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Record W1653949476

Comparison of lung adenocarcinoma and squamous cell carcinoma genomes reveals distinct regions of amplification on chromosome 3q

2005· article· en· W1653949476 on OpenAlexaboutno aff
William W. Lockwood, Cathie Garnis, Adi F. Gazdar, John D. Minna, Stephen Lam, Calum MacAulay, Wan L. Lam

Bibliographic record

VenueCancer Research · 2005
Typearticle
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyLung cancerAdenocarcinomaGenomeComparative genomic hybridizationChromosomeGeneticsCancerCopy-number variationComputational biologyGenePathologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

879 Lung cancer is a leading cause of cancer death worldwide. Non-small cell lung cancer (NSCLC) is the major disease type, with squamous cell carcinoma (SqCC) and adenocarcinoma (AC) as the two main sub-types. SqCC and AC are distinguished by differences in their histopathological and molecular characteristics: SqCC develops more rapidly and is located in the central airways, whereas AC is thought to originate from the epithelium of the lung periphery. Previous findings suggest that, although a similar degree of genetic imbalance exists for AC and SqCC, each type is characterized by a unique pattern of genomic imbalance. Objective: To comprehensively identify the underlying differences in genetic alteration patterns between SqCC and AC, we performed genome-wide tiling resolution array CGH analysis. Novel variations in copy number detected by this high resolution technology may reveal cancer-related loci and will provide potential targets for diagnosis and treatment. Design, Materials and Methods: DNA was isolated from 15 AC cell lines and 9 SqCC cell lines. Sample DNA and a pooled reference genomic DNA sample were differentially labeled and applied to the submegabase resolution tiling-set (SMRT) array for CGH analysis. This array consists of >32,000 overlapping human bacterial artificial chromosome clones that span the entire human genome, allowing true genome-wide assessment of copy number changes for a given sample. SMRT array data was assessed using multiple software applications (SeeGH, weighted frequency, aCGH smooth) and alterations in identified regions are presently be validated by fluorescent in situ hybridization using loci specific probes. Results: In total, 24 whole genome array CGH profiles of lung cancer cell lines were generated. Numerous novel, subtype-specific chromosomal alterations were observed. This included differences of alteration at chromosome arms 2q, 6q, 8q, 9q, 12q, 13q and 16p. Of specific interest were the different locations of chromosomal amplification at 3q in the sub-types. AC showed frequent gains between 3q13 and 3q22 while SqCC displayed a similar frequency at 3q23-3q26. These regions have previously been implicated in lung cancer but not mapped according to sub-type. Further analysis of genes within distinct altered regions will determine if these loci help drive the development of different lung cancer subtypes. Conclusions: Tiling resolution array CGH analysis of AC and SqCC lung cancers revealed both shared and subtype-specific regions of DNA copy aberration, suggesting that differences in tumor genomes help define distinct disease subtypes. Further characterization of the novel aberrations and minimal regions we have identified will implicate additional genes in the two tumorigenesis processes and help tailor disease diagnosis. Supported by NCI SPORE CA 70907, NCI Contract N01-85188 and Genome Canada

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: none
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.111
GPT teacher head0.415
Teacher spread0.304 · 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
Published2005
Admission routes1
Has abstractyes

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