Evidence map›Paper›PMID 41826729›Full record

ArticleCell death and differentiation2026

DPP9 inhibition boosts antitumor immunity by disrupting BRISC-mediated PD-L1 expression in clear cell renal cell carcinoma.

Wei Zhang, Yue Wang, Tao Feng, Tingting Cai, Wenfeng Wang, Shuxuan Zhu, Yingji Chen, Hailiang Zhang, Dingwei Ye, Chenji Wang and 1 more

Abstract read
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In one paragraph

Article in Cell death and differentiation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Wei Zhang *Department of Urology, Fudan University Shanghai Cancer Center, State Key Laboratory of Genetics and Development of Complex Phenotypes, MOE Engineering Research Center of Gene Technology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Yue Wang *Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Tao Feng *Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Tingting CaiDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Wenfeng WangDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Shuxuan ZhuDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Yingji ChenShanghai Pudong Hospital, Fudan University Pudong Medical Center, State Key Laboratory of Genetics and Development of Complex Phenotypes, MOE Engineering Research Center of Gene Technology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, China.
Hailiang ZhangDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Dingwei YeDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China. dwyelie@163.com.ORCID http://orcid.org/0000-0002-6761-5195
Chenji WangShanghai Pudong Hospital, Fudan University Pudong Medical Center, State Key Laboratory of Genetics and Development of Complex Phenotypes, MOE Engineering Research Center of Gene Technology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, China. chenjiwang@fudan.edu.cn.ORCID http://orcid.org/0000-0002-5752-6439
Kun ChangDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China. changkungene@126.com.ORCID http://orcid.org/0000-0002-0126-197X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 81902614National Natural Science Foundation of China (National Science Foundation of China) 82473192, 82172741National Natural Science Foundation of China (National Science Foundation of China) 92357301, 32370726, 81972396, and 91957125Natural Science Foundation of Shanghai (Natural Science Foundation of Shanghai Municipality) 22ZR1406600
6 · The paper itself

Abstract

Programmed cell death protein 1 (PD-1) and its ligand programmed cell death ligand-1 (PD-L1) are key mediators of immune checkpoint blockade therapy in clear cell renal cell carcinoma (RCC). However, immune evasion and primary resistance often limit their efficacy, highlighting the need for improved strategies. Here, we identified dipeptidyl peptidase 9 (DPP9) as a critical regulator of PD-L1 expression in ccRCC. Pharmacological inhibition of DPP9 with 1G244 restores T cell cytotoxicity and enhances checkpoint blockade efficacy. Mechanistically, DPP9 disrupts the BRISC-SHMT2 complex, enhancing BRISC-mediated deubiquitination and stabilization of IFNAR1, which activates the JAK/STAT pathway and drives PD-L1 transcription. 1G244 reverses this process by reducing DPP9 interacting with SHMT2, promoting IFNAR1 ubiquitination and degradation, thereby reducing PD-L1 levels and restoring T cell-mediated cytotoxicity. Moreover, the combination of 1G244 and anti-CTLA-4 therapy further enhanced antitumor immunity, highlighting a potential synergistic therapeutic strategy. Collectively, our findings define a novel DPP9-BRISC-SHMT2 regulatory axis in PD-L1 transcriptional control and identify 1G244 as an alternative combinatorial strategy to enhance the efficacy of cancer immunotherapy.

Indexed as

B7-H1 AntigenCarcinoma, Renal CellDipeptidyl-Peptidases and Tripeptidyl-PeptidasesKidney NeoplasmsAnimalsCell Line, TumorHumansMiceReceptor, Interferon alpha-betaUbiquitinationB7-H1 AntigenCD274 protein, humanDipeptidyl-Peptidases and Tripeptidyl-PeptidasesDPP9 protein, humanReceptor, Interferon alpha-beta

Identifiers

PMID41826729

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.