Gut microbiome characteristics in patients with hormone receptor–positive (HR+) HER2− breast cancer treated with adjuvant abemaciclib: Biomarker analysis of the TRADE trial.

I Ilana Schlam (Dana‐Farber Cancer Institute Harvard Medical School Boston Massachusetts USA) E Emily Anne Green (Department of Biostatistics, Microbiome Analysis Core, Harvard T.H. Chan School of Public Health, Boston, MA) X Xochitl Morgan (Department of Biostatistics, Microbiome Analysis Core, Harvard T.H. Chan School of Public Health, Boston, MA) J Joanna Baginska (Dana-Farber Cancer Institute, Boston, MA) A Ashka Patel S Se Eun Kim H Hillary Heiling (Dana-Farber Cancer Institute, Boston, MA) E Erin Wallace (Dana-Farber Cancer Institute, Boston, MA) E Esther Pasternak (Dana-Farber Cancer Institute, Boston, MA) N Nabihah Tayob S Sara M. Tolaney (Department of Medical Oncology, Dana-Farber Cancer Institute) E Erica L. Mayer

Abstract

563 Background: Adjuvant abemaciclib reduces recurrence risk and improves overall survival in patients with high-risk node-positive early HR+/HER2- breast cancer. However, treatment-emergent diarrhea may lead to dose modifications, treatment discontinuation, and impaired quality of life. The gut microbiome influences treatment response and toxicity across multiple cancer therapies; its role in abemaciclib-associated diarrhea remains undefined. We evaluated features of the gut microbiome during the initiation of adjuvant abemaciclib and any association with diarrhea. Methods: 90 patients with HR+/HER2− early breast cancer enrolled in the TRADE trial (NCT06001762) and were treated with dose-escalated adjuvant abemaciclib (50 mg BID x 14 days, then 100 mg BID x 14 days, then 150 mg BID onwards) plus endocrine therapy. Stool samples were collected at baseline, cycle 2 day 1 (C2D1), and end of treatment (EOT). Whole-genome shotgun metagenomic sequencing was performed, and species-level profiles were generated using MetaPhlAn4. Diarrhea was analyzed as a binary outcome (ever vs none). Associations between microbiome features and clinical variables were evaluated using linear mixed modeling with a random effect for repeated samples from the same individual (alpha diversity) or per-timepoint using PERMANOVA (beta diversity) and MaAsLin3 (species and genes, with false discovery rate correction). Models were adjusted for age, cancer stage, and type of endocrine therapy. Results: A total of 142 samples were analyzed (77 baseline, 58 C2D1, and 7 EOT; 77 total subjects, 28 with diarrhea, 49 without). Treatment was associated with a consistent microbiome shift from baseline to C2D1, characterized by a decline in alpha diversity (-0.26, 95% CI -0.39 to -0.14, p < 0.001) and a phylum-level shift with increased Bacteroidota and decreased Firmicutes abundance (p < 0.002 and p = 0.001, respectively, paired T-test). When assessing by timepoint, having any-grade diarrhea was not associated with differences in beta diversity or alpha diversity, nor with individual microbial species; pathway-level enrichment suggested diarrhea-associated functional trends that did not meet FDR significance. Limited EOT samples suggested partial recovery following treatment. Conclusions: Adjuvant abemaciclib induced consistent, treatment-related shifts in gut microbiome composition, characterized by reduced diversity and a phylum-level shift from Firmicutes to Bacteroidota, suggesting an early broad ecological treatment effect from exposure to a CDK4/6 inhibitor. This pattern has been reported in patients with inflammatory bowel disease. A species-specific diarrhea signature or predictive relationship between microbiome signature and the development of diarrhea was not observed. Further evaluation of the microbiome's evolution at EOT is ongoing. Clinical trial information: NCT06001762 .

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 563-563
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (12)

I

Ilana Schlam

Dana‐Farber Cancer Institute Harvard Medical School Boston Massachusetts USA

E

Emily Anne Green

Department of Biostatistics, Microbiome Analysis Core, Harvard T.H. Chan School of Public Health, Boston, MA

X

Xochitl Morgan

Department of Biostatistics, Microbiome Analysis Core, Harvard T.H. Chan School of Public Health, Boston, MA

J

Joanna Baginska

Dana-Farber Cancer Institute, Boston, MA

A

Ashka Patel

S

Se Eun Kim

H

Hillary Heiling

Dana-Farber Cancer Institute, Boston, MA

E

Erin Wallace

Dana-Farber Cancer Institute, Boston, MA

E

Esther Pasternak

Dana-Farber Cancer Institute, Boston, MA

N

Nabihah Tayob

S

Sara M. Tolaney

Department of Medical Oncology, Dana-Farber Cancer Institute

E

Erica L. Mayer