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Record W2334751259 · doi:10.1158/1538-7445.am2012-2930

Abstract 2930: Novel colorectal cancer loci in multiplex-proficient mismatch repair families

2012· article· en· W2334751259 on OpenAlexaffabout
Julie M. Cunningham, Mine Cicek, Fridley Brooke, Daniel Serie, William R. Bamlet, Brenda Diergaarde, Robert W. Haile, Loı̈c Le Marchand, Theodore Kontriris, Ban Younghusband, Steven Gallinger, Polly A. Newcomb, John L. Hopper, Mark A. Jenkins, Graham Casey, Fredrick R. Schumacher, Zhu Chen, Allyson Templeton, Ingrid Winship, Roger Green, Finlay Macrae, Susan Parry, Graeme P. Young, Joanne Young, Daniel D. Buchanan, Duncan C. Thomas, D. Timothy Bishop, Noralane M. Lindor, Stephen N. Thibodeau, John D. Potter, Ellen L. Goode

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity of TorontoMemorial University of Newfoundland
Fundersnot available
KeywordsMicrosatellite instabilityGenetic linkageGeneticsColorectal cancerMedicineSingle-nucleotide polymorphismCancerFamily historyLinkage (software)MicrosatelliteOncologyBiologyInternal medicineGenotypeGeneAllele

Abstract

fetched live from OpenAlex

Abstract A substantial proportion of familial colorectal cancer (CRC) is not a consequence of known susceptibility loci, such as mismatch repair (MMR) genes, supporting the existence of additional loci. To identify novel CRC loci, we conducted a genome-wide linkage scan in 356 white families with no evidence of defective MMR (i.e., no tumors with loss of expression of MMR proteins; no microsatellite instability (MSI)-high tumors, and no evidence of linkage to MMR genes). This represents the largest linkage analysis of proficient MMR (pMMR) familial CRC to date. Families were ascertained via the NCI-supported Colon Cancer Family Registry multi-site (Colon CFR) consortium, the City of Hope, and Memorial University of Newfoundland. A total of 1,612 individuals (average 5.0 per family, range 2-10 with an average of 2.2 affected and 2.8 unaffected individuals) were genotyped using genome-wide single nucleotide polymorphism linkage arrays; parametric and non-parametric linkage analysis used MERLIN in a priori-defined family groups. Five lod scores greater than 3.0 were observed, accounting for heterogeneity, in four chromosomal regions. The greatest lod scores were at 4q21.1 among families with mean age of diagnosis less than 50 years (dominant HLOD=4.51, α=0.84, 145.40 cM, rs10518142) and at 12q24.32 among all families (dominant HLOD=3.60, α=0.48, 285.15 cM, rs952093). Among families with four or more affected individuals and among clinic-based families, a common peak was observed at 15q22.31 (101.40 cM, rs1477798; dominant HLOD=3.07, α=0.29; dominant HLOD=3.03, α=0.32, respectively). Analysis of families with only two affected individuals yielded a peak at 8q13.2 (recessive HLOD=3.02, α=0.51, 132.52 cM, rs1319036). These linkage regions comprise previously unreported loci, supporting the hypothesis that novel loci contribute to CRC in familial pMMR cases. These loci are also largely distinct from those identified in case-control GWAS. To follow up on these findings, a custom Agilent Sure Select Target Enrichment panel has been designed for genes in three of these regions, in order to sequence probands using an Illumina HiSeq 2000. This study demonstrates the utility of family-based data and provides evidence for additional alleles for familial CRC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2930. doi:1538-7445.AM2012-2930

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)0.002
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.122
GPT teacher head0.427
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 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 routes2
Has abstractyes

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