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Record W2109519833 · doi:10.1158/1538-7445.am2014-554

Abstract 554: GPNMB methylation: a new marker of potentially colonic adenoma in African Americans

2014· article· en· W2109519833 on OpenAlexaff
Hamed Rahi, Tahmineh Haidary, Hassan Brim, Edward L. Lee, Babak Shokrani, Peter M. Siegel, Hassan Ashktorab

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsMethylationEpigeneticsDNA methylationColorectal cancerCpG siteCancer researchMalignant transformationColorectal adenomaAdenomaImmunohistochemistryBiologyMicrosatellite instabilityCancerPathologyMolecular biologyMedicineInternal medicineGene expressionGeneGeneticsAllele

Abstract

fetched live from OpenAlex

Abstract Background: Colorectal cancer (CRC) arises from epigenetic and genetic alterations in a stepwise histological progression sequence. Aim: We examined the role of glycoprotein non-metastatic melanoma protein B (GPNMB) gene in normal, adenoma and CRC in African American (AA) patients to elucidate epigenetic drivers of colon oncogenic transformation. Patients and Methods: Methylation status of 13 CpG sites (chr7: 23287345-23287426) in GPNMB gene's promoter, selected from IHM27 array methylation profiling, was analyzed by pyrosequencing in human CRC cell lines (HCT116, SW480, and HT29) as well as paraffin embedded samples with normal (n=20), non-advanced adenoma (NA; n=20), advanced adenoma (AD; n=48), and cancer tissue (n=20). Furthermore, GPNMB expression was analyzed by immunohistochemistry (IHC). Tumor suppressor functions of GPNMB were examined by cell proliferation, migration and invasion assays in HCT116 colon cell line that was stably transfected with a GPNMB cDNA expression vector. In addition, correlations between the methylation status of GPNMB and various clinicopathological features (age, location and sex) were analyzed. Results: GPNMB methylation was lower in normal mucosa compared to CRC samples (4/20 [20%] vs. 19/20 [95%]; P<0.001). AD also had a significantly higher GPNMB methylation frequency than normal colon samples (45/48 [94%] vs 4/20 [20%]; P<0.001). GPNMB was more frequently methylated in AD than in matched normal mucosa from three patients (3/3 [100%] vs 1/3 [33.3%]; P<0.001). Finally, the frequency of GPNMB methylation in NA differs significantly from that in the normal mucosa (16/21 [76%] vs 4/20 [20%]; P0.5). Gender, location, and age were independent of GPNMB methylation. However, there was statistically significant correlation of higher methylation at advanced stages and lower methylation at stage 1 CRCs (P<0.05). In agreement with these findings, GPNMB protein expression decreased in CRC tissues compared with AD and NA colon mucosa, p<.05. GPNMB expression silencing through promoter methylation was evident in AD and CRC. GPNMB overexpression in HCT116 colon cancer cell line decreased cell proliferation [(24h, P=0.026), (48h, P<0.001), and (72h, P=0.007)], invasion (p<.05) and migration compared to the mock-transfected cells (p>.05). Conclusion: Our data indicate a high methylation profile leading to a lower GPNMB expression in adenoma and CRC samples. As such, GPNMB might be useful as a biomarker of adenomas with high carcinogenic potential in African Americans. Citation Format: Hamed Rahi, Tahmineh Haidary, Hassan Brim, Edward L. Lee, Babak Shokrani, H Zhifeng, Peter M. Siegel, Hassan Ashktorab. GPNMB methylation: a new marker of potentially colonic adenoma in African Americans. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 554. doi:10.1158/1538-7445.AM2014-554

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)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.418
Teacher spread0.366 · 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
Published2014
Admission routes1
Has abstractyes

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