Exploiting tumor RNA-sequencing data for prediction of immune checkpoint inhibition response

April 8, 2024

Frederick De Baene, Carolina Fierro, Emmanuel Rivière, Reindert Van Cauwenberghe, Pieter-Jan Van Dam, Jo Vandesompele, Elise Van Hoof, Pieter Mestdagh

CellCarta’s study utilizes tumor RNA-sequencing data to predict immune checkpoint inhibition (ICI) response in cancer patients. The developed RNA-Seq Bio-IT model integrates features like tumor mutational burden (TMB), microsatellite instability (MSI), tumor infiltrating lymphocytes (TILs), and immune gene expression signatures to enhance the prediction of clinical responses to ICI therapy.

This model reduces the complexity and cost associated with multi-omics approaches and provides a more accurate prediction of therapy outcomes, potentially improving patient selection for ICI treatment.

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Exploiting tumor RNA-sequencing data for prediction of immune checkpoint inhibition response