1, EGFR, KLK2, NKX3.1, PDGFRA, SRD5A2, CREB3L4, PDGFRB, NRAS, PIK3CD, PIK3CG, KLK4, KIT, and ABCB1. It should be pointed out that majority of these canine PC-associated genes (13) are also deregulated in human PC ( SRD5A2, KLK2, NKX3-1, CREB3L4, EGFR, PDGFRA, PDGFRB, NRAS, PIK3CD, CTNNB1, PIK3CG, and CDKN1A ) and are used in commercial PC multi-gene assays. This study was performed using PC specimens from intact as well as neutered dogs. Another study used only the castrated dog cohort to compare gene expression profiles between PC and benign prostate tissue specimens by microarray analysis [21]. A set of 33 genes was identified that showed significantly different expression levels between cancerous and benign tissues. Since canine PC resembles human CRPC in many ways, their gene expression profiles were compared, and five of these genes - ISG15, AZGP1, GPX3, S100P, and IFITM1 - also showed similar differences in expression compared to human prostate tissue. Both studies confirmed that canine and human PC share many similarities not only clinically but also at the molecular level, but the gene expression profiles were very different, with only two common genes: KLK2 and NKX3.2. It should be noted that in both cases the mRNAs isolated from cancerous tissues were compared with the mixture of mRNAs purified from normal as well as hyperplastic prostate tissues, and it should be emphasized that several lines of evidence link the pathogenesis of BPH with prostatic inflammation [24, 25]. Since inflammation is one of the hallmarks of cancer [22, 34], this approach does not allow us to clearly separate inflammation-related genes from those directly involved in the development and progression of PC. Moreover, previous studies did not validate RNA-Seq and microarray data with complementary analyses. Therefore, in this study only BPH tissues were used to identify PC-specific genes using RNA-Seq. It should be noted that the QuantSeq method employed here sequences only the 3′ end of polyadenylated RNAs, which makes it cost-effective and suitable for degraded samples. However, in contexts different from ours, this approach has serious limitations, as it does not allow the reconstruction of full-length mRNA sequences or the detection of alternative splicing events and gene fusions, which can be identified using standard RNA-Seq. Finally, the selected DEGs were validated by NanoString, Western blotting, and IHC. A comprehensive analysis of the RNA-Seq data revealed a significant upregulation of 114 genes and a significant downregulation of 92 genes in PC samples compared to BPH samples. To validate the findings, the RNA-Seq data underwent additional rigorous bioinformatic analysis, which enabled the selection of 26 genes with the most significant FC between PC and BPH tissues for analysis by Nanostring. Thereby, significant differences were identified for the following 12 genes: ASPM, ATP6V0A4, CACNA2D1, CLDN10, CLU, GOLGA4, HELLS, KLK2, NKX3.1, SERPINB6, TOP2A, and TSPAN8. Five of these genes: TSPAN8, ASPM, CLU, TOP2A , and HELLS were overexpressed in PC compared to BPH, while the rest of them were downregulated in PC. When these results were compared with previous transcriptomic data [21, 33], two of these genes: KLK2 and NKX3.1 were also found to be downregulated in PC compared to non-malignant prostate tissues in both analyses, which strongly indicates that their suppressed expression is the hallmark of canine PC. It is worth noting that differences in the expression of KLK2 and NKX3.1 genes between malignant and non-malignant tissues were confirmed at the protein level using IHC and Western blotting [12,13, 35]. KLK2 encodes kallikrein-related peptidase (Klk2) and, in contrast to dogs, its expression in humans is higher in PC than in benign prostate tissue, where it is recognized as a biomarker associated with prostate cancer risk [36, 37]. In humans, Klk2 promotes PC cell growth and is involved in tumor metastasis [38]; however, in canine PC, its role remains completely unknown. The expression of Nkx3.1, the product of a prostate-specific tumor suppressor gene, is also markedly decreased in human PC [39, 40]. This transcription factor plays a key role in normal prostate development and tumor suppression as a negative regulator of epithelial cell growth in prostate tissue [41, 42]. However, its specific role in the development and progression of canine PC has never been investigated in experimental studies using cellular models. In addition to these genes, the downregulation of two other genes, CLDN10 and CACNA2D1 , was also observed in transcriptomic studies, but this finding has not been validated at the protein level [21].” Using the NanoString assay, statistically significant differences in the expression of the following 12 genes on the level of mRNA were confirmed: ASPM, ATP6V0A4, CACNA2D1, CLDN10, CLU, GOLGA4, HELLS, KLK2, NKX3.1, SERPINB6, TOP2A, and TSPAN8 . The protein products of these genes were subsequently subjected to validation by WB and IHC. However, protein-level validation of the DEGs using specific antibodies revealed only a markedly reduced expression of the voltage-gated calcium channel subunit α2δ1, encoded by the CACNA2D1 gene, in PC samples compared to BPH. Antibodies directed against human TOP2, GOLGA4, and CLDN10 proteins did not bind to the canine ortologs. This is likely due to the absence of cross-reactivity with canine proteins, which highlights the challenges associated with the limited availability of species-specific antibodies targeting canine proteins. At the research level, this issue can be addressed by employing alternative approaches such as mass spectrometry, particularly in combination with liquid chromatography (LC/MS/MS). Nevertheless, given the complexity of this technique, which requires specialized equipment and expertise, it cannot replace immunological methods in routine veterinary diagnostics. Little is known about the role of the α2δ1 subunit of the calcium channel in the development and progression of cancer. To date, α2δ1 has been shown to be involved in the self-renewal and tumorigenicity of human hepatocellular carcinoma (HCC) tumor-initiating cells (TICs) [43] and recognized as a TIC marker in non-small cell lung carcinoma[44]. HCC TICs with high expression of α2δ1 were also more invasive and resistant to apoptosis than their α2δ1-negative counterparts. At the molecular level, α2δ1 isoform 5 was found to play a key role in modulating calcium influx as a subunit of L- and N-type voltage-gated calcium channels, which in turn activates the ERK1/2 signaling pathway. Therefore, in the case of human HCC, voltage-gated calcium channel subunit α2δ1 seems to play an important role in its development and progression/recurrence, acting as an oncogenic protein. Interestingly, in the case of canine prostate cancer cells, downregulation of CACNA2D1 gene expression suggests the suppressive role of α2δ1 in PC development and progression. Further studies using cellular models are needed to answer this question. 5. Conclusion It should be emphasized that dogs with PC or BPH, in contrast to healthy dogs, may present in the clinic with similar clinical signs, such as straining to urinate, pollakiuria, hematuria, or constipation, which greatly hinders and often prevents distinguishing between these two conditions. Therefore, our findings identify the α2δ1 subunit as a novel and promising diagnostic biomarker for differentiating PC from BPH. Considering the availability of aspirates collected by ultrasound-guided fine-needle aspiration (US-FNA) biopsy or less invasive prostatic catheter biopsy of the canine urethra, which are used in the diagnosis of various canine prostatic diseases through different diagnostic approaches [45], e.g., flow cytometric phenotyping [46], further studies are warranted to confirm the usefulness of this biomarker in the differential diagnosis of PC and BPH. To build upon these findings and confirm the biomarker's utility across diverse datasets, the field would benefit from a large-scale meta-analysis. However, we stress that such a study would require a dedicated, harmonized reprocessing of all available raw data to properly account for technical confounders. Last but not least, the role of α2δ1 in prostate cancer biology remains unclear and requires further study using prostate cancer cell line models. Abbreviations α2δ1 – voltage-gated calcium channel alpha-2 delta-1 subunit AR – androgen receptor BPH – benign prostate hyperplasia CPM – counts per million CRPC – castration-resistant prostate cancer DAB – 3,3’-diaminobenzidine DEG – differentially expressed gene FC – fold change FDR – false discovery rate FFPE – formalin-fixed paraffin-embedded HPDx - Histopathological Diagnosis HCC – human hepatocellular carcinoma IHC – immunohistochemistry KEGG – Kyoto Encyclopedia of Genes and Genomes PC – prostate cancer PCA – principal component analysis PIA – prostatic inflammatory atrophy RNA-Seq – RNA sequencing TIC – tumor-initiating cell TNM- Tumor Nodes Metastasis Classification of Malignant Tumors UMI – unique molecular identifiers WB – Western blotting Declarations Ethics approval and consent to participate This study followed the national guidelines of The Experiments on Animals Act published on January 15 th , 2015 (Journal of Laws of the Republic of Poland, 2015, item. 266), and has been granted an exemption from requiring ethics approval by an institutional Animal Welfare Advisory Team (decision no. 11/2025). The study involved client-owned animals. Written informed consent was obtained from all owners before participation. All owners agreed to an autopsy. All efforts were made to minimize animal discomfort and ensure well-being throughout the study. Consent for publication Not applicable Availability of data and materials RNA-Seq and Nanostring data were deposited into the Gene Expression Omnibus database under accession numbers GSE299084 and GSE299093, respectively. These data are available at the following URLs: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299084, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299093,. The remaining data supporting the conclusions of this article are included within the article, and additional files, and are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research was funded in part by the National Science Center (Poland) Miniatura 2021/05/X/NZ5/01570. This work was supported by the Wroclaw University of Environmental and Life Sciences (Poland) as part of the research project no. N090/0002/23. For the purpose of Open Access, the author has applied a CC-BY public copyright license to any Author Accepted Manuscript (AAM) version arising from this submission. Authors' contributions MZ: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration, Funding acquisition. MU: Conceptualization, Methodology, Resources, Writing - Original Draft, Writing - Review & Editing, Funding acquisition. PP: Methodology, Validation, Investigation, Resources. SD: Methodology, Validation, Resources, Writing - Review & Editing. SS Methodology, Validation, Formal analysis, Resources, Writing - Review & Editing, Visualization. IS: Methodology, Validation, Formal analysis, Investigation, Writing - Review & Editing. AK: Resources. BL: Methodology Investigation. PS: Methodology Investigation. FVN: Methodology, Resources, Writing - Review & Editing. AT: Methodology, Investigation. All authors read and approved the final manuscript Acknowledgements Not applicable References Davis BW, Ostrander EA. Domestic dogs and cancer research: A breed-based genomics approach. ILAR journal. 2014;55:59–68. Johnston SD, Kamolpatana K, Root-Kustritz MV, Johnston GR. Prostatic disorders in the dog. Animal Reproduction Science. 2000;60-61:405–15. Krook L. A statistical investigation of carcinoma in the dog. Acta pathologica et microbiologica Scandinavica. 1954;35:407–22. Bell FW, Klausner JS, Hayden DW, Feeney DA, Johnston SD. Clinical and pathologic features of prostatic adenocarcinoma in sexually intact and castrated dogs: 31 cases (1970-1987). Journal of the American Veterinary Medical Association. 