MétaCan
Menu
Back to cohort
Record W2760872867 · doi:10.24870/cjb.2017-a56

Delineation of HIF1a mediated transcription program and the oncogenic signaling pathways in gastric tumors

2017· article· en· W2760872867 on OpenAlexvenueno aff
Dhanasekaran Rathinam, Kumaresan Ganesan

Bibliographic record

VenueCanadian Journal of Biotechnology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsHIF1ATranscription factorSignal transductionTranscription (linguistics)Cancer researchBiologyComputational biologyCell biologyGeneticsGeneAngiogenesis

Abstract

fetched live from OpenAlex

HIF1 is a transcription factor activated under hypoxic condition in many cancer types and has been implicated in cancer cell proliferation, invasion and energy metabolism. Towards understanding the role of HIF1 mediated transcription in gastric cancer, the HIF1 gene signatures established to date were analyzed for their expression across the mRNA profiles of gastric tumors. HIF1 regulated genes were identified to involve and associated with the signaling pathways and processes such as integrin signaling, Wnt, P53, EGF, FGF, VEGFA, PI3K, TGF and NFkB signaling pathways. The HIF1a genes were identified to play a significant role in energy metabolism including glycolysis, drug resistance due to epithelial to mesenchymal transition and cancer cell survival. In gastric tumors, the HIF1 regulated genes were observed to express in diffuse, poorly differentiated and stage-3 tumors. The analyses reveal i) activation of HIF1 in a sub-set of gastric tumors, ii) the pathways associated with the HIF1 activation in gastric tumors, and iii) genes involved in HIF1 mediated transcription in gastric cancer. We are further investigating the drugs that would best suit for this sub-set of tumors with activated HIF1.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.920

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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 designBench or experimental
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 venueCanadian Journal of BiotechnologySame topicCancer, Hypoxia, and MetabolismFrench-language works237,207