Evidence map›Paper›PMID 42719515›Full record

ArticleHuman mutation2026

Bayesian Integration of Tumor Mutational Signatures and Somatic Features Refines Pathogenicity Assessment of Germline Mismatch Repair Variants.

Yonatan Amzaleg, Kevin J McDonnell, Gregory E Idos, Christina Mathai, Stacy W Gray, Heather Hampel, David W Craig

Abstract read
In one paragraph

Article in Human mutation, 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

7 authors.

Yonatan AmzalegDepartment of Integrative Translational Science, Beckman Research Institute, City of Hope, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0000-0002-8576-9702
Kevin J McDonnellDivision of Clinical Cancer Genomics, Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0000-0002-3354-4747
Gregory E IdosDepartment of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0000-0002-6068-4139
Christina MathaiEnterprise Data Group, City of Hope, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0009-0002-0411-0517
Stacy W GrayDivision of Clinical Cancer Genomics, Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0000-0001-6948-0143
Heather HampelDivision of Clinical Cancer Genomics, Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0000-0001-7558-9794
David W CraigDepartment of Integrative Translational Science, Beckman Research Institute, City of Hope, Duarte, California, USA, cityofhope.org.ORCID https://orcid.org/0000-0003-2040-1955

Funding

USC PE-GCS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization StudiesU2CCA252971 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JOHN D. CARPTEN, HEINZ JOSEF LENZ · 2021 to 2026
$19.3M
NCI NIH HHS U2C CA252971
6 · The paper itself

Abstract

Variants of uncertain significance (VUS) in mismatch repair (MMR) genes represent a persistent bottleneck in germline interpretation for Lynch syndrome, creating a critical opportunity to leverage tumor biology to refine pathogenicity assessment. Although tumor features such as microsatellite instability (MSI) and immunohistochemistry (IHC) are routinely evaluated, they are typically interpreted separately from germline classification, and their quantitative contribution within ACMG/AMP frameworks remains poorly defined. We therefore analyzed paired germline and tumor sequencing data from 1110 tumors across 1073 patients with colorectal or endometrial cancer to determine whether mismatch repair-deficient (MMR-d) mutational signatures can be quantitatively integrated into Bayesian germline variant interpretation. Using COSMIC single-base substitution signatures, tumors were classified as MMR-d or MMR proficient, and an empirically derived likelihood ratio (LR) quantified the association between MMR-d signatures and pathogenic germline MMR variants. The presence of an MMR-d signature increased the likelihood of an underlying pathogenic germline MMR variant approximately eightfold (LR ≈ 8; log10 LR ≈ 0.90), whereas its absence provided moderate-to-strong benign evidence (LR ≈ 0.156; log10 LR ≈ -0.81). Applying this integrative framework to 45 germline MMR VUS, joint modeling of tumor mutational signatures with additional somatic and variant-level evidence resulted in clinically significant reclassification of 38 (84.4%) variants, including three reclassified as pathogenic or likely pathogenic and 35 as likely benign. A total of 16 downgraded variants were independently downgraded by Invitae. These findings demonstrate that tumor mutational signatures can be formally incorporated into Bayesian germline interpretation, transforming tumor data into quantitative pathogenicity evidence and offering a principled strategy to reduce VUS burden in hereditary cancer genetics.

Indexed as

DNA Mismatch RepairGerm-Line MutationBayes TheoremColorectal Neoplasms, Hereditary NonpolyposisFemaleHumansMicrosatellite InstabilityMutation

Identifiers

PMID42719515
PMCPMC13554728

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.