1991;199:1623–30. Lai CL, Ham RVD, Leenders GV, Lugt JVD, Mol JA, Teske E. Histopathological and immunohistochemical characterization of canine prostate cancer. The Prostate. 2008;68:477–88. LeRoy BE, Northrup N. Prostate cancer in dogs: Comparative and clinical aspects. Veterinary journal (London, England : 1997). 2009;180:149–62. Cornell KK, Bostwick DG, Cooley DM, Hall G, Harvey HJ, Hendrick MJ, et al. Clinical and pathologic aspects of spontaneous canine prostate carcinoma: A retrospective analysis of 76 cases. The Prostate. 2000;45:173–83. LeRoy BE, Thudi NK, Nadella MVP, Toribio RE, Tannehill-Gregg SH, Bokhoven AV, et al. New bone formation and osteolysis by a metastatic, highly invasive canine prostate carcinoma xenograft. The Prostate. 2006;66:1213–22. Leav I, Ling GV. Adenocarcinoma of the canine prostate. Cancer. 1968;22:1329–45. Kirby M, Hirst C, Crawford ED. Characterising the castration-resistant prostate cancer population: A systematic review. International journal of clinical practice. 2011;65:1180–92. Waters DJ, Patronek GJ, Bostwick DG, Glickman LT. Comparing the age at prostate cancer diagnosis in humans and dogs. Journal of the National Cancer Institute. 1996;88:1686–7. Fonseca-Alves CE, Kobayashi PE, Laufer-Amorim R. Evaluation of NKX3.1 and c-MYC expression in canine prostatic cancer. Research in veterinary science. 2018;118:365–70. Fonseca-Alves CE, Rodrigues MMP, Moura VMBD de, Rogatto SR, Laufer-Amorim R. Alterations of c-MYC, NKX3.1, and e-cadherin expression in canine prostate carcinogenesis. Microscopy research and technique. 2013;76:1250–6. Rivera-Calderón LG, Fonseca-Alves CE, Kobayashi PE, Carvalho M, Drigo SA, Oliveira Vasconcelos R de, et al. Alterations in PTEN, MDM2, TP53 and AR protein and gene expression are associated with canine prostate carcinogenesis. Research in veterinary science. 2016;106:56–61. Lin HY, Palmieri C. Is STAT3 and PTEN expression altered in canine prostate cancer? Journal of comparative pathology. 2016;155:185–9. Rivera-Calderón LG, Fonseca-Alves CE, Kobayashi PE, Carvalho M, Vasconcelos RO, Laufer-Amorim R. p-mTOR, p-4EBP-1 and eIF4E expression in canine prostatic carcinoma. Research in veterinary science. 2019;122:86–92. Sakai K, Shinohara Y, Kaji K, Yonezawa T, Momoi Y, Maeda S. Human epidermal growth factor receptor 2 is overexpressed in canine prostate carcinoma. Translational and Regulatory Sciences. 2021;3:1–8. Faleiro MBR, Cintra LC, Jesuino RSA, Araújo EG de, Rocha RM, Moura VMBD de. Expression of EGF receptors in canine prostate with proliferative inflammatory atrophy and carcinoma. Ciência Rural. 2017;47:e20170085. Thiemeyer H, Taher L, Schille JT, Harder L, Hungerbuehler SO, Mischke R, et al. Suitability of ultrasound-guided fine-needle aspiration biopsy for transcriptome sequencing of the canine prostate. Scientific Reports. 2019;9:1–14. Thiemeyer H, Taher L, Schille JT, Packeiser EM, Harder LK, Hewicker-Trautwein M, et al. An RNA-Seq-Based Framework for Characterizing Canine Prostate Cancer and Prioritizing Clinically Relevant Biomarker Candidate Genes. International journal of molecular sciences. 2021;22. Angel MR, Séguin B, Löhr CV, Beer TM, Feliciano J, Ramsey SA, et al. Comparative transcriptomes of canine and human prostate cancers identify mediators of castration resistance. Veterinary and comparative oncology. 2024;22. Greten FR, Grivennikov SI. Inflammation and cancer: Triggers, mechanisms, and consequences. Immunity. 2019;51:27–41. Ma Y, Yang X, Zhao W, Yang Y, Zhang Z. Calcium channel α2δ1 subunit is a functional marker and therapeutic target for tumor-initiating cells in non-small cell lung cancer. Cell Death & Disease 2021 12:3. 2021;12:1–16. Chughtai B, Forde JC, Thomas DDM, Laor L, Hossack T, Woo HH, et al. Benign prostatic hyperplasia. Nature reviews Disease primers. 2016;2:1–15. Briganti A, Capitanio U, Suardi N, Gallina A, Salonia A, Bianchi M, et al. Benign Prostatic Hyperplasia and Its Aetiologies. European Urology, Supplements. 2009;8:865–71. Feldman AT, Wolfe D. Tissue processing and hematoxylin and eosin staining. Methods in molecular biology (Clifton, NJ). 2014;1180:31–43. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics (Oxford, England). 2014;30:2114–20. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40. Babicki S, Arndt D, Marcu A, Liang Y, Grant JR, Maciejewski A, et al. Heatmapper: Web-enabled heat mapping for all. Nucleic acids research. 2016;44:W147–53. Paula Nascente E de, Amorim RL, Fonseca-Alves CE, Moura VMBD de. Comparative pathobiology of canine and human prostate cancer: State of the art and future directions. Cancers. 2022;14. Thiemeyer H, Taher L, Schille JT, Packeiser EM, Harder LK, Hewicker-Trautwein M, et al. An RNA-seq-based framework for characterizing canine prostate cancer and prioritizing clinically relevant biomarker candidate genes. International journal of molecular sciences. 2021;22. Zhao H, Wu L, Yan G, Chen Y, Zhou M, Wu Y, et al. Inflammation and tumor progression: Signaling pathways and targeted intervention. Signal Transduction and Targeted Therapy 2021 6:1. 2021;6:1–46. Fonseca-Alves CE, Kobayashi PE, Calderón LGR, Felisbino SL, Carvalho Rinaldi J de, Drigo SA, et al. Immunohistochemical panel to characterize canine prostate carcinomas according to aberrant p63 expression. PLOS ONE. 2018;13:e0199173. Hannu K, Johanna M, Ulf-Håkan S. KLK-targeted therapies for prostate cancer. EJIFCC. 2014;25:207. Klein RJ, Halldén C, Cronin AM, Ploner A, Wiklund F, Bjartell AS, et al. Blood biomarker levels to aid discovery of cancer-related single-nucleotide polymorphisms: Kallikreins and prostate cancer. Cancer Prevention Research. 2010;3:611–9. Shang Z, Niu Y, Cai Q, Chen J, Tian J, Yeh S, et al. Human kallikrein 2 (KLK2) promotes prostate cancer cell growth via function as a modulator to promote the ARA70-enhanced androgen receptor transactivation. Tumor Biology. 2014;35:1881–90. Asatiani E, Huang WX, Wang A, Ortner ER, Cavalli LR, Haddad BR, et al. Deletion, methylation, and expression of the NKX3.1 suppressor gene in primary human prostate cancer. Cancer Research. 2005;65:1164–73. Bowen C, Bubendorf L, Voeller HJ, Slack R, Willi N, Sauter G, et al. Loss of NKX3.1 expression in human prostate cancers correlates with tumor progression 1,2. Cancer Genetics Branch. 2000;60:20892–4470. Shen MM, Abate‐Shen C. Roles of the Nkx3.1 homeobox gene in prostate organogenesis and carcinogenesis. Developmental Dynamics. 2003;228:767–78. Budreika A, Phoenix JT, Kostlan RJ, Deegan CD, Ferrari MG, Young KS, et al. The homeobox transcription factor NKX3.1 displays an oncogenic role in castration-resistant prostate cancer cells. Cancers. 2025;17:306 Zhao W, Wang L, Han H, Jin K, Lin N, Guo T, et al. 1B50-1, a mAb raised against recurrent tumor cells, targets liver tumor-initiating cells by binding to the calcium channel α2δ1 subunit. Cancer Cell. 2013;23:541–56. Ma Y, Yang X, Zhao W, Yang Y, Zhang Z. Calcium channel α2δ1 subunit is a functional marker and therapeutic target for tumor-initiating cells in non-small cell lung cancer. Cell Death & Disease 2021 12:3. 2021;12:1–16. Rodak O, Dzimira S, Podolak A, Płóciennik M, Niżański W. Accuracy of ultrasonography and fine-needle aspiration cytology in the diagnosis of prostate diseases in dogs. Reproduction in Domestic Animals. 2018;53:79–84. Aresu L, Aricò A, Ferraresso S, Martini V, Comazzi S, Riondato F, et al. Minimal residual disease detection by flow cytometry and PARR in lymph node, peripheral blood and bone marrow, following treatment of dogs with diffuse large b-cell lymphoma. Veterinary Journal. 2014;200:318–24. Additional Declarations No competing interests reported. Supplementary Files Additionalfile122.08.docx Title of data: Additional Plots and Blots Description of data: Supplementary Figure 1. Scatter plot showing RNA integrity number and RNA concentration of the samples used in NanoString profiling. Supplementary Figure 2. Volcano plot showing 2923 DEGs in PC vs. BPH (-1>log 2 FC>1, FDR>0.05) out of 12185 identified genes. After additional filtering (mean normalized CPM >10 in each group), DEGs in green were selected for validation by targeted mRNA profiling (NanoString technology) based on the highest differences in expression and presence of mRNA in both samples (PC and BPH). For clarity, an enlarged section of the volcano plot shows the DEGs upregulated in PC. Supplementary Figure 3. A) Full-length blot presented in Fig.3A, and B) corresponding Stain-Free loading control. C) Blot replicate used together with A) for densitometric analysis presented in Fig. 3B. and D) corresponding Stain-Free loading control. Additionalfile2.xlsx Title of data: Results of RNA-Seq differential gene expression analysis for PC vs BPH group. Description of data: Supplementary Table 1. These genes were selected based on a log2-fold change (log2FC) less than -2 or greater than 2, a FDR greater than 0.05, and a mean normalized CPM greater than 10 in both groups. List of the DEGs. The names of the genes selected for Nanostring validation were bolded. Cite Share Download PDF Status: Published Journal Publication published 09 Oct, 2025 Read the published version in BMC Veterinary Research → Version 1 posted Editorial decision: Accepted 03 Sep, 2025 Submission checks completed at journal 02 Sep, 2025 First submitted to journal 01 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6719203","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509450782,"identity":"5047fe6e-34fe-4ff9-b4d2-046bc8fa0f5e","order_by":0,"name":"Maciej Zacharski","email":"data:image/png;base64,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","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":true,"prefix":"","firstName":"Maciej","middleName":"","lastName":"Zacharski","suffix":""},{"id":509450783,"identity":"d3608c57-e6e5-458e-b270-fa28fb888ab8","order_by":1,"name":"Maciej Ugorski","email":"","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Maciej","middleName":"","lastName":"Ugorski","suffix":""},{"id":509450784,"identity":"67be95e8-cdb8-43c7-b839-5995f76e3456","order_by":2,"name":"Przemysław Prządka","email":"","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Przemysław","middleName":"","lastName":"Prządka","suffix":""},{"id":509450785,"identity":"44250742-2228-4b68-b50a-f127e16441ac","order_by":3,"name":"Stanisław Dzimira","email":"","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Stanisław","middleName":"","lastName":"Dzimira","suffix":""},{"id":509450786,"identity":"fc078fc9-c4a7-4050-ba83-feff04b8f4ab","order_by":4,"name":"Sonja Škevin","email":"","orcid":"","institution":"Ghent University","correspondingAuthor":false,"prefix":"","firstName":"Sonja","middleName":"","lastName":"Škevin","suffix":""},{"id":509450787,"identity":"bc6e929e-9e2d-44ab-a3a8-a8e165d4c8da","order_by":5,"name":"Iwona Sidorkiewicz","email":"","orcid":"","institution":"Medical University of Białystok","correspondingAuthor":false,"prefix":"","firstName":"Iwona","middleName":"","lastName":"Sidorkiewicz","suffix":""},{"id":509450788,"identity":"f1bedba2-5653-4802-b55c-922ab965cb37","order_by":6,"name":"Bartłomiej Liszka","email":"","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Bartłomiej","middleName":"","lastName":"Liszka","suffix":""},{"id":509450789,"identity":"903693f4-2a40-489a-a4aa-f8fb673660cd","order_by":7,"name":"Piotr Skrzypczak","email":"","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Piotr","middleName":"","lastName":"Skrzypczak","suffix":""},{"id":509450790,"identity":"0d825dfd-d622-421c-9b8e-b641bc7b0f72","order_by":8,"name":"Filip Nieuwerburgh","email":"","orcid":"","institution":"Ghent University","correspondingAuthor":false,"prefix":"","firstName":"Filip","middleName":"","lastName":"Nieuwerburgh","suffix":""},{"id":509450791,"identity":"8a02822d-f181-48fd-b559-69019a15d88c","order_by":9,"name":"Adam Krętowski","email":"","orcid":"","institution":"Medical University of