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Record W4409645341 · doi:10.1158/1538-7445.am2025-3815

Abstract 3815: High-penetrance rare variants underlying familial lung cancer risk: Insights from the Genetic Epidemiology of Lung Cancer Consortium

2025· article· en· W4409645341 on OpenAlexaff
Yanhong Liu, Claudio W. Pikielny, Xiangjun Xiao, Bo Peng, Yafang Li, Jinyoung Byun, Chao Cheng, Dakai Zhu, Spiridon Tsavachidis, Colette Gaba, Elena Kupert, Ellen L. Goode, Erin L. Crawford, Kristen S. Purrington, Marshall W. Anderson, Michael D. Cole, Paul E. Brennan, Geoffrey Liu, James McKay, John K. Field, David C. Christiani, Diptasri Mandal, James C. Willey, Ann G. Schwartz, Joan E. Bailey‐Wilson, Susan M. Pinney, Christopher I. Amos

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstitutePrincess Margaret Cancer Centre
Fundersnot available
KeywordsLung cancerPenetranceMedicineEpidemiologyOncologyCancerInternal medicineGeneticsBiologyGenePhenotype

Abstract

fetched live from OpenAlex

Background: Rare, functionally deleterious genetic variants have been implicated as having substantially larger effect sizes than common variants, potentially accounting for much of the missing heritability in lung cancer (LC). Over 25 years, the Genetic Epidemiology of LC Consortium (GELCC) has curated an invaluable resource of specimens and data from individuals with a strong family history of LC. Methods: Whole-genome and exome sequencing data were analyzed in 129 high-risk familial LC (FLC) families, defined as having two first-degree relatives or three or more second-degree relatives affected by LC (177 affected FLC and 309 unaffected relatives). The discovery focused on rare (allele frequency < 1% in gnomAD global population) and deleterious variations (missense, stop-gained, frameshift) enriched in FLC. Promising candidates were further external validated in 2,408 sporadic lung cancer (SLC) cases and 885 population controls from the International Lung Cancer Consortium. Results: We identified 168 variants with moderate-to-large effects on FLC risk, 100 of which were validated for SLC risk (Table 1 Table 1. Top 20 candidates Gene Rare (MAF < 1%), deleterious variants No. of variant carrier counts Odds Ratio, LC vs Control FLC | Relative | SLC | Control FLC+SLC SLC Oncogene ERBB3 / HER3 p.A1131T 3 | 1 | 2 | 0 35 15 JAK p.V651M 2 | 3 | 7 | 0 62 51 NOTCH3 p.R1560P 3 | 1 | 4 | 0 48 29 ROS1 p.N785X 6 | 4 | 10 | 0 110 74 USP6 p.R522 fs del 3 | 6 | 6 | 0 62 45 Tumor suppressor gene ATM p.L2332P 3 | 2 | 8 | 0 76 59 LZTS2 p.K458R 4 | 4 | 18 | 0 152 133 NPIPB13 p.V270 fs del 13 | 14 | 10 | 0 159 74 PARK2 / PRKN p.P153R 3 | 3 | 8 | 0 76 59 RB1 p.A525G 3 | 0 | 6 | 0 62 45 SLX4 p.S1716T 3 | 2 | 9 | 0 83 66 SYNE1 p.M6566I 2 | 0 | 7 | 0 62 52 TGFBRAP1 p.T301R 5 | 0 | 11 | 0 110 82 WNK1 p.K583 fs del 4 | 0 | 23 | 0 187 171 Other cancer-associated gene CFTR p.R74W 4 | 2 | 4 | 0 55 30 FLG p.R3404 fs del 7 | 2 | 4 | 0 69 30 LTN1 p.R349H 6 | 1 | 10 | 0 110 74 MLNR p.Q334 fs del 3 | 2 | 19 | 0 152 134 SLC39A11 p.R38Q 4 | 2 | 13 | 0 117 96 TTYH2 p.R493C 5 | 4 | 14 | 0 131 104 Dose effect of the top candidates No. candidates 0 variant allele 67 | 194 | 1911 | 834 reference reference 1 variant allele 50 | 66 | 363 | 50 3.5 (2.6 - 4.7) 3.2 (2.3 - 4.3) 2 variant alleles 15 | 18 | 62 | 1 32 (4.5 - 230) 27 (3.8 - 195) 3+ variant alleles 45 | 31 | 72 | 0 98 (6 - 1506) 62 (3.9 -1012) lists 20 top hits). Among these, 15 variants mapped to our previously identified lung cancer linkage locus at 6q23-25 (ROS1, PARK2, SYNE1). Others were enriched in oncogenes (ERBB3, JAK1, MET), tumor suppressor genes (ATM, BRCA2, RB1), and genes involved in the extracellular matrix (COL6A3, FLG, MUC5B). Importantly, individuals carrying more than two combinations of these variants exhibited exceptionally strong dose effects, with odds ratios (OR) exceeding 27. Conclusion: Our findings underscore the significant role of rare, high-penetrance variants in FLC etiology and highlight promising targets for early detection and personalized treatment. Future in-depth mechanistic studies are planned to evaluate the pathogenic effects of these specific alleles. Citation Format: Yanhong Liu, Claudio Pikielny, Xiangjun Xiao, Bo Peng, Yafang Li, Jinyoung Byun, Chao Cheng, Dakai Zhu, Spiridon Tsavachidis, Colette Gaba, Elena Kupert, Ellen L. Goode, Erin L. Crawford, Kristen Purrington, Marshall Anderson, Michael Cole, Paul Brennan, Geoffrey Liu, James McKay, John K. Field, Rayjean J. Hung, David C. Christiani, Diptasri Mandal, James C. Willey, Ann Schwartz, Joan Bailey-Wilson, Susan M. Pinney, Christopher I. Amos. High-penetrance rare variants underlying familial lung cancer risk: Insights from the Genetic Epidemiology of Lung Cancer Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3815.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.414
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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