Biological characterization and clinical value of PLOD gene family in clear cell renal cell carcinoma

Biological characterization and clinical value of PLOD gene family in clear cell renal cell carcinoma | 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 Biological characterization and clinical value of PLOD gene family in clear cell renal cell carcinoma Xuan Shang, Liu Liu, Min Yan, Rui-Min Ren, Ke-Xin Guo, Jie Wang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4201423/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 Background Studies have identified that procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) gene family is closely related to tumor progression and metastasis in various cancers. However, the expression pattern, clinical value and function of PLOD gene family in clear cell renal cell carcinoma (ccRCC) have not yet been studied. Methods We investigated the expression, prognostic value, immune cell infiltration, genetic mutation, cell migration, and biological function of the PLOD gene family in ccRCC through comprehensive bioinformatic analysis and experimental validation, and predicted potential chemicals which regulate the expression of PLOD gene family using comparative toxicogenomics database (CTD) and docking analysis. Results The mRNA and protein expressions of PLOD gene family were highly increased in ccRCC tissues compared with normal tissues, and high expressions of all the three PLOD genes were positively related to every clinicopathological stages, poor overall survival (OS) and disease-free survival (DFS) in ccRCC patients. Fifty co-expressed genes of PLODs were found related with ccRCC. Functional enrichment analysis revealed that collagen synthesis, ECM-receptor interaction and lysine degradation were key biological functions of PLODs in ccRCC. A variety of chemicals were predicted to regulate the expression of PLOD gene family especially acetaminophen. Conclusion High expression of PLOD gene family is closely related to poor prognosis of ccRCC and they can predict any stage of ccRCC. PLOD gene family may serve as a prognostic biomarker and even a therapeutic target for ccRCC. PLOD gene family Expression signature Clear cell renal cell carcinoma Prognosis Bioinformatics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Renal cell carcinoma (RCC) is a malignant tumor of the urinary system and accounts for 2%−3% of malignant tumors[ 1 , 2 ]. Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of RCC, accounting for 75%−80% of all RCC cases[ 3 ]. In recent years, the morbidity and mortality of ccRCC are increasing, and the onset age is getting younger. Surgical resection is still the most effective treatment for localized ccRCC. However, once distant metastasis occurs, the current treatment is unsatisfactory[ 4 – 7 ]. As a kind of gene-driven malignant tumor, with the rapid technical development of molecular biology, some genes related to the occurrence and progression of ccRCC have been identified. However, the molecular mechanisms of ccRCC pathogenesis and metastasis remain unclear[ 8 – 10 ]. Thus, it is urgent to screen new diagnostic markers and therapeutic targets with great clinical values for improving the survival outcomes of ccRCC patients. PLOD gene family has the function of lysyl hydroxylase in the lysyl hydroxylation process of collagen[ 11 ]. There are three members in the PLOD family, namely PLOD1, PLOD2, and PLOD3. Overexpression of PLODs may result in tumor progression and metastasis. PLOD1 and PLOD3 can hydroxylate lysine residues in the triple helix of collagen, whereas PLOD2 is the only one that can hydroxylate lysine residues on the terminal peptides of collagen[ 12 ]. Various studies have shown that highly expressed PLODs can promote tumor invasion and recurrence, indicating that PLODs may be potential targets for tumor prognosis[ 11 , 13 ]. However, the expression and prognostic value of this promising gene family in ccRCC have rarely been investigated. In this study, we evaluated the expression, prognostic value, immune infiltration, genetic mutation, cell migration, potential biological functions and inhibitors of PLODs using public datasets and experimental validation. We found that PLODs are highly expressed in ccRCC tissues compared to matched normal tissues, and high expressions of PLODs are positively related to poor overall survival (OS) and reduced disease-free survival (DFS) in ccRCC patients. The study suggests that PLODs are potential biomarkers and therapeutic targets for ccRCC. Materials and methods GEPIA analysis Gene Expression Profiling Interactive Analysis ( GEPIA)[ 14 ] ( http://gepia.cancer-pku.cn/ ) is an online database which facilitates the standardized analysis of RNA sequencing data. GEPIA was used to analyze the expression profiles of PLODs acquired through pan-cancer analysis. The expressions of PLODs in ccRCC tissues and normal renal tissues were compared using GEPIA2. mRNA data were acquired from the Cancer Genome Atlas (TCGA) and Genotypic Tissue Expression (GTEx) databases to visualize the transcriptional profiles of PLODs. TIMER analysis Tumor IMmune Estimation Resource (TIMER)[ 15 ] ( https://cistrome.shinyapps.io/timer/ ) is an intuitive software that can be used to systematically evaluate infiltration of various immune cells and the clinical impacts. We estimated tumor immune infiltration of B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells based on TIMER. In addition, we studied the differential expressions of PLODs between tumor and contiguous normal tissues based on all TCGA tumors. Patients and kidney tissue sampling The study included four patients diagnosed as ccRCC in Shanxi Bethune Hospital, Taiyuan, China. The institutional ethics approval was authorized by Shanxi Bethune Hospital and informed written consents were obtained from all patients. The ccRCC tissues and paired adjacent normal kidney tissues were harvested during tumor resection, and were frozen in liquid nitrogen and stored at an ultra-low-temperature freezer before use. Total RNAs and proteins were extracted respectively for RT-qPCR and western blotting to verify the bioinformatic results. RNA isolation and quantitative PCR (qPCR) qPCR was performed to examine the mRNA levels of PLODs in ccRCC tissues and paired adjacent normal tissues. Total RNA was extracted from tissues using M5 Universal RNA Mini Kit (Mei5bio, Beijing, China) according to the manufacturer’s instruction. qPCR was performed according to the instructions of Vazyme HiScript III RT SuperMix for qPCR (Vazyme, Nanjing, China). Primer sets for selected genes were designed with the assistance of Sangon Biotech Co., Ltd (Shanghai, China). The expression data were normalized to the reference β-actin and the mRNA levels were calculated using the 2 −ΔΔCt method. Primer sequences for qPCR were as follows: β-actin forward: 5’-CCTGGCACCCAGCACAAT-3’, β-actin reverse: 5’-GGGCCGGACTCGTCATAC-3’. PLOD1 forward: 5’- AAGCCGGAGGACAACCTTTTA-3’, PLOD1 reverse: 5’- GCGAAGAGAATGACCAGATCC-3’. PLOD2 forward: 5’- GACAGCGTTCTCTTCGTCCTCA-3’, PLOD2 reverse: 5’- CTCCAGCCTTTTCGTGGTGACT-3’. PLOD3 forward: 5’- GCGCCAGTGGAAGTACAAGGAT-3’, PLOD3 reverse: 5’- CACTTCATCTAAAGCCCCGTTGA − 3’. Western blotting Total proteins for western blotting were extracted from ccRCC tissues and paired adjacent normal tissues. The concentration of all protein samples was determined using the bicinchoninic acid (BCA) assay (Solarbio Co., Ltd, Beijing, China). A total amount of 30 µg extracted proteins of each sample were separated by 10% SDS-PAGE gel. Next, proteins from the SDS-PAGE gel were transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, Billerica, MA, USA). Membranes were blocked with 5% nonfat milk for 1 h at room temperature. The membranes were incubated with antibody of PLOD1 (1:1000, Proteintech, 29480-1-AP), PLOD2 (1:1000, Proteintech, 66342-1-Ig), PLOD3 (1:1000, Proteintech, 60058,1-Ig) or β-actin (1:5000, Bioworld, AP0060) for overnight at 4 ℃. The membranes were washed with TBST and then were incubated with a secondary antibody conjugated with horseradish peroxidase (Zhongshan Golden Bridge Biotechnology, Beijing, China) for 1 h at room temperature, and were washed again with TBST. Finally, ECL luminescence solution (SEVEN, Beijing, China) was added and the blots were scanned using Image Lab™ Touch Software (Bio-Rad Laboratories, Hercules, CA, USA). The gray values of protein bands were determined using ImageJ, and β-actin was used for normalization. UALCAN dataset analysis UALCAN[ 16 ] ( http://ualcan.path.uab.edu/ ) is a comprehensive tool that provides analysis according to TCGA dataset. We analyzed the transcriptional levels of PLOD genes between ccRCC tissues and adjacent normal tissues. The relationship between the expression levels of PLOD genes and tumor stage were also analyzed uisng this database. Human Protein Atlas dataset analysis The Human Protein Atlas (HPA)[ 17 ] ( http://www.proteinatlas.org/ ) is a free database that provides information about human encoded proteins. HPA was used to analyze the protein expression levels of PLODs in ccRCC tissues and adjacent normal tissues. Kaplan–Meier plotter survival analysis The Kaplan-Meier (KM) plotter[ 18 ] ( https://kmplot.com/analysis/ ) is dedicated to analyze the survival biomarkers of 21 cancer types based on data from Gene Expression Omnibus database (GEO), European Genome-phenome Archive (EGA) and TCGA. We used Kaplan-Meier plotter to identify the association between PLODs and survivals (OS and DFS) in ccRCC patients. cBioPortal database analysis The cBio Cancer Genomics Portal (cBioPortal)[ 19 , 20 ] ( https://www.cbioportal.org/ ) is a network resource that can be used to analyze multidimensional cancer genomic data as well as for data visualization. We evaluated the copy number variants (CNV), mutations, and gene types in ccRCC patients based on the cBioPortal on-line instructions. In addition, we analyzed the relationship between gene mutation and ccRCC prognosis using the cBioPortal tool based on TCGA database. DFS and OS were also analyzed for with or without PLODs mutation in KIRC. Cell migration analysis PLOD3 small interfering (si)RNA and Control siRNA was transfected into 786-O cell lines using Lipofectamine2000 reagent (Invitrogen) according to the manufacture’s protocol. Migration was detected with a wound healing assay using a 6-well plate. When the confluence of 786-O cells reached ~ 90–100% in RPMI-1640 medium with 10% FBS, scratch wounds were created in each cell. After scratching, the debris was removed and FBS free medium was added, the cell images were obtained after 0, 12, 24 h of incubation at 37℃. Migration was calculated as the relative percentage of scratch area to the area at 0 h (% of wound closure) using ImageJ software. TF-Target and miRNA-Target of PLOD gene family The target genes of PLODs were predicted using Targetscan[ 21 ] ( http://www.targetscan.org/ ) and GeneCards[ 22 ] ( https://www.genecards.org/ ). The intersections of predictions from