Newly discovered blood signature presented at ESMO 2020. 

LAUSANNE, SWITZERLAND  – Novigenix SA, a pioneer in Immuno-Transcriptomics for precision oncology, today announced a new Immuno-Transcriptomic signature for predicting response to immunotherapy in metastatic urothelial cancer patients. The data are presented at the European Society for Medical Oncology (ESMO) Immuno-Oncology Congress (17-21september 2020 at Virtual congress).

Immune checkpoint inhibitors (ICIs) have become one of the main treatments for patients with metastatic urothelial cancer (UC). With only a minority of patients (20%) showing benefit from ICIs, there is a significant unmet medical need for accurate liquid biopsy solutions for patient stratification.

In the study, whole blood Immuno-Transcriptome profiles were generated by RNA sequencing from 31 patients with metastatic UC patients that were treated with anti-PD-1. Samples were collected before and after 2-6 weeks of anti-PD-1 therapy. Clinical benefit was defined as Progression-Free Survival (PFS) ≥ 6 months.

In the training cohort, a final panel of 105 genes predicted clinical benefit from anti-PD-1 therapy with an area under the curve (AUC) of 0.95 (sensitivity 90%, specificity 69%).

“The performance data of the newly discovered immune-transcriptomic signature for predicting response to immunotherapy in metastatic urothelial cancer are very encouraging,” said Dr. Niven Mehra from Department of Medical Oncology at Radboud University, Netherland.  “A prospective study has been launched to validate the test in a new cohort”.

“Whole blood ImmunoTranscriptomics is a powerful liquid biopsy tool for the early detection of cancer, and for therapy optimization. We look forward to providing new precision oncology solutions to support UC patients that benefit from ICIs, and to provide oncologists new insights into therapy response to anti-PD-1”, said Dr. Brian Hashemi, Executive Chairman of Novigenix. 

About LITOseek

Novigenix’s Blood Immuno-Transcriptomic sequence platform, LITOseek, analyzes the gene expression modifications (mRNA signatures) induced by the host response to various triggers, such as the onset of cancer. Disease specific algorithms are developed through application of Artificial Intelligence on patient mRNA signatures in combination with clinical and medical parameters. The LITOseek platform has been designed and optimized for development of precision oncology solutions based on the human Immuno-Transcriptome, with continuous improvement of the predictive and adaptive algorithms.

About Department of Medical Oncology, Radboud University

https://www.radboudumc.nl/afdelingen/medische-oncologie

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