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Record W1989502045 · doi:10.4137/cmt.s3783

Lapatinib, a Dual-Targeted Small Molecule Inhibitor of EGFR and HER2, in HER2-Amplified Breast Cancer: From Bench to Bedside

2011· article· en· W1989502045 on OpenAlexfundno aff
Roger Y. Tsang, Saeed Sadeghi, Richard S. Finn

Bibliographic record

VenueClinical Medicine Insights Therapeutics · 2011
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsnot available
FundersTerry Fox Foundation
KeywordsLapatinibTrastuzumabBreast cancerCancer researchMedicineTyrosine kinaseTyrosine-kinase inhibitorEpidermal growth factor receptorMetastatic breast cancerCancerTargeted therapyPertuzumabLetrozoleOncologyInternal medicineReceptorTamoxifen

Abstract

fetched live from OpenAlex

The HER-2/neu gene product is a 185 kDa Type I receptor tyrosine kinase which consists of an extracellular domain, transmembrane domain, kinase domain, and cytoplasmic tail. The initial discovery that amplification and subsequent overexpression of the HER-2/neu oncogene plays a pivotal role in the pathogenesis of 20%–25% of breast cancers has since led to significant clinical advances in the management of this subtype of breast cancer. The first approved HER2-targeted therapy, trastuzumab, is a humanized monoclonal antibody against the extracellular domain of HER2 and has demonstrated survival benefits in both the metastatic and adjuvant settings. Lapatinib, a small molecule tyrosine kinase inhibitor of both the epidermal growth factor receptor (EGFR) and HER2 is now also approved for advanced HER2-amplified breast cancer and is currently being evaluated in the adjuvant setting. Importantly, lapatinib has been shown to have activity in women with HER2-amplified breast cancer that is refractory to trastuzumab. In addition, it has been shown to extend survival in the front-line setting in combination with letrozole for estrogen receptor (ER) positive, HER2-positive breast cancer. Here we will review the biologic rationale and pre-clinical data that drove its initial clinical development as well as current clinical data and ongoing studies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.188
GPT teacher head0.421
Teacher spread0.232 · 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 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

Citations35
Published2011
Admission routes1
Has abstractyes

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