Comparative proteomic analysis in human and canine breast cancer cell line: identification of proteins linked to lipid dynamics and functions

Comparative proteomic analysis in human and canine breast cancer cell line: identification of proteins linked to lipid dynamics and functions | 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 Comparative proteomic analysis in human and canine breast cancer cell line: identification of proteins linked to lipid dynamics and functions Elisa Díaz-Grijuela, Ileana B. Gonzalez-Valdes, Maider Espinal, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8132817/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Breast cancer is the most common neoplasia worldwide in humans, and one of the most common in dogs. There are multiple similarities at the clinical, hormonal and molecular levels between both species, suggesting the dog could be an optimal oncological model. Alterations in lipid homeostasis and/or metabolism are necessary to acquire the hallmarks of cancer. This study focused on the identification of proteomic similarities between human and canine BC cell lines, with an emphasis on proteins related to various lipid functionalities. Three human cell lines, 184B5 – non tumoral –, MCF-7 – Luminal A – and MDA-MB231 – triple-negative –, and two canine triple-negative cell lines, CMT-U27 and IPC-366, were analysed by LC-MS/MS. A total of 721 orthologous proteins were identified, where nearly 22% of them showed significant differences (up or down) in the four tumour lines compared to 184B5 cell line, with a minimum fold change of 30%. Likewise, approximately 14% of the orthologous proteins presented significant differences with a minimum FC of 30% specific to the triple-negative phenotype, regardless of the species. Functional analysis using KEGG and Metascape revealed alterations in proteins related to proliferation, membrane trafficking and lipid metabolism, among others, in both species. This study aims to reinforce the potential of using canine models in oncology for the search for possible diagnostic and monitoring biomarker or therapeutic targets. Translational Oncology Animal Model Molecular Biomarker Orthologous Proteins Mass Spectrometry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Breast cancer (BC) represents the most common neoplasm globally in humans, with an estimated 2.45 million new diagnoses in 2025[ 1 ]. According to the most recent data from the Global Cancer Observatory of the International Agency for Research on Cancer (IARC), BC had a globally higher age-standardized incidence and mortality rate (ASR) within oncological indications, of 46.8 and 12.7 per 100,000 women, respectively[ 2 ]. In the veterinary field, BC is equally prevalent in bitches, constituting between 50 and 70%[ 3 – 5 ] of all canine cases. The estimated incidence rate is around 200 cases per 100,000 dogs, reaching up to 260 per 100,000 in unsterilized animals[ 6 – 8 ]. Approximately 50% of canine mammary tumours are malignant, which represents a significant burden in veterinary medicine[ 5 ]. In both humans and canines, BC shares clinical characteristics and predisposing factors. In both cases, the hormonal influence is key: oestrogen and progestogen promote neoplastic development through stimuli on mammary epithelial tissue, promoting cell proliferation, apoptosis resistance and DNA damage[ 9 – 13 ]. In women, prolonged exposure to oestrogen due to late menopause or nulliparity (without a history of maternity) increases the risk[ 13 , 14 ]; while in bitches, lack of sterilization, especially if it occurs after several significantly increases the likelihood of developing the disease[ 10 , 15 ]. Obesity is another shared risk factor, as adipose tissue acts as an additional source of steroid hormones, which can stimulate tumour processes[ 10 , 13 , 16 ]. The genetic component has also been identified: in humans, mutations in genes such as BRCA1, BRCA2, TP53 or ATM are related to increased susceptibility, especially in triple negative tumours. Clinical presentation in early stages is usually silent. In dogs, the diagnosis is often incidental, with tumours detected during routine examinations, and about half of them already have metastases at the time of finding[ 17 ]. In humans, early diagnosis by mammography allows for more timely intervention, although not all subtypes are easily detected, especially in dense breasts and/or young women[ 18 , 19 ]. Clinical diagnosis in humans uses mammograms, biopsies and molecular analysis; in veterinary medicine, the approach includes physical examination, haematological tests, imaging (x-rays, Doppler ultrasound, CT scans) and biopsies. In both cases, the histological evaluation is decisive, applying the Nottingham grade system to determine the degree of cell differentiation and aggressiveness of the tumour[ 20 , 21 ]. In addition, the TNM system is used to clinically stage tumours, assessing size, ganglion involvement and presence of metastasis [ 20 , 21 ]. In terms of tumour classification, similar molecular subtypes are recognized in both humans and dogs: Luminal A, Luminal B, HER2+, and triple negative. These subtypes are defined by the expression of hormone receptors (oestrogen, progesterone) and HER2, with triple negatives having the worst prognosis due to their aggressiveness and poor response to targeted therapies. In canines, however, the methods for evaluating HER2 are not directly extrapolatable from humans, since systems such as ASCO/CAP are not fully compatible[ 22 ]. Cell models have been instrumental in the study of BC. In particular, canine breast carcinomas (CMC) have been positioned as promising comparative models due to their clinical, genetic and molecular similarities with human BC. In addition, the canine genome, sequenced in 2005[ 23 ], has shown high homology with the human genome, among other alterations, especially in key genes involved in oncogenesis, such as BRCA1/2, p53, mTOR, KIT and MET[ 23 ]. Comparative studies have reinforced this similarity. For example, Paolo Uva et al. (2009)[ 24 ] analysed about 10,000 orthologous genes and found that more than 700 genes overexpressed in canine tumours were also overexpressed in human tumours, while more than 300 negatively regulated genes matched in both types of cancer. These results point to a significant functional conservation between species, which supports the use of canine models in translational research. Cancerous cells must reprogram their metabolic processes to acquire and support cancer's hallmarks, such as proliferation, apoptosis avoidance, and invasion capability, among others. For this, energetic and biosynthetic metabolism must be adjusted, including lipid metabolism, which is crucial for the membrane synthesis, cell signalling, and bioactive molecules production. In this context, proteins involved in lipid homeostasis, from enzymes to transports and metabolic pathway regulators, are altered and contribute to satisfy energetic and structural demands. Moreover, these proteins modulate the membrane dynamics and vesicle trafficking, such as intercellular communication, and promote tumour cell survival and proliferation. Understanding these changes has provided new opportunities to identify potential biomarkers for disease diagnosis and/or monitoring, as well as therapeutic targets. The main objective of this study is to identify similarities in the proteomic footprint of human and canine breast tumour cell lines, also to identifying similarities related to the TN phenotype, by tandem mass spectrometry coupled with liquid chromatography (LC-MS/MS). To do this, proteins expressed in the human cell lines most commonly used in cancer research (MCF-7, MDA-MB-231 and 184B5) will be analysed by comparing them with two canine breast carcinoma cell lines (CMT-U27 and IPC-366). The purpose is to detect proteins related to lipid homeostasis and their associated biological functions that are preserved between both species, contributing to a better understanding of cross-species molecular similarities in breast cancer 2 Material and methods 2.1 Human mammary cell lines The following human mammary cell lines were used: a breast epithelial cell line (184B5, ATCC CRL-8799) and two cell lines derived from metastatic breast adenocarcinoma, of Luminal A type (MCF-7, ATCC HTB-22) and triple-negative (MDA-MB-231, ATCC CRL-12532). 2.2 Canine mammary cell line The following canine mammary cell lines were used: the CMT-U27 cell line (invasive ductal mammary carcinoma, triple-negative) kindly provided by Dr Ana Judith Perisé Barrios from the Faculty of Veterinary Medicine at Alfonso X el Sabio University (Biomedical Research Unit, UIB-UAX, Madrid, Spain), and the IPC-366 cell line (inflammatory BC, triple-negative), kindly provided by Dr Juan Carlos Illera del Portal and Dr Sara Cristina Cáceres Ramon from the Department of Physiology at the Faculty of Veterinary Medicine at Complutense University of Madrid. 2.3 Culture conditions and sample preparation All cells were cultured at 37°C in a humidified atmosphere containing 5% CO2. The MCF-7, MDA-MB-231, and CMT-U27 cell lines were cultured in RPMI-1640 medium (Gibco), while the canine IPC-366 cell line was cultured in DMEM-F12, and the 184B5 cell line in DMEM medium (Gibco). All cells were cultured with their respective media supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (P/S). Ten cell pellets were collected, each containing approximately 2 million cells per cell line. The medium was removed, followed by a wash with PBS, and the cells were subsequently centrifuged at 1500 rpm for 5 minutes at room temperature. After the final removal of the supernatant, the pellets were stored at -80°C until use. 2.4 LC-MS Protein extraction from human and dog cell lines was performed by resuspending the cell pellet in 8 M urea, 50 mM DTT, 2.5 U/µL benzonase in 50 mM ammonium bicarbonate, vortexed and centrifuged at 14,000 x g for 1 h at 4 ⁰C. Protein quantification was performed following the Bradford assay kit instructions (Bio-Rad, Hercules, CA, USA). Fifty micrograms of protein extract were reduced with 20 mM DTT for 30 min at 30 ⁰C. Subsequently, the extract was alkylated by adding IAA to reach a final concentration of 30 mM for 30 min at 30 ⁰C protected from light. Then, proteins were enzymatically cleaved with trypsin (1:20, w/w) for 4 h at 37 ⁰C followed by a second digestion with trypsin (1:50, w/w) overnight at 37 ⁰C. Peptides were purified using Oasis HLB 96-well µElution Plate (Waters) according to manufacturer’s instructions, and diluted peptides were dried and concentrated in a SpeedVac. For LC-MS analysis, lyophilized peptides were reconstituted with 0.1% formic acid (FA) and quantified using a NanoDropTM spectrophotometer (ThermoFisher). LC-MS/MS was performed using a VanquishNeo System (ThermoFisher) coupled to an Exploris Orbitrap 480 mass spectrometer (ThermoFisher Scientific). Peptide resolution was performed using a C18 Aurora Ultimate column (75 µm x 15 cm, particle size of 1.7 µm; IonOpticks) at a flow rate of 300 nl/min using a 61-min gradient at 50°C: 2.5% to 6.3% B in 1 min, 6.3% to 25% B in 48 min, 25% to 40% B in 12 min, and 40% to 99% B in 1 min followed by a column wash of 99% B for 8 min (A = FA 0.1%; B = 80% ACN:0.1% FA). The spray voltage was set at 1.6 kV, and the ion transfer tube temperature was set at 275 ⁰C. Sample data were acquired in a data-independent mode (DIA) with a full MS scan (scan range: 350 to 1,000 m/z; resolution: 120,000; maximum injection time: 50 ms; normalized AGC target: 300%) and 25 periodical MS/MS segments, applying 20 Th isolation windows (0.5 Th overlap; resolution: 30,000; maximum injection time: 22 ms; normalized AGC target: 1000%). Peptides were fragmented using a normalized HCD collision energy of 30%. Data were acquired in profile and centroid mode for full MS scan and MS/MS, respectively. 