MétaCan
Menu
Back to cohort

N-myristoyltransferase 2: A novel marker for colorectal cancer screening.

2017· article· en· W2890235767 on OpenAlexaff
Jenny Rathinagopal, Shiby Kuriakose, Shiv Bhanot, Jordan Min, Nan Hu, Çharles N. Bernstein, John C. Fang, Tom Greene, Shailly Varma Shrivastav, Harminder Singh, Anuraag Shrivastav

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsCancerCare ManitobaUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsMedicineImmunohistochemistryColorectal cancerInternal medicineCancerGastroenterologyAdenomatous polypsPeripheral blood mononuclear cellOncologyPathologyColonoscopyBiology

Abstract

fetched live from OpenAlex

e15114 Background: Colorectal cancer (CRC) is the second most common cause of cancer related deaths in North America. Most CRCs arise from pre-malignant adenomatous polyps with some of these polyps developing into cancer over years providing an ideal opportunity for detection and intervention. However, the unpleasant nature of the current screening methods often leads to non-compliance. N-Myristoyltransferase (NMT) has been reported to be overexpressed in CRC tissues. In this study we show that NMT2, an isoform of NMT, is overexpressed in peripheral blood mononuclear cells (PBMC) of individuals with colorectal adenomatous polyps or cancers compared to healthy controls. Methods: PBMC’s were isolated from blood samples of CRC patients (n = 14), individuals with - non-adenomatous polyps (n = 8); adenomatous polyps (n = 18) and healthy controls (n = 24). Immunohistochemistry (IHC) was used to determine the NMT2 expression in these samples. IHC-scores were derived from assessment of both staining intensity (scale 0-3) and percentage of positive cells (0-100%), which were multiplied to generate an IHC -score between 0-300. Observers calculating the IHC scores were unaware of the polyp/CRC status. A receiver operating characteristic (ROC) analysis was performed to assess the overall performance of the NMT2 test via the area under the curve (AUC). Results: NMT2 was significantly overexpressed in PBMC of CRC patients (median IHC score- 196) compared to control subjects (median IHC score- 50). In addition, IHC scores were significantly higher for adenomatous polyps (median IHC score- 165) compared to those with non-adenomatous polyps (median IHC score- 54.8). We included non-adenomatous polyps and healthy subjects in “controls” and adenomatous polyps in “cases” along with CRC in the ROC analysis. The ROC curve of NMT2 expression displayed substantial separation between controls/non adenomatous polyps compared to CRC/adenomatous polyps [AUC = 0.913 (95% CI: 0.830-0.994)]. Conclusions: Our results show an increase in NMT2 expression in PBMC of CRC patients and individuals with adenomatous polyps suggesting that NMT2 could be used as a novel blood based biomarker for the screening and early detection of CRC. Validation studies are the next step.

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)0.001
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.095
GPT teacher head0.451
Teacher spread0.356 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicCancer, Lipids, and MetabolismFrench-language works237,207