Genprex has collaborated with Roche Diagnostics to validate biomarkers used for patient selection in clinical trials for non-small cell lung cancer (NSCLC).
The agreement centres on the potential use of TROP2 as a biomarker.
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Previous preclinical and clinical studies have indicated that NSCLC patients with high TROP2 H-scores and low PTEN H-scores may show better responses and experience longer progression-free survival (PFS).
Under the arrangement, Roche Diagnostics will validate the assay using its TROP2 antibody, which has been used previously in other company-sponsored studies.
The validation studies are expected to be completed by the end of this year. Following a review of the results, the approach is intended to be integrated into the NSCLC clinical programme.
Roche Diagnostics has previously received a breakthrough device designation from the US Food and Drug Administration (FDA) for an AI-driven companion diagnostic for NSCLC, which uses TROP2 scoring to evaluate specimens.
Genprex will employ the same validated antibody in its own studies to ensure methodological consistency.
Genprex president and CEO Ryan Confer said: “This strategic partnership with Roche Diagnostics, a recognised leader in NSCLC assay development and the recipient of an FDA breakthrough device designation for their AI-driven TROP2 diagnostic, is a testament to our shared commitment to advancing precision treatments in oncology.
“By utilising the same validated TROP2 antibody that Roche has used in other studies, we are poised to shorten the time for patient identification and recruitment for NSCLC clinical trials, ultimately delivering more effective, personalised treatment options.”
Genprex’s lead oncology product, Reqorsa Gene Therapy (quaratusugene ozeplasmid), is being studied for NSCLC and small cell lung cancer.
The company’s clinical focus includes gene therapies for cancer and diabetes, delivered using a non-viral, lipid-based delivery system.
In March 2025, Roche Diagnostics collaborated with the University of Liverpool to launch the Eye Cancer Artificial Intelligence Digital Bioresource (EYE-CAN-AID), a multi-modal image database designed to support earlier detection of rare eye cancers.
