Evidence map›Paper›PMID 42156138›Full record

ArticleJournal for immunotherapy of cancer2026

Pan-cancer analysis in the real-world setting uncovers immunogenomic drivers of acquired resistance post-immunotherapy.

Mohamed Reda Keddar, Sebastian Carrasco Pro, Roy Rabbie, Zeynep Kalender Atak, Francesc Muyas, Ana Camelo Stewart, Scott A Hammond, Doug C Palmer, Ross Stewart, Maureen Carey and 8 more

Abstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 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. Article
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

18 authors.

Mohamed Reda KeddarOncology Data Science and AI, Oncology R&D, AstraZeneca Cambridge Biomedical Campus, Cambridge, UK mohamedreda.keddar@astrazeneca.com.ORCID http://orcid.org/0009-0001-7711-8213
Sebastian Carrasco ProBoehringer Ingelheim USA, Ridgefield, Connecticut, USA.
Roy RabbieLate Development Oncology, AstraZeneca R&D Cambridge, Cambridge, UK.
Zeynep Kalender AtakQuotient Therapeutics, Cambridge, UK.
Francesc MuyasOncology Data Science and AI, Oncology R&D, AstraZeneca, Barcelona, Spain.
Ana Camelo StewartOncology Data Science and AI, Oncology R&D, AstraZeneca Cambridge Biomedical Campus, Cambridge, UK.
Scott A HammondOncology Research and Development, AstraZeneca, Gaithersburg, Maryland, USA.
Doug C PalmerOncology Research and Development, AstraZeneca, Gaithersburg, Maryland, USA.
Ross StewartAstraZeneca, Cambridge, Cambridgeshire, UK.
Maureen CareyTempus, Chicago, Illinois, USA.
Kathleen BurkeTempus, Chicago, Illinois, USA.
Ben SiddersBiorelate, Manchester, UK.
Jessica DaviesOncology Data Science and AI, Oncology R&D, AstraZeneca, Barcelona, Spain.
Jonathan R DryTempus, Chicago, Illinois, USA.ORCID http://orcid.org/0000-0002-1640-2616
Inigo MartincorenaWellcome Sanger Institute, Hinxton, UK.
Sajan KhoslaOncology Data Science and AI, Oncology R&D, AstraZeneca Cambridge Biomedical Campus, Cambridge, UK.
Adam SchoenfeldMemorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID http://orcid.org/0000-0002-2644-1416
Martin L MillerGSK R&D Stevenage, Stevenage, UK.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundImmune checkpoint blockade (ICB) has revolutionized cancer therapy, yet resistance-both primary and acquired-remains a significant obstacle, affecting the majority of patients.

methodsHere, we leverage a large-scale, real-world clinicogenomic dataset to systematically explore the molecular underpinnings of ICB resistance in the post-progression setting. We analyze over 5,000 pan-cancer patients with clinical and pre-/post-treatment genomic and transcriptomic data and systematically compare the clinical and molecular features of acquired versus primary ICB resistance.

resultsPost-ICB progression, acquired resistance showed extended survival compared to primary resistance across all cancer types. This clinical phenotype was paralleled by a universally immune-inflamed, albeit dysfunctional, tumor microenvironment (TME) at the onset of acquired resistance, with sustained or ICB-induced inflammatory and interferon responses. We confirm previously described mechanisms of acquired resistance, including

conclusionsThese findings emphasize the heterogeneity of molecular drivers of acquired resistance to ICB within and across cancers, and highlight the potential for personalized therapeutic interventions post-progression to improve patient outcomes.

Indexed as

Drug Resistance, NeoplasmImmune Checkpoint InhibitorsImmunotherapyNeoplasmsFemaleGenomicsHumansTumor MicroenvironmentImmune Checkpoint InhibitorsBiomarkerBreast CancerHead and Neck CancerImmune Checkpoint InhibitorLung Cancer

Identifiers

PMID42156138
PMCPMC13202055

What OpenQuestion holds

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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 OpenQuestion graph.