Spatial transcriptomics tumor microenvironment determinants of tyrosine kinase inhibitor response in renal cell carcinoma: results from a phase 2 clinical trial

Metastatic clear cell renal cell carcinoma (ccRCC) exhibits heterogeneous clinical outcomes, and limited biomarkers are available to predict response to targeted therapies. This study evaluated cell compartment-specific transcriptional biomarkers predicting clinical response to the tyrosine kinase inhibitor (TKI) sunitinib. In this phase 2 clinical trial (NCT00715442), 46 patients with metastatic ccRCC received sunitinib pre- and post-cytoreductive nephrectomy, with a primary endpoint of time-to-progression (TTP) and secondary endpoints of overall survival (OS) and sunitinib toxicity. To investigate spatial dynamics of therapeutic response to sunitinib, we applied whole-transcriptome digital spatial profiling (DSP) to tumor tissue from responders and non-responders. For 46 trial patients, median TTP was 8.2 months (95% CI: 6.1–19.3) and OS 36.3 months (95% CI: 19.7–70.5). Responders displayed a tumor microenvironment enriched in pro-inflammatory/immunostimulatory programs, while non-responders displayed enrichment of immunosuppressive programs with elevated PD-L1 expression in myeloid cells and exhausted CD8 + T-cell signatures. Sunitinib resistance mechanisms involving VEGF-dependent and independent angiogenic pathways were identified, revealing potential therapeutic targets. DSP-based machine learning models showed strong prognostic and predictive performance in sunitinib-treated patients in an external JAVELIN Renal 101 cohort, but attenuated performance in the avelumab plus axitinib cohort, indicating treatment-context specificity. Our findings highlight immune regulation as a key determinant of sunitinib response in metastatic ccRCC. Spatial profiling revealed potentially targetable mechanisms of TKI resistance involving SPP1-associated myeloid programs, CD8 + T-cell exhaustion, and angiogenic signaling, highlighting interactions between angiogenesis, lipid metabolism, and tumor immunity as determinants of therapeutic outcome.