2.5 Data analysis For data analysis of quantitative proteomics, DIA data files were analysed using Spectronaut (v 17.3, Biognosys) by directDIA analysis (dDIA). MS1/MS2 calibration and main search tolerance were set to dynamic. The maximum precursor ion charge was set to 4, and fragment selection to intensity-based. Carbamidomethyl (C) was selected as a fixed modification, and Oxidation (M), Acetyl (Protein N-term), Deamidation (N), and Gln- >pyro-Glu as variable modifications (3 maximum modifications per peptide). The enzyme was set to trypsin in a specific mode (two missed cleavages maximum). The target-decoy-based false discovery rate (FDR) filter for peptide precursor and protein level was set to 1%. The data from human and dog cell lines were compared against fasta files containing SwissProt reviewed proteins for Homo sapiens (February 2024) and SwissProt reviewed and TrEMBL unreviewed proteins for Canis lupus familiaris (December 2024), respectively. cRAPs were included in both fasta files. The biomaRt package[ 25 , 26 ] from Bioconductor was used to identify orthologous proteins between Homo sapiens (hsa) and Canis lupus familiaris (clf) to retrieve KEGG anotations[ 27 ] based on Ensembl annotations. In addition, Metascape[ 28 ] was used to perform functional enrichment analysis using data from the Reactome database. Identifications from the reverse database, common contaminants and proteins only identified through a modification peptide were removed. Label-free intensities were then logarithmized (base 2) and the samples were then grouped according to the experimental design. A filter of 70% valid values at least in one group was applied to the resulting matrix followed by a logarithmic transformation (Log2). RStudio (version 2024.09.1) was used for statistical analysis and graphical visualization through various Bioconductor packages[ 25 , 26 , 29 – 31 ]. For three-dimensional graphical visualization, VeusZ (version 3.6.2) was used. Data were imputated based on the normal distribution and normalized using the “Width adjustment” method. Statistical analysis was performed using two-sample tests for the T-test of two selected experimental groups, adjusted using the Benjamini-Hochberg method to control the false discovery rate (FDR). The limma package in R[ 30 ] was used to identify significantly differentially expressed proteins between experimental groups (FoldChange). The resulting matrixes were exported containing the p-value (-Log) and fold-change (Log2) columns that, after its transformation into linear scale, were filtered by p < 0.05 and 30% of significance and fold-change respectively. 3 Results 3.1 Proteomic Profile and functional analysis of human and canine mammary cell lines Three human mammary cell lines and two canine mammary cell lines were selected for proteomic profiling. The human 184B5 cell line (non-tumourigenic) is derived from epithelial cells of mammary tissue with no tumour-forming capability. Both human tumour cell lines, MCF-7 and MDA-MB-231, are derived from pleural effusions of women diagnosed with metastatic breast adenocarcinoma, phenotyped as Luminal A (ER +/-, PR +/- / HER2-) and triple-negative (ER-, PR-, HER2-), respectively. No paired canine cell lines were available to match the human lines. Therefore, canine tumour cell lines, CMT-U27—derived from a canine invasive ductal mammary carcinoma—and IPC-366—derived from inflammatory BC—were used, both being negative for the expression of hormone receptors and HER2 (triple-negative BC cell lines, TNBC). LC-MS/MS is a highly efficient approach for identifying proteins and determining their relative abundance. In total, 2777 and 2733 proteins were identified in the human and canine cell lines, respectively, through LC-MS/MS. ENSEMBL annotations for the human and canine cell lines were obtained from the UniProt API for RStudio[ 32 ], using the TrEMBL and SwissProt databases, respectively, for each species. Ortholog identification was performed using the biomaRt package from Bioconductor[ 25 ], recording the type of orthology (one2one, one2many, many2many), as well as the protein identity percentages (%id) between species (Query and Target). Both databases were integrated, retaining only the common one2one orthologous proteins with a confidence level of 1, resulting in a final database of 721 orthologous proteins (Supplementary Table 1A). Based on the functional analysis using Metascape (Fig. 1 a, Supplementary Table 1B, Supplementary Table 1C) and KEGG databases (Fig. 1 b, Supplementary Table 1A), most of the proteins identified are implicated in the metabolism of RNA, carbohydrates and amino acids, in addition to participating in some mitochondrial processes, the cell cycle, among others.. Several pathways and biological processes were found to be directly or indirectly related to lipid metabolism and dynamics. These include lipid metabolism, vesicle-mediated transport and membrane trafficking. All of them are directly involved in the synthesis, modification and/or distribution of cellular lipids. In addition, several proteins involved in energy metabolism, mitochondrial biogenesis and the cell cycle have also been identified, highlighting the functional interplay between these core cellular processes and metabolic Principal component analyses (PCA) of human and canine cell lines (Fig. 1 c) revealed good reproducibility of the technique, with biological replicates from the 5 tumour cell lines clustering closely together. The proteome of the human lines showed a clear differential clustering between the 184B5 line and the tumour lines MCF-7 and MDA-MB-231, along PC1 and PC2, respectively. In contrast, regarding canine lines, Fig. 1 c shows a clear distribution along the first principal component respect 184B5 cell line. 3.2 Comparative analysis of orthologous proteins To determine those orthologous proteins differentially represented between the tumour cell lines of both species and the non-tumour reference line, a comparative analysis was performed using Student’s t-test, and p-values were corrected for FDR (Benjamini-Hochberg) to control the False Discovery Rate (FDR). Despite the differences observed in the magnitude of the proteomic alterations between human and canine cell lines (Fig. 2 a-d), the comparative analysis revealed a set of orthologous proteins whose differential expression remains consistent between species. A total of 135 overrepresented orthologous proteins (FC > 1.3, Supplementary Table 1D) and 22 underrepresented proteins (FC < 0.7, Supplementary Table 1E) were identified under the same significance criteria (adjusted p-value) (Fig. 2 f-g, Fig. 3 a). These findings suggest the existence of shared molecular mechanisms in the tumour process, irrespective of the species-specific origin. The three-dimensional PCA allowed the visualization of the distribution of the five cell lines (Fig. 3 b). A clear separation was observed between the 184B5 cell line and the tumour cell lines along principal component 1 (PC1), reflecting differences in protein representation. Overrepresented proteins showed positive loadings associated with the tumour cell lines, while underrepresented proteins showed negative loadings associated with the control line (Fig. 3 c). Additionally, the tumour cell lines were differentially distributed along principal component 2 (PC2) based on species, suggesting that variables with greater loadings in this dimension could be related to species differentiation (Fig. 3 c). Consequently, variables with lower loadings for PC2 might represent proteins conserved between species, remaining consistent in both tumour contexts. 3.3 Functional analysis of differential orthologous proteins Among the set of overrepresented proteins, those involved in the cell cycle (R-HAS-69278, Fig. 4 a, Supplementary Table 2A-2B) stand out, at different stages of the mitotic phase. Proteins involved in DNA replication (S phase) – TK1, RPA1, RFC 3/4 – were found, followed by proteins related to quality control (G2/M phase) – RAD21, H2AX, PSMB6, RUVBL2, ERC66L –, and also those involved in chromosomal segregation process and cellular division (M phase) – RUVBL2 –. Furthermore, 24 overrepresented proteins were identified in cancerous cells whose roles were related to chromosome and associated proteins (via KEGG) (Fig. 4 a, Supplementary Table 2C), principally covered spindle formation proteins and histone modification proteins. Within various processes which covered the membrane trafficking, Golgi apparatus – to – endoplasmic reticulum (Golgi-to-ER) membrane retrograde transport (R-HAS-8856688) was found mainly altered by overrepresented proteins (Fig. 4 a, Supplementary Table 2A-2B). Additionally, other processes such as exocytosis, endocytosis, SNARE complex and endosome-lysosome transport were modified by proteins overrepresented in tumoural cell lines of both species, via KEGG base data (Fig. 4 a, Supplementary Table 2C). However, PDIA3 and PLD3 were overrepresented in those groups, whose roles were involved in membrane trafficking among RE and Golgi apparatus and exocytosis respectively, via KEGG base data (Supplementary Table 3C). Various metabolic pathways were altered (nucleotide, amino acids, carbohydrate metabolism), highlighting lipid metabolism, showing different pathways affected by increased or decreased levels of specific proteins. Some of the modified pathways were fatty acid degradation – ACAT2 and CPT1A –, sphingolipid metabolism – GBA1 –, and glycerophospholipid metabolism – PLD3 –, among others (Supplementary Table 2C, Supplementary Table 3C). 3.4 Comparative analysis of orthologous proteins in triple negative cell line From the comparative analysis, 81 overrepresented (Supplementary Table 4A) and 19 underrepresented (Supplementary Table 4B) orthologous proteins were found to be common within the human TN line (MDA-MB-231) and two canine TN lines (CMT-U27 and IPC-366) (Fig. 2 f-g). This set of proteins showed differences in relation to the FC of the MCF-7 lines compared to 184B5, either in terms of significance or in the direction of FC (Fig. 5 a). The PCA allowed the visualization of the distribution of the 5 study cell lines (Fig. 5 b). A clear separation of MDA-MB-231, CMT-U27 and IPC-366 from the 184B5 and/or MCF-7 cell lines has been observed along PC1. Proteins associated with the characterization of TN cell lines in both species showed a negative loading in PC1 (Fig. 5 d). Among the set of overrepresented proteins, 19 proteins are involved in mitotic anaphase and 3 (PEX19, ERLIN1, PSMD14) in ABC-family proteins mediated transport, according to Reactome annotations (Fig. 6 a, Supplementary Table 4C-D). Among the proteins involved in mitotic anaphase are that function as regulators of anaphase and chromosomal segregation – ANAPC10, NUDC, NUP188, NUP43 and ACTR10 -, CDK regulators and phosphorylation factors – CDK6 and PPP2R5D -, chromosomal integrity control – RPA2 -, as well as factors related to RNA translation and/or processing – EIF4A1, SRSF9, ALYREF, RPS13 and RPL7A - among others. On the other hand, only 5 underrepresented proteins were associated with biological processes in the Reactome database, related to disease of metabolism (GYG1, GNS, MCCC1) and membrane trafficking (GNS, TMED10 and DNASE2) (Fig. 6 b, Supplementary Table 4E-F). Meanwhile, the KEGG database identified CCDC47 and TMED10 as proteins related to membrane trafficking, specially between the endoplasmic reticulum and Golgi apparatus. Proteins overrepresented in TNBC cell lines have been identified through KEGG analysis, highlighting several functional categories (Fig. 6 a). Among these are chromosome-associated proteins related to spindle formation – KNPB1, CIAO2B, NUP32 -, as well as histone-modifying enzymes that are part of HAT – DR1 - and HMT – WDR82 – complexes. Proteins typical of exosomes from haematopoietic cells - EIF4A1, CCT5 y IMPDH2 -, bladder cancer - EIF4A1, CCT5 -, colorectal cancer - CCT5 – and BC - IMPDH2 – were also identified. In other functional group, transporters stand out, such as those involved in primary active transport – TIMM44, TIMM9, TIMM10, members of the SLC46 sideroflexin family – SFXN3 – and mitochondrial pore channels like MCU (Supplementary Table 4G). Among the KEGG functional categories, a decrease in the levels of SFXN1 – member of the SLC56 sideroflexin family -, classified as a transporter, stands out, as well as MBOAT7 which is involved in lipid metabolism, specifically in glycerophospholipid metabolism – and also included in lipid biosynthesis protein category -. 