Transcriptomics in RCC

Abstract Improvements in chemistry, molecular biology, genetics, and bioinformatics have allowed broad use of transcriptomic profiling. Understanding the population of ribonucleic acid (RNA) transcripts can provide important clinical information relevant to kidney cancer care. This includes a better understanding of kidney cancer subtype and distinct clusters within these categories. RNA-sequencing (RNA-seq) is typically done on a region within the tumor, which represents thousands to millions of heterogeneous cells and various components of the microenvironment. Computational tools can deconvolute these populations to provide insight into the microenvironment. Specific signatures of hypoxia, proliferation, angiogenesis and immune infiltration can predict response and survival. Prognostic signatures can risk stratify tumors to aid in identification of patients who might derive benefit from adjuvant therapy. As the cost of sequencing continues to decline and improved bioinformatic tools are developed, the barriers to clinical use of transcriptomic data continue to crumble. Here we review the current literature around the use of transcriptomics in kidney cancer diagnosis and management.