Cohort study demonstrates an immune-evasive microenvironment in high-ABCC2 papillary renal cell carcinoma, highlighting ABCC2 as a potential predictive biomarker for immunotherapy.
The use of immune checkpoint inhibitors is a promising therapeutic strategy for metastatic papillary renal cell carcinoma (PRCC); however, predictive biomarkers remain limited. PRCCs with high ABCC2 expression represent an aggressive subset frequently associated with metastasis. The tumor microenvironment (TME) profile of these tumors remains poorly defined. This study aims to characterize the TME of PRCC in relation to its ABCC2 status. A discovery cohort of 157 ABCC2‐high PRCCs, 156 ABCC2‐low PRCCs, and 72 normal kidneys was evaluated. Using RNA sequencing data, immune cell composition, immune checkpoint markers, and immune signature scores were assessed. Validation was performed in an independent cohort (31 ABCC2‐high, 36 ABCC2‐low, and 15 normal kidneys) using RNA in situ hybridization (RNA‐ISH) and immunohistochemistry (IHC). ABCC2‐high PRCCs demonstrated increased infiltration of cytotoxic T cells ( p < 0.001), M2 macrophages ( p = 0.021), and regulatory T cells ( p < 0.001) compared to ABCC2‐low tumors. ABCC2‐high PRCCs also had higher expression of immune checkpoint biomarkers including programmed cell death ligand 1 (PD‐L1) ( p < 0.001). The validation cohort showed this similar TME profile. Additionally, ABCC2‐high PRCCs had higher PD‐L1 IHC positivity (combined positive score ≥ 1, p = 0.035; tumor proportion score ≥ 1%, p = 0.006) and immune predictive signature score ( p = 0.029). NRF2–Antioxidant Response Element signaling pathway was enriched in ABCC2‐high PRCCs as evidenced by overrepresentation in pathway analysis, higher gene signature score ( p < 0.001), and elevated transcript signals ( NFE2L2 , p < 0.001; NQO1 , p < 0.001), compared to ABCC2‐low PRCCs. In conclusion, ABCC2‐high PRCCs are immune‐infiltrated tumors with a suppressive phenotype potentially responsive to immune checkpoint inhibitors. ABCC2 IHC may serve as a predictive biomarker to help identify patients likely to benefit from such therapy.
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Castillo et al. (2025) studied this question.
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