4 Discussion The study of the proteome in cancer allows for the analysis of the expression and functionality of proteins presents in cells, providing a closer view of the cellular phenotype. Alterations in the proteome of cancer cells reflect modification in cellular processes such as proliferation, apoptosis evasion and invasion, as well as the reprogramming of metabolic or signalling pathways. Through technologies such as mass spectrometry, protein biomarkers useful for the diagnosis, prognosis and monitoring of cancer therapies have been identified. The dog has become established as a valuable translational model in BC research due to the biological, clinical and molecular similarities it shares with humans[ 3 – 5 ]. Proteomic studies in vitro models can help identify common biomarkers and conserved molecular pathways between species, promoting a “One Health” approach in comparative oncology. The use of this model not only benefits veterinary medicine but also accelerates the development of diagnostic and therapeutic strategies applicable to human medicine. Therefore, the identification of differentially expressed proteins in BC cell samples that are conserved across species, may represent a key first step toward the development of biomarkers both for diagnosis purposes and disease monitoring. We investigated the proteome of four BC tumour cell lines from two different species: MCF-7 and MDA-MB-231 as human cell lines, and CMT-U27 and IPC-366 derived from canine tumours. To evaluate conserved proteins differentially expressed in BC, we compared them to the non-tumoural human cell line 184B5, using the set of 721 orthologous proteins identified. The Student’s t-test with FDR adjustment identified 135 overrepresented and 22 underrepresented proteins with a minimum FC of 30% in the human and canine breast cancer cell line. Likewise, a set of proteins (N overrepresented = 81, N underrepresented = 19) differentially represented in TNBC cell lines, in both human and canines, suggests the existence of shared, conserved mechanisms associated with the phenotype, independent of the species-specific origin. The functionality of all sets of proteins selected was determined using KEGG database and Metascape, to analyse which metabolic, pathways or other relevant cancer-related functions may be altered in both species (Supplementary Table 2, Supplementary Table 3). 4.1 Cell cycle and histone modification proteins Common alterations in processes related to cell proliferation, and hence promoting tumoural growth, such as activation and control of different stages of cell cycle have been determined (Table Supplementary 2, Table Supplementary 4). Among the differentially over-represented orthologous proteins in BC cell lines, notable examples include TK1[ 34 ] (early tumour progression), RUVBL1/2[ 35 ] (proliferation) and H2AX[ 36 ] (damage response), as well as regulators of the cell cycle and chromosomal stability such as RAD21[ 37 ], RFC3/4[ 38 ], ZW10[ 39 ] y BANF1[ 40 ]. Proteins related to the mitotic spindle were also identified – KIF2C[ 41 ], KIFC1[ 42 ], FAM83D[ 43 ] and DRG1[ 44 ] – together with associated factor such as NUP160[ 45 ] and CIAO1[ 46 ], with high expression reported for FAM83D and BRG1 in TCGA-BRCA[ 47 ]. Taken together, these changes point to hyperactivation of the cell cycle, spindle assembly and DNA repair/replication in BC. By contrast, in human and canine triple-negative lines, a set of over-represented proteins linked to anaphase and chromosomal segregation was found, including ANAPC10[ 48 , 49 ] (metaphase-anaphase transition), NUDC[ 50 , 51 ] and ACTR10[ 52 ] (cytoskeleton), and the nucleoporins NUP188[ 53 ] and NUP43[ 54 ]. Other identified proteins related to protein synthesis/translation and mRNA processing were RPL7A[ 51 , 55 ], RPS13[ 56 ], ALYREF[ 57 , 58 ] and eIF4E[ 57 , 59 , 60 ], alongside RPA2 associated with DNA protection processes[ 55 , 61 ]. Several of these proteins are associated with poorer prognosis or greater aggressiveness in BC (NUP43, eIF4E, ALYREF)[ 53 , 58 , 59 ]. This suggest that in TNBC lines, both human and canine, proliferation is intensified with specific reinforcement of anaphase machinery and the flow of information from gene to protein. Breast cancer cell lines show a shared upregulation of histone-modifying machinery that primes chromatin for transcriptional activation. We observed higher levels of HMT complex components (ASH2L, SETD7) and HAT complex members (TAF10, RUVBL2, demethylase RIOX1 and non-canonical PRC1 component DCAF7. HMTs regulate transcription through specific H3 lysine marks; notably, ASH2L and SETD7 act on H3K4, a modification linked to gene activation in TNBC[ 62 , 63 ], although elevated levels were also detected in MCF-7. DCAF7 has been proposed as a biomarker in MCF-7 but remains unexplored in TNBC[ 64 ], while RIOX1 has mainly been implicated in other neoplasms[ 65 , 66 ] (e.g. oesophageal squamous cell carcinoma and prostate cancer). TNBC cell lines build on this foundation with a selective intensification of the H3K4 axis, with a overrepresentation of DR1 (ATAC complex) and WDR82. DR1, along with DRAP1, is a component of the ATAC complex, linked with WDR5, which produces H3K4 methylation, being a specific target for the activation of epigenetic transcriptional activity[ 67 ]. In TNBC cell lines, it was found that blocking WDR5, negatively regulating H3K4me3, led to a reduction in fatty acid recruitment and a decrease in lipid droplets accumulation[ 68 ]. Although WDR5 was not found among the orthologous proteins identified, WDR82 was identified, which also plays a role in epigenetic. WDR82 is a H3K4 methyltransferase, promoting the expression of genes related to cell proliferation, cycle cells and DNA repair [ 69 ]. However, studies about WDR5 in BC was not found, but high levels of WDR82 have been reported in paediatric glioma [ 69 ]. Some of these proteins were identified in other oncological indication in dogs, as RFC4 in lymphoma[ 70 ] or TK1 at various malign tumours (lymphoma, haemangiosarcoma, osteosarcoma or mast cell tumour) included mammary tumours[ 71 ]. On the other hand, despite the lack of analyses related to histone modification in BC canine patients, an abnormally elevated acetylation of H4 was found in complex mammary tumours[ 72 ]. Also, a direct correlation was described between HDAC1 levels (histone deacetylase) and poor prognosis in canine mammary tumours[ 72 ]. There are no publications associated with the others mentioned proteins in canine cancer. 4.2 Membrane trafficking Breast cancer cell lines display coordinated alterations across multiple trafficking routes: ER–Golgi, endosome–lysosome, and vesicle fusion. Components of COPI/COPII and their regulators are increased, including ARF6 (membrane remodelling) and GBF1 (Golgi ARF-GEF)[ 73 ], alongside the ER chaperone PDIA3 (glycoprotein folding)[ 74 ]. Higher levels of PDIA3 were shown both in BC cell line and tumoural biopsy[ 74 ], in contrast to our results. In contrast, TMED10 (COPI/COPII; ARF recruitment)[ 75 ] activity and CCDC47[ 76 ] (ER chaperone for multipass membrane proteins) were decreased in TNBC cell lines. SNARE machinery involved in vesicle docking and fusion is altered: SNAP29 and STX7 (SNAREs complex)[ 77 ] and the recycling factors NSF and NAPG, whose deficiency perturbs Golgi architecture and induces atypical autophagy. On the other hand, CHMP2A, VPS28, VPS33A and TBC1D5 act in a sequential manner (but not directly), in endosomal-lysosome way, specifically in the intracellular processing and loading (Supplementary Table 2). In BC, an overexpression of VPS28 has been identified in mammary tissues associated with poor prognosis, and in MDA-MB-231 and MCF-7 cell lines, it has been related to an increase in proliferation and invasion, also promoting apoptosis[ 78 ]. Transporters and cofactors that couple membrane flow to lipid handling are also perturbed, associated with TNBC cell lines[ 79 , 80 ]. ABC transporters play essential roles in the transport and/or translocation of lipids. PSMD14, a regulator of BMP6 signaling, promoting pluripotency and the formation of cancer stem cells[ 81 ] and enhancing expression of ABC transporters (e.g., ABCA7, ABCC4), linking to phospholipid translocation[ 79 , 82 ]. PEX19 interfaces with peroxisomal ABCDs (ABCD1/2) to shuttle very-long-chain acyl-CoAs[ 79 , 82 ], while ERLIN1, associated with ER lipid rafts, modulates PIP3 and has reported connections to ABCD3[ 83 , 84 ]. Additionally, two lysosomal proteins were identified: DNASE2, which encodes a lysosomal endonuclease that degrades DNA during apoptosis and phagocytosis, and GNS which participates in the degradation of heparan sulphate and dermatan sulphate, critical components of the extracellular matrix[ 76 ]. Both were underrepresented in TNBC cell lines. No direct studies were found linking any of these proteins to BC. However, data from The Human Protein Atlas[ 85 , 86 ] (proteinatlas.org) and TCGA indicate high expression of GNS in tumour tissues of hepatocellular carcinoma and reduced expression in renal; decreased TMED10 levels in prostate cancer, associated with poorer prognosis; variable DNASE2 expression depending on cancer type[ 87 ]; and poorer prognosis in kidney and hepatocellular cancers associated with high CCDC47 levels[ 86 ]. Higher levels of PDIA3 have been related with well-differentiated tumoural population, while lower values have been observed in poorly differentiated tumoural population in canine mammary tumours[ 88 ]. Other proteins found to be altered in canine oncology include GIPC1 in lymphoma[ 70 ] and PDIA3 in mast cell tumours[ 89 ]. There are no publications associated with the others mentioned proteins in canine cancer. 