Waltham, Mass. — BostonGene has expanded its scientific collaboration with Dana-Farber Cancer Institute to study the biological mechanisms underlying BRCA1- and BRCA2-associated breast cancers using multimodal artificial intelligence and genomic analysis.
The collaboration will apply BostonGene’s tumor and immune biology platform to analyze individual tumors in a broader biological context, with the goal of identifying mechanisms that distinguish disease subtypes and may influence treatment response and resistance.
The research will focus on BRCA1/2-associated estrogen receptor-positive breast cancer, TP53-mutant estrogen receptor-positive breast cancer and triple-negative breast cancer.
Researchers aim to better understand why cancers with similar biological characteristics can behave differently and how those differences may inform biomarker development, patient selection and therapeutic strategies.
“Patients with hereditary BRCA1 and BRCA2 mutations face unique biological challenges, particularly across distinct disease presentations like ER+ breast cancer and TNBC,” said Filipa Lynce, M.D., Senior Physician at Dana-Farber Cancer Institute. “By combining detailed genomic and transcriptomic profiling with advanced analytics, this collaboration allows us to uncover critical molecular signatures underlying hereditary breast cancer to pave the way for more tailored, effective therapeutic strategies.”
The collaboration will also examine interactions between DNA damage response pathways and hormone signaling, which researchers said could help clarify biological differences among breast cancer subtypes.
“Unraveling the crosstalk between DNA repair deficiencies and hormone signaling is fundamental to advancing precision oncology,” said Nathan Fowler, M.D., Chief Medical Officer at BostonGene. “The opportunity is to move beyond describing these tumors by mutation or clinical subtype and understand the biology that actually differentiates them. By placing each patient into a much broader biological context, we can identify mechanisms that may explain disease behavior and ultimately translate those findings into better biomarker, patient-selection and therapeutic strategies.”
BostonGene said the project is intended to demonstrate how AI-based multimodal analysis of deeply characterized patient cohorts can generate insights for drug development, patient selection and future clinical strategies.