Białystok","correspondingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Krętowski","suffix":""},{"id":509450792,"identity":"b2468250-831c-4137-a1af-2f0d9804c40e","order_by":10,"name":"Alicja Tomaszek","email":"","orcid":"","institution":"Wroclaw University of Environmental and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Alicja","middleName":"","lastName":"Tomaszek","suffix":""}],"badges":[],"createdAt":"2025-05-21 19:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6719203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6719203/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12917-025-05046-7","type":"published","date":"2025-10-09T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90578685,"identity":"3c0019d9-ca6b-43d4-8a05-080bcc682dee","added_by":"auto","created_at":"2025-09-04 09:49:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":185502,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes (DEGs) between prostate cancer (PC) and benign prostate hyperplasia (BPH). A)\u003c/strong\u003e Principal component analysis (PCA) was employed to demonstrate the differences between PC (triangle) and BPH (circle) tissue samples, as well as the variances between replicates of individual samples. PCA elucidated that the majority of the variance (65%) was attributable to the histopathological typing of tissue specimens. \u003cstrong\u003eB)\u003c/strong\u003e Volcano plot showing highly differentially expressed genes (DEGs) in PC vs. BPH (-2\u0026gt;log2FC\u0026gt;2, FDR\u0026gt;0.05), mean normalized counts per million (CPM) \u0026gt;10 in each group. DEGs in green were selected for validation by targeted mRNA profiling (NanoString CodeSet) based on the highest differences in expression and presence of mRNA in both samples (PC and BPH). For clarity, an enlarged section of the volcano plot shows the DEGs upregulated in PC.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6719203/v1/20fac140229368d761bd3c83.png"},{"id":90578687,"identity":"8dd4f16d-7338-4dc5-8188-78ac6fb878ed","added_by":"auto","created_at":"2025-09-04 09:49:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":237205,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes (DEGs) between prostate cancer (PC) and benign prostate hyperplasia (BPH) validated by targeted mRNA profiling using\u003c/strong\u003e the \u003cstrong\u003eNanoString assay\u003c/strong\u003e. \u003cstrong\u003eA)\u003c/strong\u003e Heatmap representing Z-score based on the normalized gene expression of all Nanostring-analyzed genes shows clusters of genes with similar expression patterns. It indicates that the gene expression profiles of \u003cem\u003eTSPAN8\u003c/em\u003eand \u003cem\u003eCLU\u003c/em\u003e are closely related and distinct than from those of CACNA\u003cem\u003e2D1\u003c/em\u003eand \u003cem\u003eGOLGA\u003c/em\u003e, which constitute a separate cluster. \u003cstrong\u003eB)\u003c/strong\u003e The mean log2-normalized expression level of genes that exhibited statistically significant differences between the BPH and PC groups (**\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001). The DEGs were sorted from those with the highest expression levels in the PC compared to BPH. Error bars represent SEM.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6719203/v1/3bf644e1d6590678f17f4a7e.png"},{"id":90579573,"identity":"4eddbe8d-1f78-4910-8cad-0df975e165f8","added_by":"auto","created_at":"2025-09-04 09:57:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":563452,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of the voltage-gated calcium channel subunit α2δ1\u003c/strong\u003e \u003cstrong\u003e(α2δ1) in PC and BPH tissue specimens\u003c/strong\u003e. \u003cstrong\u003eA) \u003c/strong\u003eWestern blotting analysis of anti-\u003cstrong\u003e \u003c/strong\u003eα2δ1\u003cstrong\u003e \u003c/strong\u003emurine monoclonal antibody binding to proteins of PC and BPH tissues. Tissue lysates equivalent to 30 µg of protein were separated by SDS-PAGE under reducing conditions on a 7.5% gel and electrophoretically transferred onto a PVDF membrane. The densitometry analysis was performed by normalizing the bioluminescent signals against the total protein stain-free signal from the corresponding lane of the blot. Band intensities were analyzed with Image Lab software version 6.0.0 build 25 (Bio-Rad Laboratories) and GraphPad. Prism version 5. (**\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). Full-length blots are presented in \u003cstrong\u003eAdditional file 1, Supplementary Figure 3.\u003c/strong\u003e). \u003cstrong\u003eB) \u003c/strong\u003ePositive correlation between intensity of α2δ1\u003cstrong\u003e \u003c/strong\u003eprotein expression (Western blotting) and α2δ1 mRNA expression (DDD) in BPH. r\u003csub\u003es \u003c/sub\u003e= 0.81; \u003cem\u003ep \u003c/em\u003e= 0.0014.\u0026nbsp; \u003cstrong\u003eC)\u003c/strong\u003e Immunohistochemical staining of BPH and PC \u003cstrong\u003e(D) \u003c/strong\u003ewith anti-α2δ1 rabbit polyclonal antibodies. \u003cstrong\u003eE)\u003c/strong\u003e Reaction intensities with anti-α2δ1 rabbit polyclonal antibodies were calculated on the basis of a semiquantitative scoring system [0 - no staining, + (1) - low, ++ (2) - moderate, +++ (3) – high]. Error bars represent SEM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6719203/v1/418e1d0cf78a58b2640ba436.png"},{"id":93419729,"identity":"88665a2d-f4e9-4002-a8e8-c129f49c4891","added_by":"auto","created_at":"2025-10-13 16:06:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2579687,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6719203/v1/4ec8d6cb-26de-4fab-b969-3bd95c49cb50.pdf"},{"id":90578688,"identity":"899521b6-2d6a-4549-b5f1-67e556d01971","added_by":"auto","created_at":"2025-09-04 09:49:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1232418,"visible":true,"origin":"","legend":"\u003cp\u003eTitle of data: \u003cstrong\u003eAdditional Plots and Blots\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescription of data:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1. \u003c/strong\u003eScatter plot showing RNA integrity number and RNA concentration of the samples used in NanoString profiling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure 2.\u003c/strong\u003e Volcano plot showing 2923 DEGs in PC vs.\u0026nbsp;BPH (-1\u0026gt;log\u003csub\u003e2\u003c/sub\u003eFC\u0026gt;1, FDR\u0026gt;0.05) out of 12185 identified genes. After additional filtering (mean normalized CPM \u0026gt;10 in each group), DEGs in green were selected for validation by targeted mRNA profiling (NanoString technology) based on the highest differences in expression and presence of mRNA in both samples (PC and BPH). For clarity, an enlarged section of the volcano plot shows the DEGs upregulated in PC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure 3.\u003c/strong\u003e A) Full-length blot presented in Fig.3A, and B) corresponding Stain-Free loading control. C) Blot replicate used together with A) for densitometric analysis presented in Fig. 3B. and D) corresponding Stain-Free loading control.\u003c/p\u003e","description":"","filename":"Additionalfile122.08.docx","url":"https://assets-eu.researchsquare.com/files/rs-6719203/v1/a92ef90a8b556852a1424827.docx"},{"id":90578689,"identity":"702e529e-83ed-442b-9929-d22313607fb3","added_by":"auto","created_at":"2025-09-04 09:49:50","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":47718,"visible":true,"origin":"","legend":"\u003cp\u003eTitle of data: Results of RNA-Seq differential gene expression analysis for PC vs BPH group.\u003c/p\u003e\n\u003cp\u003eDescription of data:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 1.\u003c/strong\u003e These genes were selected based on a log2-fold change (log2FC) less than -2 or greater than 2, a FDR greater than 0.05, and a mean normalized CPM greater than 10 in both groups. List of the DEGs. The names of the genes selected for Nanostring validation were bolded.\u003c/p\u003e","description":"","filename":"Additionalfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6719203/v1/f5db76194e57098aa3657e66.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transcriptional analysis reveals a markedly reduced expression of the voltage-dependent calcium channel α2δ1 subunit in canine prostate cancer compared to benign prostatic hyperplasia","fulltext":[{"header":"1. Background","content":"\u003cp\u003eDogs are one of the few species, other than humans, that develop spontaneous prostate cancer (PC) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, unlike in humans, canine PC is a rare disease, affecting only 0.2\u0026ndash;0.6% of dogs [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is characterized by late onset, androgen independence, and is generally highly aggressive and metastatic, with the bones and lungs being the primary sites of metastasis [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], making it comparable to human castration-resistant prostate cancer (CRPC) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, given the range of similarities between prostate cancer in dogs and humans, dog represent a relevant model for the human disease [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and preclinical studies of new diagnostic and therapeutic approaches in dogs may benefit both species affected by prostate cancer.\u003c/p\u003e\u003cp\u003eTo date, our knowledge of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC is very limited. Using IHC and the data on differential gene expression between tumor and non-tumor tissues in human PC, only a few changes in the expression of specific markers/proteins have so far been reported in canine PC compared to normal and hyperplastic canine prostate. Similar to findings in humans, decresed expression of Nkx3.1 and overexpression of C-MYC [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], reduced expression of PTEN, p53, and the androgen receptor (AR), as well as increased expression of MDM2 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], have been observed. Likewise, elevated levels of HER-2, mTOR, and eIF4E proteins have been detected in canine PC compared with normal prostate [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In addition, loss of membranous E-cadherin, together with cytoplasmic and nuclear β-catenin staining, suggests that activation of the WNT/β-catenin pathway may play a role in the pathogenesis of canine PC. Despite the advantages of this approach, which strongly support the usefulness of canine PC as a model for studying human PC, these studies have a major limitation in that they cannot identify genes specifically involved in the development and progression of canine PC. Such limitations can be overcome using high-throughput methods such as whole-transcriptome RNA sequencing (RNA-Seq) or microarray profiling, which provide information on the expression of thousands of genes simultaneously. RNA-Seq revealed clear differences in gene expression profiles between non-malignant and malignant canine prostate tissue samples [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, most of these DEGs were mapped to at least one of 49 biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), suggesting that these pathways are deregulated in canine PC. Based on these data, the DEGs were grouped into five super-pathways named Inflammatory Response and Cytokines, Regulation of Immune System and Cell Death, Cell Cycle, Phagosome and Autophagy, and Cell Surface and PI3K Signaling. With this approach, a set of 16 DEGs representing the most interesting potential biomarkers was proposed, half of which have already been found to be associated with PC [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Similarly, using the microarray technique, 33 genes with significantly different expressions between PC and benign prostate tissues were identified [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. According to this data, AR-regulated genes and neuroendocrine-associated genes were downregulated in cancerous tissues. However, most previous reports lacked specific information on DEGs between PC and BPH tissues, as in these studies both normal and hyperplastic prostatic tissues were combined in the single control group. In the present study, only BPH tissue samples were used for comparison. This approach, aimed at identifying PC-specific genes, has a major advantage: it enables the exclusion of inflammation-related genes. Inflammation is one of the hallmarks of cancer [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and multiple lines of evidence link the pathogenesis of BPH with prostatic inflammation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Here, we compared the transcriptomes of canine BPH and PC to identify genes and their protein products that may serve as candidate diagnostic biomarkers for distinguishing between these two conditions. As noted above, the current understanding of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC remains limited and is still at an early exploratory stage, particularly in comparison with human PC. Consequently, the identification of canine PC-specific genes presents new opportunities to advance the field through the integration of molecular and cell biology approaches.