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Association of rapid progression on CDK4/6 inhibitor (CDKi) for metastatic HR+HER2- breast cancer (mHRBC) with genomic, proteomic, and immune microenvironment alterations.

2025· article· en· W4410802815 on OpenAlexaff
Brie Chun, Allison Creason, Shaun M. Goodyear, Laura M. Heiser, Zahi Mitri

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsBC Cancer Agency
FundersCollins Medical TrustConquer Cancer Foundation
KeywordsMedicineMetastatic breast cancerImmune systemTumor microenvironmentCancerBreast cancerCancer researchOncologyInternal medicineImmunology

Abstract

fetched live from OpenAlex

e13102 Background: First-line CDKi and endocrine therapy has improved survival for many patients (pts) with mHRBC. Yet, some pts still experience rapid disease progression within 6 months of CDKi initiation and require a tailored therapeutic approach. To understand tumor and microenvironment factors associated with rapid progression, we performed digital spatial protein profiling (DSP), RNA sequencing (RNAseq) and multiplexed immunohistochemistry (mIHC) on samples collected from pts before and after CDKi. Methods: We retrospectively identifiedpts with mHRBC treated with a CDKi with available archival samples obtained within 2.5 years of CDKi initiation and 1 year of CDKi discontinuation. FFPE slides from each sample were processed for DSP, RNAseq, and mIHC. DSP protein expression was normalized by geometric mean, with expression for each protein averaged across 3 regions-of-interest per pt. Gene set variation analysis was performed on RNA signatures. For mIHC, tumor and stromal regions were segmented, and cells were phenotyped and quantified. Means comparisons for each assay were made between groups using the t-test, and unadjusted p values are presented. This study was approved by the OHSU Institutional Review Board. Results: Samples from 25 unique pt cases were submitted for profiling (Table). On pre-CDKi samples, pts progressing ≤6 months of CDKi therapy had greater mitotic spindle (p = 0.00092), E2F (p = 0.0087) and G2M checkpoint (p = 0.0087) RNA signature expression. By comparison, in post-CDKi samples, reduced mitotic spindle signature expression (p = 0.016), but not E2F or G2M, occurred in pts treated ≤6 months. A decrease in TGF-beta signature expression (p = 0.032) was also observed. On post-CDKi samples, PI3K/AKT RNA signature expression numerically decreased in those treated ≤6 months. Although a concomitant decrease in pan-AKT protein expression was not detected in these pts, an increase in pan-AKT protein expression following CDKi (p = 0.0055) was observed in pts treated for > 6 months. Pts with ≤6 months of CDKi had greater pre-CDKi density of various immune cell subsets including CD20+ B cells, TIM3+ CD8+ T cells, Th-like and Th1 T cells. Conclusions: Pts who progress rapidly despite CDKi treatment have tumors with distinct RNA signatures and immune contexture. CDKi treatment appears to exert differential effects on the mitotic spindle, TGF-beta pathways, and PI3K/AKT pathways based on the duration of CDKi response, whether related to underlying tumor biology or an effect of drug mechanism. Efforts to integrate RNA-seq with DSP protein expression and spatial analysis of mIHC data are ongoing. Patient sample characteristics. No. patients Assay performed DSP 23 (pre-CDKi: 18, post-CDKi: 10) RNAseq 18 (pre-CDKi: 14, post-CDKi: 8) mIHC 17 (pre-CDKi: 13, post-CDKI: 8) Clinical NGS 18 PIK3CAmut 8 ESR1 mut 5 RB1 mut 4

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.424
Teacher spread0.388 · 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 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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Citations0
Published2025
Admission routes1
Has abstractyes

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