Identification of key genes and pathways in human clear cell renal cell carcinoma (ccRCC) by co-expression analysis

Human clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In our study, we screened differential expressed genes, and constructed protein-protein interaction (PPI) network and a weighted gene co-expression network to identify key genes and pathways associated with the progression of ccRCC (n = 56). Functional and pathway enrichment analysis demonstrated that upregulated differentially expressed genes (DEGs) were significantly enriched in response to wounding, positive regulation of immune system process, leukocyte activation, immune response and cell activation. Downregulated DEGs were significantly enriched in oxidation reduction, monovalent inorganic cation transport, ion transport, excretion and anion transport. In the PPI network, top 10 hub genes were identified (TOP2A, MYC, ALB, CDK1, VEGFA, MMP9, PTPRC, CASR, EGFR and PTGS2). In co-expression network, 6 ccRCC-related modules were identified. They were associated with immune response, metabolic process, cell cycle regulation, angiogenesis and ion transport. In conclusion, our study illustrated the hub genes and pathways involved in the progress of ccRCC, and further molecular biological experiments are needed to confirm the function of the candidate biomarkers in human ccRCC.

[1]  Yunlong Liu,et al.  Identification of genes and pathways involved in kidney renal clear cell carcinoma , 2014, BMC Bioinformatics.

[2]  Brad T. Sherman,et al.  DAVID: Database for Annotation, Visualization, and Integrated Discovery , 2003, Genome Biology.

[3]  G. Freeman,et al.  Novel Roles of c-Met in the Survival of Renal Cancer Cells through the Regulation of HO-1 and PD-L1 Expression* , 2015, The Journal of Biological Chemistry.

[4]  J. Coulson,et al.  Combined Analyses of the VHL and Hypoxia Signaling Axes in an Isogenic Pairing of Renal Clear Cell Carcinoma Cells. , 2015, Journal of proteome research.

[5]  Davide Heller,et al.  STRING v10: protein–protein interaction networks, integrated over the tree of life , 2014, Nucleic Acids Res..

[6]  J. Côté,et al.  Protein arginine methyltransferase 7 promotes breast cancer cell invasion through the induction of MMP9 expression , 2014, Oncotarget.

[7]  J. Ochocki,et al.  Fructose-1, 6-bisphosphatase opposes renal carcinoma progression , 2014, Nature.

[8]  Jun Dong,et al.  Geometric Interpretation of Gene Coexpression Network Analysis , 2008, PLoS Comput. Biol..

[9]  A. Gibson,et al.  Cisplatin-Induced Renal Injury Is Independently Mediated by OCT2 and p53 , 2014, Clinical Cancer Research.

[10]  Robert J Gillies,et al.  Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes. , 2015, Cancer research.

[11]  Jing Liu,et al.  Strong correlation between ASPM gene expression and HCV cirrhosis progression identified by co-expression analysis. , 2017, Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver.

[12]  N. Dubrawsky.  Cancer statistics , 1989, CA: a cancer journal for clinicians.

[13]  Yingying Wang,et al.  The expression of CDK1 is associated with proliferation and can be a prognostic factor in epithelial ovarian cancer , 2015, Tumor Biology.

[14]  P. A. Futreal,et al.  Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing , 2014, Nature Genetics.

[15]  M. Lindskog,et al.  Prognostic significance of serum albumin in patients with metastatic renal cell carcinoma , 2014, Medical Oncology.

[16]  Hong-zhao Li,et al.  MicroRNA-185 inhibits cell proliferation and induces cell apoptosis by targeting VEGFA directly in von Hippel-Lindau-inactivated clear cell renal cell carcinoma. , 2015, Urologic oncology.

[17]  Yi Guo,et al.  Human Papillomavirus 16 E6 Contributes HIF-1α Induced Warburg Effect by Attenuating the VHL-HIF-1α Interaction , 2014, International journal of molecular sciences.

[18]  G. Sotgiu,et al.  EGFR kinase-dependent and kinase-independent roles in clear cell renal cell carcinoma. , 2016, American journal of cancer research.

[19]  J. Houštěk,et al.  A new role for the von Hippel-Lindau tumor suppressor protein: stimulation of mitochondrial oxidative phosphorylation complex biogenesis. , 2004, Carcinogenesis.

[20]  S. Yeh,et al.  Infiltrating neutrophils promote renal cell carcinoma progression via VEGFa/HIF2α and estrogen receptor β signals , 2015, Oncotarget.

[21]  Karl J. Dykema,et al.  Identification of deregulated oncogenic pathways in renal cell carcinoma: an integrated oncogenomic approach based on gene expression profiling , 2007, Oncogene.

[22]  S. Raska.  THE METABOLISM OF THE KIDNEY. , 1944, Science.

[23]  Jin-cheng Pan,et al.  Matrix metalloproteinase-9 is required for vasculogenic mimicry by clear cell renal carcinoma cells. , 2015, Urologic oncology.

[24]  Cheng Li,et al.  GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses , 2017, Nucleic Acids Res..

[25]  M. Scalise,et al.  OCTN Cation Transporters in Health and Disease , 2013, Journal of biomolecular screening.