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003ch2\u003e2.1. Tissue specimens and histochemistry\u003c/h2\u003e\n\u003cp\u003eThe study was conducted on prostate specimens collected from 15 dogs with PC and 7 dogs with BPH between 2017 and 2023. Dogs underwent surgery (prostate coagulation, prostatectomy, prostate biopsy, n=12) or euthanasia (n=6) at the Department and Clinic of Surgery, Faculty of Veterinary Medicine, University of Environmental and Life Sciences, Wroclaw, Poland. The remaining samples (n=4) were collected during the necropsy of animals performed within 24 hours of the animals\u0026rsquo; demise. All owners agreed to the necropsy. Dogs undergoing surgical treatment or euthanasia underwent computed tomography (CT) of the thorax and abdomen to assess the presence of metastatic lesions. According to owner reports, these dogs had no history of chronic systemic diseases and were not receiving any treatment prior to sample collection. Breed, age, neutering status. and TNM classification are presented in \u003cstrong\u003eTable 1\u003c/strong\u003e. For the dogs from which material was collected post-mortem, information on neutering status and health history was unavailable, which is a limitation of the study\u003cstrong\u003e.\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Specimen characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutering Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollection Procedure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHPDx\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eclassification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasurements performed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eRNA-Seq\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eNanostring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eWB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eIHC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003enecropsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003enecropsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003enecropsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003enecropsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT0N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT0N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eEntlebucher Mount. Dog\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003eBPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT0N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT2N1M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT1N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eeuthanasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT2N1M1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eeuthanasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT3N1M1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eFrench Bulldog\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eeuthanasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT2N1M1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eLabrador Retriever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT2N1M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMaltese Dog\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT3N1M1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT1N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT3N1M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eeuthanasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT3N1M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eStaffordshire Bull Terrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT1N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eBoxer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT1N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eeuthanasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT3N1M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003ePoodle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eeuthanasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT3N1M1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003esurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003ePC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eT1N0M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHPDx - Histopathological Diagnosis, WB \u0026ndash; Western blotting, IHC \u0026ndash; immunohistochemistry, TNM \u0026ndash; TNM Classification of Malignant Tumors \u003c/p\u003e\n\u003cp\u003eFor the histochemistry, the material was fixed in buffered 7% formalin and embedded in paraffin. The 3-\u0026micro;m-thick cut sections were mounted on Superfrost Plus slides, deparaffinized in xylene, and rehydrated to distilled water. The samples were then incubated in Mayer\u0026rsquo;s hematoxylin for 3 minutes and washed with three changes of tap water or until blue stopped coming off the slides. Following this, the slides were counterstained in alcoholic eosin for 10 seconds without rinsing, dehydrated through two changes of 95% ethanol, two changes of 100% ethanol, two changes of acetone, and cleared in two changes of xylene (10 seconds each). Finally, the slides were mounted with cover slides [26].\u003c/p\u003e\n\u003ch2\u003e 2.2. RNA isolation\u003c/h2\u003e\n\u003cp\u003eTotal RNA was purified from 30 milligrams of tissue using the RNeasy Fibrous Tissue Mini Kit (Qiagen) according to the manufacturer\u0026rsquo;s instructions. The protocol included on-column DNase digestion to remove genomic DNA. The purity and concentration of the RNA were assessed using a DS-11 FX spectrophotometer (Denovix), and its quality was assessed by Experion microchip electrophoresis (Biorad).\u003c/p\u003e\n\u003cp\u003eAll RNA samples met the quality control thresholds required for downstream analysis. Samples used for RNA-Seq had a mean RNA Integrity Number (RIN) of 8.4 (range: 7.6\u0026ndash;9.9) and a mean concentration of 723 \u0026micro;g/\u0026micro;l (range: 188\u0026ndash;1182 \u0026micro;g/\u0026micro;l). For the Nanostring assay, the mean RIN was 8.0 (range: 5.4\u0026ndash;9.6) with a mean concentration of 1064.4 \u0026micro;g/\u0026micro;l (range: 118\u0026ndash;2063 \u0026micro;g/\u0026micro;l) (\u003cstrong\u003eAdditional file 1. Supplementary Figure 1\u003c/strong\u003e).\u003c/p\u003e\n\u003ch2\u003e 2.3. RNA sequencing\u003c/h2\u003e\n\u003cp\u003eThe library was prepared using 350 ng of total RNA and the QuantSeq 3\u0026rsquo; mRNA library preparation FWD kit (Lexogen) according to the manufacturer\u0026rsquo;s instructions. Briefly, the first strand of cDNA was synthesized, RNA was removed, and the second strand was synthesized using Unique Molecular Identifiers (UMI). Library preparation encompassed 13 cycles of PCR enrichment (initial denaturation: 98 \u0026deg;C, 30 sec.; 13 cycles of 98 \u0026deg;C for 10 sec, 65 \u0026deg;C for 20 sec, 72 \u0026deg;C for 30 sec; final elongation: 72 \u0026deg;C, 1 min) followed by purification of the amplified product. Subsequent to this, a quality control assessment of the libraries was conducted using the Bioanalyser High Sensitivity DNA chip (Agilent Technologies). Thereafter, the libraries were quantitatively assessed by qPCR in accordance with the Illumina protocol. This facilitated the equimolar pooling of the libraries, which were subsequently sequenced on the NextSeq500 (Illumina) instrument using single reads of 75 base pairs on a high-output configuration.\u003c/p\u003e\n\u003cp\u003eReads trimmed and filtered with Trimmomatic [27] were mapped to the \u003cem\u003eC. lupus familiaris\u003c/em\u003e genome version CanFam3.1, annotation release 101, (GeneBank accession: GCF_000002285.3) using STAR v2.7.6a aligner [28]. RSEM v1.2.28 [29] was used to calculate gene count with \u0026ndash;rsem-calculate-expression option. The gene counts were made into a count table in R, where genes with no count and low count genes were filtered out. EdgeR v3.30.3 [30] package was used for normalization, calculating dispersion and testing for differential expression.\u003c/p\u003e\n\u003ch2\u003e 2.4. Targeted mRNA profiling\u003c/h2\u003e\n\u003cp\u003eTo evaluate the transcriptomic profiles custom NanoString CodeSet (NanoString Technologies) was utilized. Total RNA was extracted from fresh frozen samples using the RNeasy Fibrous Tissue Mini Kit (Qiagen). RNA samples were prepared by hybridization (65\u0026deg;C) to nCounter Reporter and Capture probes according to the manufacturer protocol. Subsequent to the automated sample cleanup, reporter capture, and alignment on the cartridge by the nCounter Prep Station, the RNA samples were deemed ready for analysis. The sample cartridges were then placed in the nCounter Digital Analyzer for data collection. The study incorporated 555 field-of-view readings, and nSolver 4.0.7 analysis software (NanoString) was employed for data analysis. This software included background correction (20 counts were designated as the background threshold) and normalization using both positive control and five reference (housekeeping) genes. \u003cem\u003eP\u003c/em\u003e-values were adjusted to account for multiple testing using the Benjamini-Hochberg false discovery rate (FDR) method and adjusted p-value \u0026le;0.05 was considered significant. The threshold value for significance was set at a fold change (FC) of \u0026ge;1.5 to identify DEGs.\u003c/p\u003e\n\u003cp\u003eThe Nanostring normalized data were calculated using the Rosalind web-based software with the settings described above for nSolver 4.0.7 analysis software (NanoString). For the calculation of the Z-values and creation of the gene expression heatmap, normalized expression data and the Heatmapper web-based tool was used [31]. The genes and samples were clustered using average linkage and Pearson Distance Measurement Method.