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Record W3006851051 · doi:10.1093/jcag/gwz047.040

A41 LOSS OF SATB2 EXPRESSION IN COLORECTAL CANCER IS ASSOCIATED WITH DURATION OF INFLAMMATORY BOWEL DISEASE

2020· article· en· W3006851051 on OpenAlexaff
J Atin, Cristian Hernández-Rocha, Krzysztof Borowski, Joanne M. Stempak, Michelle I. Smith, James Conner, Mark S. Silverberg

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicFerroptosis and cancer prognosis
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsMedicineColorectal cancerInternal medicineUlcerative colitisInflammatory bowel diseaseGastroenterologyColectomyDiseaseCancerImmunohistochemistryColitisBiomarkerOncology

Abstract

fetched live from OpenAlex

Abstract Background Patients with inflammatory bowel disease (IBD) are at higher risk for developing colitis-associated colorectal cancer (CAC). Clinical and endoscopic features are used to stratify the risk of CAC, but new biomarkers are necessary to improve this stratification. Recent studies have shown that loss of expression of special AT-rich sequence binding protein 2 (SATB2) is frequent in CAC compared to sporadic colorectal cancer and this SATB2 status is found in pre-cancerous dysplastic lesions as well. However, the relationship of known clinical risk factors for CAC and loss of SATB2 has not been explored. Aims To assess the association of loss of SATB2 expression in CAC with clinical characteristics of IBD. Methods Patients with a known diagnosis of ileocolonic or colonic Crohn’s disease (CD), ulcerative colitis (UC), or IBD unclassified (IBDU) who underwent colectomy between October 2010 and December 2017 for CAC were included. SATB2 expression in neoplastic tissue was evaluated using immunohistochemistry (IHC), where less than 5% of tumor cells showing staining was considered loss of SATB2. Tumor grade, P53 and mismatch repair (MMR) status were assessed as well. Available clinical data such as sex, smoking status, IBD diagnosis (CD, UC or IBDU), age at IBD diagnosis, duration of IBD, extent of colitis and previous medications were collected. We used a generalized linear model to assess the association between these biomarkers and clinical data. Results A total of 58 patients with mean age at CAC diagnosis of 50.3 ±13 years, 27 (46%) females were analyzed. Mean IBD duration was 17.6 ±10 years and 22 (37.9%), 34 (58.6%) and 2 (3.4%) were CD, UC and IBDU, respectively. Thirty-two (55.2%) CACs had loss of SATB2 expression. There was no association between age at CAC diagnosis or grade of the tumor and loss of SATB2. However, longer duration of IBD (21.2 ± 9 years vs 13.7 ± 9 years, p = 0.01) was significantly associated with loss of SATB2. There was no association between SATB2 status and other explored clinical or endoscopic variables. Tumors with P53 mutation were associated with a younger age at diagnosis of CAC (47.2 ±13 vs 55.0 ±12 years, p = 0.03), but no other associations of this marker or MMR with clinical or endoscopic variables of IBD were found. Conclusions Loss of SATB2 expression is significantly associated with IBD duration, a well-known risk factor for CAC. This association with duration of IBD could denote an effect of longer chronic inflammation on SATB2 status. Given the previously reported association of loss of expression of SATB2 with pre-cancerous lesions in IBD patients, this could be a potential biomarker for risk of CAC. Funding Agencies National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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