Researchers have identified novel biomarkers in renal cell carcinoma subtypes, according to a new study published by Li et al in Cell Reports Medicine. The findings may help identify therapeutic targets in non–clear cell renal cell carcinomas.
Background
Renal cell carcinoma is a diverse cancer type with more than 20 known subtypes. The disease can be largely classified as either clear cell or non–clear cell renal cell carcinoma. About 20% of all renal cell carcinoma cases are non–clear cell renal cell carcinoma and most subtypes in this category are very rare and relatively understudied.
Despite having different molecular compositions, non–clear cell renal cell carcinomas are treated with the standard of care devised for the more common type of renal cell carcinoma, thereby affecting treatment outcomes. Differential diagnosis of non–clear cell renal cell carcinoma tumors can be challenging as a result of overlapping morphologic features and a lack of specificity in current biomarkers.
“[T]he standard of care for [non–clear cell renal cell carcinoma] is evolving,” explained co–senior study author Saravana Mohan Dhanasekaran, PhD, Associate Research Scientist at the Michigan Medicine Center for Translational Pathology. “Rare cancers are often left out from major profiling efforts, so therapeutic and diagnostic advances in this space have been limited. Until now, no single center has had enough samples of the quality needed for comprehensive multiomics profiling, as we’ve carried out in this study,” he added.
Study Methods and Results
Through prior studies, the researchers used proteogenomics in clear cell renal cell carcinoma to characterize 213 patients with 305 tumors and 166 benign kidney tissues as well as nominate both biomarkers and therapeutic biomarkers for the subtype.
In the new study, the researchers conducted an integrative analysis of comprehensive proteogenomic data sets from 48 patients with non–clear cell renal cell carcinoma with 48 tumors and 22 benign kidney tissues—with the goal of improving the understanding of the mechanisms of renal cell carcinoma subtypes. They leveraged high-quality renal cell carcinoma samples available through the National Cancer Institute’s (NCI) Clinical Proteomic Tumor Analysis Consortium to generate and process multiple data types.
The researchers then compared proteogenomic, metabolomic, and posttranslational modification features in clear cell renal cell carcinoma tumors with non–clear cell renal cell carcinoma tumors—including some rare tumor subtypes. They performed integrative analyses on the multiomics data to get a comprehensive understanding of the mechanisms driving the diverse renal cell carcinoma subtypes included in the study.
“The kidney is an amazing organ. It has so many cell types, but that means it also has many cancers. We have to look at it from many angles to get a cohesive story,” Dr. Dhanasekaran noted.
The researchers revealed molecular features shared by both the clear cell and non–clear cell renal cell carcinoma tumors as well as features unique to various non–clear cell renal cell carcinoma subtypes. They also found indicators of genetic instability, which was associated with lower survival rates.
Renal cell carcinoma tumors with high genome instability overexpressed IGF2BP3 and PYCR1. The researchers hypothesized that these biomarkers could be used to validate in independent cohorts and eventually develop assays to detect genome instability and identify higher-risk patients who may benefit from personalized treatment strategies.
Further, the researchers discovered differential diagnosis biomarkers capable of distinguishing between malignant and benign tumors. They suggested that these differential biomarkers could be added to existing panels to improve diagnostic accuracy. Integrating RNA sequencing of single cells with bulk transcriptome data enabled the prediction of cell of origin for a range of tumor types and clarified proteogenomic signatures for various renal cell carcinoma subtypes.
Conclusions
The researchers hope the new findings can enhance the ability to accurately diagnose many renal cell carcinoma subtypes, including some rare subtypes. The recent studies have generated a large renal cell carcinoma proteogenomic database that may serve as a valuable public resource for future investigations.
“Our study significantly contributes to this growing effort by the rare renal cancer community by characterizing high-quality, rare tumor specimens, providing a useful public data resource,” Dr. Dhanasekaran highlighted.
“To really understand what’s happening, genomics data is not enough. We need to look at proteins. Our [study] … deeply explores the protein side of non–clear cell [renal cell carcinoma] and ties it to the genomic work previously done on renal cell carcinomas,” emphasized co–senior study author Alexey Nesvizhskii, PhD, the Godfrey Dorr Stobbe Professor of Bioinformatics in the Department of Pathology and Computational Medicine and Bioinformatics as well as Director of the Proteomics Resource Facility at the University of Michigan Health Rogel Cancer Center. “This [research] addresses unmet clinical needs for many patients, including those with rare subtypes that are often misclassified, delaying proper care. Identifying these potential biomarkers is helping advance patient care,” he concluded.
Disclosure: The research in this study was supported by the NCI’s Clinical Proteomic Tumor Analysis Consortium and in part by the Intramural Research Program of the National Institutes of Health. For full disclosures of the study authors, visit cell.com.
