MétaCan
Menu
Back to cohort
Record W1510819614 · doi:10.1158/0008-5472.can-05-1513

Multiple Microalterations Detected at High Frequency in Oral Cancer

2005· article· en· W1510819614 on OpenAlexaff
Corisande Baldwin, Cathie Garnis, Lewei Zhang, Miriam P. Rosin, Wan L. Lam

Bibliographic record

VenueCancer Research · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Dental and Craniofacial Research
KeywordsTiling arrayComparative genomic hybridizationGenomeGeneBiologyComputational biologyCancerGeneticsDNA microarrayGene expression

Abstract

fetched live from OpenAlex

The development of array comparative genomic hybridization (array CGH) at tiling-path resolution has enabled the detection of gene-sized segmental DNA copy number gains and losses. Here, we present the first application of whole genome tiling-path array CGH to archival clinical specimens for the detailed analysis of oral squamous cell carcinomas (OSCC). We describe the genomes of 20 OSCCs as well as a selection of matched normal DNA in unprecedented detail. Examination of their whole genome profiles enabled the identification of alterations ranging in size from whole-arm, segmental, to gene size alterations. Tiling-path resolution enabled the detection of many more alterations within each tumor than previously reported, many of which include narrow alterations found to be frequent events among the 20 OSCCs. We report the presence of several novel frequent submegabase alterations, such as the 0.58 Mb gain at 5p15.2 containing triple functional domain (TRIO), detected in 45% of cases. We also report the first coamplification of two gene clusters, by fine-mapping the precise base pair boundaries of the high-level amplification at 11q22.2-22.3 containing both matrix metalloproteinase and baculoviral IAP repeat-containing protein 2 (BIRC) gene clusters. These results show the large improvement in detection sensitivity and resolution compared with genome interval marker arrays and the utility of tiling resolution array CGH for the detection of both submegabase and single copy gains and losses in cancer gene discovery.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.036
GPT teacher head0.341
Teacher spread0.305 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations123
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicGenomic variations and chromosomal abnormalitiesFrench-language works237,207