Evidence map›Paper›PMID 41259021›Full record

ArticleThe Journal of pathology2026

Papillary renal cell carcinoma with high-ABCC2 shows an immune-evasive profile associated with favorable response to immunotherapy.

Vincent Francis Castillo, Abraam Zakhary, Fabio Rotondo, Caterina Di Ciano-Oliveira, Malek Hamdani, Emelyn Adona, Theodorus van der Kwast, Kiril Trpkov, Rola Saleeb

Abstract read
In one paragraph

Article in The Journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Vincent Francis CastilloDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
Abraam ZakharyDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
Fabio RotondoLi Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Caterina Di Ciano-OliveiraLi Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Malek HamdaniDepartment of Laboratory Medicine, Unity Health Toronto, Toronto, ON, Canada.
Emelyn AdonaDepartment of Laboratory Medicine, Unity Health Toronto, Toronto, ON, Canada.
Theodorus van der KwastDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
Kiril TrpkovDepartment of Pathology and Laboratory Medicine, Alberta Precision Laboratories and University of Calgary, Calgary, AB, Canada.
Rola SaleebDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.

Funding

Kidney Cancer Research Network of Canada in partnership with Kidney Cancer Canada and the Canadian Urological Association Scholarship FundKidney Foundation of Canada KHRG2023-1037992Ontario Institute for Cancer Research CPTRG-057Ontario Institute for Cancer Research IA-1-024
6 · The paper itself

Abstract

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. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Indexed as

ATP-Binding Cassette, Sub-Family C ProteinsBiomarkers, TumorCarcinoma, Renal CellImmune Checkpoint InhibitorsImmunotherapyKidney NeoplasmsTumor MicroenvironmentAgedFemaleHumansLymphocytes, Tumor-InfiltratingMaleMiddle AgedMultidrug Resistance-Associated Protein 2Treatment OutcomeABCC2 protein, humanATP-Binding Cassette, Sub-Family C ProteinsBiomarkers, TumorImmune Checkpoint InhibitorsMultidrug Resistance-Associated Protein 2ABCC2immune checkpoint inhibitorimmunotherapykidney cancerpapillary renal cell carcinomapredictivetumor microenvironment

Identifiers

PMID41259021
PMCPMC12805615

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.