the two databases were matched by FunRich software to ascertain their regulatory targets. Starbase[ 23 ] ( http://starbase.sysu.edu.cn/ ) and Targetscan ( http://www.targetscan.org/vert_72/ ) were used to locate the upstream miRNAs. Interactions of PLOD genes verified by STRING STRING[ 24 ] ( https://string-db.org/ ) is a free online database developed by European Molecular Biology Laboratory for functional connection of genes and for retrieval of interacting genes. STRING was used to search co-expression genes of PLODs and to conduct protein-protein interaction (PPI) networks with an interaction score > 0.4. Analysis of biological functions and pathways Metascape[ 25 ] ( http://metascape.org ) is a web tool developed for powerful computational analysis of large-scale datasets. Using Metascape performing annotation analysis, we predicted potential biological functions of PLODs and pathways involved in ccRCC and analyzed the GO and KEGG pathway enrichments. Prediction of chemicals interacting with PLOD gene family Comparative Toxicogenomics Database (CTD) [ 26 ] ( http://ctdbase.org/ ) is a powerful public database that integrates large numbers of data among chemicals, genes, functional phenotypes and diseases. It provides information on the associations of chemical-gene/protein, chemical-disease, and gene-disease, and thus is helpful in the predicting mechanistic hypotheses about the effect of environment on disease. We used CTD to predict potential chemicals which interact with PLOD gene family. In the CTD database, we chose chemicals with “interaction” > 3 as the cut-off criteria to perform further analysis. Docking analysis of affinity between chemicals and PLOD gene family Molecular docking approach was used to identify the affinities of predicted chemicals with PLOD1, PLOD2, and PLOD3. The structures of the chemicals from PubChem database ( http://pubchem.ncbi.nlm.nih.gov/ ) were downloaded, and Chem3D software was used to minimize the ligand molecular energy. The 3D structures of PLOD genes were obtained from PDB database ( http://www1.rcsb.org/ ) or UniProt database ( http://www.uniprot.org/ ). AutoDockTools 1.5.6 software was used to find out the active pockets. Vina script was run to calculate the molecular binding energy, Vina ≤ −7.0 kcal.mol −1 indicated strong binding of “ligand” with “receptor”. PyMOL software was used to display the results. Statistical analysis All statistical analyses were performed using Graph-Pad Prism 6.0 software. Data were represented as the mean ± standard error of mean (SEM). Two-tail t -test was used to compare the means of two sample groups. Statistical significance was set at P < 0.05. Results High mRNA and protein expressions of PLOD gene family in ccRCC We first identified the mRNA levels of PLOD genes in various cancers using TIMER and GEPIA database. The transcription levels of PLOD genes were noticeably upregulated in several cancers compared with respective normal tissues, especially in ccRCC (Fig. 1 , 2 A). We also used UALCAN online tool to further verify the transcriptional levels of PLODs in TCGA database. Results show that all the three PLOD genes were low expressed in normal kidney tissues while were significantly upregulated in ccRCC tissues (Fig. 2 B)​. These results suggest that the expression level of PLOD gene family might be an indicator of ccRCC. To verify the above bioinformatic results shown in Figs. 1 and 2 , RT-qPCR and western blotting were performed in ccRCC cell line and human ccRCC tissues and corresponding normal kidney tissues. RT-qPCR results showed that the mRNA levels of PLOD genes in ccRCC cell lines and tissues were significantly upregulated (Fig. 3 A, D), which are consistent with the bioinformatic results. Western blotting results show that the protein expression levels of PLOD1, PLOD2 and PLOD3 in ccRCC cell lines and tissues were also significantly higher than the normal kidney epithelial cell and tissues (Fig. 3 B, C, E, F). Immunohistochemical features of PLODs proteins in human ccRCC and normal kidney tissues The immunohistochemical stains of PLOD1, PLOD2 and PLOD3 proteins in ccRCC tissues and normal kidney tissues were retrieved from HPA database. Results reveal that the positively stained signals of PLOD1, PLOD2 and PLOD3 were all weak in normal kidney tissues but were strong in ccRCC tissues (Fig. 4 ), which are consistent with the western blots. Values of PLOD gene family in determining the clinicopathological stages and prognostics of ccRCC Gene expression level may affect cancer development. We investigated the relationship between the expression levels of PLOD genes and the clinicopathological stages of ccRCC using UALCAN online tool. Results show that the expression levels of PLOD family members were all significantly high in various clinical stages ( P < 0.001) compared with the normal tissues (Fig. 5 A). No difference of PLODs expression levels was found among the four stages (Fig. 5 A), suggesting that PLOD levels can indicate any stages of ccRCC, including the stage 1. There was also no difference among PLOD members in indicating the clinicopathological stages (Fig. 5 A), which suggests that all the three PLOD members can reflect the progression of ccRCC. Kaplan-Meier plotter survival curves were established to further evaluate the correlation between differentially expressed PLOD genes and ccRCC prognosis. We selected median value to divide samples into high and low expression groups. Results show that higher mRNA expression of PLOD1, PLOD2 and PLOD3 were associated with poorer OS in ccRCC patients (Fig. 5 B). The prognostic values of PLOD genes were also conducted by comparing PLODs levels and the DFS of ccRCC patients. Higher mRNA levels of PLOD1, PLOD2 and PLOD3 were associated with worse DFS (Fig. 5 C). These results suggest that PLOD gene family could be used as predicters of the clinical outcomes of ccRCC. Tumor microenvironment (TME) has essential impact on tumor growth, metastasis, prognosis, and therapeutic response to anticancer drugs[ 27 ]. The potential association of PLODs expression levels with immune infiltration in ccRCC were investigated based on TIMER database. The expression level of PLOD1 was not correlated with immune infiltration (Fig. 6 A). The expressions of PLOD2 and PLOD3 had remarkable negative correlations with tumor purity in ccRCC (cor = −0.124 and −0.094, respectively, P < 0.05) (Fig. 6 B, C). The abundance of B cells, macrophages, neutrophils and dendritic cells showed positive association with PLOD2 (cor = 0.182, 0.181, 0.273, 0.151, respectively, P < 0.05) (Fig. 6 B). Significantly positive correlation was found between PLOD3 expression and B cells and dendritic cells infiltration (cor = 0.137 and 0.114, respectively, P < 0.05) (Fig. 6 C). Generally, among these immune cells, B cells and dendritic cells were most closely connected to the occurrence and development of ccRCC. Genetic alterations of PLOD gene family in ccRCC patients Genetic alterations in the three PLOD genes of ccRCC patients was ascertained using cBioPortal database. Figure 7 A shows the frequency of genetic alterations, Fig. 7 B exhibits genetic alterations of PLOD genes in ccRCC patients. The percentage changes of DNA alterations were 0.7% in PLOD1, 1.6% in PLOD2, and 3% in PLOD3. We further examined the relationship between changes of PLOD gene expressions and the prognosis of ccRCC using the cBioPortal database. Survival curves were established to demonstrate the OS and DFS of ccRCC patients with altered or unaltered mRNA expressions of PLODs. The alterations of PLOD genes were closely related to OS in ccRCC patients ( P = 5.339e-3), while were not significantly associated with DFS ( P = 0.0962) (Fig. 7 C, D). Migration and infiltration function play an essential role in tumor progression. To explore whether PLOD3 affected the migration of ccRCC cells, we conducted wound healing assay. Results showed that knocking down PLOD3 was able to inhibit the scratch healing rate of 786-O cells (Fig. 8 A, B). Then we analyzed the effect of PLOD3 on the epithelial-mesenchymal transition (EMT) process of 786-O cells. The results indicated that knocking down PLOD3 inhibited the EMT process of 786-O cells as evidenced by increased epithelial marker E-Cadherin and decreased mesenchymal maker Vimentin (Fig. 8 C-E). These findings suggested that knocking down PLOD3 effectively suppressed the migration of 786-O cells. Identification of transcription factors and microRNAs regulating PLOD gene family expression in ccRCC MicroRNAs (miRNAs) are a large set of non-coding small RNAs that binds to 3’UTR of target mRNA to regulate gene expression, which leads to aberrant expression profiles of target genes. miRNAs are closely related to transcription factors (TFs) in regulating gene expressions in response to cellular environment and signaling[ 28 , 29 ]. Here, we used TF-target databases (hTFtarget and Genecards) and miRNA-target databases (Starbase and Targetscan) to predict the upstream TFs and miRNAs that regulate the expression of PLOD genes. We found 123 TFs (Fig. 9 A) and 113 miRNAs (Fig. 9 B) that regulate the expression of PLOD gene family in ccRCC. The numbers of TFs regulating PLOD1, PLOD2 and PLOD3 were respectively 85, 79 and 96, as shown by the intersection selected from GeneCard and hTFtarget database. The numbers of miRNAs that regulate PLOD1, PLOD2 and PLOD3 were respectively 42, 68 and 16, as shown by the intersection selected from Starbase and Targetscan database (Additional file 1: Figure S1 and S2). Correlation among PLOD genes and their co-expressed genes in ccRCC To investigate the potential functions of PLOD genes in ccRCC, we further clarified the synergy among PLOD family members. By mining the GEPIA database, we found that the expressions of PLOD1 was positively correlated with PLOD2 and PLOD3 (R = 0.28 and 0.53, respectively, P < 0.05), and the expression of PLOD2 was positively correlated with PLOD3 (R = 0.22, P < 0.05) (Fig. 10 A-C). We further explored the interaction between PLOD gene family and their co-expressed genes in ccRCC using STRING database, and found that the top 50 co-expressed genes of PLOD gene family were: COL11A1, COL12A1, COL13A1,COL14A1, COL15A1, COL16A1, COL17A1, COL18A1, COL1A1, COL20A1, COL22A1, COL25A1, COL26A1, COL27A1, COL2A1, COL3A1, COL4A1, COL4A2, COL4A5, COL4A6, COL5A1, COL5A2, COL5A3, COL6A1, COL6A2, COL6A3, COL6A6, COL7A1, COL8A1, COL8A2, COL9A2, COL9A3, COLGALT1, COLGALT2, COLQ, CRTAP, EHMT2, FKBP10, IFITM5, KDM1A, LEPRE1, NSD1, P4HA1, P4HA2, PLOD1, PLOD2, PLOD3, SETD7, SETD8, and TMEM38B (Fig. 10 D; Additional file 1: Table S1 ). These top 50 co-expressed genes were selected to conduct the following functional analysis. Functional enrichment analysis of co-expressed genes of PLOD gene family in ccRCC To better understand the potential mechanisms of PLOD gene family in regulating ccRCC, we used Metascape to construct Gene Ontology (GO) enrichment and KEGG pathway analysis. The GO analysis was conducted on three aspects, including