France-based biotech endogene.bio has published research suggesting that endometriosis is molecularly heterogeneous across patients, lesion sites, and cell types -- a finding that could help explain why patients often experience different outcomes with the same therapy.
The preprint, titled "Beyond one-size-fits-all: single-cell transcriptomic signatures predict drug efficacy and reveal responder subgroups in endometriosis," combines single-cell RNA sequencing with a computational drug-response framework to identify distinct cellular response patterns that may predict which therapies are most likely to work for specific patient groups.
"Endometriosis is currently classified based on symptoms and anatomical or surgical features, but these approaches don't capture the biological programs active inside the tissue."
-- Cristina Fernandez Molina, Co-founder & Head of Science at endogene.bio
What This Means for Patients
Even though it may seem like each person’s experience with this disease is different and hard to predict, endogene.bio's research reveals that there are actually common patterns at the cellular level. These patterns help explain why endometriosis acts the way it does and how lesions respond to treatment—offering new ways to better understand and personalize care for each affected patient.
This research represents a significant step toward personalized medicine for endometriosis. Rather than treating all patients with the same approach, understanding the molecular diversity of the disease could lead to:
- Better treatment matching: Identifying which patients are most likely to respond to specific therapies
- Reduced trial and error: Avoiding ineffective treatments that delay relief
- New drug development: Targeting specific cellular subtypes that drive disease in different patients
Looking Ahead
While this is still early-stage research (preprint), it adds to the growing body of evidence that endometriosis is far more complex than previously understood. As single-cell technologies become more accessible, we may see a future where treatment decisions are guided by molecular profiling of individual patients.
Stay tuned for updates as this research progresses through peer review and further validation.