Real-world Clinical Multi-omics Analyses Reveal Bifurcation of ER-independent and ER-dependent Drug Resistance to CDK4/6 Inhibitors

Overview

Journal Nat Commun

Date 2025 Jan 22

PMID 39843429

Authors

Zhengyan Kan

Ji Wen

Vinicius Bonato

Jennifer Webster

Wenjing Yang

Vladimir Ivanov

Kimberly Hyunjung Kim

Whijae Roh

Chaoting Liu

Xinmeng Jasmine Mu

Jennifer Lapira-Miller

Jon Oyer

Todd VanArsdale

Paul A Rejto

Jadwiga Bienkowska

Affiliations

Soon will be listed here.

Abstract

To better understand drug resistance mechanisms to CDK4/6 inhibitors and inform precision medicine, we analyze real-world multi-omics data from 400 HR+/HER2- metastatic breast cancer patients treated with CDK4/6 inhibitors plus endocrine therapies, including 200 pre-treatment and 227 post-progression samples. The prevalences of ESR1 and RB1 alterations significantly increase in post-progression samples. Integrative clustering analysis identifies three subgroups harboring different resistance mechanisms: ER driven, ER co-driven and ER independent. The ER independent subgroup, growing from 5% pre-treatment to 21% post-progression, is characterized by down-regulated estrogen signaling and enrichment of resistance markers including TP53 mutations, CCNE1 over-expression and Her2/Basal subtypes. Trajectory inference analyses identify a pseudotime variable strongly correlated with ER independence and disease progression; and revealed bifurcated evolutionary trajectories for ER-independent vs. ER-dependent drug resistance mechanisms. Machine learning models predict therapeutic dependency on ESR1 and CDK4 among ER-dependent tumors and CDK2 dependency among ER-independent tumors, confirmed by experimental validation.

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