Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome.

ABSTRACT:

Background

Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers.

Methods

We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient's response to a variety of therapies in multiple cancer types without training on previous treatment response data. We study ENLIGHT in two translationally oriented scenarios: personalized oncology (PO), aimed at prioritizing treatments for a single patient, and clinical trial design (CTD), selecting the most likely responders in a patient cohort.

Findings

Evaluat

SUBMITTER: Dinstag G 

PROVIDER: S-EPMC10029756 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature