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Abstract P4-09-12: Baseline and End-of-Treatment Biomarkers in Patients With PIK3CA-Mutated, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer From BYLieve Study Cohorts A and B

2023· article· en· W4322774598 on OpenAlexaff
Dejan Juric, Nicholas C. Turner, Sherene Loi, Fabrice André, Stephen Chia, Komal Jhaveri, Patrick Neven, Rebecca Dent, Eva Ciruelos, Mukta Joshi, Estelle Roux, Heather Patino, Murat Akdere, Hope Rugo

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineFulvestrantInternal medicineOncologyLetrozoleBiomarkerCancerBreast cancerAromatase inhibitorCohortHazard ratioCancer researchEstrogen receptorBiologyConfidence intervalAromataseGenetics

Abstract

fetched live from OpenAlex

Abstract Introduction: Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) is mutated in ~40% of patients (pts) with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2−) advanced breast cancer (ABC). PIK3CA mutations are associated with resistance to endocrine therapy (ET) and worse overall survival. Alpelisib (ALP), an α-selective PI3K inhibitor and degrader, is indicated in combination with fulvestrant (FUL) for pts with PIK3CA-mutated (mut) HR+, HER2− ABC following progression on/after ET-based treatments. In the Phase 2, open-label, 3-cohort, noncomparative BYLieve study, clinical benefit of ALP in combination with ET was observed in the post-cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) setting in pts with PIK3CA-mut, HR+, HER2− ABC. Here we report the results of a biomarker analysis using paired baseline (Cycle 1 Day 1) and end-of-treatment (EOT) circulating tumor DNA (ctDNA) samples from pts in BYLieve Cohorts A and B. Methods: In the BYLieve study, pts with PIK3CA-mut, HR+, HER2− ABC had CDK4/6i + aromatase inhibitor (Cohort A; N=127) or CDK4/6i + FUL (Cohort B; N=126) as treatment immediately prior to receiving ALP + FUL and ALP + letrozole, respectively. In this biomarker analysis, gene alterations were detected in ctDNA at baseline and EOT using next-generation sequencing (PanCancer V2 panel). Pts included in this interim analysis had confirmed PIK3CA mutations and matched baseline/EOT samples with enough sequencing coverage and ctDNA fraction to detect mutations at both time points. ctDNA fractions, tumor mutation burden (TMB) distributions, genomic landscapes, gain/loss of PIK3CA and estrogen receptor 1 (ESR1), chromosome 8/11 amplification profiles, and alterations in PI3K pathway and potential CDK4/6i resistance markers were assessed across time points. Sample sizes were small; results should thus be interpreted with caution. Results: Forty-three pts were included in the Cohort A biomarker population and 40 pts were included in Cohort B. ctDNA fraction was numerically higher at EOT compared with baseline in both cohorts; further analyses will be presented. In Cohort A, no significant differences were observed in TMB at EOT compared with baseline (P=0.21). In Cohort B, TMB was higher at EOT compared with baseline (P=0.053). Chromosome 8/11 amplifications were consistent between baseline and EOT for both cohorts. Small variations were observed in ESR1/PIK3CA mutations between baseline and EOT on both cohorts (Table). The status of potential CDK4/6i resistance markers was relatively unchanged at EOT (Table). Loss-of-function mutations in PTEN, a known PI3K inhibitor resistance marker, increased from 9% at baseline to 14% at EOT in Cohort A and from 12% at baseline to 22% at EOT in Cohort B. Conclusions: Between baseline and EOT, only small variations in gene alterations in PIK3CA-mutated HR+, HER2– ABC were observed in the post-CDK4/6i setting. As the disease progressed, increases in loss-of-function mutations in PTEN at EOT in both Cohorts A and B suggested loss of PTEN in PI3K pathway may drive resistance to ALP. Early intervention with ALP, when the tumor is particularly driven by PIK3CA oncogenic mutations and before it develops more genomic complexity, may potentially provide better clinical outcomes. Table. Gene Alteration Gain/Loss at Baseline/EOT Across Cohorts A and B Citation Format: Dejan Juric, Nicholas Turner, Sherene Loi, Fabrice Andre, Stephen K. Chia, Komal Jhaveri, Patrick Neven, Rebecca Dent, Eva Ciruelos, Mukta Joshi, Estelle Roux, Heather Patino, Murat Akdere, Hope Rugo. Baseline and End-of-Treatment Biomarkers in Patients With PIK3CA-Mutated, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer From BYLieve Study Cohorts A and B [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-09-12.

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 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 score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.361
Teacher spread0.326 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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