4.3 Lipid metabolism Lipid metabolism reprogramming is crucial for cancerous cells in order to sustain rapid growth and proliferation. It shows altered lipid synthesis and distribution that impact in cell dynamics, such as intracellular compartments, vesicular trafficking and membrane-dependent signaling pathways. In this study, an increase of ACAT2 and CPT1A was observed, involved in fatty acid degradation. Tan et al. 2021 proposed CPT1A as a diagnostic and monitoring biomarker when they observed increased serum levels of CPT1A in BC patients which were reduced reduced post-surgery[ 90 ]. Also, an increase in PTGES2 was shown in tumoural BC cell line, which is involved in prostaglandins synthesis pathways through COX action on arachidonic acid[ 91 ]. PTGES2 overexpression was linked to other neoplasm such as pancreatic cancer[ 92 ]. On the other hand, lower levels of GBA1, PLD3 and ACSF2 were observed, involved respectively in sphingolipid, glycerophospholipid metabolism and lipid biosynthesis. Basal levels of these proteins play a protector role, for example, GBA1 promotes ceramide production involved in cell death[ 93 ], and ACSF2 catalyses the transformation of fatty acid to acyl-CoA for normal membrane phospholipid synthesis, storage lipid synthesis or the entrance to β-oxidation pathways, avoiding ROS overproduction[ 94 ]. There are no specific studies of those proteins in breast cancer, although they have been linked to other neoplasms such as liver cancer[ 93 , 94 ]. Against this shared backdrop, the triple-negative phenotype showed a distinctive signal: MBOAT7 was significantly decreased in TNBC lines from both species, with no change in MCF-7 versus control. MBOAT7 plays a central role in the remodelling of phosphatidylinositol (PI) in the Lands’ cycle, esterifying lysophosphatidylinositol lipids to form PI species in the inner leaflet of cellular membrane[ 95 ]. No studies have been identified linking it to breast cancer; however, it is considered a potential prognostic biomarker in hepatocellular carcinoma and kidney cancer, with high MBOAT7 expression being associated with poorer prognosis [ 95 ]. These findings not only suggest the existence of shared mechanisms in the tumorigenic process of BC in human and dogs but also point to more specific alterations associated with the triple-negative phenotype. 5 Conclusion In conclusion, we determined proteomic similarities founded in human and canine breast cancer cell line (independent and specific of the tumoural phenotype), which reinforces the utilization of canine model in oncological comparative investigations. A relevant protein’s set related, directly or indirectly, to lipid homeostasis was identified, and hence to lipid metabolism reprogramming. In this study suggest the existence of conservative mechanisms associated with the adaptation of the tumour to its bioenergetic and structural demands, particularly in relation to cell proliferation, membrane dynamics and vesicular traffic. Furthermore, we identified some proteins involved in neoplasm, which roles in BC have not yet been fully explored. Finally, proteomic studies in canine cancer models are limited, for what these approximations represent an important step to expand their characterization and consolidate as model for translational oncology. Declarations Ethics and Consent to Participate declaration not applicable. Compliance with ethical standards. This article does not contain any studies with human participants or animals performed by any of the authors; the authors have no ethical conflicts to declare. Funding information. This work was funded by grants from Gobierno de Navarra, Departamento de Industria y de Transición Ecológica y Digital Empresarial (0011-1365-2023-000241 supporting all authors), Gobierno de Navarra (0011-1408-2023-000010 to E.D-G.) and Ministerio de Ciencia, Innoviación y Universidades de Gobierno de España (SNEO-20222260 to C.C-M., A.H-L., G.B-G., E.A). Author Contribution E.D.G. conceived and designed the experiments, conducted the statistical analyses, prepared the figures, and wrote the manuscript. I.B.G.V., E.S., and J.F.I. performed the LC-MS/MS measurements, data preparation, and contributed to the design of the analysis. M.E. and C.C.M. assisted in the experimental procedures. M.B. and R.U. contributed to the experimental design. A.H.L. was in charge of sample acquisition, laboratory protocols and procedures and critical reading of the manuscript. E.A. contributed to the experimental design and secured funding for the study. 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Supplementary Files SupplementaryTable1.Functionalandstatisticalanalysis.xlsx SupplementaryTable2.Overrepresentedorhologousproteins.xlsx SupplementaryTable3.Underrepresentedorthologousprotein.xlsx SupplementaryTable4.TNcelllines.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. 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1","display":"","copyAsset":false,"role":"figure","size":162679,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional analysis of the identified orthologous proteins. (a) Significantly enriched biological process based on Reactome (via Metascape). (b) Number of proteins within KEGG categories: Brite Hierarchies and Metabolism. (c) PCA of these proteins. Processes of particular interest in this study are indicated with red arrows.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/28b71ac7eee17e3e542f5a80.png"},{"id":97667517,"identity":"c1e0dd2f-93e4-42d7-904c-420a579bef2b","added_by":"auto","created_at":"2025-12-08 09:23:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":270159,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential expression analysis of orthologous proteins between tumoural and non-tumoural mammary cell lines across species (a-d) Volcano plots representing changes in protein abundance (Fold Change) and statistical significance (t-test adjusted by FDR) for : (a) MCF-7 vs 184B5, (b) MDA-MB-231 vs 184B5, (c) CMT-U27 vs 184B5, (d) IPC-366 vs 184B5. (e) Heatmap of differentially expressed orthologous proteins (FDR \u0026lt; 0.05) in all four tumoural cell lines compared to the 184B5 cell line. (f) Venn diagram showing the overlap of differentially expressed proteins (FDR \u0026lt; 0.05) overrepresented in all tumoural cell lines (FC \u0026gt; 30%) relative to 184B5 cell line, generated using the InteractiVenn tool[33]. (g) Venn diagram showing the overlap of differentially expressed proteins (FDR \u0026lt; 0.05) underrepresented in all tumoural cell lines (FC \u0026lt; 30) relative to 184B5 cell line, generated using the InteractiVenn tool[33]. Abbreviations: IP, IPC-366 ; CM, CMT-U27; B, 184B5; LA: MCF-7, TN: MDA-MB-231\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/fc614d1b271971155bada48c.png"},{"id":97669594,"identity":"dccd027f-6313-4c9f-a6a9-96b04c070926","added_by":"auto","created_at":"2025-12-08 09:28:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":225334,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterisation of differentially expressed orthologous proteins (FDR \u0026lt; 0.05; Log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; 1.3 or \u0026lt; -1.3 in all four tumoural cell lines compared to 184B5). (a) Heatmap showing the expression patterns of orthologous proteins consistently differentially expressed across all tumoural cell lines. (b) PCA of these proteins. (c) Loadings of each orthologous protein on the first three principal components (PCA). Abbreviations: IP, IPC-366 ; CM, CMT-U27; B, 184B5; LA: MCF-7, TN: MDA-MB-231.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/d4c44f255893928a23419542.png"},{"id":97464939,"identity":"f9685df1-194d-4ac1-a197-53b13155f6df","added_by":"auto","created_at":"2025-12-04 16:16:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84244,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional analysis of (a) overrepresented and (b) underrepresented orthologous proteins in tumour cell lines from both species. For each group, the following are shown: significantly enriched biological process based on Reactome (via Metascape), the percentage distribution of proteins within KEGG categories: Brite Hierarchies and Metabolism. Processes of particular interest in this study are indicated with red arrows.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/1797bf9d5462864e69c6e2df.png"},{"id":97669888,"identity":"b45c0d98-a8f4-4980-ae36-f1aa548bb519","added_by":"auto","created_at":"2025-12-08 09:29:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":267029,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of differentially expressed orthologous proteins (FDR \u0026lt; 0.05; Log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; 1.3 or \u0026lt; -1.3 in all triple negative tumoral cell lines compared to 184B5). (a) Heatmap showing the expression patterns of orthologous proteins consistently differentially expressed across all triple negative tumoral cell lines. (b) PCA of these proteins. (c) Loadings of each orthologous protein on the first three principal components. Abbreviations: IP, IPC-366; CM, CMT-U27; B, 184B5; LA: MCF-7, TN: MDA-MB-231.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/edcdeef73d103d418b2ad5ea.png"},{"id":97668661,"identity":"5de2692a-dc79-43a6-8b75-fc7e5cd21832","added_by":"auto","created_at":"2025-12-08 09:25:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":63208,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional analysis of (a) overrepresented and (b) underrepresented orthologous proteins in TN cell lines from both species. For each group, the following are shown: significantly enriched biological process based on Reactome (via Metascape), the percentage distribution of proteins within KEGG categories: Brite Hierarchies and Metabolism. Processes of particular interest in this study are indicated with red arrows.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/7cea6fe0255b46dcfcced548.png"},{"id":98622975,"identity":"8aac5def-d50c-4da3-a8ca-76ec091eebb7","added_by":"auto","created_at":"2025-12-19 17:03:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1819662,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/eefbb9e1-f594-47a9-b7f9-84a214f3d571.pdf"},{"id":97669868,"identity":"9a144749-8baf-402d-9025-62f00a2c8c43","added_by":"auto","created_at":"2025-12-08 09:29:11","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":237430,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.Functionalandstatisticalanalysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/c6cdb6aead43585f957b32fc.xlsx"},{"id":97668801,"identity":"f8c5640a-21d6-4e81-a022-cea23af4f977","added_by":"auto","created_at":"2025-12-08 09:26:17","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":56759,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.Overrepresentedorhologousproteins.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/0d15ac0d3bf5bcca7cb93757.xlsx"},{"id":97464944,"identity":"abdc0eb9-5381-4809-8b1c-524011a3766c","added_by":"auto","created_at":"2025-12-04 16:16:44","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":23038,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.Underrepresentedorthologousprotein.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/56bebc73eb0663c41018b4b8.xlsx"},{"id":97464943,"identity":"0e1548c1-ce3d-4d3a-bec5-6e72ef117b54","added_by":"auto","created_at":"2025-12-04 16:16:44","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":63202,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable4.TNcelllines.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8132817/v1/a9c173584abb0a1c0dd792f4.