[26]  T. Choueiri,et al.  Primary anti-vascular endothelial growth factor (VEGF)-refractory metastatic renal cell carcinoma: clinical characteristics, risk factors, and subsequent therapy. , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.

[27]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[28]  A. Jemal,et al.  Cancer statistics, 2017 , 2017, CA: a cancer journal for clinicians.

[29]  Jaap Keijer,et al.  HIF and reactive oxygen species regulate oxidative phosphorylation in cancer. , 2008, Carcinogenesis.

[30]  Gary D. Bader,et al.  An automated method for finding molecular complexes in large protein interaction networks , 2003, BMC Bioinformatics.

[31]  R. Deberardinis,et al.  Dysregulated metabolism contributes to oncogenesis. , 2015, Seminars in cancer biology.

[32]  C. Gieger,et al.  Human metabolic individuality in biomedical and pharmaceutical research , 2011, Nature.

[33]  G. Freeman,et al.  Orchestration and Prognostic Significance of Immune Checkpoints in the Microenvironment of Primary and Metastatic Renal Cell Cancer , 2015, Clinical Cancer Research.

[34]  X. Cheng,et al.  MKL1 potentiates lung cancer cell migration and invasion by epigenetically activating MMP9 transcription , 2015, Oncogene.

[35]  Meng Zhang,et al.  Overexpression of Topoisomerase 2-Alpha Confers a Poor Prognosis in Pancreatic Adenocarcinoma Identified by Co-Expression Analysis , 2017, Digestive Diseases and Sciences.

[36]  D. Grignon,et al.  Clear cell renal cell carcinoma. , 2005, Clinics in laboratory medicine.

[37]  G. Yousef,et al.  Identification and validation of dysregulated metabolic pathways in metastatic renal cell carcinoma , 2014, Tumor Biology.

[38]  舒志强,et al.  von Hippel Lindau , 2010, Radiopaedia.org.

[39]  Kaiyu Qian,et al.  Overexpression of COL3A1 confers a poor prognosis in human bladder cancer identified by co-expression analysis , 2017, Oncotarget.

[40]  J. Varani,et al.  Role of calcium sensing receptor (CaSR) in tumorigenesis. , 2013, Best practice & research. Clinical endocrinology & metabolism.

[41]  Chin-Lee Wu,et al.  Co-expression network analysis identified six hub genes in association with progression and prognosis in human clear cell renal cell carcinoma (ccRCC) , 2017, Genomics data.

[42]  I. Tannock,et al.  Systemic therapy for non-clear cell renal cell carcinomas: a systematic review and meta-analysis. , 2015, European urology.

[43]  N. Jonjić,et al.  EGFR expression is linked to osteopontin and Nf-κB signaling in clear cell renal cell carcinoma , 2012, Clinical and Translational Oncology.

[44]  Svetlana V. Harbaugh,et al.  The von Hippel-Lindau Tumor Suppressor Protein and Egl-9-Type Proline Hydroxylases Regulate the Large Subunit of RNA Polymerase II in Response to Oxidative Stress , 2008, Molecular and Cellular Biology.

[45]  Guoping Fan,et al.  Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells , 2009, BMC Genomics.

[46]  M. Babjuk,et al.  Regulatory T cells, dendritic cells and neutrophils in patients with renal cell carcinoma. , 2013, Immunology Letters.

[47]  Terukazu Nakamura,et al.  CDK1 and CDK2 activity is a strong predictor of renal cell carcinoma recurrence. , 2014, Urologic oncology.

[48]  J. Patard,et al.  Metabolism of kidney cancer: from the lab to clinical practice. , 2013, European urology.

[49]  Sajjad Karim,et al.  Molecular Interaction of a Kinase Inhibitor Midostaurin with Anticancer Drug Targets, S100A8 and EGFR: Transcriptional Profiling and Molecular Docking Study for Kidney Cancer Therapeutics , 2015, PloS one.

[50]  J. Ward,et al.  Role of Myc in hepatocellular proliferation and hepatocarcinogenesis. , 2014, Journal of hepatology.

[51]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[52]  Yuxin Yin,et al.  PTEN stabilizes TOP2A and regulates the DNA decatenation , 2015, Scientific Reports.

[53]  L. O’Driscoll,et al.  Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis. , 2013, Carcinogenesis.

[54]  R. Zare,et al.  MYC oncogene overexpression drives renal cell carcinoma in a mouse model through glutamine metabolism , 2015, Proceedings of the National Academy of Sciences.

[55]  Peter Bühlmann,et al.  Mining Tissue Microarray Data to Uncover Combinations of Biomarker Expression Patterns that Improve Intermediate Staging and Grading of Clear Cell Renal Cell Cancer , 2009, Clinical Cancer Research.

[56]  A. Bishop,et al.  Embryonic stem cells , 2004, Cell proliferation.

[57]  C. Chai,et al.  Cyclooxygenase-2 (COX-2) up-regulation is a prognostic marker for poor clinical outcome of upper tract urothelial cancer. , 2012, Anticancer research.

[58]  Fan Yang,et al.  Reciprocal regulation of HIF-1α and lincRNA-p21 modulates the Warburg effect. , 2014, Molecular cell.

[59]  Tomoyoshi Soga,et al.  Oncometabolites: linking altered metabolism with cancer. , 2013, The Journal of clinical investigation.