biological processes (BP), cellular components (CC), and molecular functions (MF). GO functional enrichment analysis demonstrated that these genes (PLOD gene family and the top 50 co-expressed genes) were significantly enriched in some terms and pathways, including extracellular matrix structural constituent conferring tensile strength, complex of collagen trimers, collagen fibril organization, etc. These GO terms may play critical roles in the pathogenesis and progression of ccRCC (Fig. 11 A−C; Additional file 1: Table S2). Result of KEGG pathway analysis show that PLOD genes and their top 50 co-expressed genes were enriched mainly in three functional pathways, including hsa04974 (protein digestion and absorption), hsa04512 (ECM-receptor interaction), and hsa00310 (lysine degradation) (Fig. 11 D, F; Additional file 1: Table S3). The detailed signaling of these three KEGG pathways are shown in Fig. 11 G−I. These functional terms and pathways were mostly associated with extracellular matrix structural constituent, collagen synthesis and lysine degradation. Predicted chemicals interacting with PLOD genes and docking analysis CTD database was used to predict chemicals that may interact with PLOD genes. Results of CTD analysis show that 9, 51 and 18 chemicals interacted with PLOD1, PLOD2 and PLOD3, respectively. Notably, bisphenol A, tetrachlorodibenzodioxin, acetaminophen, ethanol, and nanotubes/carbon were the common chemicals regulating all the three PLOD genes (Fig. 12 A, B). The 3D structures of PLOD1 and PLOD2 were downloaded from UniProt database, and the 3D structure of PLOD3 was obtained from PDB database (PDB ID: 6FXR). The binding energies of acetaminophen with PLOD1, PLOD2 and PLOD3 were −6.1 kcal·mol − 1 , −6.2 kcal·mol − 1 , and −6.3 kcal·mol −1 , respectively, suggesting that the binding between acetaminophen and the three “receptors” (PLOD proteins) were strong. From the results of ligand-receptor protein interaction, we found that acetaminophen could form hydrogen bonds with LYS77, ARG179 and GLN129, and had hydrophobic interactions with the amino acid residues TYR223 and GLN180, of PLOD1. In addition, acetaminophen formed hydrogen bonds with ASN223 and SER166, while had hydrophobic interaction with TRP145 and GLN192, of PLOD2. Furthermore, acetaminophen formed hydrogen bonds with ARG411, ARG57, GLY266 and HIS505, and showed hydrophobic interaction with TEP281, of PLOD3 (Fig. 12 C). These forces enable acetaminophen to bind stably to the pockets of the three PLOD proteins. Discussion The importance of PLOD gene family has drawn increasing attention due to their critical role in the synthesis of collagen. Previous studies indicate that PLODs are involved in various malignant behaviors of tumors, such as proliferation, invasion, and metastasis[ 30 – 33 ]. Although the roles of PLODs in the development and progression of several tumors have been reported, the potential functions and prognostic values of PLODs in ccRCC have yet to be comprehensively elucidated. In the present study, we performed bioinformatic analysis and experimental validation, including mRNA and protein expression, prognostic value, immune-infiltration, genetic alteration, potential function of PLOD family members in ccRCC, and also predicted some chemicals which may affect PLOD genes and thus may have potential therapeutic effects on ccRCC. We found that PLODs were upregulated in ccRCC tissues compared to normal kidney tissues. RT-qPCR and western blotting validations confirmed the bioinformatic results. We further identified that high expression levels of PLOD genes are significantly associated with poor survival (including OS and DFS) in patients with ccRCC. GO and KEGG pathway enrichment analyses demonstrate that PLOD genes were mainly involved in the regulation of collagen metabolism and extracellular matrix composition. We also predicted that acetaminophen is a potential inhibitor for all the PLOD genes and thus may become a therapeutic drug for ccRCC. PLOD1 is overexpressed in various malignant cancers, including gastric cancer, glioma, glioblastoma multiforme and osteosarcoma[31, 34−38]. Zhang et al . reported that PLOD1 promotes cell growth and aerobic glycolysis through activating the SOX9/PI3K/Akt/mTOR signaling in gastric cancer[ 37 ]. Wang et al . demonstrated that highly expressed PLOD1 promotes glioblastoma progression via NF-κB signaling and PLOD1 may serve as a potential treatment target for mesenchymal GBM[ 38 ]. Dysregulated PLOD1 is also associated with osteosarcoma[ 31 ]. Wu et al . revealed that PLOD1 enhances tumorigenesis and metastasis in osteosarcoma, and PLOD1 expression is regulated by miR-34c, suggesting that miR-34c/PLOD1 may be a potential therapeutic target for osteosarcoma treatment[ 39 ]. PLOD2 is the key enzyme catalyzing the hydroxylation of lysyl and stabilizing collagen crosslinks. Increasing evidences show that PLOD2 is highly expressed in various tumors, and overexpressed PLOD2 is associated with poor outcomes, such as oral squamous cell carcinoma, hepatocellular carcinoma, breast cancer and sarcoma[40−44]. It has been reported that PLOD2 is upregulated and positively correlated with the metastasis of breast cancer, providing a potential treatment target for breast cancer[ 45 ]. PLOD2 is regulated by many factors. For example, HIF-1α regulates the expression of PLOD2 to promote metastasis of endometrial carcinoma[ 46 ]. In the central nervous system, hypoxia-induced PLOD2 can facilitate tumorigenesis via the PI3K/Akt signaling in glioma[ 47 ]. PLOD2 inhibits the expression of HK2 via the STAT3 signaling pathway, resulting in decreases of proliferation, invasiveness and aerobic glycolysis in colorectal cancer cells[ 48 ]. PLOD3 is a multifunctional enzyme, mainly catalyzes the hydroxylation of lysine residues in collagen. PLOD3 is overexpressed in many solid tumors, including ovarian cancer, colon adenocarcinoma and hepatocellular carcinoma[49−51]. PLOD3 plays considerable roles in lung cancer metastasis via the STAT3 signaling pathway[ 52 ]. A recent study showed that PLOD3 plays essential roles in the progression of non-small cell lung cancer via regulating the PKCδ/CDK1/LIMD1/YAP1 axis[ 53 ]. We identified high expressions of all the three PLOD genes in ccRCC tissues, and the high expression levels of the three PLOD genes showed no difference among the four stages of ccRCC. There is also no difference among the three PLOD genes in indicating the clinicopathological stages. These results suggest either of the three PLOD genes and its product can indicate ccRCC at any stages. This finding may simplify the clinical procedures using any of PLODs in the diagnosis and prognosis evaluation of ccRCC. Previous studies revealed that the mechanisms of PLOD gene family in cancer development are mainly involved in the regulation of collagen metabolism, extracellular matrix construction, and immune microenvironment[ 11 , 13 ]. In the present study, mutations of PLODs in ccRCC were found closely related to the prognosis of ccRCC patients. However, we did not investigate the relationship between special types of mutations and the prognosis of ccRCC, such as functional mutations, hot regions and mutational pattern. This area warrants further studies. By mining the protein-protein interaction networks, we found that COL11A1 was the most closely related protein with PLOD gene family. COL11A1 exerts crucial role in bone development and collagen fiber assembly. COL11A1 is upregulated in several cancers[54−56]. COL11A1 overexpression accelerates tumor progression and cancer-associated fibroblasts activation via the TGF-β3 signaling pathway in ovarian cancer cells[ 57 ]. In addition, COL11A1 promotes cell proliferation, migration and inhibits cell apoptosis in non-small cell lung cancer cells[ 58 ]. COL11A1 also promotes the invasion and migration of pancreatic cancer cells by facilitating epithelial-mesenchymal transition through AKT/GSK-3β/Snail signaling pathway[ 59 ]. The effect and signaling of COL11A1 on the tumor cells of ccRCC also need further studies. Our functional enrichment analyses on PLODs in ccRCC indicated that PLOD genes are mainly involved in collagen synthesis and lysine hydroxylation. KEGG pathways enrichment analysis indicated that PLOD genes are mainly involved in ECM-receptor interactions and lysine degradation. Collagen is one of the main components of the extracellular matrix, and the hydroxylation of lysine residues is a key step in collagen biosynthesis. Increased collagen deposition and cross-linking promote cancer development and progression by enhancing cancer cell migration, invasion, and proliferation [11] . A study found that the invasion of ccRCC is closely related to ECM[ 60 , 61 ]. Therefore, we speculate that PLOD genes are involved in the malignant biological process of ccRCC. Conclusion High expressions of PLOD genes are positively associated with all the four clinical stages and the poor prognosis of ccRCC. Total 123 TFs and 133 miRNAs are identified to regulate the expressions of PLOD genes. The functions of PLOD genes in ccRCC mainly involve to collagen synthesis, ECM-receptor interaction and lysine degradation. High expression of PLOD genes may serve as biomarkers indicating poor prognosis of ccRCC. Some predicted chemicals targeting PLOD genes may have therapeutic potentials for ccRCC. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Shanxi Bethune Hospital/Shanxi Academy of Medical Sciences (Approval No.: YXLL-2021-066). All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation and conducted according to the principles expressed in the Helsinki Declaration of 1964 and later versions. All patients have signed informed consent. Consent for publication All authors agree to publish. Availability of data and material All data in this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by Key Medical Science and Technology Program of Shanxi Province (2020XM01), Shanxi “1331” Project Quality and Efficiency Improvement Plan (1331 KFC), and Basic Research Program of Shanxi Province (202103021223238). Author contributions XS carried out experiments, data analysis and drafted manuscript. LL performed data analysis, drew figures and drafted manuscript. MY, RMR, KXG, JW, WZ, JSC and JLL performed data analysis. LJG and JMC supervised the study and revised manuscript. All authors read and approved the submission. Acknowledgements We thank the mentioned public databases for providing us the data and analytical tools. References Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. Cancer J Clin. 2019;69(1):7–34. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. Cancer J Clin. 2020;70(1):7–30. Nabi S, Kessler ER, Bernard B, Flaig TW, Lam ET. Renal cell carcinoma: a review of biology and pathophysiology. F1000Research 2018, 7:307. 