Identifying potential genetic and microRNA biomarkers for renal cell carcinoma risk and prognosis

Xiang Shu, The University of Texas School of Public Health

Abstract

Kidney cancer remains one of top 10 most common cancer diagnosed in the U.S. Over 80% of kidney cancers are renal cell carcinoma (RCC). Extra genetic susceptibility loci of RCC remain to be explored with the fact that a relatively high heritability was found for the disease. Furthermore, there is urgency to identify reliable genetic and molecular predictors for RCC recurrence and overall survival which are still limited. This dissertation aims to search for potential genetic and miRNA biomarkers for both RCC risk and prognosis. ^ In the first project, we genotyped 2,159 single nucleotide polymorphisms (SNPs) located in the 127 significantly mutated genes that were identified by The Cancer Genome Atlas (TCGA) Pan-Cancer Analysis in 788 newly diagnosed RCC cases and 797 healthy controls. RCC cases were recruited at MD Anderson Cancer Center, and healthy controls without a history of cancer (except nonmelanoma skin cancer) were recruited using random digit dialing (RDD) method. Nominal significant associations with RCC risk were then tested in a subset of existing RCC genome-wide association study (GWAS) at MD Anderson (557 cases vs 1095 controls) and in an external publicly available RCC GWAS data set downloaded from dbGaP (1,311 cases vs 3,424 controls). Three potential susceptibility loci were identified by conducting multivariable logistic regression and meta-analysis with rs6466135 being most significant (effect allele: A, OR meta=0.85, 95% CI=0.77-0.94, P meta=0.001). The associations with RCC recurrence and overall survival (OS) were identified and validated in two datasets by conducting multivariable Cox regression. A novel locus at chromosome 2q34 (represented by rs10932384) was significantly associated with both recurrence and OS among localized RCC patients (recurrence: HR meta=0.52, 95% CI=0.39-0.68, P meta=3.81x10 -6; OS: HR meta=0.50, 95% CI=0.37-0.67, P meta=6x10-6). Furthermore, C allele of rs10932384 was significantly correlated with mutation frequency of ERBB4 in the ccRCC patients (p=0.003).^ In the second project, we utilized tumor/adjacent normal tissues collected from 203 RCC patients in a multi-phase study (discovery: 64, first validation: 68, second validation: 71) and identify a robust 17-miRNA signature for RCC tumorigenesis from tumor-normal comparison. We also successfully validated that miR-139-5p and miR-204-5p were significantly associated with RCC recurrence. Higher risk score derived from these two miRNAs conferred higher risk of recurrence (P for trend=0.035 and P for trend=0.003 for discovery and validation, respectively). Interestingly, the tumorigenesis- and recurrence-associated miR-204-5p is also obesity-related. The obesity-related target genes were predicted by ToppMiR (https://toppmir.cchmc.org/) for miR-204-5p. We further validated 13 pairs of negatively correlated miRNA-genes pairs by performing Pearson’s correlation in two separate datasets. Top significant correlations were identified for ROR2, ADAM2, PTX3 and IGF2BP2 (all P meta <0.001).^ In summary, potential new susceptibility loci of RCC and new genetic predictors for RCC clinical outcomes were identified by our analysis in the first project. Chromosome 2q34 may harbor a critical germline variant (represented by rs10932384) which was associated with both RCC recurrence and overall survival. Furthermore, a robust 17-miRNA signature was generated for RCC tumorigenesis and miR-139-5p and miR-204-5p were found to be jointly predicting RCC recurrence. Our analysis in the second project may provide new insight of biological mechanisms involved in the interplays of obesity, RCC development and recurrence.^

Subject Area

Public health|Epidemiology

Recommended Citation

Shu, Xiang, "Identifying potential genetic and microRNA biomarkers for renal cell carcinoma risk and prognosis" (2016). Texas Medical Center Dissertations (via ProQuest). AAI10182178.
http://digitalcommons.library.tmc.edu/dissertations/AAI10182178

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