Evidence map›Paper›PMID 41614225›Full record

ArticleCancer science2026

Refining Tumor Mutational Burden as a Predictive Biomarker for Pembrolizumab: A Real-World Analysis in Japanese Patients.

Tomoyo Yasuda, Mio Yumura, Azusa Hamasaki, Tongyi Fei, Takashi Kubo, Hitoshi Ichikawa, Takashi Kohno, Kuniko Sunami

Abstract read
In one paragraph

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

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

8 authors.

Tomoyo YasudaSysmex Corporation, Kobe, Hyogo, Japan.
Mio YumuraSysmex Corporation, Kobe, Hyogo, Japan.
Azusa HamasakiSysmex Corporation, Kobe, Hyogo, Japan.
Tongyi FeiSysmex Corporation, Kobe, Hyogo, Japan.ORCID https://orcid.org/0000-0002-6926-9556
Takashi KuboDepartment of Clinical Genomics, National Cancer Center Research Institute, Tokyo, Japan.
Hitoshi IchikawaDepartment of Clinical Genomics, National Cancer Center Research Institute, Tokyo, Japan.
Takashi KohnoDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.ORCID https://orcid.org/0000-0002-5371-706X
Kuniko SunamiDepartment of Laboratory Medicine, National Cancer Center Hospital, Tokyo, Japan.ORCID https://orcid.org/0000-0002-7137-5649

Funding

Sysmex Corporation C2019-071
6 · The paper itself

Abstract

Tumor mutational burden (TMB) is a key biomarker for predicting the response to immune checkpoint inhibitors (ICIs). However, its predictive accuracy in real-world clinical practice, particularly in Asian populations, remains inadequately evaluated. We addressed this issue by analyzing real-world data from 63,952 patients registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database, which integrates genomic and clinical information from Japanese patients with various advanced solid tumors. We assessed the therapeutic efficacy of pembrolizumab in 1899 patients who underwent one of three comprehensive genomic profiling tests: FoundationOne CDx, the OncoGuide NCC Oncopanel System, or the GenMine TOP Cancer Genome Profiling System. Based on the reported TMB values, patients were classified as TMB-high (≥ 10 mutations per megabase) or TMB-low (< 10 mutations per megabase). The objective response rate (ORR) among 946 TMB-high patients exceeded 30% and was significantly higher than that observed in 953 TMB-low patients (16.8%, p < 0.001). Notably, patients with borderline TMB values (10 to less than 13 mutations per megabase) exhibited relatively modest responses (20.8%). The ORR improved when hotspot mutations were excluded from the TMB calculation, suggesting that this adjustment enhances the predictive accuracy of TMB. These findings support the clinical utility of TMB as a biomarker for predicting ICI response in routine oncology practice. In particular, excluding hotspot mutations from TMB calculations may improve response prediction in patients whose TMB values are near the threshold.

Indexed as

Antibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalBiomarkers, TumorMutationNeoplasmsAdultAgedAged, 80 and overEast Asian PeopleFemaleHumansJapanMaleMiddle AgedTreatment OutcomeAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalBiomarkers, Tumorpembrolizumabcomprehensive genomic profilingimmune checkpoint inhibitorsprecision oncologyreal‐world data analysistumor mutation burden

Identifiers

PMID41614225
PMCPMC13045439

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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.