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Single-cell analysis reveals the pan-cancer invasiveness-associated transition of adipose-derived stromal cells into COL11A1-expressing cancer-associated fibroblasts. PLoS Comput Biol. 2021;17(7):e1009228. Wu YH, Huang YF, Chang TH, Chen CC, Wu PY, Huang SC, Chou CY. COL11A1 activates cancer-associated fibroblasts by modulating TGF-β3 through the NF-κB/IGFBP2 axis in ovarian cancer cells. Oncogene. 2021;40(26):4503–19. Tu H, Li J, Lin L, Wang L. COL11A1 Was Involved in Cell Proliferation, Apoptosis and Migration in Non-Small Cell Lung Cancer Cells. J Invest surgery: official J Acad Surg Res. 2021;34(6):664–9. Wang H, Zhou H, Ni H, Shen X. COL11A1-Driven Epithelial-Mesenchymal Transition and Stemness of Pancreatic Cancer Cells Induce Cell Migration and Invasion by Modulating the AKT/GSK-3β/Snail Pathway. Biomolecules 2022, 12(3). Ahluwalia P, Ahluwalia M, Mondal AK, Sahajpal N, Kota V, Rojiani MV, Rojiani AM, Kolhe R. Prognostic and therapeutic implications of extracellular matrix associated gene signature in renal clear cell carcinoma. Sci Rep. 2021;11(1):7561. Oxburgh L. The Extracellular Matrix Environment of Clear Cell Renal Cell Carcinoma. Cancers 2022, 14(17). Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4201423","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":287888850,"identity":"bb358d29-4b7d-4f80-b026-61dfd07c2047","order_by":0,"name":"Xuan Shang","email":"","orcid":"","institution":"The First Hospital, Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Shang","suffix":""},{"id":287888851,"identity":"7e242003-1236-410a-8747-a55ab4cb1279","order_by":1,"name":"Liu Liu","email":"","orcid":"","institution":"Shanxi Medical 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14:59:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4201423/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4201423/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54395205,"identity":"a2397b24-2c56-419f-8044-0ea8fcc97396","added_by":"auto","created_at":"2024-04-09 21:19:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1957132,"visible":true,"origin":"","legend":"\u003cp\u003eThe mRNA expression levels of PLOD gene family in different types of human cancer compared with normal tissues.\u003cstrong\u003e \u003c/strong\u003eNote that PLOD1, PLOD2 and PLOD3 were highly expressed in KIRC.\u003cstrong\u003e (A)\u003c/strong\u003e Results of TIMER dataset showing the transcription levels of PLOD1, PLOD2 and PLOD3 in different types of cancer tissues and matched normal tissues. \u003cstrong\u003e(B)\u003c/strong\u003e Results of GEPIA database analysis. Potplot and boxplot showed the mRNA expression of PLOD1, PLOD2 and PLOD3 in all kind of cancers. * \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05, *** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001. KIRC, kidney renal clear cell carcinoma (an alternative name of ccRCC).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/0694b25b3efbacb028c4eab9.png"},{"id":54395206,"identity":"141704f1-6055-4cb2-b222-c15794524957","added_by":"auto","created_at":"2024-04-09 21:19:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":532999,"visible":true,"origin":"","legend":"\u003cp\u003eExpression levels of PLOD genes in ccRCC. (\u003cstrong\u003eA\u003c/strong\u003e) Boxplot results of mRNA expression levels of PLOD1, PLOD2 and PLOD3 in ccRCC analyzed using GEPIA. (\u003cstrong\u003eB\u003c/strong\u003e) Boxplot of UALCAN database analysis showed the relative mRNA expression of PLOD1, PLOD2 and PLOD3 in ccRCC tissues compared with adjacent normal kidney tissues.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/d962c3ab081c3420ca9e9623.png"},{"id":54394488,"identity":"92a7b50f-b29b-4c08-b8d6-5a508d38a169","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":615258,"visible":true,"origin":"","legend":"\u003cp\u003eElevated expression of PLOD gene family in ccRCC cell lines and tissures. (A)\u003cstrong\u003e \u003c/strong\u003eThe mRNA levels of PLOD gene family in normal kidney epithelial cell HK-2 and ccRCC cell lines (A498 and 786-O) detected by qPCR (n=3). (B) The protein levels of PLOD gene family in normal kidney epithelial cell HK-2 and ccRCC cell lines (A498 and 786-O) detected by western blotting (n=3).(C) The relative protein expression levels of PLOD gene family in figure 3B were analyzed by ImageJ software. (\u003cstrong\u003eD\u003c/strong\u003e) qPCR analysis showed the relative mRNA levels of PLOD gene family in ccRCC tissues compared with adjacent normal kidney tissues (n=4). (\u003cstrong\u003eE\u003c/strong\u003e) Western blotting analysis of PLOD gene family expression levels in ccRCC tissues (T) and matched normal kidney tissues (N) (n=4). (\u003cstrong\u003eF\u003c/strong\u003e) The relative protein expression levels of PLOD gene family in figure 3E were analyzed using ImageJ software. * \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003e P \u003c/em\u003e\u0026lt; 0.01, ***\u003cem\u003e P \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/0f8448f0b50b4f4424fa63e6.png"},{"id":54394489,"identity":"237b351b-b81b-4071-b5a9-057d062c27f1","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2457871,"visible":true,"origin":"","legend":"\u003cp\u003eImmunohistochemical stains of PLOD1, PLO2 and PLOD3 proteins in ccRCC tissues and normal kidney tissues retrieved from HPA dataset.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/83141d555f228d28801ffa66.png"},{"id":54394492,"identity":"ac5fdcbb-0621-4a14-987b-bfa0eac13c6a","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1064398,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations of PLOD genes expressions with clinicopathological stages and survivals of ccRCC.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Boxplots show the relative expressions of PLOD1, PLOD2 and PLOD3 in normal individuals and ccRCC patients with different clinical stages using UACLAN. *** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001. \u003cstrong\u003e(B)\u003c/strong\u003e High levels of PLOD1, PLOD2 and PLOD3 were associated with poor OS in ccRCC. \u003cstrong\u003e(C)\u003c/strong\u003e High levels of PLOD1, PLOD2 and PLOD3 were associated with poor DFS in ccRCC.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/906ab19f11d151e87bb0f55e.png"},{"id":54394494,"identity":"2d1765a2-a117-4a83-b45a-122f4498eb07","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2078874,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations of PLOD gene family expression with immune cells infiltration in ccRCC derived from TIMER database. (\u003cstrong\u003eA\u003c/strong\u003e) Correlations between each type of TIICs (B-cells, CD8\u003csup\u003e+\u003c/sup\u003e T-cells, CD4\u003csup\u003e+\u003c/sup\u003e T-cells, macrophages, neutrophils and dendritic cells) and PLOD1 (\u003cstrong\u003eA\u003c/strong\u003e), PLOD2 (\u003cstrong\u003eB\u003c/strong\u003e), or PLOD3 (\u003cstrong\u003eC\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/67141e2a1ff03e8dd60b7df9.png"},{"id":54394497,"identity":"c7a22b65-ac95-4b42-83bf-f8208084ca91","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":248945,"visible":true,"origin":"","legend":"\u003cp\u003eGenetic alteration frequencies of PLOD genes and their associations with survival of ccRCC using cBioPortal. (\u003cstrong\u003eA\u003c/strong\u003e) Alteration frequency of PLOD genes according to cBioPortal database. (\u003cstrong\u003eB\u003c/strong\u003e) The genetic alterations of PLOD genes in ccRCC. (\u003cstrong\u003eC\u003c/strong\u003e) and (\u003cstrong\u003eD\u003c/strong\u003e) OS and DFS of ccRCC patients with altered (red) and unaltered (blue) mRNA expression of PLOD gene family.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/248ec2ccb55aa49aa607a5f4.png"},{"id":54394496,"identity":"1c802b25-7d63-4d03-8ca7-8cbf5fb10907","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1623413,"visible":true,"origin":"","legend":"\u003cp\u003eKnocking down PLOD3 in 786-O cells effectively inhibited cell migration. (A, B) After knocking down PLOD3 in 786-O cells, the scratch healing rate was measured. (C-E) Western blot analysis of E-Cadherin and Vimentin in 786-O cells with knocking down of PLOD3. * \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003e P \u003c/em\u003e\u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/1991c0b999aac56bafa23335.png"},{"id":54395207,"identity":"4aaf9750-0fcd-460b-b06c-27383e850f51","added_by":"auto","created_at":"2024-04-09 21:19:56","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2097150,"visible":true,"origin":"","legend":"\u003cp\u003eTF-targets and miRNAs-targets regulating PLOD genes. (\u003cstrong\u003eA\u003c/strong\u003e) TF-targets. Yellow, common TFs associated with PLOD1, PLOD2 and PLOD3. Green, TFs associated with two PLOD genes. Blue, TFs associated with one PLOD gene. (\u003cstrong\u003eB\u003c/strong\u003e) miRNAs-targets. Orange, miRNAs associated with PLOD1. Yellow, miRNAs associated with PLOD2. Red, associated with PLOD3. Blue, miRNAs associated with two PLOD genes.\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/355c44bfe9e37700a2c44200.png"},{"id":54394493,"identity":"2b205884-786b-47fc-81bd-5c5fc3fdc8f6","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":2860124,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations among PLOD genes and their co-expressed genes. (\u003cstrong\u003eA-C\u003c/strong\u003e) Correlations among PLOD1, PLOD2 and PLOD3 derived from GEPIA database. (\u003cstrong\u003eD\u003c/strong\u003e) Protein interaction network of 50 functional proteins with confidence score of \u0026gt; 0.4 based on STRING database.\u003c/p\u003e","description":"","filename":"Figure10.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/1d6b0c64d8aae4b4679f8941.png"},{"id":54394499,"identity":"f09bf846-92e4-4422-810a-a212639be038","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":2608979,"visible":true,"origin":"","legend":"\u003cp\u003eGO and KEGG pathway enrichment analyses of the top 50 co-expressed genes of PLOD genes.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA-C\u003c/strong\u003e) GO enrichment. (\u003cstrong\u003eD-F\u003c/strong\u003e) KEGG pathway enrichment. (\u003cstrong\u003eG-I\u003c/strong\u003e) Top 3 KEGG pathways derived from (D).\u003c/p\u003e","description":"","filename":"Figure11.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/a544ea6dcbda31f10b58b70b.png"},{"id":54394498,"identity":"369f699e-f737-4bf9-bbcf-8d38fbccc5d8","added_by":"auto","created_at":"2024-04-09 21:11:56","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":1903841,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted chemicals interacting with PLOD genes and the docking results. (\u003cstrong\u003eA\u003c/strong\u003e) Chemicals. Total 13, 67 and 25 chemicals were predicted which interacted with PLOD1, PLOD2 and PLOD3, respectively. Red circle means PLOD gene family, green diamond indicates chemical, yellow diamond refers to common chemical. (\u003cstrong\u003eB\u003c/strong\u003e) Venn diagram shows the numbers of chemicals that interacted with PLOD genes. (\u003cstrong\u003eC\u003c/strong\u003e) Docking results of affinity between PLOD genes and Acetaminophen.