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Single nucleotide polymorphisms (SNPs) of the platinum pharmacogenetic and VEGF pathways: Association with survival of platinum-treated stage IV non-small cell lung cancer (NSCLC) patients.

2012· article· en· W2609778940 on OpenAlexaff
Sinéad Cuffe, Xiaoping Qiu, Abul Kalam Azad, Xin Qiu, Kevin Boyd, Qin Kuang, Sharon Marsh, Sevtap Savas, Marjan Emami, Nicole Perera, Prakruthi R. Palepu, Zhuo Chen, Devalben Patel, Dangxiao Cheng, Ronald Feld, Natasha B. Leighl, Frances A. Shepherd, Ming‐Sound Tsao, Wei Xu, Geoffrey Liu

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsMemorial University of NewfoundlandUniversity of AlbertaPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsSingle-nucleotide polymorphismMedicineOncologyInternal medicineLung cancerHazard ratioGenotypeBiologyGeneticsGeneConfidence interval

Abstract

fetched live from OpenAlex

7586 Background: Two potentially important host pathways in lung cancer systemic therapy are: (i) the pharmacogenetic pathway of platinum agents (DNA repair, metabolism, and multidrug resistance genes); and (ii) the vascular endothelial growth factor (VEGF) pathway. We investigated the relationship between SNPs in these two pathways and clinical outcome in platinum-treated NSCLC patients. Methods: 188 platinum-treated Stage IV NSCLC patients underwent SNP genotyping for the platinum-related (48 SNPs in 7 genes) and VEGF (64 SNPs in 3 genes) pathways. SNPs were selected from the literature and through tagging. Association of SNPs and overall (OS) and progression free survival (PFS) were assessed using multivariate Cox proportional hazards models. Results: 72% were Caucasian; 73%, adenocarcinoma; 92%, ECOG PS 0-1; median age, 60 years; 54% received > one line of systemic therapy; 10% received anti-VEGF therapy/placebo; Median OS, 1.3 yrs; median follow up, 2.2 yrs. The top significant SNPs in the platinum-related pathway were in ABCC2 (rs8187710 and rs2756109, r2=0.68). The G variants of the top SNP, ABCC2 rs8187710 (4554G>A), were associated with worse OS (adjusted hazard ratio [aHR], 2.62; 95%CI: 1.5-4.5; p=0.0005) and PFS (aHR, 1.97; 95%CI: 1.2-3.4; p=0.01). Functionally, 4554G>A impairs ATP-ase activity and is associated with higher cellular accumulation of ABCC2 substrates [PMID: 22027652]; furthermore, ABCC2 expression is associated with cisplatin resistance and clinical outcome in other cancers [PMID: 17145840]. Within the VEGF pathway, the top significant SNPs were in the same haplotype block of VEGFR1/FLT1 (rs1324057, rs7324547, r2=1.0): for rs1324057, the aHR for OS was 1.59 (95%CI 1.2-2.1); p=0.001; and the aHR for PFS, 1.48 (95%CI 1.1-1.9); p=0.004. VEGFR1/FLT1 rs7324547 has been associated with esophageal cancer risk [PMID: 21751195], but has not been assessed in lung cancer. Conclusions: SNPS of the VEGFR1 and ABCC2 genes are strongly associated with OS and PFS in this cohort of platinum-treated advanced NSCLC patients. Future studies should assess whether these are predictive or prognostic markers.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.383
Teacher spread0.333 · 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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