\u003c/p\u003e\n\u003ch2\u003e 2.5. Western Blotting\u003c/h2\u003e\n\u003cp\u003eTissue samples, weighing 30 milligrams, were homogenized in 350 microliters of ice-cold RIPA buffer (50 mM Tris-HCl, 150 mM NaCl, 1.0% NP-40, pH 8.0). The resulting mixture was then subjected to a 30-minute incubation on ice. Subsequently, the samples were subjected to a centrifugal process at 16,000 \u0026times; g for 20 minutes at a temperature of 4\u0026deg;C. The resultant clear upper layer was collected and stored on ice. Protein quantification was performed using the BCA assay (Pierce) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003eProtein samples (30 \u0026mu;g) were prepared by mixing with 5x Laemmli buffer (containing 15% 2-mercaptoethanol) and subsequently denatured at 95\u0026deg;C for five minutes. Following this step, the samples were allowed to cool on ice, and then loaded onto mini-gels prepared with 7.5% or 12% TGX Stain-free Fast Cast Kit (Bio-Rad). Electrophoresis was conducted at 120 V. After 45 seconds UV-activation of the gel\u0026rsquo;s Stain-free chemistry, proteins were transferred to a PVDF membrane at 350 mA for 60 minutes, blocked for 1 hour in blocking buffer (5% skimmed milk, 0.05% Tween-20 in PBS) and then incubated with primary antibodies diluted in the blocking buffer (mouse-raised monoclonal antibody anti- voltage-gated calcium channel subunit \u0026alpha;2\u0026delta;1, Thermo-Fisher, cat.no MA3-921; rabbit monoclonal antibody anti-TOP2A, CST, cat. no. 12286T; rabbit polyclonal antibody anti-GOLGA4, CST, cat. no. 79145S; rabbit polyclonal antibodies anti-CLDN10, Abclonal, cat. no. A9853) overnight at 4 \u0026deg;C. The following day, the membrane was washed, and incubated for 1 hour at room temperature with anti-mouse HRP-conjugated antibody (Jackson ImmunoResearch, cat. no. 115-035-003, diluted 10000x) for \u0026alpha;2\u0026delta;1 detection, or with a goat polyclonal anti-rabbit HRP-conjugated antibody (DAKO, cat.no P044801-2, diluted 5000x) for detection of the remaining targets. Secondary antibodies were diluted in the blocking buffer. Following a thorough washing step, total protein was subjected to visualization through the implementation of the Stain-free chemistry method. The subsequent imaging of target-specific bioluminescent signals was conducted utilizing the SuperSignal West Femto ECL substrate (Pierce) and the Chemidoc Touch (Bio-Rad) imaging system. The densitometry analysis was performed by normalizing the bioluminescent signals against the total protein stain-free signal from the corresponding lane of the blot.\u003c/p\u003e\n\u003ch2\u003e 2.6. Immunohistochemistry\u003c/h2\u003e\n\u003cp\u003eFor IHC, FFPE tissues were freshly cut into 3-\u0026micro;m-thick sections and mounted on Superfrost Plus slides (Menzel Gl\u0026auml;ser). Staining was then performed on a LEICA BOND-MAX (Leica Biosystems) according to the following protocol. Initially, the tissues were deparaffinized using Bond Dewax Solution (Leica Biosystems) and then pre-treated with Bond Epitope Retrieval Solution 1 (Leica Biosystems) for a period of 20 minutes. The activity of the endogenous peroxidase was blocked by Peroxide Block using the BOND Polymer Refine Detection System (Leica Biosystems). Rabbit polyclonal antibodies against \u0026alpha;2\u0026delta;1 were purchased from ABclonal (cat.no A15260). The antibodies were diluted 1:100 with Bond Primary Antibody Diluent (Leica Biosystems) and sections were incubated with primary antibodies for 15 minutes at RT. The samples were then incubated with post-primary and polymer using the BOND Polymer Refine Detection System (Leica Biosystems). The reaction substrate was 3,3\u0026rsquo;-diaminobenzidine (DAB chromogen) and all sections were counterstained with hematoxylin (BOND Polymer Refine Detection System, Leica Biosystems). Control experiments were performed in the absence of primary antibody. The results of the immunohistochemical reaction were scored within each sample using a semiquantitative scoring system (0 - no staining, + (1) - low, ++ (2) - moderate, +++ (3) - high), taking into account the intensity of cell staining.\u003c/p\u003e\n\u003ch2\u003e 2.7. Statistical analysis\u003c/h2\u003e\n\u003cp\u003eStatistical analysis of the RNA-Seq and Nanostring data is described in their respective sections of the Methods. Data normality was assessed using the Shapiro-Wilk test. To evaluate differences in mean values for the Western Blot densitometry and IHC data between the BPH and PC groups, the Mann-Whitney U test was used. A \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003ch2\u003e 2.8. Availability of data and materials\u003c/h2\u003e\n\u003cp\u003eRNA-Seq and Nanostring data were deposited into the Gene Expression Omnibus database under accession numbers GSE299084 and GSE299093, respectively. These data are available at the following URLs: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299084,\u003c/p\u003e\n\u003cp\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299093.\u003c/p\u003e\n\u003cp\u003eThe remaining data supporting the conclusions of this article are included within the article, and additional files, and are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eEach tissue specimen was divided into three parts: fresh-frozen, RNA-later-treated-frozen and formalin fixed paraffin embedded (FFPE). RNA-later\u0026ndash;treated frozen tissue samples from dogs 3, 4, 5, 10, and 18 were used for RNA-seq, and all such samples, except one, were used for Nanostring; fresh frozen tissue samples from 13 dogs (1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 14, 15, 22) were used for WB; FFPE sections from 15 dogs (1, 2, 3, 5, 7, 9, 12,\u0026nbsp;15\u0026ndash;22) were used for IHC (Table 1). Sample selection criteria differed between the initial transcriptomic profiling and subsequent experiments. For the RNA-Seq analysis, conducted on a preliminary set of samples, specimens with the highest RIN were chosen. Following the completion of sample collection, tissues for Nanostring, WB, and IHC validation were selected based on availability.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;3.1. Comparative molecular profiling of prostate carcinoma and benign prostate hyperplasia\u003c/h2\u003e\n\u003cp\u003eRNA-Seq data from two PC tissues and three BPH tissues subjected to bioinformatic analysis revealed 2923 DEGs out of a total of 12 185 genes identified in the studied samples (\u003cstrong\u003eAdditional file 1,\u003c/strong\u003e \u003cstrong\u003eSupplementary Figure 2\u003c/strong\u003e). After subjecting the RNA-Seq data to principal component analysis (PCA), it was established that the substantial disparities (65%) in transcriptomic profiles between PC and BPH samples were in congruence with the histopathological evaluation of the corresponding tissue specimens (\u003cstrong\u003eFig. 1A\u003c/strong\u003e). Nevertheless, PCA also revealed heightened heterogenicity between PC samples as opposed to BPH samples. Among the DEGs exhibiting at least a minimum expression level in both groups, 114 genes demonstrated significant upregulation, while 92 genes exhibited significant downregulation in the PC samples compared to the BPH specimens. These genes were selected based on a log\u003csub\u003e2\u003c/sub\u003e-fold change (log\u003csub\u003e2\u003c/sub\u003eFC) less than -2 or greater than 2, the FDR less than 0.05, and a mean normalized counts per million (CPM) greater than 10 in each group (\u003cstrong\u003eFig. 1B;\u003c/strong\u003e \u003cstrong\u003eAdditional file 2. Supplementary Table 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eIn the next step, 19 upregulated and 7 downregulated DEGs were selected to validate the RNA-Seq data using the Nanostring technology on a larger (n = 14 PC, n = 7 BPH) patient cohort (\u003cstrong\u003eFigure 1B\u003c/strong\u003e; \u003cstrong\u003eAdditional file 2, Supplementary Table 1\u003c/strong\u003e). In most cases, this selection was based on the highest FC, but based on the literature data some of the genes were excluded (\u003cem\u003eSELP\u003c/em\u003e, \u003cem\u003eRGS4\u003c/em\u003e, \u003cem\u003eMATN2\u003c/em\u003e, \u003cem\u003eMATN4\u003c/em\u003e, \u003cem\u003eCHAF1A\u003c/em\u003e, \u003cem\u003eNUP107\u003c/em\u003e, \u003cem\u003eATF3\u003c/em\u003e), and some, with lower FC, were added to the validation set (\u003cem\u003eCLU\u003c/em\u003e, \u003cem\u003eGOLGA4\u003c/em\u003e, \u003cem\u003eSERPINB6\u003c/em\u003e). The total RNA isolated from fresh frozen tissue samples was subjected to PCR-free targeted mRNA profiling by Direct Digital Detection. The complete results are presented as a heatmap of normalized gene expression (\u003cstrong\u003eFigure 2A\u003c/strong\u003e). The cluster consisting of PC overexpressed genes was further divided into two subclusters. The three genes highly upregulated in PC samples compared to BPH, \u003cem\u003eTSPAN8\u003c/em\u003e, \u003cem\u003eCLU\u003c/em\u003e and \u003cem\u003eCHI3L1\u003c/em\u003e, represented the first sub-cluster. Whereas the remaining genes (\u003cem\u003eASPM, TOP2A, HELLS, COL6A3, IGFBP2, MSH6, SULF2, MSH2, IGFBP5, SMOC2, FBN2, SGO2, CENPF, GLI1\u003c/em\u003e), representing the second sub-cluster, did not show such robust differences between the study groups. The cluster of PC underexpressed genes contained 8 genes \u003cem\u003e(NKX3.1, CLDN10, ATP6V0A4, KLK2, CD303\u003c/em\u003e, \u003cem\u003eGOLGA4A\u003c/em\u003e, \u003cem\u003eCACNA2D1\u003c/em\u003e and \u003cem\u003eSERPINB6\u003c/em\u003e), among which the last three showed the most similar expression pattern. Based on NanoString assay, we found statistically significant differences in the expression of the following 12 genes: \u003cem\u003eASPM, ATP6V0A4, CACNA2D1\u003c/em\u003e, \u003cem\u003eCLDN10\u003c/em\u003e, \u003cem\u003eCLU, GOLGA4\u003c/em\u003e, \u003cem\u003eHELLS\u003c/em\u003e, \u003cem\u003eKLK2, NKX3.1\u003c/em\u003e, \u003cem\u003eSERPINB6\u003c/em\u003e, \u003cem\u003eTOP2A\u003c/em\u003e, and \u003cem\u003eTSPAN8\u003c/em\u003e (\u003cstrong\u003eFigure 2B, Table 2\u003c/strong\u003e). Five of these genes: \u003cem\u003eTSPAN8\u003c/em\u003e, \u003cem\u003eASPM\u003c/em\u003e, \u003cem\u003eCLU\u003c/em\u003e, \u003cem\u003eTOP2A\u003c/em\u003e, and \u003cem\u003eHELLS\u003c/em\u003e were overexpressed in PC compared to BPH, while the remaining were downregulated in PC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Results of Nanostring gene expression analysis for PC vs BPH group.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"425\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLog\u003csub\u003e2\u003c/sub\u003eFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eadj. P-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASPM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.63\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTSPAN8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOP2A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCLU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHELLS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.69\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0050\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eCOL6A3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.0643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eCHI3L1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.1176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eIGFBP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.0932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eMSH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.1075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eSULF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.0895\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eMSH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.1176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eIGFBP5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.3107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.3522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eSMOC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.6420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.6615\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eFBN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.7353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.7353\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eSGO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.5242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.5570\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eCENPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.4012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.4400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eCD302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.1176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eNPTX1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.1296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.1632\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOLGA4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eGLI1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.0380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.0646\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSERPINB6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.61\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCACNA2D1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-6.09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eATP6V0A4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-7.