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative proteomic analysis in human and canine breast cancer cell line: identification of proteins linked to lipid dynamics and functions","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eBreast cancer (BC) represents the most common neoplasm globally in humans, with an estimated 2.45\u0026nbsp;million new diagnoses in 2025[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the most recent data from the Global Cancer Observatory of the International Agency for Research on Cancer (IARC), BC had a globally higher age-standardized incidence and mortality rate (ASR) within oncological indications, of 46.8 and 12.7 per 100,000 women, respectively[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the veterinary field, BC is equally prevalent in bitches, constituting between 50 and 70%[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] of all canine cases. The estimated incidence rate is around 200 cases per 100,000 dogs, reaching up to 260 per 100,000 in unsterilized animals[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Approximately 50% of canine mammary tumours are malignant, which represents a significant burden in veterinary medicine[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn both humans and canines, BC shares clinical characteristics and predisposing factors. In both cases, the hormonal influence is key: oestrogen and progestogen promote neoplastic development through stimuli on mammary epithelial tissue, promoting cell proliferation, apoptosis resistance and DNA damage[\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In women, prolonged exposure to oestrogen due to late menopause or nulliparity (without a history of maternity) increases the risk[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]; while in bitches, lack of sterilization, especially if it occurs after several significantly increases the likelihood of developing the disease[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Obesity is another shared risk factor, as adipose tissue acts as an additional source of steroid hormones, which can stimulate tumour processes[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The genetic component has also been identified: in humans, mutations in genes such as BRCA1, BRCA2, TP53 or ATM are related to increased susceptibility, especially in triple negative tumours.\u003c/p\u003e\u003cp\u003eClinical presentation in early stages is usually silent. In dogs, the diagnosis is often incidental, with tumours detected during routine examinations, and about half of them already have metastases at the time of finding[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In humans, early diagnosis by mammography allows for more timely intervention, although not all subtypes are easily detected, especially in dense breasts and/or young women[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eClinical diagnosis in humans uses mammograms, biopsies and molecular analysis; in veterinary medicine, the approach includes physical examination, haematological tests, imaging (x-rays, Doppler ultrasound, CT scans) and biopsies. In both cases, the histological evaluation is decisive, applying the Nottingham grade system to determine the degree of cell differentiation and aggressiveness of the tumour[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In addition, the TNM system is used to clinically stage tumours, assessing size, ganglion involvement and presence of metastasis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn terms of tumour classification, similar molecular subtypes are recognized in both humans and dogs: Luminal A, Luminal B, HER2+, and triple negative. These subtypes are defined by the expression of hormone receptors (oestrogen, progesterone) and HER2, with triple negatives having the worst prognosis due to their aggressiveness and poor response to targeted therapies. In canines, however, the methods for evaluating HER2 are not directly extrapolatable from humans, since systems such as ASCO/CAP are not fully compatible[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCell models have been instrumental in the study of BC. In particular, canine breast carcinomas (CMC) have been positioned as promising comparative models due to their clinical, genetic and molecular similarities with human BC. In addition, the canine genome, sequenced in 2005[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], has shown high homology with the human genome, among other alterations, especially in key genes involved in oncogenesis, such as BRCA1/2, p53, mTOR, KIT and MET[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Comparative studies have reinforced this similarity. For example, Paolo Uva et al. (2009)[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] analysed about 10,000 orthologous genes and found that more than 700 genes overexpressed in canine tumours were also overexpressed in human tumours, while more than 300 negatively regulated genes matched in both types of cancer. These results point to a significant functional conservation between species, which supports the use of canine models in translational research.\u003c/p\u003e\u003cp\u003eCancerous cells must reprogram their metabolic processes to acquire and support cancer's hallmarks, such as proliferation, apoptosis avoidance, and invasion capability, among others. For this, energetic and biosynthetic metabolism must be adjusted, including lipid metabolism, which is crucial for the membrane synthesis, cell signalling, and bioactive molecules production. In this context, proteins involved in lipid homeostasis, from enzymes to transports and metabolic pathway regulators, are altered and contribute to satisfy energetic and structural demands. Moreover, these proteins modulate the membrane dynamics and vesicle trafficking, such as intercellular communication, and promote tumour cell survival and proliferation. Understanding these changes has provided new opportunities to identify potential biomarkers for disease diagnosis and/or monitoring, as well as therapeutic targets.\u003c/p\u003e\u003cp\u003eThe main objective of this study is to identify similarities in the proteomic footprint of human and canine breast tumour cell lines, also to identifying similarities related to the TN phenotype, by tandem mass spectrometry coupled with liquid chromatography (LC-MS/MS). To do this, proteins expressed in the human cell lines most commonly used in cancer research (MCF-7, MDA-MB-231 and 184B5) will be analysed by comparing them with two canine breast carcinoma cell lines (CMT-U27 and IPC-366). The purpose is to detect proteins related to lipid homeostasis and their associated biological functions that are preserved between both species, contributing to a better understanding of cross-species molecular similarities in breast cancer\u003c/p\u003e"},{"header":"2 Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Human mammary cell lines\u003c/h2\u003e\u003cp\u003eThe following human mammary cell lines were used: a breast epithelial cell line (184B5, ATCC CRL-8799) and two cell lines derived from metastatic breast adenocarcinoma, of Luminal A type (MCF-7, ATCC HTB-22) and triple-negative (MDA-MB-231, ATCC CRL-12532).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Canine mammary cell line\u003c/h2\u003e\u003cp\u003eThe following canine mammary cell lines were used: the CMT-U27 cell line (invasive ductal mammary carcinoma, triple-negative) kindly provided by Dr Ana Judith Peris\u0026eacute; Barrios from the Faculty of Veterinary Medicine at Alfonso X el Sabio University (Biomedical Research Unit, UIB-UAX, Madrid, Spain), and the IPC-366 cell line (inflammatory BC, triple-negative), kindly provided by Dr Juan Carlos Illera del Portal and Dr Sara Cristina C\u0026aacute;ceres Ramon from the Department of Physiology at the Faculty of Veterinary Medicine at Complutense University of Madrid.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Culture conditions and sample preparation\u003c/h2\u003e\u003cp\u003eAll cells were cultured at 37\u0026deg;C in a humidified atmosphere containing 5% CO2. The MCF-7, MDA-MB-231, and CMT-U27 cell lines were cultured in RPMI-1640 medium (Gibco), while the canine IPC-366 cell line was cultured in DMEM-F12, and the 184B5 cell line in DMEM medium (Gibco). All cells were cultured with their respective media supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (P/S). Ten cell pellets were collected, each containing approximately 2\u0026nbsp;million cells per cell line. The medium was removed, followed by a wash with PBS, and the cells were subsequently centrifuged at 1500 rpm for 5 minutes at room temperature. After the final removal of the supernatant, the pellets were stored at -80\u0026deg;C until use.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 LC-MS\u003c/h2\u003e\u003cp\u003eProtein extraction from human and dog cell lines was performed by resuspending the cell pellet in 8 M urea, 50 mM DTT, 2.5 U/\u0026micro;L benzonase in 50 mM ammonium bicarbonate, vortexed and centrifuged at 14,000 x g for 1 h at 4 ⁰C. Protein quantification was performed following the Bradford assay kit instructions (Bio-Rad, Hercules, CA, USA). Fifty micrograms of protein extract were reduced with 20 mM DTT for 30 min at 30 ⁰C. Subsequently, the extract was alkylated by adding IAA to reach a final concentration of 30 mM for 30 min at 30 ⁰C protected from light. Then, proteins were enzymatically cleaved with trypsin (1:20, w/w) for 4 h at 37 ⁰C followed by a second digestion with trypsin (1:50, w/w) overnight at 37 ⁰C. Peptides were purified using Oasis HLB 96-well \u0026micro;Elution Plate (Waters) according to manufacturer\u0026rsquo;s instructions, and diluted peptides were dried and concentrated in a SpeedVac.\u003c/p\u003e\u003cp\u003eFor LC-MS analysis, lyophilized peptides were reconstituted with 0.1% formic acid (FA) and quantified using a NanoDropTM spectrophotometer (ThermoFisher). LC-MS/MS was performed using a VanquishNeo System (ThermoFisher) coupled to an Exploris Orbitrap 480 mass spectrometer (ThermoFisher Scientific). Peptide resolution was performed using a C18 Aurora Ultimate column (75 \u0026micro;m x 15 cm, particle size of 1.7 \u0026micro;m; IonOpticks) at a flow rate of 300 nl/min using a 61-min gradient at 50\u0026deg;C: 2.5% to 6.3% B in 1 min, 6.3% to 25% B in 48 min, 25% to 40% B in 12 min, and 40% to 99% B in 1 min followed by a column wash of 99% B for 8 min (A\u0026thinsp;=\u0026thinsp;FA 0.1%; B\u0026thinsp;=\u0026thinsp;80% ACN:0.1% FA). The spray voltage was set at 1.6 kV, and the ion transfer tube temperature was set at 275 ⁰C. Sample data were acquired in a data-independent mode (DIA) with a full MS scan (scan range: 350 to 1,000 m/z; resolution: 120,000; maximum injection time: 50 ms; normalized AGC target: 300%) and 25 periodical MS/MS segments, applying 20 Th isolation windows (0.5 Th overlap; resolution: 30,000; maximum injection time: 22 ms; normalized AGC target: 1000%). Peptides were fragmented using a normalized HCD collision energy of 30%. Data were acquired in profile and centroid mode for full MS scan and MS/MS, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Data analysis\u003c/h2\u003e\u003cp\u003eFor data analysis of quantitative proteomics, DIA data files were analysed using Spectronaut (v 17.3, Biognosys) by directDIA analysis (dDIA). MS1/MS2 calibration and main search tolerance were set to dynamic. The maximum precursor ion charge was set to 4, and fragment selection to intensity-based. Carbamidomethyl (C) was selected as a fixed modification, and Oxidation (M), Acetyl (Protein N-term), Deamidation (N), and Gln- \u0026gt;pyro-Glu as variable modifications (3 maximum modifications per peptide). The enzyme was set to trypsin in a specific mode (two missed cleavages maximum). The target-decoy-based false discovery rate (FDR) filter for peptide precursor and protein level was set to 1%. The data from human and dog cell lines were compared against fasta files containing SwissProt reviewed proteins for Homo sapiens (February 2024) and SwissProt reviewed and TrEMBL unreviewed proteins for Canis lupus familiaris (December 2024), respectively. cRAPs were included in both fasta files. The biomaRt package[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] from Bioconductor was used to identify orthologous proteins between Homo sapiens (hsa) and Canis lupus familiaris (clf) to retrieve KEGG anotations[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] based on Ensembl annotations. In addition, Metascape[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] was used to perform functional enrichment analysis using data from the Reactome database.