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Novel genome-wide significant germline genetic variants associated with venous thrombo-embolism (VTE) and arterial embolism (ATE) risk in patients with <i>ALK</i> and <i>ROS1</i> fusion non-small cell lung cancer (NSCLC).

2024· article· en· W4399281115 on OpenAlexafffund
Sam Khan, Beatriz Jiménez, Katrina Hueniken, Tianzhichao Hou, Devalben Patel, Tracy Stockley, Ming‐Sound Tsao, Alona Zer, Mor Moskovitz, Yehuda Rosenberg, Penelope Ann Bradbury, Lawson Eng, Natasha B. Leighl, Adrian G. Sacher, Geoffrey Liu, Frances A. Shepherd

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersPrincess Margaret Cancer Foundation
KeywordsMedicinePulmonary embolismVenous thromboembolismGermlineInternal medicineOncologyCardiologyThrombosisGeneticsGene

Abstract

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12092 Background: In a recent meta-analysis, non small cell lung cancers (NSCLC) with ALK or ROS1 fusions had higher rates of VTE compared to KRAS or EGFR mutant NSCLC, and were associated with increased ATE risk, particularly around diagnosis. The underlying mechanisms of how these somatic fusions affect thrombosis remain unclear. We examined clinico-demographic and germline genetic factors associated with VTE and ATE in NSCLC patients with ALK/ROS1 fusions in this first comprehensive genome wide association analysis (GWAS). Methods: In this prospective cohort, germline DNA from whole blood was obtained from 150 patients with ALK fusions and 32 with ROS1 fusions at Princess Margaret Cancer Centre (recruited 2014- 2023). Clinico-demographic, treatment and outcome data were collected from electronic medical charts. Overall survival (OS) by VTE or ATE status was assessed via Cox regression, treating ATE and VTE as time-varying covariates. Genotyping utilized the Infinium Global Screening Array (v3.0 Illumina); quality-control removed 3 patients from final analysis. Using linear regression, outcomes were weighted; no VTE/ATE events (0), one VTE/ATE event (1), or multiple ATE/VTEs (>2). Global significance was set at p < 5 x10-8 and adjusted for age, sex, body mass index (BMI), and ethnic/population stratification (top 3 principal components). Results: There were 97 females (54%) and 82 males (46%), mean age was 57.4 years, 70% had stage 4 disease, 96% adenocarcinoma; 35% experienced VTE/ATE at any time; 13% had 2+ VTE/ATE events. For those with VTE, 32 scored 1, 22 scored 2 and 6 scored 3 on Khorana score. Higher BMI was a significant risk factor for VTE/ATE (adjusted odds ratio 1.59 per 5-unit increase, p=0.01). Shorter OS was observed in patients with VTE (Hazard ratio (HR)=3.15, p<0.001) and ATE (HR=2.51, p=0.036), compared to those without. Two novel GWAS gene peaks on the Manhattan plot (previously not reported to be associated with VTE/ATE) had globally significant associations with risk of VTE/ATE: at Chromosome 6q15 (intergenic region between RNGTT and LOC101928936; 5/10 top variants with top risk-allele p=3.594E-09) and at 15p22 ( TLN2 gene; 2/10 top variants p=1.095E-08). TLN2 is a cytoskeletal protein involved in the assembly of actin filaments and linkages with extracellular matrices. Additional identified variants potentially associated with VTE/ATE in ALK/ROS1 fusion patients were found in: CTBP2, NALCN, WDR7, PAX7, ZNF385D, SORBS2, and CSMD1. Conclusions: Two novel globally significant variants, associated with VTE/ATE, are unique to patients with ALK/ROS1 fusion NSCLC. If validated, these biomarkers may help identify ALK/ROS1 patients who are at highest risk of VTE/ATE who may benefit from prophylactic anticoagulation. Further investigation and clinical evaluation are warranted.

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)0.002
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.345
Teacher spread0.328 · 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
Published2024
Admission routes2
Has abstractyes

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