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Record W2994126611 · doi:10.14740/gr1145

Glucose Metabolic Reprogramming and Cell Proliferation Arrest in Colorectal Micropapillary Carcinoma

2019· article· en· W2994126611 on OpenAlexvenueno aff
Monika Vyas, Natalie Patel, Romulo Celli, Narendra Wajapeyee, Dhanpat Jain, Xuchen Zhang

Bibliographic record

VenueGastroenterology Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Cancer Institute
KeywordsMedicineReprogrammingCancer researchCell growthColorectal cancerCell biologyInternal medicineCellBiologyCancerBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Micropapillary carcinoma (MPC) has been reported as an aggressive variant of colorectal carcinoma (CRC) associated with frequent lymphovascular invasion and poor outcome. Altered glycogen metabolism by metabolic reprogramming plays a critical role for cancer cell growth and survival. We aimed to investigate glucose metabolic reprogramming in colorectal MPC. METHODS: Immmunostains for Ki-67 and glucose transporter 1 (GLUT1) were performed on 10 colorectal MPCs. Real-time PCR analysis of expressions of GLUT1 and glycogen metabolizing enzymes: glycogen synthase (GYS1) and glycogen phosphorylase (PYGL) was performed on cultured monolayer and three-dimensional (3D) spheroid HCT116 colon cancer cells. RESULTS: GLUT1 was strongly expressed in MPC as compared to adjacent conventional glandular component, and was also significantly increased expression in 3D spheroids. Upregulation of GYS1 and PYGL was markedly increased in 3D spheroids. The proliferation rate (Ki-67) of MPC was significantly lower compared to conventional glandular component. The 3D spheroids showed increased cell cycle arrest. Our results demonstrate altered glycogen metabolism in colorectal MPC. CONCLUSION: The reprogramming of glycogen metabolism in MPC provides a source of energy contributing to tumor cell survival in a low proliferation state. Targeting glucose-regulated metabolism may warrant consideration as possible MPC therapies.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.613

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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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