Mutation status coupled with RNA-sequencing data can efficiently identify important non-significantly mutated genes serving as diagnostic biomarkers of endometrial cancer

BackgroundEndometrial cancers (ECs) are one of the most common types of malignant tumor in females. Substantial efforts had been made to identify significantly mutated genes (SMGs) in ECs and use them as biomarkers for the classification of histological subtypes and the prediction of clinical outcomes. However, the impact of non-significantly mutated genes (non-SMGs), which may also play important roles in the prognosis of EC patients, has not been extensively studied. Therefore, it is essential for the discovery of biomarkers in ECs to further investigate the non-SMGs that were highly associated with clinical outcomes.ResultsFor the 9681 non-SMGs reported by the mutation annotation pipeline, there were 1053, 1273 and 395 non-SMGs differentially expressed between the patient groups divided by the clinical endpoints of histological grade, histological type as well as the International Federation of Gynecology and Obstetrics (FIGO) stage of ECs, respectively. In the gene set enrichment analysis, the cancer-related pathways, namely neuroactive ligand-receptor interaction signaling pathway, cAMP signaling pathway and calcium signaling pathway, were significantly enriched with the differentially expressed non-SMGs for all the three endpoints. We further identified 23, 19 and 24 non-SMGs, which were highly associated with histological grade, histological type and FIGO stage, respectively, from the differentially expressed non-SMGs by using the variable combination population analysis (VCPA) approach and found that 69.6% (16/23), 78.9% (15/19) and 66.7% (16/24) of the identified non-SMGs had been previously reported to be correlated with cancers. In addition, the averaged areas under the receiver operating characteristic curve (AUCs) achieved by the predictive models with identified non-SMGs as predictors in predicting histological type, histological grade, and FIGO stage were 0.993, 0.961 and 0.832, respectively, which were superior to those achieved by the models with SMGs as features (averaged AUCs = 0.928, 0.864 and 0.535, resp.).ConclusionsBesides the SMGs, the non-SMGs reported in the mutation annotation analysis may also involve the crucial genes that were highly associated with clinical outcomes. Combining the mutation status with the gene expression profiles can efficiently identify the cancer-related non-SMGs as predictors for cancer prognostic prediction and provide more supplemental candidates for the discovery of biomarkers.

[1]  J. Trovik,et al.  Markers for individualised therapy in endometrial carcinoma. , 2012, The Lancet. Oncology.

[2]  Serena Pillozzi,et al.  hLH/hCG-receptor expression correlates with in vitro invasiveness in human primary endometrial cancer. , 2008, Gynecologic oncology.

[3]  P. Bork,et al.  A method and server for predicting damaging missense mutations , 2010, Nature Methods.

[4]  P. Goodfellow,et al.  Estrogen receptor-alpha as a predictive biomarker in endometrioid endometrial cancer. , 2016, Gynecologic oncology.

[5]  Mingming Jia,et al.  COSMIC: exploring the world's knowledge of somatic mutations in human cancer , 2014, Nucleic Acids Res..

[6]  Wei Guo,et al.  TFAP2B overexpression contributes to tumor growth and a poor prognosis of human lung adenocarcinoma through modulation of ERK and VEGF/PEDF signaling , 2014, Molecular Cancer.

[7]  David Botstein,et al.  RERG Is a Novel ras-related, Estrogen-regulated and Growth-inhibitory Gene in Breast Cancer* , 2001, The Journal of Biological Chemistry.

[8]  Pekka Kohonen,et al.  Enhanced serine production by bone metastatic breast cancer cells stimulates osteoclastogenesis , 2010, Breast Cancer Research and Treatment.

[9]  B. Weigelt,et al.  Classification of endometrial carcinoma: more than two types. , 2014, The Lancet. Oncology.

[10]  S. Gabriel,et al.  Discovery and saturation analysis of cancer genes across 21 tumor types , 2014, Nature.

[11]  Chen,et al.  Genome-wide analysis associates familial colorectal cancer with increases in copy number variations and a rare structural variation at 12 p 12 . 3 , 2014 .

