122P - Comprehensive multi-omics profiling identifies prognostic and predictive subtypes in renal cell carcinoma

Background

Renal Cell Carcinoma (RCC) subtypes are identified based on their histological features, which are crucial for determining prognosis and treatment options. Nevertheless, the histological classification of RCC often faces challenges in predicting treatment responses and outcomes because of its heterogeneity. To address this issue, multi-omics approaches have revealed a new molecular subtype by analyzing the genome and expression profiles of various tumor types. In this study, we performed an extensive profiling of RCC.

Methods

A total of 113 paired tumor and adjacent non-tumor tissues, as well as PBMC samples, were collected from Korean RCC patients. This study was approved by the Institutional Review Board of the Severance Hospital, Yonsei University Health System (IRB No. 4-2018-0986) and Chonnam National University Hospital (IRB No. NUHH-2018-167). All patients provided consent for their samples to be used for research purposes. These samples underwent Whole Exome Sequencing (WES), RNA sequencing (WTS), Proteomics, and Phospho-proteomics analyses.

Results

The multi-omics analysis of 113 clear cell renal cell carcinoma (ccRCC) patients reveals distinct genomic, proteomic, and clinical characteristics separating RCC tumors from normal tissues. The study identifies four RCC subtypes (C1-4) with unique molecular profiles and prognostic implications. C1-3 are mostly ccRCC, while C4 includes non-clear cell RCC (nccRCC) or other cancer types. C3 shows the poorest prognosis, whereas C1 has the best. C1 also exhibits a strong adaptive immune response and angiogenesis, correlating with favorable post-surgery outcomes. C2 is enriched in DNA repair pathways with specific gene alterations, while C3 is linked to an inflammatory response and resistance to certain treatments.

Conclusions

This study employs a large-scale multi-omics approach to RCC, offering insights into its biological foundations and supporting rational treatment selection by linking multi-omics-derived phenotypes to clinical outcomes in ccRCC.

Editorial acknowledgement

Clinical trial identification

Legal entity responsible for the study

The authors.

Funding

National Cancer Center Korea.

Disclosure

S. Park: Financial Interests, Institutional, Sponsor/Funding: National Cancer Center, Korea. All other authors have declared no conflicts of interest.