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Record W7132871786

Development of CDK4/6 Inhibitor Resistant ER-positive HER2-negative Breast Cancer Cell Lines to Elucidate Novel Mechanisms of Resistance

2023· dissertation· W7132871786 on OpenAlexaff
Lauren Elizabeth Bathurst

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsUniversity of Toronto
FundersGeorge Mason University
KeywordsPalbociclibAcquired resistanceDownregulation and upregulationBreast cancerCell cultureDiseaseCancerCell cycle
DOInot available

Abstract

fetched live from OpenAlex

Treatment with CDK4/6 inhibitors (CDK4/6i) in combination with hormone therapy is now the standard of care for patients with advanced or metastatic ER-positive/HER2-negative (ER+/HER2-) breast cancer. However, many patients experience disease progression due to intrinsic or acquired resistance. Predictive biomarkers to identify patients most likely to respond to initial therapy as well as therapeutic targets to overcome or delay onset of resistance, are needed to improve patient outcomes. To achieve these outcomes will require a better understanding of the molecular mechanisms responsible for CDK4/6i sensitivity and resistance. In this study, I established in-vitro models of acquired resistance to two CDK4/6i, palbociclib and abemaciclib, using MCF7 and T47D cell lines. Genomic, transcriptomic, and proteomic analyses were performed in parental cells and resistant derivatives. Strikingly, acquired resistance across all models was associated with an upregulated interferon (IFN) response as well as loss of ER/PR expression and signaling. Importantly, expression of an IFN-based gene signature (IFN-sig) derived from these models was also upregulated in early-stage breast tumours intrinsically resistant to CDK4/6i as well as to endocrine therapy, and thus warrants further clinical evaluation as a novel predictive biomarker. While additional signaling pathways altered in resistant cell lines included cyclin D-CDK4/6-RB, EGFR/HER, and AKT/mTORC1, therapeutic targeting of these pathways could not re-sensitize all models to CDK4/6 inhibition. However, EGFR/HER or AKT/mTOR inhibitors in combination with CDK4/6i synergistically reduced cell viability in parental cell lines, representing potential treatment strategies to delay onset of resistance. In summary, I have developed and characterized CDK4/6i resistant ER+/HER2- breast cancer cell lines and demonstrated that mechanisms of resistance are diverse. Importantly, I have identified the IFN-sig as a potential novel predictive biomarker of CDK4/6i response, and potential treatment strategies to overcome or prevent the development of resistance, for further evaluation.

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 categoriesMeta-epidemiology (narrow)
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 score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.332
Teacher spread0.313 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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