[12]  Yu-Chan Chang,et al.  Phosphoserine Aminotransgerase I Is A predictor of Early Recurrence and Poor Prognosis of Resected Stage I Non-small Cell Lung Cancer That Induces Metastasis via MMP1 Activation , 2013 .

[13]  P. Campbell,et al.  Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes , 2015, Nature Communications.

[14]  Matthew A Powell,et al.  Inhibition of activated fibroblast growth factor receptor 2 in endometrial cancer cells induces cell death despite PTEN abrogation. , 2008, Cancer research.

[15]  C. Bandera,et al.  The molecular genetics of endometrial carcinoma. , 1997, Progress in clinical and biological research.

[16]  Tomoko Umaki,et al.  Possible Prediction of Chemoradiosensitivity of Esophageal Cancer by Serum Protein Profiling , 2005, Clinical Cancer Research.

[17]  Patrick Neven,et al.  Endometrial cancer. , 2005, Lancet.

[18]  B. Clarke,et al.  Endometrial carcinoma: controversies in histopathological assessment of grade and tumour cell type , 2010, Journal of Clinical Pathology.

[19]  J. Listgarten,et al.  Predictive Models for Breast Cancer Susceptibility from Multiple Single Nucleotide Polymorphisms , 2004, Clinical Cancer Research.

[20]  Steven J. M. Jones,et al.  Integrated genomic characterization of endometrial carcinoma , 2013, Nature.

[21]  Steven A. Roberts,et al.  Mutational heterogeneity in cancer and the search for new cancer-associated genes , 2013 .

[22]  Li Ding,et al.  Clinical significance of CTNNB1 mutation and Wnt pathway activation in endometrioid endometrial carcinoma. , 2014, Journal of the National Cancer Institute.

[23]  S. Henikoff,et al.  Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm , 2009, Nature Protocols.

[24]  Brad T. Sherman,et al.  Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists , 2008, Nucleic acids research.

[25]  T. Cupples,et al.  Ubiquinol cytochrome c reductase (UQCRFS1) gene amplification in primary breast cancer core biopsy samples. , 2004, Gynecologic oncology.

[26]  Rui Li,et al.  Comprehensive analysis of 19q12 amplicon in human gastric cancers , 2006, Modern Pathology.

[27]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[28]  Jun Ma,et al.  Overexpression of Phosphoserine Aminotransferase 1 (PSAT1) Predicts Poor Prognosis and Associates with Tumor Progression in Human Esophageal Squamous Cell Carcinoma , 2016, Cellular Physiology and Biochemistry.

[29]  Tsz-Kwong Man,et al.  Expression profiles of osteosarcoma that can predict response to chemotherapy. , 2005, Cancer research.

[30]  Kristian Cibulskis,et al.  Drug-sensitive FGFR2 mutations in endometrial carcinoma , 2008, Proceedings of the National Academy of Sciences.

[31]  R. Kurman,et al.  The utility of the revised International Federation of Gynecology and Obstetrics histologic grading of endometrial adenocarcinoma using a defined nuclear grading system. A gynecologic oncology group study , 1995, Cancer.

[32]  Yusuke Nakamura,et al.  Genetic variations in the gene encoding TFAP2B are associated with type 2 diabetes mellitus , 2005, Journal of Human Genetics.

[33]  T Chard,et al.  Regulation of endometrial cancer cell growth by luteinizing hormone (LH) and follicle stimulating hormone (FSH) , 2000, British Journal of Cancer.

[34]  A. Jemal,et al.  Cancer statistics, 2016 , 2016, CA: a cancer journal for clinicians.

[35]  N. Turner,et al.  Fibroblast growth factor signalling: from development to cancer , 2010, Nature Reviews Cancer.

[36]  Christopher R. Cabanski,et al.  Integrated RNA and DNA sequencing improves mutation detection in low purity tumors , 2014, Nucleic acids research.

[37]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[38]  P. A. Futreal,et al.  Emerging patterns of somatic mutations in cancer , 2013, Nature Reviews Genetics.