\u003c/p\u003e\u003cp\u003eIdentifications from the reverse database, common contaminants and proteins only identified through a modification peptide were removed. Label-free intensities were then logarithmized (base 2) and the samples were then grouped according to the experimental design. A filter of 70% valid values at least in one group was applied to the resulting matrix followed by a logarithmic transformation (Log2).\u003c/p\u003e\u003cp\u003eRStudio (version 2024.09.1) was used for statistical analysis and graphical visualization through various Bioconductor packages[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. For three-dimensional graphical visualization, VeusZ (version 3.6.2) was used. Data were imputated based on the normal distribution and normalized using the \u0026ldquo;Width adjustment\u0026rdquo; method. Statistical analysis was performed using two-sample tests for the T-test of two selected experimental groups, adjusted using the Benjamini-Hochberg method to control the false discovery rate (FDR). The limma package in R[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] was used to identify significantly differentially expressed proteins between experimental groups (FoldChange). The resulting matrixes were exported containing the p-value (-Log) and fold-change (Log2) columns that, after its transformation into linear scale, were filtered by p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and 30% of significance and fold-change respectively.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Proteomic Profile and functional analysis of human and canine mammary cell lines\u003c/h2\u003e\u003cp\u003eThree human mammary cell lines and two canine mammary cell lines were selected for proteomic profiling. The human 184B5 cell line (non-tumourigenic) is derived from epithelial cells of mammary tissue with no tumour-forming capability. Both human tumour cell lines, MCF-7 and MDA-MB-231, are derived from pleural effusions of women diagnosed with metastatic breast adenocarcinoma, phenotyped as Luminal A (ER +/-, PR +/- / HER2-) and triple-negative (ER-, PR-, HER2-), respectively. No paired canine cell lines were available to match the human lines. Therefore, canine tumour cell lines, CMT-U27\u0026mdash;derived from a canine invasive ductal mammary carcinoma\u0026mdash;and IPC-366\u0026mdash;derived from inflammatory BC\u0026mdash;were used, both being negative for the expression of hormone receptors and HER2 (triple-negative BC cell lines, TNBC).\u003c/p\u003e\u003cp\u003eLC-MS/MS is a highly efficient approach for identifying proteins and determining their relative abundance. In total, 2777 and 2733 proteins were identified in the human and canine cell lines, respectively, through LC-MS/MS. ENSEMBL annotations for the human and canine cell lines were obtained from the UniProt API for RStudio[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], using the TrEMBL and SwissProt databases, respectively, for each species. Ortholog identification was performed using the biomaRt package from Bioconductor[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], recording the type of orthology (one2one, one2many, many2many), as well as the protein identity percentages (%id) between species (Query and Target). Both databases were integrated, retaining only the common one2one orthologous proteins with a confidence level of 1, resulting in a final database of 721 orthologous proteins (Supplementary Table\u0026nbsp;1A).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBased on the functional analysis using Metascape (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, Supplementary Table\u0026nbsp;1B, Supplementary Table\u0026nbsp;1C) and KEGG databases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, Supplementary Table\u0026nbsp;1A), most of the proteins identified are implicated in the metabolism of RNA, carbohydrates and amino acids, in addition to participating in some mitochondrial processes, the cell cycle, among others.. Several pathways and biological processes were found to be directly or indirectly related to lipid metabolism and dynamics. These include lipid metabolism, vesicle-mediated transport and membrane trafficking. All of them are directly involved in the synthesis, modification and/or distribution of cellular lipids. In addition, several proteins involved in energy metabolism, mitochondrial biogenesis and the cell cycle have also been identified, highlighting the functional interplay between these core cellular processes and metabolic\u003c/p\u003e\u003cp\u003ePrincipal component analyses (PCA) of human and canine cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec) revealed good reproducibility of the technique, with biological replicates from the 5 tumour cell lines clustering closely together. The proteome of the human lines showed a clear differential clustering between the 184B5 line and the tumour lines MCF-7 and MDA-MB-231, along PC1 and PC2, respectively. In contrast, regarding canine lines, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec shows a clear distribution along the first principal component respect 184B5 cell line.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Comparative analysis of orthologous proteins\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo determine those orthologous proteins differentially represented between the tumour cell lines of both species and the non-tumour reference line, a comparative analysis was performed using Student\u0026rsquo;s t-test, and p-values were corrected for FDR (Benjamini-Hochberg) to control the False Discovery Rate (FDR).\u003c/p\u003e\u003cp\u003eDespite the differences observed in the magnitude of the proteomic alterations between human and canine cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-d), the comparative analysis revealed a set of orthologous proteins whose differential expression remains consistent between species. A total of 135 overrepresented orthologous proteins (FC\u0026thinsp;\u0026gt;\u0026thinsp;1.3, Supplementary Table\u0026nbsp;1D) and 22 underrepresented proteins (FC\u0026thinsp;\u0026lt;\u0026thinsp;0.7, Supplementary Table\u0026nbsp;1E) were identified under the same significance criteria (adjusted p-value) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef-g, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). These findings suggest the existence of shared molecular mechanisms in the tumour process, irrespective of the species-specific origin.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe three-dimensional PCA allowed the visualization of the distribution of the five cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). A clear separation was observed between the 184B5 cell line and the tumour cell lines along principal component 1 (PC1), reflecting differences in protein representation. Overrepresented proteins showed positive loadings associated with the tumour cell lines, while underrepresented proteins showed negative loadings associated with the control line (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Additionally, the tumour cell lines were differentially distributed along principal component 2 (PC2) based on species, suggesting that variables with greater loadings in this dimension could be related to species differentiation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Consequently, variables with lower loadings for PC2 might represent proteins conserved between species, remaining consistent in both tumour contexts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Functional analysis of differential orthologous proteins\u003c/h2\u003e\u003cp\u003eAmong the set of overrepresented proteins, those involved in the cell cycle (R-HAS-69278, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Supplementary Table\u0026nbsp;2A-2B) stand out, at different stages of the mitotic phase. Proteins involved in DNA replication (S phase) \u0026ndash; TK1, RPA1, RFC 3/4 \u0026ndash; were found, followed by proteins related to quality control (G2/M phase) \u0026ndash; RAD21, H2AX, PSMB6, RUVBL2, ERC66L \u0026ndash;, and also those involved in chromosomal segregation process and cellular division (M phase) \u0026ndash; RUVBL2 \u0026ndash;. Furthermore, 24 overrepresented proteins were identified in cancerous cells whose roles were related to chromosome and associated proteins (via KEGG) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Supplementary Table\u0026nbsp;2C), principally covered spindle formation proteins and histone modification proteins.\u003c/p\u003e\u003cp\u003eWithin various processes which covered the membrane trafficking, Golgi apparatus \u0026ndash; to \u0026ndash; endoplasmic reticulum (Golgi-to-ER) membrane retrograde transport (R-HAS-8856688) was found mainly altered by overrepresented proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Supplementary Table\u0026nbsp;2A-2B). Additionally, other processes such as exocytosis, endocytosis, SNARE complex and endosome-lysosome transport were modified by proteins overrepresented in tumoural cell lines of both species, via KEGG base data (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Supplementary Table\u0026nbsp;2C). However, PDIA3 and PLD3 were overrepresented in those groups, whose roles were involved in membrane trafficking among RE and Golgi apparatus and exocytosis respectively, via KEGG base data (Supplementary Table\u0026nbsp;3C).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eVarious metabolic pathways were altered (nucleotide, amino acids, carbohydrate metabolism), highlighting lipid metabolism, showing different pathways affected by increased or decreased levels of specific proteins. Some of the modified pathways were fatty acid degradation \u0026ndash; ACAT2 and CPT1A \u0026ndash;, sphingolipid metabolism \u0026ndash; GBA1 \u0026ndash;, and glycerophospholipid metabolism \u0026ndash; PLD3 \u0026ndash;, among others (Supplementary Table\u0026nbsp;2C, Supplementary Table\u0026nbsp;3C).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Comparative analysis of orthologous proteins in triple negative cell line\u003c/h2\u003e\u003cp\u003eFrom the comparative analysis, 81 overrepresented (Supplementary Table\u0026nbsp;4A) and 19 underrepresented (Supplementary Table\u0026nbsp;4B) orthologous proteins were found to be common within the human TN line (MDA-MB-231) and two canine TN lines (CMT-U27 and IPC-366) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef-g). This set of proteins showed differences in relation to the FC of the MCF-7 lines compared to 184B5, either in terms of significance or in the direction of FC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eThe PCA allowed the visualization of the distribution of the 5 study cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). A clear separation of MDA-MB-231, CMT-U27 and IPC-366 from the 184B5 and/or MCF-7 cell lines has been observed along PC1. Proteins associated with the characterization of TN cell lines in both species showed a negative loading in PC1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAmong the set of overrepresented proteins, 19 proteins are involved in mitotic anaphase and 3 (PEX19, ERLIN1, PSMD14) in ABC-family proteins mediated transport, according to Reactome annotations (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, Supplementary Table\u0026nbsp;4C-D). Among the proteins involved in mitotic anaphase are that function as regulators of anaphase and chromosomal segregation \u0026ndash; ANAPC10, NUDC, NUP188, NUP43 and ACTR10 -, CDK regulators and phosphorylation factors \u0026ndash; CDK6 and PPP2R5D -, chromosomal integrity control \u0026ndash; RPA2 -, as well as factors related to RNA translation and/or processing \u0026ndash; EIF4A1, SRSF9, ALYREF, RPS13 and RPL7A - among others.