High-grade serous ovarian cancer (HGSC) is the most common and deadliest form of ovarian cancer. Most patients are diagnosed at an advanced stage, when surgery and chemotherapy have limited long-term impact. Under the current standard of care, the five-year survival rate is less than 35%. Immunotherapies, such as immune checkpoint inhibitors (ICIs), have transformed outcomes in several other cancers, yet HGSC patients rarely benefit, with response rates between 8-28%. Existing companion diagnostics are designed for cancers where genomic instability predicts immune responsiveness. However, in HGSC these markers have shown little to no ability to predict responsiveness leaving clinicians without a reliable tool to identify patients who may benefit from immunotherapy.

STRATsig ST-3 is a novel gene expression–based biomarker that identifies high-grade serous ovarian cancer (HGSC) patients most likely to benefit from immune checkpoint inhibitor therapy by measuring the tumor’s functional immune state. Validated across three independent patient cohorts, the signature predicts an immune-responsive tumor microenvironment associated with longer overall survival and can identify approximately one-third of HGSC patients who may respond to immunotherapy.  As such, STRATsig ST-3 helps address a critical gap in patient stratification where existing companion diagnostics have shown limited predictive value in HGSC. 

The university is seeking licensing partners and research sponsors to support the continued development and validation of STRATsig ST-3. Interested companies and organizations are encouraged to engage with the university to discuss licensing opportunities, sponsored research agreements, and strategic development partnerships.

Technology Overview

Current Challenges

While diagnostic tools exist to predict immune responsiveness based on genomic instability exist for several types of cancer, these markers have been largely unsuccessful in predicting responsiveness in HGSC. As such, clinicians lack reliable tools to identify which patients are most likely to benefit from immunotherapy. This often leads to treatment exposure without clear clinical gain, adding unnecessary toxicity, cost, and time delays for patients. These limitations highlight a critical unmet need in HGSC to guide effective treatment decisions.

Our Innovation

This invention, STRATsig S-T3, is a gene-expression-based biomarker designed specifically for HGSC to identify patients most likely to benefit from ICIs. Unlike current companion diagnostics that rely on genomic instability markers, STRATsig S-T3 directly measures the functional immune state of the tumor. The signature reflects a coordinated pattern of gene activity associated with reduced immunosuppression, enhanced antigen presentation, and lower T-cell dysfunction to predict an immune-responsive tumor microenvironment. 

The technology works by analyzing tumor gene expression data and applying a stratification algorithm that groups tumors based on immune-related gene activity. This approach was validated across three independent HGSC patient cohorts, where the STRATsig S-T3 group demonstrated significantly longer overall survival. Importantly, its performance was consistent regardless of age, stage, or debulking status. It identifies approximately one-third of HGSC patients who may benefit from immunotherapy.

By focusing on immune biology, STRATsig S-T3 overcomes limitations of existing companion diagnostics and provides the first HGSC-specific tool capable of stratifying patients who may be responsive to ICIs.

Benefits of this Technology

  • First biomarker designed for HGSC and measures immune biology directly
  • Isolates a subgroup (roughly 1/3 of all patients) who are most likely to respond to ICI therapy
  • Consistently validated across large, independent cohorts
  • Works with standard tumor samples, allowing it to be easily integrated

Stage of Development

STRATsig ST-3 and its algorithm have been completed and published in a peer-reviewed journal (J Trans Med). This signature was validated across multiple HGSC retrospective cohorts (3 cohorts, n=647), and the molecular profile mapped to reduced immunosuppression, enhanced antigen presentation, and lower T-cell dysfunction.