Louis Spencer Krane
Tulane University School of Medicine
Clinical Oncology: Outcomes & Complications
Moderated Poster Session
Introduction & Objective : Kidney cancer makes up almost 4% of all new cancer cases per year, accounting for more than 14,000 deaths annually in the United States. Clear cell renal cell carcinoma (ccRCC) accounts for the vast majority of renal malignancies. Currently, there are no widely adopted biomarkers that predict patient outcomes with ccRCC. The aim of this study is to identify a miRNA signature that could be used to predict patient survival.
We pulled miRNA expression level 3 data from the Cancer Genome Atlas (TCGA) repository, an NIH funded open genomic database with 538 patients diagnosed with localized ccRCC (https://portal.gdc.cancer.gov). The expression data was correlated to each patient’s metadata containing 528 subjects. We performed regression analysis Kaplan-Meier curves and Heatmap clustering using R packages ComplexHeatmap and Survival. Statistics were performed using R v3.4.4
Results : From the downloaded TCGA data we were able to single out 4 miRNAs that significantly affected survival and created a score utilizing each miRNA’s weight. There were 101 subjects in the low score group and 427 with a high score. After the data was normalized, hsa-mir-29b-1 showed increased while hsa-let-7d, hsa-mir-181a-1, and hsa-mir-204 showed decreased expression in the lower survival group. Patients with a low score had decreased survival (P<0.0005) when compared to those with who scored high
Patients with increased mir-29b-1 expression and decreased let-7d, mir-181a-1, mir-204 have significantly worse survival then other patients with ccRCC. Patients with this miRNA signature may need to be treated more aggressively or with adjuvant therapy to improve survival. Future studies will help determine whether the miRNA identified can be targeted pharmacologically for survival.
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