\u003c/p\u003e","description":"","filename":"Figure12.png","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/cae3e378c9cf5a95d586acf7.png"},{"id":60276929,"identity":"d315b668-ba44-4be3-a77e-86e46d9a8218","added_by":"auto","created_at":"2024-07-15 05:33:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":23110830,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/edb2b198-8a2e-428d-a72a-546c8f01ff97.pdf"},{"id":54394501,"identity":"4c16cede-ea04-4161-9a0f-5d1ec64e1963","added_by":"auto","created_at":"2024-04-09 21:11:57","extension":"docx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":291459,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4201423/v1/d7e2d16ba8541e7b01464491.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biological characterization and clinical value of PLOD gene family in clear cell renal cell carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal cell carcinoma (RCC) is a malignant tumor of the urinary system and accounts for 2%\u0026minus;3% of malignant tumors[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of RCC, accounting for 75%\u0026minus;80% of all RCC cases[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In recent years, the morbidity and mortality of ccRCC are increasing, and the onset age is getting younger. Surgical resection is still the most effective treatment for localized ccRCC. However, once distant metastasis occurs, the current treatment is unsatisfactory[\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. As a kind of gene-driven malignant tumor, with the rapid technical development of molecular biology, some genes related to the occurrence and progression of ccRCC have been identified. However, the molecular mechanisms of ccRCC pathogenesis and metastasis remain unclear[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Thus, it is urgent to screen new diagnostic markers and therapeutic targets with great clinical values for improving the survival outcomes of ccRCC patients.\u003c/p\u003e \u003cp\u003ePLOD gene family has the function of lysyl hydroxylase in the lysyl hydroxylation process of collagen[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. There are three members in the PLOD family, namely PLOD1, PLOD2, and PLOD3. Overexpression of PLODs may result in tumor progression and metastasis. PLOD1 and PLOD3 can hydroxylate lysine residues in the triple helix of collagen, whereas PLOD2 is the only one that can hydroxylate lysine residues on the terminal peptides of collagen[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Various studies have shown that highly expressed PLODs can promote tumor invasion and recurrence, indicating that PLODs may be potential targets for tumor prognosis[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the expression and prognostic value of this promising gene family in ccRCC have rarely been investigated.\u003c/p\u003e \u003cp\u003eIn this study, we evaluated the expression, prognostic value, immune infiltration, genetic mutation, cell migration, potential biological functions and inhibitors of PLODs using public datasets and experimental validation. We found that PLODs are highly expressed in ccRCC tissues compared to matched normal tissues, and high expressions of PLODs are positively related to poor overall survival (OS) and reduced disease-free survival (DFS) in ccRCC patients. The study suggests that PLODs are potential biomarkers and therapeutic targets for ccRCC.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGEPIA analysis\u003c/h2\u003e \u003cp\u003eGene Expression Profiling Interactive Analysis \u003cb\u003e(\u003c/b\u003eGEPIA)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia.cancer-pku.cn/\u003c/span\u003e\u003cspan address=\"http://gepia.cancer-pku.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is an online database which facilitates the standardized analysis of RNA sequencing data. GEPIA was used to analyze the expression profiles of PLODs acquired through pan-cancer analysis. The expressions of PLODs in ccRCC tissues and normal renal tissues were compared using GEPIA2. mRNA data were acquired from the Cancer Genome Atlas (TCGA) and Genotypic Tissue Expression (GTEx) databases to visualize the transcriptional profiles of PLODs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTIMER analysis\u003c/h2\u003e \u003cp\u003eTumor IMmune Estimation Resource (TIMER)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cistrome.shinyapps.io/timer/\u003c/span\u003e\u003cspan address=\"https://cistrome.shinyapps.io/timer/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is an intuitive software that can be used to systematically evaluate infiltration of various immune cells and the clinical impacts. We estimated tumor immune infiltration of B cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, neutrophils, macrophages, and dendritic cells based on TIMER. In addition, we studied the differential expressions of PLODs between tumor and contiguous normal tissues based on all TCGA tumors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePatients and kidney tissue sampling\u003c/h2\u003e \u003cp\u003eThe study included four patients diagnosed as ccRCC in Shanxi Bethune Hospital, Taiyuan, China. The institutional ethics approval was authorized by Shanxi Bethune Hospital and informed written consents were obtained from all patients. The ccRCC tissues and paired adjacent normal kidney tissues were harvested during tumor resection, and were frozen in liquid nitrogen and stored at an ultra-low-temperature freezer before use. Total RNAs and proteins were extracted respectively for RT-qPCR and western blotting to verify the bioinformatic results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eRNA isolation and quantitative PCR (qPCR)\u003c/h2\u003e \u003cp\u003eqPCR was performed to examine the mRNA levels of PLODs in ccRCC tissues and paired adjacent normal tissues. Total RNA was extracted from tissues using M5 Universal RNA Mini Kit (Mei5bio, Beijing, China) according to the manufacturer\u0026rsquo;s instruction. qPCR was performed according to the instructions of Vazyme HiScript III RT SuperMix for qPCR (Vazyme, Nanjing, China). Primer sets for selected genes were designed with the assistance of Sangon Biotech Co., Ltd (Shanghai, China). The expression data were normalized to the reference β-actin and the mRNA levels were calculated using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. Primer sequences for qPCR were as follows: β-actin forward: 5\u0026rsquo;-CCTGGCACCCAGCACAAT-3\u0026rsquo;, β-actin reverse: 5\u0026rsquo;-GGGCCGGACTCGTCATAC-3\u0026rsquo;. PLOD1 forward: 5\u0026rsquo;- AAGCCGGAGGACAACCTTTTA-3\u0026rsquo;, PLOD1 reverse: 5\u0026rsquo;- GCGAAGAGAATGACCAGATCC-3\u0026rsquo;. PLOD2 forward: 5\u0026rsquo;- GACAGCGTTCTCTTCGTCCTCA-3\u0026rsquo;, PLOD2 reverse: 5\u0026rsquo;- CTCCAGCCTTTTCGTGGTGACT-3\u0026rsquo;. PLOD3 forward: 5\u0026rsquo;- GCGCCAGTGGAAGTACAAGGAT-3\u0026rsquo;, PLOD3 reverse: 5\u0026rsquo;- CACTTCATCTAAAGCCCCGTTGA \u0026minus;\u0026thinsp;3\u0026rsquo;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eWestern blotting\u003c/h2\u003e \u003cp\u003eTotal proteins for western blotting were extracted from ccRCC tissues and paired adjacent normal tissues. The concentration of all protein samples was determined using the bicinchoninic acid (BCA) assay (Solarbio Co., Ltd, Beijing, China). A total amount of 30 \u0026micro;g extracted proteins of each sample were separated by 10% SDS-PAGE gel. Next, proteins from the SDS-PAGE gel were transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, Billerica, MA, USA). Membranes were blocked with 5% nonfat milk for 1 h at room temperature. The membranes were incubated with antibody of PLOD1 (1:1000, Proteintech, 29480-1-AP), PLOD2 (1:1000, Proteintech, 66342-1-Ig), PLOD3 (1:1000, Proteintech, 60058,1-Ig) or β-actin (1:5000, Bioworld, AP0060) for overnight at 4 ℃. The membranes were washed with TBST and then were incubated with a secondary antibody conjugated with horseradish peroxidase (Zhongshan Golden Bridge Biotechnology, Beijing, China) for 1 h at room temperature, and were washed again with TBST. Finally, ECL luminescence solution (SEVEN, Beijing, China) was added and the blots were scanned using Image Lab\u0026trade; Touch Software (Bio-Rad Laboratories, Hercules, CA, USA). The gray values of protein bands were determined using ImageJ, and β-actin was used for normalization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eUALCAN dataset analysis\u003c/h2\u003e \u003cp\u003eUALCAN[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ualcan.path.uab.edu/\u003c/span\u003e\u003cspan address=\"http://ualcan.path.uab.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a comprehensive tool that provides analysis according to TCGA dataset. We analyzed the transcriptional levels of PLOD genes between ccRCC tissues and adjacent normal tissues. The relationship between the expression levels of PLOD genes and tumor stage were also analyzed uisng this database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eHuman Protein Atlas dataset analysis\u003c/h2\u003e \u003cp\u003eThe Human Protein Atlas (HPA)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.proteinatlas.org/\u003c/span\u003e\u003cspan address=\"http://www.proteinatlas.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a free database that provides information about human encoded proteins. HPA was used to analyze the protein expression levels of PLODs in ccRCC tissues and adjacent normal tissues.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eKaplan\u0026ndash;Meier plotter survival analysis\u003c/h2\u003e \u003cp\u003eThe Kaplan-Meier (KM) plotter[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is dedicated to analyze the survival biomarkers of 21 cancer types based on data from Gene Expression Omnibus database (GEO), European Genome-phenome Archive (EGA) and TCGA. We used Kaplan-Meier plotter to identify the association between PLODs and survivals (OS and DFS) in ccRCC patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ecBioPortal database analysis\u003c/h2\u003e \u003cp\u003eThe cBio Cancer Genomics Portal (cBioPortal)[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a network resource that can be used to analyze multidimensional cancer genomic data as well as for data visualization. We evaluated the copy number variants (CNV), mutations, and gene types in ccRCC patients based on the cBioPortal on-line instructions. In addition, we analyzed the relationship between gene mutation and ccRCC prognosis using the cBioPortal tool based on TCGA database. DFS and OS were also analyzed for with or without PLODs mutation in KIRC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCell migration analysis\u003c/h2\u003e \u003cp\u003ePLOD3 small interfering (si)RNA and Control siRNA was transfected into 786-O cell lines using Lipofectamine2000 reagent (Invitrogen) according to the manufacture\u0026rsquo;s protocol. Migration was detected with a wound healing assay using a 6-well plate. When the confluence of 786-O cells reached\u0026thinsp;~\u0026thinsp;90\u0026ndash;100% in RPMI-1640 medium with 10% FBS, scratch wounds were created in each cell. After scratching, the debris was removed and FBS free medium was added, the cell images were obtained after 0, 12, 24 h of incubation at 37℃. Migration was calculated as the relative percentage of scratch area to the area at 0 h (% of wound closure) using ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTF-Target and miRNA-Target of PLOD gene family\u003c/h2\u003e \u003cp\u003eThe target genes of PLODs were predicted using Targetscan[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.targetscan.org/\u003c/span\u003e\u003cspan address=\"http://www.targetscan.