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCLDN10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-8.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNKX3-1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-8.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKLK2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-12.73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBolded font marks genes showing statistically significant differential expression.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;3.2. Validation of selected DEG expression on the protein level\u003c/h2\u003e\n\u003cp\u003eIn order to provide further validation of the data on protein level, the expression of DEGs was analyzed employing WB and IHC. The targets for protein-level validation via immunochemical methods were selected from the set of Nanostring-confirmed DEGs based on the commercial availability of antibodies. The qualified antibodies were directed against human antigenic epitopes which share over 90% sequence homology with canine epitopes and preferably were monoclonal. Therefore, the following DEGs were subjected to analysis by WB: \u003cem\u003eTOP2\u003c/em\u003e, \u003cem\u003eGOLGA4\u003c/em\u003e, \u003cem\u003eCLDN10\u003c/em\u003e, and \u003cem\u003eCACNA2D1\u003c/em\u003e. Despite the availability of antibodies, the NKX3.1 protein and kallikrein-related peptidase 2 (encoded by the \u003cem\u003eKLK2\u003c/em\u003e gene) were excluded from WB analysis due to their well-documented association with PC.\u003c/p\u003e\n\u003cp\u003eWB analysis using mouse monoclonal antibodies directed against voltage-dependent \u0026alpha;2\u0026delta;1 revealed the presence of an intense band with an apparent molecular mass of approximately 150 kDa in tissue lysates from BPH, which was barely detectable PC protein extracts (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). Densitometric analysis showed that the mean normalized volume of the \u0026alpha;2\u0026delta;1 band is 11 times lower in PC than in BPH and the difference is statistically significant. Spearman\u0026rsquo;s correlation analysis shows a strong significant positive correlation between the expression of \u0026alpha;2\u0026delta;1 protein and mRNA (r\u003csub\u003es\u003c/sub\u003e = 0.81; \u003cem\u003ep\u003c/em\u003e = 0.0014) (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). These findings were further confirmed by IHC. The expression of \u0026alpha;2\u0026delta;1 in paraffin sections of PC and BPH tissue samples was analyzed using the rabbit polyclonal antibodies. On average, PC samples stained weaker with the anti-\u0026alpha;2\u0026delta;1 antibody than the BPH samples (\u003cstrong\u003eFigure 3B, Table 3\u003c/strong\u003e). No binding to canine proteins was observed in the case of antibodies directed against DNA topoisomerase II\u0026alpha; (coded by \u003cem\u003eTOP2A\u003c/em\u003e), Golgin subfamily A member/GOLGA4 protein (coded by \u003cem\u003eGOLGA4\u003c/em\u003e), and claudin-10 (coded by \u003cem\u003eCLDN10\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003eTable 3. A summary of the semiquantitative assessment of \u0026alpha;2\u0026delta;1 immunohistochemical labeling in the canine prostate gland with prostate cancer (PC) and benign prostatic hyperplasia (BPH)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"356\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHistopathological diagnosis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistribution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStaining\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eintensity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003eBPH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003eBPH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003every low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003eBPH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003eBPH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e+++\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003eBPH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e++\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003every low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003every low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0/+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e+/++\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003every low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003every low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDog 22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cem\u003ePC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eabsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSamples were grouped in 6 categories based on the number of cells positive for \u0026alpha;2\u0026delta;1 expression: absent (0% labelled cells), very low (1-5% labelled cells), low (6-20% labelled cells), moderate (21-50% labelled cells), high (51-60% labelled cells), very high (\u0026gt;60% labelled cells). Staining intensity: (0) absent, (+) weak, (++) moderate, (+++) intense.\u003c/p\u003e"},{"header":" 4. Discussion","content":"\u003cp\u003eIn the case of canine PC, knowledge of its molecular mechanisms and regulatory networks is mostly derived from comparative studies and is limited to changes in the expression of a few genes/proteins known from studies of human PC pathogenesis [32]. These limitations could be overcome using high-throughput methods, but screening of PC tissue versus benign prostate tissue using such an approach, involving the analysis of thousands of genes, has only been performed a few times, and none of these reports supported their findings with a protein-level data. Thiemeyer et al. [33] used RNA-Seq to compare gene expression profiles in malignant and non-malignant prostate tissues to identify potential biomarkers associated with the development and progression of canine PC. As many as 4098 DEGs were found between PC and benign prostate samples, and 688 proteins encoded by these genes were associated with specific biological processes, such as inflammatory response and cytokines, regulation of the immune system and cell death, cell cycle, phagosome and autophagy, and cell surface and PI3K signaling, which are known to be highly deregulated in cancer in general. These cellular processes were described by the authors as \u0026ldquo;hallmarks of canine PC\u0026rdquo;. Taking into account their own RNA-Seq data and information from databases and literature on PC-associated genes, the following 16 DEGs were selected as the most promising potential biomarkers of canine PC: \u003cem\u003eAR, CDKN1A, CTNNB1, EGFR, KLK2, NKX3.1, PDGFRA, SRD5A2, CREB3L4, PDGFRB, NRAS, PIK3CD, PIK3CG, KLK4, KIT,\u003c/em\u003e and \u003cem\u003eABCB1.\u003c/em\u003e It should be pointed out that majority of these canine PC-associated genes (13) are also deregulated in human PC (\u003cem\u003eSRD5A2, KLK2, NKX3-1, CREB3L4, EGFR, PDGFRA, PDGFRB, NRAS, PIK3CD, CTNNB1, PIK3CG,\u003c/em\u003e and \u003cem\u003eCDKN1A\u003c/em\u003e) and are used in commercial PC multi-gene assays. This study was performed using PC specimens from intact as well as neutered dogs. Another study used only the castrated dog cohort to compare gene expression profiles between PC and benign prostate tissue specimens by microarray analysis [21]. A set of 33 genes was identified that showed significantly different expression levels between cancerous and benign tissues. Since canine PC resembles human CRPC in many ways, their gene expression profiles were compared, and five of these genes - \u003cem\u003eISG15, AZGP1, GPX3, S100P, and IFITM1\u003c/em\u003e - also showed similar differences in expression compared to human prostate tissue. Both studies confirmed that canine and human PC share many similarities not only clinically but also at the molecular level, but the gene expression profiles were very different, with only two common genes: \u003cem\u003eKLK2\u003c/em\u003e and \u003cem\u003eNKX3.2.\u003c/em\u003e It should be noted that in both cases the mRNAs isolated from cancerous tissues were compared with the mixture of mRNAs purified from normal as well as hyperplastic prostate tissues, and it should be emphasized that several lines of evidence link the pathogenesis of BPH with prostatic inflammation [24, 25]. Since inflammation is one of the hallmarks of cancer [22, 34], this approach does not allow us to clearly separate inflammation-related genes from those directly involved in the development and progression of PC. Moreover, previous studies did not validate RNA-Seq and microarray data with complementary analyses. Therefore, in this study only BPH tissues were used to identify PC-specific genes using RNA-Seq. It should be noted that the QuantSeq method employed here sequences only the 3\u0026prime; end of polyadenylated RNAs, which makes it cost-effective and suitable for degraded samples. However, in contexts different from ours, this approach has serious limitations, as it does not allow the reconstruction of full-length mRNA sequences or the detection of alternative splicing events and gene fusions, which can be identified using standard RNA-Seq. Finally, the selected DEGs were validated by NanoString, Western blotting, and IHC.\u003c/p\u003e\n\n\u003cp\u003eA comprehensive analysis of the RNA-Seq data revealed a significant upregulation of 114 genes and a significant downregulation of 92 genes in PC samples compared to BPH samples. To validate the findings, the RNA-Seq data underwent additional rigorous bioinformatic analysis, which enabled the selection of 26 genes with the most significant FC between PC and BPH tissues for analysis by Nanostring. Thereby, significant differences were identified for the following 12 genes: \u003cem\u003eASPM, ATP6V0A4, CACNA2D1, CLDN10, CLU, GOLGA4, HELLS, KLK2, NKX3.1, SERPINB6, TOP2A,\u003c/em\u003e and \u003cem\u003eTSPAN8.\u003c/em\u003e Five of these genes: \u003cem\u003eTSPAN8, ASPM, CLU, TOP2A\u003c/em\u003e, and \u003cem\u003eHELLS\u003c/em\u003e were overexpressed in PC compared to BPH, while the rest of them were downregulated in PC. When these results were compared with previous transcriptomic data [21, 33], two of these genes: \u003cem\u003eKLK2\u003c/em\u003e and \u003cem\u003eNKX3.1\u003c/em\u003e were also found to be downregulated in PC compared to non-malignant prostate tissues in both analyses, which strongly indicates that their suppressed expression is the hallmark of canine PC. It is worth noting that differences in the expression of\u003cem\u003e KLK2\u003c/em\u003e and \u003cem\u003eNKX3.1\u003c/em\u003e genes between malignant and non-malignant tissues were confirmed at the protein level using IHC and Western blotting [12,13, 35]. \u003cem\u003eKLK2\u003c/em\u003e encodes kallikrein-related peptidase (Klk2) and, in contrast to dogs, its expression in humans is higher in PC than in benign prostate tissue, where it is recognized as a biomarker associated with prostate cancer risk [36, 37]. In humans, Klk2 promotes PC cell growth and is involved in tumor metastasis [38]; however, in canine PC, its role remains completely unknown. The expression of Nkx3.1, the product of a prostate-specific tumor suppressor gene, is also markedly decreased in human PC [39, 40]. This transcription factor plays a key role in normal prostate development and tumor suppression as a negative regulator of epithelial cell growth in prostate tissue [41, 42]. However, its specific role in the development and progression of canine PC has never been investigated in experimental studies using cellular models. In addition to these genes, the downregulation of two other genes, \u003cem\u003eCLDN10\u003c/em\u003e and \u003cem\u003eCACNA2D1\u003c/em\u003e, was also observed in transcriptomic studies, but this finding has not been validated at the protein level [21].