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Targeting the Hedgehog Pathway for Locally Advanced and Metastatic Basal Cell Carcinoma

2017· review· en· W2588244614 on OpenAlexaff
Bita Esmaeli, Vivian T. Yin

Bibliographic record

VenueCurrent Pharmaceutical Design · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVismodegibHedgehog signaling pathwayBasal cell carcinomaMedicineSmoothenedHedgehogPTCH1Cancer researchInternal medicineOncologyBioinformaticsSurgeryBasal cellBiologySignal transduction

Abstract

fetched live from OpenAlex

Basal cell caricnoma (BCC), the most common periocular magliancy, is treated with complete surgical excision. However, in patients not amenable to surgery or when surgical resection means loss of vital organs or disfiguring procedures due to locally advanced or metastatic disease, targeting the hedgehog pathway offers a novel treatment approach for such patients. Mutation in PTCH1 and SMO has been identified in patients with basal cell nevoid syndrome as well as in patients with sporadic BCC. Inhibition of SMO by vismodegib or sonidegib, the two sonic hedgehog inhibitor drugs approved by the Food and Drug Administration in the United States, has shown overall response rate for locally advanced and metastatic BCC around 50%. The most common side effects were muscle cramps, weight loss, fatigue, and lost appetite. Resistance to vismodegib has been attributed to mutation in SMO or activation of RAS/MAPK pathway. New research into dual inhibition aims to overcome this resistance and provide more lasting response.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.265
GPT teacher head0.440
Teacher spread0.175 · 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 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

Citations25
Published2017
Admission routes1
Has abstractyes

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