\u003c/p\u003e\u003cp\u003eOn the other hand, only 5 underrepresented proteins were associated with biological processes in the Reactome database, related to disease of metabolism (GYG1, GNS, MCCC1) and membrane trafficking (GNS, TMED10 and DNASE2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb, Supplementary Table\u0026nbsp;4E-F). Meanwhile, the KEGG database identified CCDC47 and TMED10 as proteins related to membrane trafficking, specially between the endoplasmic reticulum and Golgi apparatus.\u003c/p\u003e\u003cp\u003eProteins overrepresented in TNBC cell lines have been identified through KEGG analysis, highlighting several functional categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). Among these are chromosome-associated proteins related to spindle formation \u0026ndash; KNPB1, CIAO2B, NUP32 -, as well as histone-modifying enzymes that are part of HAT \u0026ndash; DR1 - and HMT \u0026ndash; WDR82 \u0026ndash; complexes. Proteins typical of exosomes from haematopoietic cells - EIF4A1, CCT5 y IMPDH2 -, bladder cancer - EIF4A1, CCT5 -, colorectal cancer - CCT5 \u0026ndash; and BC - IMPDH2 \u0026ndash; were also identified. In other functional group, transporters stand out, such as those involved in primary active transport \u0026ndash; TIMM44, TIMM9, TIMM10, members of the SLC46 sideroflexin family \u0026ndash; SFXN3 \u0026ndash; and mitochondrial pore channels like MCU (Supplementary Table\u0026nbsp;4G).\u003c/p\u003e\u003cp\u003eAmong the KEGG functional categories, a decrease in the levels of SFXN1 \u0026ndash; member of the SLC56 sideroflexin family -, classified as a transporter, stands out, as well as MBOAT7 which is involved in lipid metabolism, specifically in glycerophospholipid metabolism \u0026ndash; and also included in lipid biosynthesis protein category -.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe study of the proteome in cancer allows for the analysis of the expression and functionality of proteins presents in cells, providing a closer view of the cellular phenotype. Alterations in the proteome of cancer cells reflect modification in cellular processes such as proliferation, apoptosis evasion and invasion, as well as the reprogramming of metabolic or signalling pathways. Through technologies such as mass spectrometry, protein biomarkers useful for the diagnosis, prognosis and monitoring of cancer therapies have been identified.\u003c/p\u003e\u003cp\u003eThe dog has become established as a valuable translational model in BC research due to the biological, clinical and molecular similarities it shares with humans[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Proteomic studies in vitro models can help identify common biomarkers and conserved molecular pathways between species, promoting a \u0026ldquo;One Health\u0026rdquo; approach in comparative oncology. The use of this model not only benefits veterinary medicine but also accelerates the development of diagnostic and therapeutic strategies applicable to human medicine. Therefore, the identification of differentially expressed proteins in BC cell samples that are conserved across species, may represent a key first step toward the development of biomarkers both for diagnosis purposes and disease monitoring.\u003c/p\u003e\u003cp\u003eWe investigated the proteome of four BC tumour cell lines from two different species: MCF-7 and MDA-MB-231 as human cell lines, and CMT-U27 and IPC-366 derived from canine tumours. To evaluate conserved proteins differentially expressed in BC, we compared them to the non-tumoural human cell line 184B5, using the set of 721 orthologous proteins identified. The Student\u0026rsquo;s t-test with FDR adjustment identified 135 overrepresented and 22 underrepresented proteins with a minimum FC of 30% in the human and canine breast cancer cell line. Likewise, a set of proteins (N overrepresented\u0026thinsp;=\u0026thinsp;81, N underrepresented\u0026thinsp;=\u0026thinsp;19) differentially represented in TNBC cell lines, in both human and canines, suggests the existence of shared, conserved mechanisms associated with the phenotype, independent of the species-specific origin.\u003c/p\u003e\u003cp\u003eThe functionality of all sets of proteins selected was determined using KEGG database and Metascape, to analyse which metabolic, pathways or other relevant cancer-related functions may be altered in both species (Supplementary Table\u0026nbsp;2, Supplementary Table\u0026nbsp;3).\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Cell cycle and histone modification proteins\u003c/h2\u003e\u003cp\u003eCommon alterations in processes related to cell proliferation, and hence promoting tumoural growth, such as activation and control of different stages of cell cycle have been determined (Table Supplementary 2, Table Supplementary 4). Among the differentially over-represented orthologous proteins in BC cell lines, notable examples include TK1[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] (early tumour progression), RUVBL1/2[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] (proliferation) and H2AX[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] (damage response), as well as regulators of the cell cycle and chromosomal stability such as RAD21[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], RFC3/4[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], ZW10[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] y BANF1[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Proteins related to the mitotic spindle were also identified \u0026ndash; KIF2C[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], KIFC1[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], FAM83D[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] and DRG1[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] \u0026ndash; together with associated factor such as NUP160[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and CIAO1[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], with high expression reported for FAM83D and BRG1 in TCGA-BRCA[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Taken together, these changes point to hyperactivation of the cell cycle, spindle assembly and DNA repair/replication in BC.\u003c/p\u003e\u003cp\u003eBy contrast, in human and canine triple-negative lines, a set of over-represented proteins linked to anaphase and chromosomal segregation was found, including ANAPC10[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] (metaphase-anaphase transition), NUDC[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and ACTR10[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] (cytoskeleton), and the nucleoporins NUP188[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and NUP43[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Other identified proteins related to protein synthesis/translation and mRNA processing were RPL7A[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], RPS13[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], ALYREF[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] and eIF4E[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], alongside RPA2 associated with DNA protection processes[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Several of these proteins are associated with poorer prognosis or greater aggressiveness in BC (NUP43, eIF4E, ALYREF)[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. This suggest that in TNBC lines, both human and canine, proliferation is intensified with specific reinforcement of anaphase machinery and the flow of information from gene to protein.\u003c/p\u003e\u003cp\u003eBreast cancer cell lines show a shared upregulation of histone-modifying machinery that primes chromatin for transcriptional activation. We observed higher levels of HMT complex components (ASH2L, SETD7) and HAT complex members (TAF10, RUVBL2, demethylase RIOX1 and non-canonical PRC1 component DCAF7. HMTs regulate transcription through specific H3 lysine marks; notably, ASH2L and SETD7 act on H3K4, a modification linked to gene activation in TNBC[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], although elevated levels were also detected in MCF-7. DCAF7 has been proposed as a biomarker in MCF-7 but remains unexplored in TNBC[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], while RIOX1 has mainly been implicated in other neoplasms[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] (e.g. oesophageal squamous cell carcinoma and prostate cancer).\u003c/p\u003e\u003cp\u003eTNBC cell lines build on this foundation with a selective intensification of the H3K4 axis, with a overrepresentation of DR1 (ATAC complex) and WDR82. DR1, along with DRAP1, is a component of the ATAC complex, linked with WDR5, which produces H3K4 methylation, being a specific target for the activation of epigenetic transcriptional activity[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. In TNBC cell lines, it was found that blocking WDR5, negatively regulating H3K4me3, led to a reduction in fatty acid recruitment and a decrease in lipid droplets accumulation[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Although WDR5 was not found among the orthologous proteins identified, WDR82 was identified, which also plays a role in epigenetic. WDR82 is a H3K4 methyltransferase, promoting the expression of genes related to cell proliferation, cycle cells and DNA repair [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. However, studies about WDR5 in BC was not found, but high levels of WDR82 have been reported in paediatric glioma [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSome of these proteins were identified in other oncological indication in dogs, as RFC4 in lymphoma[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] or TK1 at various malign tumours (lymphoma, haemangiosarcoma, osteosarcoma or mast cell tumour) included mammary tumours[\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. On the other hand, despite the lack of analyses related to histone modification in BC canine patients, an abnormally elevated acetylation of H4 was found in complex mammary tumours[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Also, a direct correlation was described between HDAC1 levels (histone deacetylase) and poor prognosis in canine mammary tumours[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. There are no publications associated with the others mentioned proteins in canine cancer.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Membrane trafficking\u003c/h2\u003e\u003cp\u003eBreast cancer cell lines display coordinated alterations across multiple trafficking routes: ER\u0026ndash;Golgi, endosome\u0026ndash;lysosome, and vesicle fusion. Components of COPI/COPII and their regulators are increased, including ARF6 (membrane remodelling) and GBF1 (Golgi ARF-GEF)[\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], alongside the ER chaperone PDIA3 (glycoprotein folding)[\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Higher levels of PDIA3 were shown both in BC cell line and tumoural biopsy[\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e], in contrast to our results. In contrast, TMED10 (COPI/COPII; ARF recruitment)[\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] activity and CCDC47[\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] (ER chaperone for multipass membrane proteins) were decreased in TNBC cell lines.