\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eUsing the NanoString assay, statistically significant differences in the expression of the following 12 genes on the level of mRNA were confirmed: \u003cem\u003eASPM, ATP6V0A4, CACNA2D1, CLDN10, CLU, GOLGA4, HELLS, KLK2, NKX3.1, SERPINB6, TOP2A, \u003c/em\u003eand \u003cem\u003eTSPAN8\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e The protein products of these genes were subsequently subjected to validation by WB and IHC. However, protein-level validation of the DEGs using specific antibodies revealed only a markedly reduced expression of the voltage-gated calcium channel subunit \u0026alpha;2\u0026delta;1, encoded by the \u003cem\u003eCACNA2D1\u003c/em\u003e gene, in PC samples compared to BPH. Antibodies directed against human TOP2, GOLGA4, and CLDN10 proteins did not bind to the canine ortologs. This is likely due to the absence of cross-reactivity with canine proteins, which highlights the challenges associated with the limited availability of species-specific antibodies targeting canine proteins. At the research level, this issue can be addressed by employing alternative approaches such as mass spectrometry, particularly in combination with liquid chromatography (LC/MS/MS). Nevertheless, given the complexity of this technique, which requires specialized equipment and expertise, it cannot replace immunological methods in routine veterinary diagnostics.\u003c/p\u003e\n\u003cp\u003eLittle is known about the role of the \u0026alpha;2\u0026delta;1 subunit of the calcium channel in the development and progression of cancer. To date, \u0026alpha;2\u0026delta;1 has been shown to be involved in the self-renewal and tumorigenicity of human hepatocellular carcinoma (HCC) tumor-initiating cells (TICs) [43] and recognized as a TIC marker in non-small cell lung carcinoma[44]. HCC TICs with high expression of \u0026alpha;2\u0026delta;1 were also more invasive and resistant to apoptosis than their \u0026alpha;2\u0026delta;1-negative counterparts. At the molecular level, \u0026alpha;2\u0026delta;1 isoform 5 was found to play a key role in modulating calcium influx as a subunit of L- and N-type voltage-gated calcium channels, which in turn activates the ERK1/2 signaling pathway. Therefore, in the case of human HCC, voltage-gated calcium channel subunit \u0026alpha;2\u0026delta;1 seems to play an important role in its development and progression/recurrence, acting as an oncogenic protein. Interestingly, in the case of canine prostate cancer cells, downregulation of \u003cem\u003eCACNA2D1\u003c/em\u003e gene expression suggests the suppressive role of \u0026alpha;2\u0026delta;1 in PC development and progression. Further studies using cellular models are needed to answer this question.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIt should be emphasized that dogs with PC or BPH, in contrast to healthy dogs, may present in the clinic with similar clinical signs, such as straining to urinate, pollakiuria, hematuria, or constipation, which greatly hinders and often prevents distinguishing between these two conditions. Therefore, our findings identify the \u0026alpha;2\u0026delta;1 subunit as a novel and promising diagnostic biomarker for differentiating PC from BPH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering the availability of aspirates collected by ultrasound-guided fine-needle aspiration (US-FNA) biopsy or less invasive prostatic catheter biopsy of the canine urethra, which are used in the diagnosis of various canine prostatic diseases through different diagnostic approaches [45], e.g., flow cytometric phenotyping [46], further studies are warranted to confirm the usefulness of this biomarker in the differential diagnosis of PC and BPH. To build upon these findings and confirm the biomarker\u0026apos;s utility across diverse datasets, the field would benefit from a large-scale meta-analysis. However, we stress that such a study would require a dedicated, harmonized reprocessing of all available raw data to properly account for technical confounders.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLast but not least, the role of \u0026alpha;2\u0026delta;1 in prostate cancer biology remains unclear and requires further study using prostate cancer cell line models.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u0026alpha;2\u0026delta;1 \u0026ndash; voltage-gated calcium channel alpha-2 delta-1 subunit\u003c/p\u003e\n\u003cp\u003eAR \u0026ndash; androgen receptor\u003c/p\u003e\n\u003cp\u003eBPH \u0026ndash; benign prostate hyperplasia\u003c/p\u003e\n\u003cp\u003eCPM \u0026ndash; counts per million\u003c/p\u003e\n\u003cp\u003eCRPC \u0026ndash; castration-resistant prostate cancer\u003c/p\u003e\n\u003cp\u003eDAB \u0026ndash; 3,3\u0026rsquo;-diaminobenzidine\u003c/p\u003e\n\u003cp\u003eDEG \u0026ndash; differentially expressed gene\u003c/p\u003e\n\u003cp\u003eFC \u0026ndash; fold change\u003c/p\u003e\n\u003cp\u003eFDR \u0026ndash; false discovery rate\u003c/p\u003e\n\u003cp\u003eFFPE \u0026ndash; formalin-fixed paraffin-embedded\u003c/p\u003e\n\u003cp\u003eHPDx -\u0026nbsp;Histopathological Diagnosis\u003c/p\u003e\n\u003cp\u003eHCC \u0026ndash; human hepatocellular carcinoma\u003c/p\u003e\n\u003cp\u003eIHC \u0026ndash; immunohistochemistry\u003c/p\u003e\n\u003cp\u003eKEGG \u0026ndash; Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003ePC \u0026ndash; prostate cancer\u003c/p\u003e\n\u003cp\u003ePCA \u0026ndash; principal component analysis\u003c/p\u003e\n\u003cp\u003ePIA \u0026ndash; prostatic inflammatory atrophy\u003c/p\u003e\n\u003cp\u003eRNA-Seq \u0026ndash; RNA sequencing\u003c/p\u003e\n\u003cp\u003eTIC \u0026ndash; tumor-initiating cell\u003c/p\u003e\n\u003cp\u003eTNM- Tumor Nodes Metastasis Classification of Malignant Tumors\u003c/p\u003e\n\u003cp\u003eUMI \u0026ndash; unique molecular identifiers\u003c/p\u003e\n\u003cp\u003eWB \u0026ndash; Western blotting\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study followed the national guidelines of The Experiments on Animals Act published on January 15\u003csup\u003eth\u003c/sup\u003e, 2015 (Journal of Laws of the Republic of Poland, 2015, item. 266), and has been granted an exemption from requiring ethics approval by an institutional Animal Welfare Advisory Team (decision no. 11/2025). The study involved client-owned animals. Written informed consent was obtained from all owners before participation. All owners agreed to an autopsy. All efforts were made to minimize animal discomfort and ensure well-being throughout the study.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eRNA-Seq and Nanostring data were deposited into the Gene Expression Omnibus database under accession numbers GSE299084 and GSE299093, respectively. These data are available at the following URLs: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299084,\u003c/p\u003e\n\u003cp\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299093,.\u003c/p\u003e\n\u003cp\u003eThe remaining data supporting the conclusions of this article are included within the article, and additional files, and are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research was funded in part by the National Science Center (Poland) Miniatura 2021/05/X/NZ5/01570.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Wroclaw University of Environmental and Life Sciences (Poland) as part of the research project no. N090/0002/23.\u003c/p\u003e\n\u003cp\u003eFor the purpose of Open Access, the author has applied a CC-BY public copyright license to any Author Accepted Manuscript (AAM) version arising from this submission.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eMZ:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - Original Draft, Writing - Review \u0026amp; Editing, Visualization, Project administration, Funding acquisition.\u0026nbsp;\u003cstrong\u003eMU:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Resources, Writing - Original Draft, Writing - Review \u0026amp; Editing, Funding acquisition.\u0026nbsp;\u003cstrong\u003ePP:\u003c/strong\u003e Methodology, Validation, Investigation, Resources.\u0026nbsp;\u003cstrong\u003eSD:\u003c/strong\u003e Methodology, Validation, Resources, Writing - Review \u0026amp; Editing.\u0026nbsp;\u003cstrong\u003eSS\u003c/strong\u003e Methodology, Validation, Formal analysis, Resources, Writing - Review \u0026amp; Editing, Visualization.\u0026nbsp;\u003cstrong\u003eIS:\u003c/strong\u003e Methodology, Validation, Formal analysis, Investigation, Writing - Review \u0026amp; Editing.\u0026nbsp;\u003cstrong\u003eAK:\u003c/strong\u003e Resources.\u0026nbsp;\u003cstrong\u003eBL:\u003c/strong\u003e Methodology Investigation.\u0026nbsp;\u003cstrong\u003ePS:\u003c/strong\u003e Methodology Investigation.\u0026nbsp;\u003cstrong\u003eFVN:\u003c/strong\u003e Methodology, Resources, Writing - Review \u0026amp; Editing.\u0026nbsp;\u003cstrong\u003eAT:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDavis BW, Ostrander EA. Domestic dogs and cancer research: A breed-based genomics approach. ILAR journal. 2014;55:59\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eJohnston SD, Kamolpatana K, Root-Kustritz MV, Johnston GR. Prostatic disorders in the dog. Animal Reproduction Science. 2000;60-61:405\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eKrook L. A statistical investigation of carcinoma in the dog. Acta pathologica et microbiologica Scandinavica. 1954;35:407\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eBell FW, Klausner JS, Hayden DW, Feeney DA, Johnston SD. Clinical and pathologic features of prostatic adenocarcinoma in sexually intact and castrated dogs: 31 cases (1970-1987). Journal of the American Veterinary Medical Association. 1991;199:1623\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eLai CL, Ham RVD, Leenders GV, Lugt JVD, Mol JA, Teske E. Histopathological and immunohistochemical characterization of canine prostate cancer. The Prostate. 2008;68:477\u0026ndash;88.\u003c/li\u003e\n\u003cli\u003eLeRoy BE, Northrup N. Prostate cancer in dogs: Comparative and clinical aspects. Veterinary journal (London, England : 1997). 2009;180:149\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eCornell KK, Bostwick DG, Cooley DM, Hall G, Harvey HJ, Hendrick MJ, et al. Clinical and pathologic aspects of spontaneous canine prostate carcinoma: A retrospective analysis of 76 cases. The Prostate. 2000;45:173\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eLeRoy BE, Thudi NK, Nadella MVP, Toribio RE, Tannehill-Gregg SH, Bokhoven AV, et al. New bone formation and osteolysis by a metastatic, highly invasive canine prostate carcinoma xenograft. The Prostate. 2006;66:1213\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eLeav I, Ling GV. Adenocarcinoma of the canine prostate. Cancer. 1968;22:1329\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eKirby M, Hirst C, Crawford ED. Characterising the castration-resistant prostate cancer population: A systematic review. International journal of clinical practice. 2011;65:1180\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eWaters DJ, Patronek GJ, Bostwick DG, Glickman LT. Comparing the age at prostate cancer diagnosis in humans and dogs. Journal of the National Cancer Institute. 1996;88:1686\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eFonseca-Alves CE, Kobayashi PE, Laufer-Amorim R. Evaluation of NKX3.1 and c-MYC expression in canine prostatic cancer. Research in veterinary science. 2018;118:365\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eFonseca-Alves CE, Rodrigues MMP, Moura VMBD de, Rogatto SR, Laufer-Amorim R. Alterations of c-MYC, NKX3.1, and e-cadherin expression in canine prostate carcinogenesis. Microscopy research and technique. 