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Clinical Features and Multiplatform Molecular Analysis Assist in Understanding Patient Response to Anti-PD-1/PD-L1 in Renal Cell Carcinoma.

Eileen ShiuanAnupama ReddyStephanie O DudzinskiAaron R LimAyaka SugiuraRachel A HongoKirsten YoungXian-De LiuChristof C SmithJamye O'NealKimberly B DahlmanRenee McAlisterBeiru ChenKristen RumaNathan RoscoeJehovana BenderJoolz WardJu Young KimChristine VaupelJennifer BordeauxShridar GanesanTina M MayerGregory M RiedlingerBenjamin G VincentNancy B DavisScott M HaakeJeffrey C RathmellEric JonaschBrian I RiniW Kimryn RathmellKathryn E Beckermann
Published in: Cancers (2021)
Predicting response to ICI therapy among patients with renal cell carcinoma (RCC) has been uniquely challenging. We analyzed patient characteristics and clinical correlates from a retrospective single-site cohort of advanced RCC patients receiving anti-PD-1/PD-L1 monotherapy (N = 97), as well as molecular parameters in a subset of patients, including multiplexed immunofluorescence (mIF), whole exome sequencing (WES), T cell receptor (TCR) sequencing, and RNA sequencing (RNA-seq). Clinical factors such as the development of immune-related adverse events (odds ratio (OR) = 2.50, 95% confidence interval (CI) = 1.05-5.91) and immunological prognostic parameters, including a higher percentage of circulating lymphocytes (23.4% vs. 17.4%, p = 0.0015) and a lower percentage of circulating neutrophils (61.8% vs. 68.5%, p = 0.0045), correlated with response. Previously identified gene expression signatures representing pathways of angiogenesis, myeloid inflammation, T effector presence, and clear cell signatures also correlated with response. High PD-L1 expression (>10% cells) as well as low TCR diversity (≤644 clonotypes) were associated with improved progression-free survival (PFS). We corroborate previously published findings and provide preliminary evidence of T cell clonality impacting the outcome of RCC patients. To further biomarker development in RCC, future studies will benefit from integrated analysis of multiple molecular platforms and prospective validation.
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