Evidence map›Paper›PMID 42909279›Full record

ReviewFrontiers in cell and developmental biology2026

Pan-cancer biomarkers of immune therapy resistance: mechanisms and clinical translation.

Chao Wang, Dong Yang

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 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

2 authors.

Chao WangDepartment of Gastric Surgery, Liaoning Cancer Hospital & Institute, Shenyang, China.
Dong YangDepartment of Gastric Surgery, Liaoning Cancer Hospital & Institute, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint blockade targeting PD-1/PD-L1 has reshaped cancer therapy across multiple tumor types. However, primary and acquired resistance remain major barriers to durable clinical benefit. Increasing evidence indicates that immunotherapy resistance is not driven by isolated molecular alterations, but by coordinated changes involving tumor-intrinsic immune escape, immunosuppressive tumor microenvironments, systemic inflammatory remodeling, and adaptive biomarker evolution under therapeutic pressure. This review focuses on pan-cancer biomarkers of immune therapy resistance from the perspective of mechanisms and clinical translation. First, we summarize targetable biomarker classes that link resistance biology to therapeutic sensitization across cancers, including transcription factors, genomic alterations, immune checkpoint proteins and metabolic regulators. For each class, we highlight representative cancer types in which experimental or clinical evidence supports their role in immunotherapy resistance. Second, we discuss the mechanistic basis of resistance-associated biomarkers, emphasizing antigen presentation defects, impaired interferon signaling, oncogenic pathway activation, T-cell exhaustion, myeloid and stromal immunosuppression, metabolic reprogramming, and dynamic systemic immune remodeling. These mechanisms provide a biological perspective for interpreting biomarkers not only as predictors of treatment response, but also as functional indicators of resistance evolution. By integrating biomarker classification, resistance mechanisms, and therapeutic sensitization strategies, this review aims to provide a new perspective for using pan-cancer resistance biomarkers to guide rational combination immunotherapy and improve precision cancer treatment.

Indexed as

biomarkersclinical translationimmune therapy resistancemechanismspan-cancer

Identifiers

PMID42909279
PMCPMC13683937

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.