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Record W4401425810 · doi:10.1080/07357907.2024.2388107

The Landscape and Prognosis of Microsatellite Stable (MSS) Esophageal, Gastro-Esophageal Junction and Gastric Adenocarcinomas with High Tumor Mutation Burden (TMB)

2024· article· en· W4401425810 on OpenAlexaff
Ioannis A. Voutsadakis

Bibliographic record

VenueCancer Investigation · 2024
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsNOSM UniversityEssar Steel Algoma (Canada)Sault Area Hospital
Fundersnot available
KeywordsMutationEsophageal adenocarcinomaMedicineEsophagogastric junctionMicrosatelliteInternal medicineMicrosatellite instabilityCancer researchEsophageal cancerGastroenterologyAdenocarcinomaCancerOncologyBiologyGeneGeneticsAllele

Abstract

fetched live from OpenAlex

Background A minority of patients with MSS tumors present a high tumor mutation burden (TMB) without underlying MMR defects.Methods Publicly available genomic series were assessed for identification of patients with MSS gastric gastroesophageal junction, and esophageal adenocarcinomas and a high TMB, defined as more than 10 mutations per Mb. These were compared with MSS cancers and a low TMB for genetic alterations and for survival outcomes.Results Patients with MSS cancers with high TMB in the MSK series were older but did not differ in other clinicopathologic parameters compared with MSS patients with low TMB. Mutations in tumor suppressors TP53 and APC and oncogenes KRAS and ERBB4 as well as amplifications of ERBB2 were more prevalent in the high TMB group of MSS cancers. Mutations in DDR associated genes, in epigenetic modifiers and in genes associated with immune response were more prevalent in the hIgh TMB group patients. However, high TMB was not associated with an improved survival in MSS gastric/gastroesophageal junction/esophageal adenocarcinomas (Log Rank p = 0.5).Conclusion MSS Gastric/gastroesophageal junction/esophageal adenocarcinomas with TMB above 10 mutations per Mb possess a genomic landscape with increased alteration frequencies in common gastroesophageal cancer genes and pathways.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.494

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)0.0000.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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