Xerna™ TME Panel is a machine learning-based transcriptomic biomarker designed to predict therapeutic response in multiple cancers

Frontiers in Oncology

Oncology

Hong Liu¹  Arthur M. Krieg¹  Mokenge Malafa²  Jeeyun Lee³  Matjaž Žganec⁴  Daniel Pointing⁴  Luka Ausec⁴  Robert Cvitkovič⁴  Rafael Rosengarten⁴  Miha Štajdohar⁴  Seema Iyer⁵  Valerie Chamberlain Santos⁵  Bronislaw Pytowski⁵  Kerry Culm⁵  Laura Benjamin⁵  Mark Uhlik⁵ 

[1] Checkmate Pharmaceuticals, Inc., Cambridge, MA, United States;Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States;Department of Hematology and Oncology, Samsung Medical Center, Seoul, Republic of Korea;Genialis, Inc., Boston, MA, United States;OncXerna Therapeutics, Inc., Waltham, MA, United States;

关键词: pan-tumor;    immunotherapy;    anti-angiogenic agent;    diagnostic assay;    predictive biomarker;   

DOI  :  10.3389/fonc.2023.1158345

 received in 2023-02-03, accepted in 2023-04-25,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionMost predictive biomarkers approved for clinical use measure single analytes such as genetic alteration or protein overexpression. We developed and validated a novel biomarker with the aim of achieving broad clinical utility. The Xerna™ TME Panel is a pan-tumor, RNA expression-based classifier, designed to predict response to multiple tumor microenvironment (TME)-targeted therapies, including immunotherapies and anti-angiogenic agents.MethodsThe Panel algorithm is an artificial neural network (ANN) trained with an input signature of 124 genes that was optimized across various solid tumors. From the 298-patient training data, the model learned to discriminate four TME subtypes: Angiogenic (A), