Evidence map›Paper›PMID 40447313›Full record

ArticleJournal for immunotherapy of cancer2025

Super-high tumor mutational burden predicts complete remission following immunotherapy: from Peto's paradox to druggable cancer hallmark.

Ming Zheng

Erratum issuedAbstract 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. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Ming ZhengBeijing Institute of Basic Medical Sciences, Beijing, China zhengming_china@163.com.ORCID http://orcid.org/0000-0002-3651-7701

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe somatic mutation theory predicts that cancer risk should scale proportionally with lifetime cell divisions; yet large-bodied and long-lived species exhibit lower-than-expected cancer incidence-a long-standing contradiction termed Peto's paradox. Resolving this paradox and clarifying how tumor mutational burden (TMB) shapes treatment response to immune-checkpoint inhibitor (ICI) therapy remain unmet needs in precision oncology.

methodsThis study analyzed three data streams: (1) human cancer incidence data from North American registries; (2) cancer mortality records for 110,148 mammals (191 species) linked to body mass, life expectancy, and cancer risk, and (3) >30,000 tumors profiled in three independent pan-cancer cohorts and clinical outcomes in >2,700 ICI-treated patients. A digital-medicine approach using 1,000 bootstraps was employed to generate digital randomized cohorts for internal validation, with clinicogenomic covariates matched to mirror real-world clinical features.

results(1) Both cancer incidence and mutational accumulation are age-coupled in humans (

conclusionsSomatic mutational accumulation emerges as a unifying determinant of cancer risk in human and non-human species, resolving Peto's paradox and redefining TMB as a clinically actionable cancer hallmark. Quantifying TMB stratifies immunotherapy efficacy dose-dependently, with super-high TMB predicting durable tumor eradication; thus, therapeutically boosting neoantigen load in low-TMB tumors may convert ICI non-responders to responders. By proposing a universal framework-"cancer disease continuum"-unified by mutational burden as a shared hallmark across tumor initiation, progression, and immunogenicity, this study recasts mutational burden as both a biological price of longevity and an Achilles' heel exploitable for durable, complete tumor remission in personalized medicine.

Indexed as

Immune Checkpoint InhibitorsImmunotherapyMutationNeoplasmsAdultAgedFemaleHumansMaleMiddle AgedImmune Checkpoint InhibitorsImmune Checkpoint InhibitorImmunotherapy

Identifiers

PMID40447313
PMCPMC12128474

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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.