Integrated genomic analysis identifies clinically relevant subtypes of renal clear cell carcinoma

BackgroundRenal cell carcinoma (RCC) account for over 80% of renal malignancies. The most common type of RCC can be classified into three subtypes including clear cell, papillary and chromophobe. ccRCC (the Clear Cell Renal Cell Carcinoma) is the most frequent form and shows variations in genetics and behavior. To improve accuracy and personalized care and increase the cure rate of cancer, molecular typing for individuals is necessary.MethodsWe adopted the genome, transcriptome and methylation HMK450 data of ccRCC in The Cancer Genome Atlas Network in this research. Consensus Clustering algorithm was used to cluster the expression data and three subtypes were found. To further validate our results, we analyzed an independent data set and arrived at a consistent conclusion. Next, we characterized the subtype by unifying genomic and clinical dimensions of ccRCC molecular stratification. We also implemented GSEA between the malignant subtype and the other subtypes to explore latent pathway varieties and WGCNA to discover intratumoral gene interaction network. Moreover, the epigenetic state changes between subgroups on methylation data are discovered and Kaplan-Meier survival analysis was performed to delve the relation between specific genes and prognosis.ResultsWe found a subtype of poor prognosis in clear cell renal cell carcinoma, which is abnormally upregulated in focal adhesions and cytoskeleton related pathways, and the expression of core genes in the pathways are negatively correlated with patient outcomes.ConclusionsOur work of classification schema could provide an applicable framework of molecular typing to ccRCC patients which has implications to influence treatment decisions, judge biological mechanisms involved in ccRCC tumor progression, and potential future drug discovery.

[1]  Matthew D. Wilkerson,et al.  ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking , 2010, Bioinform..

[2]  Catherine A. Shang,et al.  Whole-genome landscapes of major melanoma subtypes , 2017, Nature.

[3]  H. Ling,et al.  Diallyl disulfide suppresses epithelial-mesenchymal transition, invasion and proliferation by downregulation of LIMK1 in gastric cancer , 2016, Oncotarget.

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

[5]  R. Kirken,et al.  Inhibition of JAK3 with a novel, selective, and orally active small molecule induces therapeutic response in T-cell malignancies , 2013, Leukemia.

[6]  H. Brauch,et al.  Loss of alleles of loci on the short arm of chromosome 3 in renal cell carcinoma , 1988, Nature.

[7]  Katherine A. Hoadley,et al.  Intrinsic subtypes of high-grade bladder cancer reflect the hallmarks of breast cancer biology , 2014, Proceedings of the National Academy of Sciences.

[8]  Jun Kawai,et al.  Alternate transcription of the Toll-like receptor signaling cascade , 2006, Genome Biology.

[9]  T. Rana,et al.  miR-1298 Inhibits Mutant KRAS-Driven Tumor Growth by Repressing FAK and LAMB3. , 2016, Cancer research.

[10]  Tao Zhang,et al.  Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma , 2016, Oncotarget.

[11]  Xiaolong Yang,et al.  LATS1 tumour suppressor affects cytokinesis by inhibiting LIMK1 , 2004, Nature Cell Biology.

[12]  Quyen N. Do,et al.  Modeling Renal Cell Carcinoma in Mice: Bap1 and Pbrm1 Inactivation Drive Tumor Grade. , 2017, Cancer discovery.

[13]  David T. W. Jones,et al.  Hotspot mutations in H3F3A and IDH1 define distinct epigenetic and biological subgroups of glioblastoma. , 2012, Cancer cell.

[14]  R. Braziel,et al.  Functional RNAi screen targeting cytokine and growth factor receptors reveals oncorequisite role for interleukin-2 gamma receptor in JAK3 mutation-positive leukemia , 2014, Oncogene.

[15]  The Cancer Genome Atlas Research Network.  COMPREHENSIVE MOLECULAR CHARACTERIZATION OF CLEAR CELL RENAL CELL CARCINOMA , 2013, Nature.

[16]  Konstantinos J. Mavrakis,et al.  Disordered methionine metabolism in MTAP/CDKN2A-deleted cancers leads to dependence on PRMT5 , 2016, Science.

[17]  Robert J. Lonigro,et al.  Integrative Clinical Genomics of Metastatic Cancer , 2017, Nature.

[18]  Rameen Beroukhim,et al.  Genetic and functional studies implicate HIF1α as a 14q kidney cancer suppressor gene. , 2011, Cancer discovery.

[19]  Hui Zhou,et al.  MicroRNA-138 inhibits migration and invasion of non-small cell lung cancer cells by targeting LIMK1. , 2016, Molecular medicine reports.

[20]  P. Stephens,et al.  Characterization of Clinical Cases of Advanced Papillary Renal Cell Carcinoma via Comprehensive Genomic Profiling. , 2018, European urology.

[21]  Stefano Monti,et al.  Gene expression profiling reveals reproducible human lung adenocarcinoma subtypes in multiple independent patient cohorts. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[22]  Richard A. Scolyer.  Whole genome landscapes of major melanoma subtypes , 2018 .

[23]  Chronic Disease Division.  Cancer facts and figures , 2010 .

[24]  Claudia Berrondo,et al.  Expression of the Long Non-Coding RNA HOTAIR Correlates with Disease Progression in Bladder Cancer and Is Contained in Bladder Cancer Patient Urinary Exosomes , 2016, PloS one.

[25]  S. Gabriel,et al.  Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. , 2010, Cancer cell.

[26]  J. Renauld,et al.  Cooperating JAK1 and JAK3 mutants increase resistance to JAK inhibitors. , 2014, Blood.

[27]  C. Tanyel,et al.  The role of components of the extracellular matrix and inflammation on oral squamous cell carcinoma metastasis. , 2014, Archives of oral biology.

[28]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of clear cell renal cell carcinoma , 2013, Nature.

[29]  E. Maher,et al.  VHL, the story of a tumour suppressor gene , 2014, Nature Reviews Cancer.

[30]  Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma , 2017, Scientific Reports.

[31]  M. VanBrocklin,et al.  Activated MEK cooperates with Cdkn2a and Pten loss to promote the development and maintenance of melanoma , 2017, Oncogene.

[32]  E. H. Mitchell,et al.  WNT5A Inhibits Metastasis and Alters Splicing of Cd44 in Breast Cancer Cells , 2013, PloS one.

[33]  N. Grishin,et al.  BAP1 loss defines a new class of renal cell carcinoma , 2012, Nature Genetics.

[34]  Xiaohui Liu,et al.  Consensus clustering and functional interpretation of gene-expression data , 2004, Genome Biology.

[35]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[36]  O. Bernard,et al.  A role for LIM kinase in cancer invasion , 2003, Proceedings of the National Academy of Sciences of the United States of America.