By Clinical Research News Staff 

October 7, 2025 | Recurrent ovarian cancer treatment has always had dismal responses because differences between cancer patients are not fully understood, according to Denarda Dangaj Laniti, Ph.D., who heads the Tumor Microenvironment and Biomarker Discovery lab at the Department of Oncology of the Lausanne University Hospital and the Lausanne, Switzerland branch of the Ludwig Institute for Cancer Research. To tackle this challenge, she and her team conducted a large-scale clinical research study to provide insight into how immune and genomic signatures may finally guide more effective care. 

The multinational team has developed an immune classification system that sorts ovarian tumors into four categories—purely inflamed, mixed-inflamed, excluded, and desert—based on T-cell infiltration patterns. This framework, built from the analysis of 697 ovarian cancer samples from 595 patients in five independent clinical cohorts, could become a clinical tool for identifying which women are most likely to respond to immunotherapy and combination treatments. 

The results found that patients with inflamed or mixed-inflamed tumors tended to survive longer following chemotherapy compared to those with excluded or desert tumors. Tumors with BRCA1 mutations, which disrupt DNA repair mechanisms, were particularly notable for sustaining an inflamed immune profile even at recurrence. This association between genomic instability and immune activity offers a potential biomarker for guiding therapy. 

In preclinical studies, researchers tested treatment strategies tailored to these immune subtypes. Mice bearing BRCA1-mutated tumors responded well to a cocktail of standard chemotherapy, a PARP inhibitor, and a COX inhibitor, which together prolonged survival. Adding checkpoint blockade immunotherapy doubled survival time by reactivating CD8+ T cells, the body’s cancer-fighting lymphocytes.  

The paradox of ovarian cancer has long been its “hot” immune profile—immune cells visibly infiltrate tumors—yet inconsistent responses to immunotherapy. By mapping not just T cells but also supporting immune networks like dendritic cells and macrophages, the new research clarifies why some tumors resist, as well as points to strategies to overcome that resistance. 

For clinicians, the next step will be validation in prospective studies. If confirmed, the immune-genomic classifier could serve as a biomarker to stratify patients at the outset of recurrence, sparing some from ineffective treatments and directing others to promising drug combinations. Currently, Dangaj Laniti and her colleagues hope to implement a biomarker-driven approach for clinical practice. To achieve this, it will require collaborations with clinical translation partnerships with cancer centers and aid from industry collaborators for designing prospective studies.  

To read the full story written by Deborah Borfitz, visit Diagnostic World News.