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and GeneCards[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The intersections of predictions from the two databases were matched by FunRich software to ascertain their regulatory targets. Starbase[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://starbase.sysu.edu.cn/\u003c/span\u003e\u003cspan address=\"http://starbase.sysu.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Targetscan (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.targetscan.org/vert_72/\u003c/span\u003e\u003cspan address=\"http://www.targetscan.org/vert_72/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were used to locate the upstream miRNAs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eInteractions of PLOD genes verified by STRING\u003c/h2\u003e \u003cp\u003eSTRING[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a free online database developed by European Molecular Biology Laboratory for functional connection of genes and for retrieval of interacting genes. STRING was used to search co-expression genes of PLODs and to conduct protein-protein interaction (PPI) networks with an interaction score\u0026thinsp;\u0026gt;\u0026thinsp;0.4.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of biological functions and pathways\u003c/h2\u003e \u003cp\u003eMetascape[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://metascape.org\u003c/span\u003e\u003cspan address=\"http://metascape.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a web tool developed for powerful computational analysis of large-scale datasets. Using Metascape performing annotation analysis, we predicted potential biological functions of PLODs and pathways involved in ccRCC and analyzed the GO and KEGG pathway enrichments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePrediction of chemicals interacting with PLOD gene family\u003c/h2\u003e \u003cp\u003eComparative Toxicogenomics Database (CTD) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ctdbase.org/\u003c/span\u003e\u003cspan address=\"http://ctdbase.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a powerful public database that integrates large numbers of data among chemicals, genes, functional phenotypes and diseases. It provides information on the associations of chemical-gene/protein, chemical-disease, and gene-disease, and thus is helpful in the predicting mechanistic hypotheses about the effect of environment on disease. We used CTD to predict potential chemicals which interact with PLOD gene family. In the CTD database, we chose chemicals with \u0026ldquo;interaction\u0026rdquo; \u0026gt; 3 as the cut-off criteria to perform further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDocking analysis of affinity between chemicals and PLOD gene family\u003c/h2\u003e \u003cp\u003eMolecular docking approach was used to identify the affinities of predicted chemicals with PLOD1, PLOD2, and PLOD3. The structures of the chemicals from PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"http://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were downloaded, and Chem3D software was used to minimize the ligand molecular energy. The 3D structures of PLOD genes were obtained from PDB database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www1.rcsb.org/\u003c/span\u003e\u003cspan address=\"http://www1.rcsb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) or UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"http://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). AutoDockTools 1.5.6 software was used to find out the active pockets. Vina script was run to calculate the molecular binding energy, Vina\u0026thinsp;\u0026le;\u0026thinsp;\u0026minus;7.0 kcal.mol\u003csup\u003e\u0026minus;1\u003c/sup\u003e indicated strong binding of \u0026ldquo;ligand\u0026rdquo; with \u0026ldquo;receptor\u0026rdquo;. PyMOL software was used to display the results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using Graph-Pad Prism 6.0 software. Data were represented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of mean (SEM). Two-tail \u003cem\u003et\u003c/em\u003e-test was used to compare the means of two sample groups. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eHigh mRNA and protein expressions of PLOD gene family in ccRCC\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe first identified the mRNA levels of PLOD genes in various cancers using TIMER and GEPIA database. The transcription levels of PLOD genes were noticeably upregulated in several cancers compared with respective normal tissues, especially in ccRCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). We also used UALCAN online tool to further verify the transcriptional levels of PLODs in TCGA database. Results show that all the three PLOD genes were low expressed in normal kidney tissues while were significantly upregulated in ccRCC tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB)​. These results suggest that the expression level of PLOD gene family might be an indicator of ccRCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e To verify the above bioinformatic results shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, RT-qPCR and western blotting were performed in ccRCC cell line and human ccRCC tissues and corresponding normal kidney tissues. RT-qPCR results showed that the mRNA levels of PLOD genes in ccRCC cell lines and tissues were significantly upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, D), which are consistent with the bioinformatic results. Western blotting results show that the protein expression levels of PLOD1, PLOD2 and PLOD3 in ccRCC cell lines and tissues were also significantly higher than the normal kidney epithelial cell and tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C, E, F).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemical features of PLODs proteins in human ccRCC and normal kidney tissues\u003c/h2\u003e \u003cp\u003eThe immunohistochemical stains of PLOD1, PLOD2 and PLOD3 proteins in ccRCC tissues and normal kidney tissues were retrieved from HPA database. Results reveal that the positively stained signals of PLOD1, PLOD2 and PLOD3 were all weak in normal kidney tissues but were strong in ccRCC tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), which are consistent with the western blots.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eValues of PLOD gene family in determining the clinicopathological stages and prognostics of ccRCC\u003c/h2\u003e \u003cp\u003eGene expression level may affect cancer development. We investigated the relationship between the expression levels of PLOD genes and the clinicopathological stages of ccRCC using UALCAN online tool. Results show that the expression levels of PLOD family members were all significantly high in various clinical stages (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with the normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). No difference of PLODs expression levels was found among the four stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), suggesting that PLOD levels can indicate any stages of ccRCC, including the stage 1. There was also no difference among PLOD members in indicating the clinicopathological stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), which suggests that all the three PLOD members can reflect the progression of ccRCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan-Meier plotter survival curves were established to further evaluate the correlation between differentially expressed PLOD genes and ccRCC prognosis. We selected median value to divide samples into high and low expression groups. Results show that higher mRNA expression of PLOD1, PLOD2 and PLOD3 were associated with poorer OS in ccRCC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The prognostic values of PLOD genes were also conducted by comparing PLODs levels and the DFS of ccRCC patients. Higher mRNA levels of PLOD1, PLOD2 and PLOD3 were associated with worse DFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). These results suggest that PLOD gene family could be used as predicters of the clinical outcomes of ccRCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTumor microenvironment (TME) has essential impact on tumor growth, metastasis, prognosis, and therapeutic response to anticancer drugs[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The potential association of PLODs expression levels with immune infiltration in ccRCC were investigated based on TIMER database. The expression level of PLOD1 was not correlated with immune infiltration (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The expressions of PLOD2 and PLOD3 had remarkable negative correlations with tumor purity in ccRCC (cor\u0026thinsp;=\u0026thinsp;\u0026minus;0.124 and \u0026minus;0.094, respectively, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB, C). The abundance of B cells, macrophages, neutrophils and dendritic cells showed positive association with PLOD2 (cor\u0026thinsp;=\u0026thinsp;0.182, 0.181, 0.273, 0.151, respectively, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Significantly positive correlation was found between PLOD3 expression and B cells and dendritic cells infiltration (cor\u0026thinsp;=\u0026thinsp;0.137 and 0.114, respectively, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Generally, among these immune cells, B cells and dendritic cells were most closely connected to the occurrence and development of ccRCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eGenetic alterations of PLOD gene family in ccRCC patients\u003c/h2\u003e \u003cp\u003eGenetic alterations in the three PLOD genes of ccRCC patients was ascertained using cBioPortal database. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA shows the frequency of genetic alterations, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB exhibits genetic alterations of PLOD genes in ccRCC patients. The percentage changes of DNA alterations were 0.7% in PLOD1, 1.6% in PLOD2, and 3% in PLOD3. We further examined the relationship between changes of PLOD gene expressions and the prognosis of ccRCC using the cBioPortal database. Survival curves were established to demonstrate the OS and DFS of ccRCC patients with altered or unaltered mRNA expressions of PLODs. The alterations of PLOD genes were closely related to OS in ccRCC patients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.339e-3), while were not significantly associated with DFS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0962) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMigration and infiltration function play an essential role in tumor progression. To explore whether PLOD3 affected the migration of ccRCC cells, we conducted wound healing assay. Results showed that knocking down PLOD3 was able to inhibit the scratch healing rate of 786-O cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA, B). Then we analyzed the effect of PLOD3 on the epithelial-mesenchymal transition (EMT) process of 786-O cells. The results indicated that knocking down PLOD3 inhibited the EMT process of 786-O cells as evidenced by increased epithelial marker E-Cadherin and decreased mesenchymal maker Vimentin (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC-E). These findings suggested that knocking down PLOD3 effectively suppressed the migration of 786-O cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of transcription factors and microRNAs regulating PLOD gene family expression in ccRCC\u003c/h2\u003e \u003cp\u003eMicroRNAs (miRNAs) are a large set of non-coding small RNAs that binds to 3\u0026rsquo;UTR of target mRNA to regulate gene expression, which leads to aberrant expression profiles of target genes. miRNAs are closely related to transcription factors (TFs) in regulating gene expressions in response to cellular environment and signaling[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Here, we used TF-target databases (hTFtarget and Genecards) and miRNA-target databases (Starbase and Targetscan) to predict the upstream TFs and miRNAs that regulate the expression of PLOD genes. We found 123 TFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA) and 113 miRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB) that regulate the expression of PLOD gene family in ccRCC. The numbers of TFs regulating PLOD1, PLOD2 and PLOD3 were respectively 85, 79 and 96, as shown by the intersection selected from GeneCard and hTFtarget database. The numbers of miRNAs that regulate PLOD1, PLOD2 and PLOD3 were respectively 42, 68 and 16, as shown by the intersection selected from Starbase and Targetscan database (Additional file 1: Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eCorrelation among PLOD genes and their co-expressed genes in ccRCC\u003c/h2\u003e \u003cp\u003eTo investigate the potential functions of PLOD genes in ccRCC, we further clarified the synergy among PLOD family members. By mining the GEPIA database, we found that the expressions of PLOD1 was positively correlated with PLOD2 and PLOD3 (R\u0026thinsp;=\u0026thinsp;0.28 and 0.53, respectively, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the expression of PLOD2 was positively correlated with PLOD3 (R\u0026thinsp;=\u0026thinsp;0.22, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe further explored the interaction between PLOD gene family and their co-expressed genes in ccRCC using STRING database, and found that the top 50 co-expressed genes of PLOD gene family were: COL11A1, COL12A1, COL13A1,COL14A1, COL15A1, COL16A1, COL17A1, COL18A1, COL1A1, COL20A1, COL22A1, COL25A1, COL26A1, COL27A1, COL2A1, COL3A1, COL4A1, COL4A2, COL4A5, COL4A6, COL5A1, COL5A2, COL5A3, COL6A1, COL6A2, COL6A3, COL6A6, COL7A1, COL8A1, COL8A2, COL9A2, COL9A3, COLGALT1, COLGALT2, COLQ, CRTAP, EHMT2, FKBP10, IFITM5, KDM1A, LEPRE1, NSD1, P4HA1, P4HA2, PLOD1, PLOD2, PLOD3, SETD7, SETD8, and TMEM38B (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eD; Additional file 1: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These top 50 co-expressed genes were selected to conduct the following functional analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eFunctional enrichment analysis of co-expressed genes of PLOD gene family in ccRCC\u003c/h2\u003e \u003cp\u003eTo better understand the potential mechanisms of PLOD gene family in regulating ccRCC, we used Metascape to construct Gene Ontology (GO) enrichment and KEGG pathway analysis. The GO analysis was conducted on three aspects, including biological processes (BP), cellular components (CC), and molecular functions (MF). GO functional enrichment analysis demonstrated that these genes (PLOD gene family and the top 50 co-expressed genes) were significantly enriched in some terms and pathways, including extracellular matrix structural constituent conferring tensile strength, complex of collagen trimers, collagen fibril organization, etc. These GO terms may play critical roles in the pathogenesis and progression of ccRCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA\u0026minus;C; Additional file 1: Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eResult of KEGG pathway analysis show that PLOD genes and their top 50 co-expressed genes were enriched mainly in three functional pathways, including hsa04974 (protein digestion and absorption), hsa04512 (ECM-receptor interaction), and hsa00310 (lysine degradation) (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eD, F; Additional file 1: Table S3). The detailed signaling of these three KEGG pathways are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eG\u0026minus;I. These functional terms and pathways were mostly associated with extracellular matrix structural constituent, collagen synthesis and lysine degradation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003ePredicted chemicals interacting with PLOD genes and docking analysis\u003c/h2\u003e \u003cp\u003eCTD database was used to predict chemicals that may interact with PLOD genes. Results of CTD analysis show that 9, 51 and 18 chemicals interacted with PLOD1, PLOD2 and PLOD3, respectively. Notably, bisphenol A, tetrachlorodibenzodioxin, acetaminophen, ethanol, and nanotubes/carbon were the common chemicals regulating all the three PLOD genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eA, B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe 3D structures of PLOD1 and PLOD2 were downloaded from UniProt database, and the 3D structure of PLOD3 was obtained from PDB database (PDB ID: 6FXR). The binding energies of acetaminophen with PLOD1, PLOD2 and PLOD3 were \u0026minus;6.1 kcal\u0026middot;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u0026minus;6.2 kcal\u0026middot;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and \u0026minus;6.3 kcal\u0026middot;mol\u003csup\u003e\u0026minus;1\u003c/sup\u003e, respectively, suggesting that the binding between acetaminophen and the three \u0026ldquo;receptors\u0026rdquo; (PLOD proteins) were strong. From the results of ligand-receptor protein interaction, we found that acetaminophen could form hydrogen bonds with LYS77, ARG179 and GLN129, and had hydrophobic interactions with the amino acid residues TYR223 and GLN180, of PLOD1. In addition, acetaminophen formed hydrogen bonds with ASN223 and SER166, while had hydrophobic interaction with TRP145 and GLN192, of PLOD2. Furthermore, acetaminophen formed hydrogen bonds with ARG411, ARG57, GLY266 and HIS505, and showed hydrophobic interaction with TEP281, of PLOD3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eC). These forces enable acetaminophen to bind stably to the pockets of the three PLOD proteins.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe importance of PLOD gene family has drawn increasing attention due to their critical role in the synthesis of collagen. Previous studies indicate that PLODs are involved in various malignant behaviors of tumors, such as proliferation, invasion, and metastasis[\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Although the roles of PLODs in the development and progression of several tumors have been reported, the potential functions and prognostic values of PLODs in ccRCC have yet to be comprehensively elucidated. In the present study, we performed bioinformatic analysis and experimental validation, including mRNA and protein expression, prognostic value, immune-infiltration, genetic alteration, potential function of PLOD family members in ccRCC, and also predicted some chemicals which may affect PLOD genes and thus may have potential therapeutic effects on ccRCC. We found that PLODs were upregulated in ccRCC tissues compared to normal kidney tissues. RT-qPCR and western blotting validations confirmed the bioinformatic results. We further identified that high expression levels of PLOD genes are significantly associated with poor survival (including OS and DFS) in patients with ccRCC. GO and KEGG pathway enrichment analyses demonstrate that PLOD genes were mainly involved in the regulation of collagen metabolism and extracellular matrix composition. We also predicted that acetaminophen is a potential inhibitor for all the PLOD genes and thus may become a therapeutic drug for ccRCC.\u003c/p\u003e \u003cp\u003ePLOD1 is overexpressed in various malignant cancers, including gastric cancer, glioma, glioblastoma multiforme and osteosarcoma[31, 34\u0026minus;38]. Zhang \u003cem\u003eet al\u003c/em\u003e. reported that PLOD1 promotes cell growth and aerobic glycolysis through activating the SOX9/PI3K/Akt/mTOR signaling in gastric cancer[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Wang \u003cem\u003eet al\u003c/em\u003e. demonstrated that highly expressed PLOD1 promotes glioblastoma progression via NF-κB signaling and PLOD1 may serve as a potential treatment target for mesenchymal GBM[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Dysregulated PLOD1 is also associated with osteosarcoma[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Wu \u003cem\u003eet al\u003c/em\u003e. revealed that PLOD1 enhances tumorigenesis and metastasis in osteosarcoma, and PLOD1 expression is regulated by miR-34c, suggesting that miR-34c/PLOD1 may be a potential therapeutic target for osteosarcoma treatment[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePLOD2 is the key enzyme catalyzing the hydroxylation of lysyl and stabilizing collagen crosslinks. Increasing evidences show that PLOD2 is highly expressed in various tumors, and overexpressed PLOD2 is associated with poor outcomes, such as oral squamous cell carcinoma, hepatocellular carcinoma, breast cancer and sarcoma[40\u0026minus;44]. It has been reported that PLOD2 is upregulated and positively correlated with the metastasis of breast cancer, providing a potential treatment target for breast cancer[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. PLOD2 is regulated by many factors. For example, HIF-1α regulates the expression of PLOD2 to promote metastasis of endometrial carcinoma[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In the central nervous system, hypoxia-induced PLOD2 can facilitate tumorigenesis via the PI3K/Akt signaling in glioma[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. PLOD2 inhibits the expression of HK2 via the STAT3 signaling pathway, resulting in decreases of proliferation, invasiveness and aerobic glycolysis in colorectal cancer cells[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePLOD3 is a multifunctional enzyme, mainly catalyzes the hydroxylation of lysine residues in collagen. PLOD3 is overexpressed in many solid tumors, including ovarian cancer, colon adenocarcinoma and hepatocellular carcinoma[49\u0026minus;51]. PLOD3 plays considerable roles in lung cancer metastasis via the STAT3 signaling pathway[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. A recent study showed that PLOD3 plays essential roles in the progression of non-small cell lung cancer via regulating the PKCδ/CDK1/LIMD1/YAP1 axis[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe identified high expressions of all the three PLOD genes in ccRCC tissues, and the high expression levels of the three PLOD genes showed no difference among the four stages of ccRCC. There is also no difference among the three PLOD genes in indicating the clinicopathological stages. These results suggest either of the three PLOD genes and its product can indicate ccRCC at any stages. This finding may simplify the clinical procedures using any of PLODs in the diagnosis and prognosis evaluation of ccRCC.