2013;76:1250\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eRivera-Calder\u0026oacute;n LG, Fonseca-Alves CE, Kobayashi PE, Carvalho M, Drigo SA, Oliveira Vasconcelos R de, et al. Alterations in PTEN, MDM2, TP53 and AR protein and gene expression are associated with canine prostate carcinogenesis. Research in veterinary science. 2016;106:56\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eLin HY, Palmieri C. Is STAT3 and PTEN expression altered in canine prostate cancer? Journal of comparative pathology. 2016;155:185\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eRivera-Calder\u0026oacute;n LG, Fonseca-Alves CE, Kobayashi PE, Carvalho M, Vasconcelos RO, Laufer-Amorim R. p-mTOR, p-4EBP-1 and eIF4E expression in canine prostatic carcinoma. Research in veterinary science. 2019;122:86\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eSakai K, Shinohara Y, Kaji K, Yonezawa T, Momoi Y, Maeda S. Human epidermal growth factor receptor 2 is overexpressed in canine prostate carcinoma. Translational and Regulatory Sciences. 2021;3:1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eFaleiro MBR, Cintra LC, Jesuino RSA, Ara\u0026uacute;jo EG de, Rocha RM, Moura VMBD de. Expression of EGF receptors in canine prostate with proliferative inflammatory atrophy and carcinoma. Ci\u0026ecirc;ncia Rural. 2017;47:e20170085.\u003c/li\u003e\n\u003cli\u003eThiemeyer H, Taher L, Schille JT, Harder L, Hungerbuehler SO, Mischke R, et al. Suitability of ultrasound-guided fine-needle aspiration biopsy for transcriptome sequencing of the canine prostate. Scientific Reports. 2019;9:1\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eThiemeyer H, Taher L, Schille JT, Packeiser EM, Harder LK, Hewicker-Trautwein M, et al. An RNA-Seq-Based Framework for Characterizing Canine Prostate Cancer and Prioritizing Clinically Relevant Biomarker Candidate Genes. International journal of molecular sciences. 2021;22.\u003c/li\u003e\n\u003cli\u003eAngel MR, S\u0026eacute;guin B, L\u0026ouml;hr CV, Beer TM, Feliciano J, Ramsey SA, et al. Comparative transcriptomes of canine and human prostate cancers identify mediators of castration resistance. Veterinary and comparative oncology. 2024;22.\u003c/li\u003e\n\u003cli\u003eGreten FR, Grivennikov SI. Inflammation and cancer: Triggers, mechanisms, and consequences. Immunity. 2019;51:27\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eMa Y, Yang X, Zhao W, Yang Y, Zhang Z. Calcium channel \u0026alpha;2\u0026delta;1 subunit is a functional marker and therapeutic target for tumor-initiating cells in non-small cell lung cancer. Cell Death \u0026amp; Disease 2021 12:3. 2021;12:1\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eChughtai B, Forde JC, Thomas DDM, Laor L, Hossack T, Woo HH, et al. Benign prostatic hyperplasia. Nature reviews Disease primers. 2016;2:1\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eBriganti A, Capitanio U, Suardi N, Gallina A, Salonia A, Bianchi M, et al. Benign Prostatic Hyperplasia and Its Aetiologies. European Urology, Supplements. 2009;8:865\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eFeldman AT, Wolfe D. Tissue processing and hematoxylin and eosin staining. Methods in molecular biology (Clifton, NJ). 2014;1180:31\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eBolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics (Oxford, England). 2014;30:2114\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eDobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eLi B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323.\u003c/li\u003e\n\u003cli\u003eRobinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eBabicki S, Arndt D, Marcu A, Liang Y, Grant JR, Maciejewski A, et al. Heatmapper: Web-enabled heat mapping for all. Nucleic acids research. 2016;44:W147\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003ePaula Nascente E de, Amorim RL, Fonseca-Alves CE, Moura VMBD de. Comparative pathobiology of canine and human prostate cancer: State of the art and future directions. Cancers. 2022;14.\u003c/li\u003e\n\u003cli\u003eThiemeyer H, Taher L, Schille JT, Packeiser EM, Harder LK, Hewicker-Trautwein M, et al. An RNA-seq-based framework for characterizing canine prostate cancer and prioritizing clinically relevant biomarker candidate genes. International journal of molecular sciences. 2021;22.\u003c/li\u003e\n\u003cli\u003eZhao H, Wu L, Yan G, Chen Y, Zhou M, Wu Y, et al. Inflammation and tumor progression: Signaling pathways and targeted intervention. Signal Transduction and Targeted Therapy 2021 6:1. 2021;6:1\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eFonseca-Alves CE, Kobayashi PE, Calder\u0026oacute;n LGR, Felisbino SL, Carvalho Rinaldi J de, Drigo SA, et al. Immunohistochemical panel to characterize canine prostate carcinomas according to aberrant p63 expression. PLOS ONE. 2018;13:e0199173. \u003c/li\u003e\n\u003cli\u003eHannu K, Johanna M, Ulf-H\u0026aring;kan S. KLK-targeted therapies for prostate cancer. EJIFCC. 2014;25:207.\u003c/li\u003e\n\u003cli\u003eKlein RJ, Halld\u0026eacute;n C, Cronin AM, Ploner A, Wiklund F, Bjartell AS, et al. Blood biomarker levels to aid discovery of cancer-related single-nucleotide polymorphisms: Kallikreins and prostate cancer. Cancer Prevention Research. 2010;3:611\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eShang Z, Niu Y, Cai Q, Chen J, Tian J, Yeh S, et al. Human kallikrein 2 (KLK2) promotes prostate cancer cell growth via function as a modulator to promote the ARA70-enhanced androgen receptor transactivation. Tumor Biology. 2014;35:1881\u0026ndash;90.\u003c/li\u003e\n\u003cli\u003eAsatiani E, Huang WX, Wang A, Ortner ER, Cavalli LR, Haddad BR, et al. Deletion, methylation, and expression of the NKX3.1 suppressor gene in primary human prostate cancer. Cancer Research. 2005;65:1164\u0026ndash;73.\u003c/li\u003e\n\u003cli\u003eBowen C, Bubendorf L, Voeller HJ, Slack R, Willi N, Sauter G, et al. Loss of NKX3.1 expression in human prostate cancers correlates with tumor progression 1,2. Cancer Genetics Branch. 2000;60:20892\u0026ndash;4470.\u003c/li\u003e\n\u003cli\u003eShen MM, Abate‐Shen C. Roles of the Nkx3.1 homeobox gene in prostate organogenesis and carcinogenesis. Developmental Dynamics. 2003;228:767\u0026ndash;78.\u003c/li\u003e\n\u003cli\u003eBudreika A, Phoenix JT, Kostlan RJ, Deegan CD, Ferrari MG, Young KS, et al. The homeobox transcription factor NKX3.1 displays an oncogenic role in castration-resistant prostate cancer cells. Cancers. 2025;17:306\u003c/li\u003e\n\u003cli\u003eZhao W, Wang L, Han H, Jin K, Lin N, Guo T, et al. 1B50-1, a mAb raised against recurrent tumor cells, targets liver tumor-initiating cells by binding to the calcium channel \u0026alpha;2\u0026delta;1 subunit. Cancer Cell. 2013;23:541\u0026ndash;56.\u003c/li\u003e\n\u003cli\u003eMa Y, Yang X, Zhao W, Yang Y, Zhang Z. Calcium channel \u0026alpha;2\u0026delta;1 subunit is a functional marker and therapeutic target for tumor-initiating cells in non-small cell lung cancer. Cell Death \u0026amp; Disease 2021 12:3. 2021;12:1\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eRodak O, Dzimira S, Podolak A, Pł\u0026oacute;ciennik M, Niżański W. Accuracy of ultrasonography and fine-needle aspiration cytology in the diagnosis of prostate diseases in dogs. Reproduction in Domestic Animals. 2018;53:79\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eAresu L, Aric\u0026ograve; A, Ferraresso S, Martini V, Comazzi S, Riondato F, et al. Minimal residual disease detection by flow cytometry and PARR in lymph node, peripheral blood and bone marrow, following treatment of dogs with diffuse large b-cell lymphoma. Veterinary Journal. 2014;200:318\u0026ndash;24.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-veterinary-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Veterinary Research](http://bmcvetres.biomedcentral.com/)","snPcode":"12917","submissionUrl":"https://submission.nature.com/new-submission/12917/3?","title":"BMC Veterinary Research","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"canine prostate cancer, benign prostate hyperplasia, gene-expression profiling, calcium channel subunit α2δ1, CACNA2D1","lastPublishedDoi":"10.21203/rs.3.rs-6719203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6719203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDespite its low incidence, the aggressive nature and high metastatic potential of canine prostate cancer (PC) make it a serious problem in veterinary medicine. However, knowledge of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC is still limited. Using high-throughput methods, many PC-related genes have been identified by comparing gene expression profiles in malignant and non-malignant prostate tissues. In these studies, the reference group containing both normal and hyperplastic prostate tissues specimens was compared to the group composed of cancerous tissues specimens. However, this approach does not allow the exclusion of inflammation-related genes from those directly involved in PC development and progression. Furthermore, the RNA-Seq and microarray data were not validated by additional analyses, including immunohistochemistry (IHC). Therefore, to identify PC-specific genes, a comparative analysis of gene expression profiles in PC and benign prostate hyperplasia (BPH) tissue samples was performed using RNA-Seq, and the results were validated by Nanostring technology, Western blotting (WB) and IHC.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eUsing the NanoString assay, significant differences were identified for 12 genes, of which \u003cem\u003eASPM, CLU, TOP2A, TSPAN8/TM4SF3\u003c/em\u003e and \u003cem\u003eHELLS\u003c/em\u003e were overexpressed in PC compared to BPH, while \u003cem\u003eATP6V0A4, CACNA2D1, CLDN10, GOLGA4, KLK2, NKX3.1\u003c/em\u003e and \u003cem\u003eSERPINB6\u003c/em\u003e were downregulated in PC. Validation of the differentially expressed genes (DEGs) at the protein level using WB and IHC revealed a highly decreased expression of the voltage-gated calcium channel subunit alpha-2 delta-1 (α2δ1), encoded by the \u003cem\u003eCACNA2D1\u003c/em\u003e gene, in PC samples compared to BPH.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur findings make α2δ1 protein a novel and promising diagnostic biomarker to differentiate PC from BPH.\u003c/p\u003e","manuscriptTitle":"Transcriptional analysis reveals a markedly reduced expression of the voltage-dependent calcium channel α2δ1 subunit in canine prostate cancer compared to benign prostatic hyperplasia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 09:49:45","doi":"10.21203/rs.3.rs-6719203/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-09-03T05:54:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-02T11:35:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Veterinary Research","date":"2025-09-01T08:17:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-veterinary-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Veterinary Research](http://bmcvetres.biomedcentral.com/)","snPcode":"12917","submissionUrl":"https://submission.nature.com/new-submission/12917/3?","title":"BMC Veterinary Research","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dc671830-df75-40e4-8317-9758dca72f48","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-13T16:01:25+00:00","versionOfRecord":{"articleIdentity":"rs-6719203","link":"https://doi.org/10.1186/s12917-025-05046-7","journal":{"identity":"bmc-veterinary-research","isVorOnly":false,"title":"BMC Veterinary Research"},"publishedOn":"2025-10-09 15:57:47","publishedOnDateReadable":"October 9th, 2025"},"versionCreatedAt":"2025-09-04 09:49:45","video":"","vorDoi":"10.1186/s12917-025-05046-7","vorDoiUrl":"https://doi.org/10.1186/s12917-025-05046-7","workflowStages":[]},"version":"v1","identity":"rs-6719203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6719203","identity":"rs-6719203","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}