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Record W1987882758 · doi:10.4161/cbt.3.1.590

Evaluation of Microsatellite Instability, hMLH1 Expression and hMLH1 Promoter Hypermethylation in Defining the MSI Phenotype of Colorectal Cancer

2004· article· en· W1987882758 on OpenAlex
Christian Arnold, Ajay Goel, Carolyn C. Compton, Victoria Marcus, Donna Niedzwiecki, Jeannette M. Dowell, L Wasserman, Toru Inoue, Robert J. Mayer, Monica M. Bertagnolli, C. Richard Boland

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Biology & Therapy · 2004
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMcGill University
FundersNational Cancer InstituteUniversity of California, San FranciscoUniversity of California, San Diego
KeywordsMicrosatellite instabilityDNA mismatch repairMethylationDNA methylationColorectal cancerBiologyCancer researchCancerImmunohistochemistryMicrosatelliteMolecular biologyGeneGene expressionGeneticsAlleleImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: About 15% of all colorectal cancers (CRCs) demonstrate high levels of microsatellite instability (MSI-H) and are currently best identified by molecular analysis of microsatellite markers. Most sporadic CRCs with MSI-H are known to be associated with the methylation of the hMLH1 promoter. Promoter methylation coincided with lack of hMLH1 expression. We aimed to investigate the association between MSI status, hMLH1 protein expression and methylation status of the hMLH1 promoter, and to determine the usefulness of each method in defining the MSI phenotype in sporadic CRCs. MATERIALS AND METHODS: CRCs from 173 patients from the Cancer and Leukemia Group B (CALGB) were assessed for their MSI status. An additional cohort of 18 MSI-H tumors from the University of California San Diego (UCSD) was included in the analysis of the MSI-H subgroup. MSI testing was performed by PCR using five standard MSI markers. hMLH1 promoter analysis was investigated by methylation specific PCR (MSP), and expression of the MMR genes hMLH1 and hMSH2 was examined by immunohistochemistry (IHC). RESULTS: Of the 173 CALGB tumors, 111 (64%) were MSS, 35 (20%) were MSI-L and 27 (16%) MSI-H, respectively. Data on hMLH1 protein expression, hMSH2 protein expression and hMLH1 methylation are available on 128, 173 and 81 of these tumors, respectively. Presence of hMLH1 and hMSH2 protein expression was significantly associated with MSI status. Four of 45 (8.9%) MSI-H tumors and 0 of 146 (0%) MSS/MSI-L tumors did not express hMSH2 (p = 0.0028). hMLH1 protein expression was present in 107 of 108 (99%) MSS and MSI-L tumors versus 11 of 20 (55%) MSI-H tumors (p < 0.0001). Of 61 MSS and MSI-L cancers studied for methylation, 11 (18%) were methylated at the hMLH1 promoter whereas 14 of 20 (70%) MSI-H cancers were methylated (p = 0.0001). In 27 MSI-H tumors studied for hMLH1 protein expression and methylation, 93% of tumors with loss of expression (93%) were also methylated while 42% (5/12) with positive immunostaining for hMLH1 were methylated at the hMLH1 promoter (p = 0.009). CONCLUSIONS: Promoter methylation and hMLH1 expression are significantly associated with the MSI-H phenotype in CRC. Promoter methylation analysis provides a useful means to screen for MSI-H tumors. Our data further suggests that hMLH1 promoter methylation analysis alone cannot replace MSI testing, as a significant number of MSI-H tumors could be potentially overseen by such an approach. We suggest that phenotypic evaluation of CRC is performed most reliably with MSI testing, although expression analysis and investigation of the promoter methylation status may complement the screening process.

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.

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)0.001
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 score0.257
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.046
GPT teacher head0.354
Teacher spread0.308 · 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