Evidence map›Paper›PMID 40345706›Full record

ArticleJournal for immunotherapy of cancer2025

Defects in the necroptosis machinery are a cancer resistance mechanism to checkpoint inhibitor immunotherapy.

Anna Sax, Peter May, Stefan Enssle, Nardine Soliman, Tatiana Nedelko, Giada Mandracci, Fabian Stögbauer, Laura Joachim, Christof Winter, Florian Bassermann and 4 more

Abstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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  3. Review
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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

14 authors.

Anna Sax *Department of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Peter May *Department of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Stefan EnssleDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Nardine SolimanDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Tatiana NedelkoDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Giada MandracciDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Fabian StögbauerInstitute of Pathology, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Laura JoachimDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Christof WinterInstitute of Clinical Chemistry and Pathobiochemistry, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Florian BassermannDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Katja SteigerInstitute of Pathology, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Nadia El KhawankyDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Hendrik PoeckBavarian Cancer Research Center (BZKF), Munich & Regensburg, Germany.
Simon HeideggerDepartment of Medicine III, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany simon.heidegger@tum.de.ORCID http://orcid.org/0000-0001-6394-5130

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmune checkpoint inhibitors (ICIs) of programmed cell death protein-1 (PD-1) or cytotoxic T-lymphocytes-associated protein 4 (CTLA-4) reinvigorate strong polyclonal T-cell immune responses against tumor cells. For many patients, these therapies fail because the development of spontaneous immune responses is often compromised, as the tumor microenvironment (TME) lacks proinflammatory signals resulting in suboptimal activation of antigen-presenting cells (APCs). Necroptosis is a special form of programmed cell death associated with leakage of inflammatory factors that can lead to APC maturation. However, it is unclear to which extent functional necroptosis in tumor cells contributes to ICI immunotherapy.

methodsWith genetically engineered tumor cell lines that lack specific components of the necroptosis machinery (mixed lineage kinase domain-like pseudokinase (MLKL), receptor interacting protein kinase 3 (RIPK3)), we addressed the importance of necroptotic tumor cell death for the efficacy of ICI immunotherapy in murine models. Preclinical data were aligned with genome-wide transcriptional programs in patient tumor samples at diagnosis and during ICI treatment for the activity of these pathways and association with treatment outcome.

resultsMice bearing MLKL-deficient or RIPK3-deficient tumors failed to control tumor growth in response to anti-PD-1/anti-CTLA-4 immunotherapy. Mechanistically, defects in the necroptosis pathway resulted in reduced tumor antigen cross-presentation by type 1 conventional dendritic cells (DCs) in tumor-draining lymph nodes, and subsequently impaired immunotherapy-induced expansion of circulating tumor antigen-specific CD8

conclusionsDefective necroptosis signaling in tumor cells is a cancer resistance mechanism to ICI immunotherapy. Reversion of epigenetic silencing of the necroptosis pathway can render tumors susceptible to checkpoint inhibition.

Indexed as

Drug Resistance, NeoplasmImmune Checkpoint InhibitorsImmunotherapyNecroptosisNeoplasmsAnimalsCell Line, TumorHumansMiceTumor MicroenvironmentImmune Checkpoint InhibitorsImmune Checkpoint InhibitorImmunotherapyT cellTumor microenvironment - TME

Identifiers

PMID40345706
PMCPMC12067934

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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.