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This study investigated whether the diversity and composition of T-cell receptor (TCR) repertoires in tumors could predict which advanced renal cell carcinoma patients would respond to immune checkpoint inhibitor therapy. Researchers found that responders had more evenly distributed TCRβ repertoires and greater TCRγ diversity, while non-responders showed dominance of specific clones. A predictive model combining TCRβ and TCRγ features achieved 90% accuracy in identifying responders, with certain TRBV genes associated with better clinical outcomes and longer progression-free survival.
Why it matters
Currently, there are no reliable biomarkers to predict which renal cell carcinoma patients will benefit from immune checkpoint inhibitors, leading to unnecessary treatment exposure and costs for non-responders. If validated in larger prospective studies, TCR repertoire profiling of baseline tumor samples could enable personalized treatment selection and improve patient outcomes by identifying those most likely to respond to immunotherapy.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape of advanced renal cell carcinoma (RCC), yet only a subset of patients derives durable clinical benefit and no robust predictive biomarkers have been implemented in routine clinical practice. As T-cell receptor (TCR)-mediated antigen recognition underlies effective antitumor immunity, characterization of the intratumoral TCR repertoire may provide clinically relevant information for patient stratification. Here, we evaluated the predictive value of the baseline intratumoral TCR{beta} and TCR{gamma} repertoires in a real-world cohort of patients with advanced RCC treated predominantly with first-line immune checkpoint inhibitor-based regimens. Responders exhibited a significantly more even TCR{beta} repertoire together with increased TCR{gamma} diversity and clonal richness, whereas non-responders showed greater TCR{gamma} clonal dominance. In addition, the preferential usage of specific TRBV genes, including TRBV5.7, TRBV7.1, and TRBV18, was associated with clinical response and longer progression-free survival. In this exploratory cohort, integration of the most informative TCR{beta} and TCR{gamma} variables into a combined random forest model yielded an area under the receiver operating characteristic curve of 0.90 in leave-one-out cross-validation, with 100% sensitivity and 81.8% specificity at the selected threshold. To our knowledge, this is the first study to simultaneously characterize baseline intratumoral TCR{beta} and TCR{gamma} repertoires in patients with advanced RCC predominantly receiving first-line immune checkpoint blockade. These findings support baseline intratumoral TCR repertoire features as candidate tissue biomarkers for pretreatment patient stratification and provide a rationale for the prospective validation of TCR repertoire profiling as a predictor of immunotherapy benefit in RCC.