Immunotherapy in Renal Cell Carcinoma: Modulating the Tumor Microenvironment, Overcoming Resistance Mechanisms, and Implementing Biomarker-Guided Combination Treatments

Main Article Content

Xiaoyi Zhang
Na Xiao
Toru Yoshino
Zizhuo Yang
Jun Chen

Abstract

Renal cell carcinoma (RCC) is distinguished by a highly inflamed tumor microenvironment (TME) that offers both opportunities and challenges for immunotherapy. This review synthesizes current insights into the immunological landscape of RCC, highlighting robust cluster of differentiation 8‑positiv (CD8⁺) T-cell infiltration, unconventional antigen sources such as endogenous retroviruses and frameshift neoantigens, and the heterogeneity of immune niches revealed by single-cell and spatial profiling. We then examine the clinical impact and mechanisms of immune checkpoint inhibitors —including programmed cell death protein 1 (PD‑1), programmed death‑ligand 1 (PD‑L1), and cytotoxic T‑lymphocyte‑associated protein 4 (CTLA‑4)—tumor vaccines, cellular therapies such as chimeric antigen receptor T cell (CAR‑T) therapy and tumor‑infiltrating lymphocytes (TILs) and bispecific antibody constructs, emphasizing advances in dosing, engineering, and combination regimens. Combination strategies—including dual checkpoint blockade, integration with anti-angiogenic tyrosine kinase inhibitors, radiotherapy, metabolism-targeted agents such as adenosine and poly (ADP‑ribose) polymerase (PARP) inhibitors, and hypoxia modulators—are reviewed for their capacity to overcome resistance and remodel the microenvironment. We further explore intrinsic and acquired resistance mechanisms, the immunosuppressive roles of myeloid and stromal elements, and emerging biomarker approaches spanning genomic, transcriptomic, spatial, and circulating analytes. Finally, we discuss current limitations—such as variable clinical response, toxicities, and biomarker gaps—and outline future prospects, including personalized combination regimens, next-generation engineered cell products, and artificial intelligence (AI)-driven precision monitoring. Together, these insights chart a path toward more effective, individualized immunotherapy in RCC.
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Computer Science and Artificial Intelligence

How to Cite

Zhang, X., Xiao, N., Yoshino, T., Yang, Z., & Chen, J. (2025). Immunotherapy in Renal Cell Carcinoma: Modulating the Tumor Microenvironment, Overcoming Resistance Mechanisms, and Implementing Biomarker-Guided Combination Treatments. AI Med, 1(3). https://doi.org/10.71423/aimed.20250806

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