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Record W2031665600 · doi:10.2174/13816128113199990597

Regulation of MET Receptor Signaling by SOCS1 and its Implications for Hepatocellular Carcinoma

2014· review· en· W2031665600 on OpenAlexaff
Yirui Gui, Mehdi Yeganeh, Yuneivy Cepero-Donates, Sheela Ramanathan, Caroline Saucier, Subburaj Ilangumaran

Bibliographic record

VenueCurrent Pharmaceutical Design · 2014
Typereview
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSuppressor of cytokine signaling 1Cancer researchSuppressor of cytokine signallingSignal transductionSOCS3BiologySOCS6Receptor tyrosine kinaseSOCS5CytokineEpigeneticsHepatocellular carcinomaCell biologyCancerImmunologySuppressorSTAT3GeneticsGene

Abstract

fetched live from OpenAlex

The SOCS1 gene is a frequent target of epigenetic repression in hepatocellular carcinoma. Many other types of cancer also harbor methylated SOCS1 gene. Besides, recent studies implicate microRNAs targeting SOCS1 in cancer progression. These findings suggest a broad tumor suppressor role of SOCS1 and have stimulated the quest to elucidate the underlying molecular mechanisms. The essential physiological function of SOCS1 is to attenuate interferon gamma signaling in immune cells. SOCS1 binds activated JAK kinases and the receptor chains of several cytokines, some of which are implicated in cancer progression. SOCS1 also facilitates ubiquitination and proteasomal degradation of many signaling molecules downstream of cytokine and growth factor receptors. We have shown that SOCS1 inhibits signaling via the hepatocyte growth factor receptor c-MET in hepatocytes. Aberrant MET signaling, implicated in the progression of many types of cancers, also contributes to the development of chemoresistance to tyrosine kinase inhibitors and drugs targeting other oncogenic signaling pathways. Here, we discuss the SOCS1-dependent regulation of MET signaling as an important mechanism underlying the tumor suppressor role of SOCS1 that is relevant not only to hepatocellular carcinoma but also to other types of cancers.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.285
GPT teacher head0.453
Teacher spread0.167 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2014
Admission routes1
Has abstractyes

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