\u003c/p\u003e\u003cp\u003eSNARE machinery involved in vesicle docking and fusion is altered: SNAP29 and STX7 (SNAREs complex)[\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] and the recycling factors NSF and NAPG, whose deficiency perturbs Golgi architecture and induces atypical autophagy. On the other hand, CHMP2A, VPS28, VPS33A and TBC1D5 act in a sequential manner (but not directly), in endosomal-lysosome way, specifically in the intracellular processing and loading (Supplementary Table\u0026nbsp;2). In BC, an overexpression of VPS28 has been identified in mammary tissues associated with poor prognosis, and in MDA-MB-231 and MCF-7 cell lines, it has been related to an increase in proliferation and invasion, also promoting apoptosis[\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTransporters and cofactors that couple membrane flow to lipid handling are also perturbed, associated with TNBC cell lines[\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. ABC transporters play essential roles in the transport and/or translocation of lipids. PSMD14, a regulator of BMP6 signaling, promoting pluripotency and the formation of cancer stem cells[\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] and enhancing expression of ABC transporters (e.g., ABCA7, ABCC4), linking to phospholipid translocation[\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. PEX19 interfaces with peroxisomal ABCDs (ABCD1/2) to shuttle very-long-chain acyl-CoAs[\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e], while ERLIN1, associated with ER lipid rafts, modulates PIP3 and has reported connections to ABCD3[\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdditionally, two lysosomal proteins were identified: DNASE2, which encodes a lysosomal endonuclease that degrades DNA during apoptosis and phagocytosis, and GNS which participates in the degradation of heparan sulphate and dermatan sulphate, critical components of the extracellular matrix[\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Both were underrepresented in TNBC cell lines.\u003c/p\u003e\u003cp\u003eNo direct studies were found linking any of these proteins to BC. However, data from The Human Protein Atlas[\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e] (proteinatlas.org) and TCGA indicate high expression of GNS in tumour tissues of hepatocellular carcinoma and reduced expression in renal; decreased TMED10 levels in prostate cancer, associated with poorer prognosis; variable DNASE2 expression depending on cancer type[\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]; and poorer prognosis in kidney and hepatocellular cancers associated with high CCDC47 levels[\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHigher levels of PDIA3 have been related with well-differentiated tumoural population, while lower values have been observed in poorly differentiated tumoural population in canine mammary tumours[\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Other proteins found to be altered in canine oncology include GIPC1 in lymphoma[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] and PDIA3 in mast cell tumours[\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. There are no publications associated with the others mentioned proteins in canine cancer.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Lipid metabolism\u003c/h2\u003e\u003cp\u003eLipid metabolism reprogramming is crucial for cancerous cells in order to sustain rapid growth and proliferation. It shows altered lipid synthesis and distribution that impact in cell dynamics, such as intracellular compartments, vesicular trafficking and membrane-dependent signaling pathways. In this study, an increase of ACAT2 and CPT1A was observed, involved in fatty acid degradation. Tan et al. 2021 proposed CPT1A as a diagnostic and monitoring biomarker when they observed increased serum levels of CPT1A in BC patients which were reduced reduced post-surgery[\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlso, an increase in PTGES2 was shown in tumoural BC cell line, which is involved in prostaglandins synthesis pathways through COX action on arachidonic acid[\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. PTGES2 overexpression was linked to other neoplasm such as pancreatic cancer[\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. On the other hand, lower levels of GBA1, PLD3 and ACSF2 were observed, involved respectively in sphingolipid, glycerophospholipid metabolism and lipid biosynthesis. Basal levels of these proteins play a protector role, for example, GBA1 promotes ceramide production involved in cell death[\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e], and ACSF2 catalyses the transformation of fatty acid to acyl-CoA for normal membrane phospholipid synthesis, storage lipid synthesis or the entrance to β-oxidation pathways, avoiding ROS overproduction[\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. There are no specific studies of those proteins in breast cancer, although they have been linked to other neoplasms such as liver cancer[\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAgainst this shared backdrop, the triple-negative phenotype showed a distinctive signal: MBOAT7 was significantly decreased in TNBC lines from both species, with no change in MCF-7 versus control. MBOAT7 plays a central role in the remodelling of phosphatidylinositol (PI) in the Lands\u0026rsquo; cycle, esterifying lysophosphatidylinositol lipids to form PI species in the inner leaflet of cellular membrane[\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. No studies have been identified linking it to breast cancer; however, it is considered a potential prognostic biomarker in hepatocellular carcinoma and kidney cancer, with high MBOAT7 expression being associated with poorer prognosis [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese findings not only suggest the existence of shared mechanisms in the tumorigenic process of BC in human and dogs but also point to more specific alterations associated with the triple-negative phenotype.\u003c/p\u003e\u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn conclusion, we determined proteomic similarities founded in human and canine breast cancer cell line (independent and specific of the tumoural phenotype), which reinforces the utilization of canine model in oncological comparative investigations. A relevant protein\u0026rsquo;s set related, directly or indirectly, to lipid homeostasis was identified, and hence to lipid metabolism reprogramming. In this study suggest the existence of conservative mechanisms associated with the adaptation of the tumour to its bioenergetic and structural demands, particularly in relation to cell proliferation, membrane dynamics and vesicular traffic. Furthermore, we identified some proteins involved in neoplasm, which roles in BC have not yet been fully explored. Finally, proteomic studies in canine cancer models are limited, for what these approximations represent an important step to expand their characterization and consolidate as model for translational oncology.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics and Consent to Participate declaration\u003c/h2\u003e\u003cp\u003enot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompliance with ethical standards.\u003c/strong\u003e\u003cp\u003eThis article does not contain any studies with human participants or animals performed by any of the authors; the authors have no ethical conflicts to declare.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding information.\u003c/h2\u003e\u003cp\u003eThis work was funded by grants from Gobierno de Navarra, Departamento de Industria y de Transici\u0026oacute;n Ecol\u0026oacute;gica y Digital Empresarial (0011-1365-2023-000241 supporting all authors), Gobierno de Navarra (0011-1408-2023-000010 to E.D-G.) and Ministerio de Ciencia, Innoviaci\u0026oacute;n y Universidades de Gobierno de Espa\u0026ntilde;a (SNEO-20222260 to C.C-M., A.H-L., G.B-G., E.A).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.D.G. conceived and designed the experiments, conducted the statistical analyses, prepared the figures, and wrote the manuscript. I.B.G.V., E.S., and J.F.I. performed the LC-MS/MS measurements, data preparation, and contributed to the design of the analysis. M.E. and C.C.M. assisted in the experimental procedures. M.B. and R.U. contributed to the experimental design. A.H.L. was in charge of sample acquisition, laboratory protocols and procedures and critical reading of the manuscript. E.A. contributed to the experimental design and secured funding for the study. G.B.G. provided general scientific oversight., E.A. contributed with experimental design, funding and critical review\u0026nbsp;of\u0026nbsp;results. All authors reviewed and approved the final\u0026nbsp;manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerlay J, LM; EM; LF; CM; ML; PM; ZA; SI; BF (2024) Global Cancer Observatory: Cancer Tomorrow (version 1.1). 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Mol Metab 34:136. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.MOLMET.2020.01.011\u003c/span\u003e\u003cspan address=\"10.1016/J.MOLMET.2020.01.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Translational Oncology, Animal Model, Molecular Biomarker, Orthologous Proteins, Mass Spectrometry","lastPublishedDoi":"10.21203/rs.3.rs-8132817/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8132817/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast cancer is the most common neoplasia worldwide in humans, and one of the most common in dogs. There are multiple similarities at the clinical, hormonal and molecular levels between both species, suggesting the dog could be an optimal oncological model. Alterations in lipid homeostasis and/or metabolism are necessary to acquire the hallmarks of cancer. This study focused on the identification of proteomic similarities between human and canine BC cell lines, with an emphasis on proteins related to various lipid functionalities. Three human cell lines, 184B5 \u0026ndash; non tumoral \u0026ndash;, MCF-7 \u0026ndash; Luminal A \u0026ndash; and MDA-MB231 \u0026ndash; triple-negative \u0026ndash;, and two canine triple-negative cell lines, CMT-U27 and IPC-366, were analysed by LC-MS/MS. A total of 721 orthologous proteins were identified, where nearly 22% of them showed significant differences (up or down) in the four tumour lines compared to 184B5 cell line, with a minimum fold change of 30%. Likewise, approximately 14% of the orthologous proteins presented significant differences with a minimum FC of 30% specific to the triple-negative phenotype, regardless of the species. Functional analysis using KEGG and Metascape revealed alterations in proteins related to proliferation, membrane trafficking and lipid metabolism, among others, in both species. This study aims to reinforce the potential of using canine models in oncology for the search for possible diagnostic and monitoring biomarker or therapeutic targets.\u003c/p\u003e","manuscriptTitle":"Comparative proteomic analysis in human and canine breast cancer cell line: identification of proteins linked to lipid dynamics and functions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 16:16:39","doi":"10.21203/rs.3.rs-8132817/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e8cc4248-0132-4271-a00f-6a255478c8ca","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-17T19:53:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 16:16:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8132817","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8132817","identity":"rs-8132817","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}