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Immune checkpoint inhibitors (ICIs) have significantly transformed the treatment paradigm for metastatic renal cell carcinoma (RCC), offering prolonged overall survival and achieving remarkable deep and durable responses.

However, given the multiple ICI-containing, standard-of-care regimens approved for RCC, identifying biomarkers that predict therapeutic response and resistance is of critical importance. Although tumor-intrinsic features such as pathological characteristics, genomic alterations, and transcriptional signatures have been extensively investigated, they have yet to provide definitive, robust predictive biomarkers.

Current research is exploring host factors through in-depth characterization of the immune system. Additionally, innovative technological approaches are being developed to overcome challenges presented by existing techniques, such as tumor heterogeneity.

Promising avenues in biomarker discovery include the study of the microbiome, radiomics, and spatial transcriptomics.

In both clear and non-clear cell RCC, the search for clinically relevant biomarkers is still ongoing. The future of biomarkers will hold the combination of different multi-omic techniques, incorporating both tumor- and host-related factors. Faced with an increasing amount of data, deep learning models could facilitate the extraction of relevant features that allow for better prediction of clinical outcomes.

Read an interview about the review here and expert commentary about it here.