Evidence map›Paper›PMID 41959104›Full record

ArticlebioRxiv : the preprint server for biology2026

Defining mutational signatures of lung cancer-associated carcinogens through

Natasha Q Gurevich, Darren J Chiu, Masanao Yajima, Jonathan Huggins, Sarah A Mazzilli, Joshua D Campbell

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for 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

6 authors.

Natasha Q GurevichSection of Computational Biomedicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts.
Darren J ChiuSection of Computational Biomedicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts.
Masanao YajimaDepartment of Mathematics & Statistics, Boston University, Boston, Massachusetts.
Jonathan HugginsDepartment of Mathematics & Statistics, Boston University, Boston, Massachusetts.
Sarah A MazzilliSection of Computational Biomedicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts.
Joshua D CampbellSection of Computational Biomedicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts.

Funding

Predoctoral Training in Bioinformatics and Computational BiologyT32GM100842 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI TULLIUS, THOMAS D · 2012 to 2022
$2.8M
Utilizing Bayesian modeling to improve mutational signature inference in large-scale datasetsU01CA253500 · NCI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI CAMPBELL, JOSHUA D, YAJIMA, MASANAO · 2021 to 2023
$1.2M
Robust, scalable, and accurate discovery of mutational signaturesR01GM144963 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI HUGGINS, JONATHAN · 2021 to 2023
$592k
NCI NIH HHS U01 CA253500NIGMS NIH HHS R01 GM144963NIGMS NIH HHS T32 GM100842
6 · The paper itself

Abstract

While distinct environmental exposures imprint unique mutational signatures on cancer genomes, the specific causal patterns for many known carcinogens remain uncharacterized in relevant human tissues. To address this gap, we developed a novel, physiologically relevant system that uses a combination of airway epithelial cells and whole genome sequencing to characterize mutational patterns induced by genotoxic carcinogens associated with lung cancer. After validating the platform's accuracy by successfully recapturing the known signature for Benzo(a)pyrene (BaP), we used this system to gain detailed insights into the types of mutations that occur with exposure to N-nitrosotris-(2-chloroethyl) urea (NTCU) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), genotoxic compounds that induce lung squamous cell carcinoma and lung adenocarcinoma in mouse models, respectively. Cells exposed to NTCU had significantly more somatic SNVs compared to control samples. An average of 82.3% of mutations in NTCU samples were attributed to a novel mutational signature distinct from those in the COSMIC database but highly correlated with recent

Indexed as

bioinformaticscancer genomicslung cancerMutational signatures

Identifiers

PMID41959104
PMCPMC13061053

What OpenQuestion holds

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LicenceCC BY-NC
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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.