\u003c/p\u003e \u003cp\u003ePrevious studies revealed that the mechanisms of PLOD gene family in cancer development are mainly involved in the regulation of collagen metabolism, extracellular matrix construction, and immune microenvironment[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In the present study, mutations of PLODs in ccRCC were found closely related to the prognosis of ccRCC patients. However, we did not investigate the relationship between special types of mutations and the prognosis of ccRCC, such as functional mutations, hot regions and mutational pattern. This area warrants further studies.\u003c/p\u003e \u003cp\u003eBy mining the protein-protein interaction networks, we found that COL11A1 was the most closely related protein with PLOD gene family. COL11A1 exerts crucial role in bone development and collagen fiber assembly. COL11A1 is upregulated in several cancers[54\u0026minus;56]. COL11A1 overexpression accelerates tumor progression and cancer-associated fibroblasts activation via the TGF-β3 signaling pathway in ovarian cancer cells[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In addition, COL11A1 promotes cell proliferation, migration and inhibits cell apoptosis in non-small cell lung cancer cells[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. COL11A1 also promotes the invasion and migration of pancreatic cancer cells by facilitating epithelial-mesenchymal transition through AKT/GSK-3β/Snail signaling pathway[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The effect and signaling of COL11A1 on the tumor cells of ccRCC also need further studies.\u003c/p\u003e \u003cp\u003eOur functional enrichment analyses on PLODs in ccRCC indicated that PLOD genes are mainly involved in collagen synthesis and lysine hydroxylation. KEGG pathways enrichment analysis indicated that PLOD genes are mainly involved in ECM-receptor interactions and lysine degradation. Collagen is one of the main components of the extracellular matrix, and the hydroxylation of lysine residues is a key step in collagen biosynthesis. Increased collagen deposition and cross-linking promote cancer development and progression by enhancing cancer cell migration, invasion, and proliferation\u003csup\u003e[11]\u003c/sup\u003e. A study found that the invasion of ccRCC is closely related to ECM[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Therefore, we speculate that PLOD genes are involved in the malignant biological process of ccRCC.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eHigh expressions of PLOD genes are positively associated with all the four clinical stages and the poor prognosis of ccRCC. Total 123 TFs and 133 miRNAs are identified to regulate the expressions of PLOD genes. The functions of PLOD genes in ccRCC mainly involve to collagen synthesis, ECM-receptor interaction and lysine degradation. High expression of PLOD genes may serve as biomarkers indicating poor prognosis of ccRCC. Some predicted chemicals targeting PLOD genes may have therapeutic potentials for ccRCC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Shanxi Bethune Hospital/Shanxi Academy of Medical Sciences (Approval No.: YXLL-2021-066). All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation and conducted according to the principles expressed in the Helsinki Declaration of 1964 and later versions. All patients have signed informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors agree to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data in this study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Key Medical Science and Technology Program of Shanxi Province (2020XM01), Shanxi \u0026ldquo;1331\u0026rdquo; Project Quality and Efficiency Improvement Plan (1331 KFC), and Basic Research Program of Shanxi Province (202103021223238).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXS carried out experiments, data analysis and drafted manuscript. LL performed data analysis, drew figures and drafted manuscript. MY, RMR, KXG, JW, WZ, JSC and JLL performed data analysis. LJG and JMC supervised the study and revised manuscript. All authors read and approved the submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the mentioned public databases for providing us the data and analytical tools.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel RL, Miller KD, Jemal A. Cancer statistics, 2019. Cancer J Clin. 2019;69(1):7\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiegel RL, Miller KD, Jemal A. Cancer statistics, 2020. Cancer J Clin. 2020;70(1):7\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNabi S, Kessler ER, Bernard B, Flaig TW, Lam ET. 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Cell Death Dis. 2018;9(12):1138.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi WH, Huang K, Wen FB, Cui GH, Guo HZ, Zhao S. PLOD3 regulates the expression of YAP1 to affect the progression of non-small cell lung cancer via the PKCδ/CDK1/LIMD1 signaling pathway. Lab Invest. 2022;102(4):440\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNallanthighal S, Heiserman JP, Cheon DJ. Collagen Type XI Alpha 1 (COL11A1): A Novel Biomarker and a Key Player in Cancer. Cancers 2021, 13(5).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi W, Chen Z, Liu H, Miao C, Feng R, Wang G, Chen G, Chen Z, Fan P, Pang W, et al. COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation. Front Immunol. 2022;13:937125.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu K, Cai L, Cui C, de Los Toyos JR, Anastassiou D. Single-cell analysis reveals the pan-cancer invasiveness-associated transition of adipose-derived stromal cells into COL11A1-expressing cancer-associated fibroblasts. PLoS Comput Biol. 2021;17(7):e1009228.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu YH, Huang YF, Chang TH, Chen CC, Wu PY, Huang SC, Chou CY. COL11A1 activates cancer-associated fibroblasts by modulating TGF-β3 through the NF-κB/IGFBP2 axis in ovarian cancer cells. Oncogene. 2021;40(26):4503\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTu H, Li J, Lin L, Wang L. COL11A1 Was Involved in Cell Proliferation, Apoptosis and Migration in Non-Small Cell Lung Cancer Cells. J Invest surgery: official J Acad Surg Res. 2021;34(6):664\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Zhou H, Ni H, Shen X. COL11A1-Driven Epithelial-Mesenchymal Transition and Stemness of Pancreatic Cancer Cells Induce Cell Migration and Invasion by Modulating the AKT/GSK-3β/Snail Pathway. \u003cem\u003eBiomolecules\u003c/em\u003e 2022, 12(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhluwalia P, Ahluwalia M, Mondal AK, Sahajpal N, Kota V, Rojiani MV, Rojiani AM, Kolhe R. Prognostic and therapeutic implications of extracellular matrix associated gene signature in renal clear cell carcinoma. Sci Rep. 2021;11(1):7561.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOxburgh L. The Extracellular Matrix Environment of Clear Cell Renal Cell Carcinoma. Cancers 2022, 14(17).\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":"PLOD gene family, Expression signature, Clear cell renal cell carcinoma, Prognosis, Bioinformatics","lastPublishedDoi":"10.21203/rs.3.rs-4201423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4201423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eStudies have identified that procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) gene family is closely related to tumor progression and metastasis in various cancers. However, the expression pattern, clinical value and function of PLOD gene family in clear cell renal cell carcinoma (ccRCC) have not yet been studied.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe investigated the expression, prognostic value, immune cell infiltration, genetic mutation, cell migration, and biological function of the PLOD gene family in ccRCC through comprehensive bioinformatic analysis and experimental validation, and predicted potential chemicals which regulate the expression of PLOD gene family using comparative toxicogenomics database (CTD) and docking analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mRNA and protein expressions of PLOD gene family were highly increased in ccRCC tissues compared with normal tissues, and high expressions of all the three PLOD genes were positively related to every clinicopathological stages, poor overall survival (OS) and disease-free survival (DFS) in ccRCC patients. Fifty co-expressed genes of PLODs were found related with ccRCC. Functional enrichment analysis revealed that collagen synthesis, ECM-receptor interaction and lysine degradation were key biological functions of PLODs in ccRCC. A variety of chemicals were predicted to regulate the expression of PLOD gene family especially acetaminophen.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHigh expression of PLOD gene family is closely related to poor prognosis of ccRCC and they can predict any stage of ccRCC. PLOD gene family may serve as a prognostic biomarker and even a therapeutic target for ccRCC.\u003c/p\u003e","manuscriptTitle":"Biological characterization and clinical value of PLOD gene family in clear cell renal cell carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-09 21:11:51","doi":"10.21203/rs.3.rs-4201423/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":"f79869d6-b1fb-4e14-8caf-2b489a4926dd","owner":[],"postedDate":"April 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-15T05:25:37+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-09 21:11:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4201423","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4201423","identity":"rs-4201423","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}