[39]  Michael Krawczak,et al.  Genome-wide analysis associates familial colorectal cancer with increases in copy number variations and a rare structural variation at 12p12.3. , 2014, Carcinogenesis.

[40]  R. Slebos,et al.  The frequency of p53, k‐ras mutations, and microsatellite instability differs in uterine endometrioid and serous carcinoma , 2000, Cancer.

[41]  Anders Larsson,et al.  Adipocytokines levels at delivery, functional variation of TFAP2β, and maternal and neonatal anthropometric parameters , 2013, Obesity.

[42]  R Eils,et al.  Comparison of performance of one-color and two-color gene-expression analyses in predicting clinical endpoints of neuroblastoma patients , 2010, The Pharmacogenomics Journal.

[43]  Sung-Liang Yu,et al.  NDST4 Is a Novel Candidate Tumor Suppressor Gene at Chromosome 4q26 and Its Genetic Loss Predicts Adverse Prognosis in Colorectal Cancer , 2013, PloS one.

[44]  Jaime Prat,et al.  Prognostic parameters of endometrial carcinoma. , 2004, Human pathology.

[45]  Yusuke Nakamura,et al.  Proteomic characterization of ovarian cancers identifying annexin‐A4, phosphoserine aminotransferase, cellular retinoic acid‐binding protein 2, and serpin B5 as histology‐specific biomarkers , 2012, Cancer science.

[46]  Menglong Li,et al.  Identifying oncogenes as features for clinical cancer prognosis by Bayesian nonparametric variable selection algorithm , 2015 .

[47]  Rebecca L. Siegel Mph,et al.  Cancer statistics, 2016 , 2016 .

[48]  J. Lin,et al.  Increased expression of luteinizing hormone/human chorionic gonadotropin receptor gene in human endometrial carcinomas. , 1994, The Journal of clinical endocrinology and metabolism.

[49]  Mef Nilbert,et al.  Distinct sets of gene alterations in endometrial carcinoma implicate alternate modes of tumorigenesis , 2002, Cancer.

[50]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[51]  R. Lothe,et al.  The recently suggested intestinal cancer stem cell marker DCLK1 is an epigenetic biomarker for colorectal cancer , 2014, Epigenetics.

[52]  H. Grabsch,et al.  Overexpression of the mitotic checkpoint genes BUB1, BUBR1, and BUB3 in gastric cancer—association with tumour cell proliferation , 2003, The Journal of pathology.

[53]  Olivier Gevaert,et al.  Development of prognostic signatures for intermediate-risk papillary thyroid cancer , 2016, BMC Cancer.

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

[55]  Chiara Benedetto,et al.  Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis , 2015, PloS one.

[56]  K. Lloyd,et al.  CA125 and UQCRFS1 FISH studies of ovarian carcinoma. , 2003, Gynecologic oncology.

[57]  Hiroki Kuniyasu,et al.  Expression of Bub1 Gene Correlates with Tumor Proliferating Activity in Human Gastric Carcinomas , 2001, Pathobiology.

[58]  Thomas Zeng,et al.  Use of mutation profiles to refine the classification of endometrial carcinomas , 2012, The Journal of pathology.

[59]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[60]  Peilin Jia,et al.  VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data , 2014, PLoS Comput. Biol..

[61]  I. Jonassen,et al.  Integrated genomic profiling of endometrial carcinoma associates aggressive tumors with indicators of PI3 kinase activation , 2009, Proceedings of the National Academy of Sciences.

[62]  Qing-Song Xu,et al.  Using variable combination population analysis for variable selection in multivariate calibration. , 2015, Analytica chimica acta.

[63]  C. Mathers,et al.  Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012 , 2015, International journal of cancer.

[64]  I. Yeh,et al.  Molecular Profiling of Endometrial Malignancies , 2010, Obstetrics and gynecology international.

[65]  Ryan D. Morin,et al.  Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution , 2009, Nature.

[66]  Xiaojun Zhao,et al.  Combination analysis of Bub1 and Mad2 expression in endometrial cancer: act as a prognostic factor in endometrial cancer , 2013, Archives of Gynecology and Obstetrics.