MicroRNA spatial profiling for assessing drug efficacy in BRCA1 -related triple-negative breast tumors

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Authors: Omar N. Mohd, Lin Wang, Barbara Sardella, David Jou, Gerburg M. Wulf, Frank John Slack, Yujing Jan Heng, Patrick S. Doyle
Cited by: 0
References: 42

Abstract

Abstract BRCA1/2 -mutated breast cancers exhibit homologous recombination deficiency (HRD) and are initially sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors, but 40-70% of patients develop resistance, creating a need for predictive biomarkers that capture treatment-associated spatial heterogeneity. Using the K14-Cre Brca1 f/f Trp53 f/f model with tumors that acquired PARP inhibitor resistance, we evaluated PARP inhibitor combinations with either PI3K inhibition or Poly(I:C) in vivo . To determine how treatment altered tumor spatial microRNA (miRNA) profiles, we applied our hydrogel-based, nanoliter well array in situ miRNA assay to quantify and spatially profile miRNAs on FFPE sections from tumors treated for 10 days and developed spatial miRNA analysis frameworks integrating latent Dirichlet allocation (LDA) and principal component analysis (PCA). We also incorporated immune architecture using Structural Similarity Index Measure (SSIM) maps to assess co-localization of immune infiltration and miRNA topics. Both combinations improved antitumor activity compared to PARP inhibition alone. The resulting spatial miRNA topics stratified early tumors according to subsequent PARP inhibitor sensitivity or resistance and distinguished their treatment regimens, while SSIM analysis revealed co-localization of immune infiltration and miRNA topics. This integrative spatial miRNA assay and analysis identified a let-7a-dominant topic associated with PARP inhibitor resistance, indicating that spatial miRNA profiling may inform therapeutic stratification in BRCA1/2 -related breast cancers.

Fields of Study & Subjects

PARP inhibition in cancer therapy Breast Cancer Treatment Studies MicroRNA in disease regulation

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
12 January 2026
Language
EN
Document type
Preprint