Identification of novel diagnostic and prognostic biomarker panels for cancer through big-data analysis

Kevin Sheng, Virginia, USA 16-18

Through the integrated use of genome-wide RNA sequencing data retrieved from The Cancer Genome Atlas (TCGA) and RNA interference data retrieved from Project Achilles by Broad Institute, diagnostic and prognostic biomarker panels with higher sensitivity and specificity than current clinically used markers were identified in lung adenocarcinoma, glioblastoma, and clear cell renal carcinoma. These panels were found to outperform current diagnostic and prognostic markers and characterize patient responses to specific treatments via bioinformatical analyses, presenting potential for integration into standard clinical practice. Based upon these results, further adaptation of this novel method across all cancers may lead to the discovery of significantly better biomarkers.

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