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Multi-Omic Kidney Cancer Analysis Identifies Subtypes for Stratifying Patients

NEW YORK – Researchers from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) have generated multi-omic profiles for clear cell renal cell carcinoma (ccRCC), the most common form of kidney cancer, defining subtypes that might be useful to stratify patients for treatment.

In a study published in Cell on Thursday, the scientists used a combination of genomics, epigenomics, transcriptomics, proteomics, and phosphoproteomics to analyze 103 treatment-naïve ccRCC tumors along with 80 samples of paired normal adjacent tissues.

Their analysis identified four immune-based ccRCC subtypes as well as a molecular subtype characterized by genomic instability. It also linked genomic alterations to protein-level changes impacting cellular functions, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling.

Using mass spectrometry, the CPTAC team identified a total of 11,355 proteins and 42,889 phosphopeptides, with 7,150 proteins and 20,976 phosphopeptides quantified across all samples. They combined this data with whole-genome sequencing, exome sequencing, total RNA sequencing, and DNA methylation profiling.

The researchers derived a number of insights into the disease from an analysis of this data, foremost among them the identification of several immune-based subtypes that could be useful in guiding patient therapy. Looking at the cellular composition of the tumor microenvironment as well as cellular signaling and pathway activation, they were able to distinguish between patients with a pro-angiogenic subtype and those with what they termed an "immune-invasive" subtype.

They also observed protein signaling patterns including "the ubiquitous activation of EGFR and downstream signaling cascades (MAPK1), as well as cell-cycle checkpoint regulation (WEE1-CDK1)," that the authors wrote suggested the potential of "additional therapeutic targets that have been evaluated extensively in other cancer types but minimally in ccRCC."

The CPTAC team also identified a subset of patients with genomic instability, a finding that they wrote "could have clinical utility that warrants further investigation, as this group may have worse prognosis and benefit from continual surveillance post-treatment."

The study also demonstrated the utility of a multi-omics analysis, finding, for instance, evidence at the protein level of ccRCC-linked metabolic shifts that were not observable at the transcript level. Specifically, they observed at the protein level "the upregulation of glycolysis and the corresponding downregulation of the Krebs cycle and the electron transport chain … associated with the Warburg effect."

The Warburg effect is the tendency of cancer cells to prefer glycolysis rather than oxidative phosphorylation for metabolism, even under conditions where oxygen is available.

Downregulation of Krebs cycle components and proteins involved in the electron transport chain was not observable at the mRNA level, the authors noted, adding that "this finding is significant, as recent large-scale ccRCC studies have focused on mRNA expression data to depict the metabolic shift in ccRCC and have evaluated transcriptomic signatures to stratify patients with more aggressive disease."

"Our multi-level 'omics' analysis identifies underlying molecular mechanisms that are not fully captured at the genomic and transcriptomic levels and defines proteomic, phosphoproteomic, and immune signatures necessary to stratify ccRCC patients, with the goal of developing rational therapeutic interventions," the authors wrote.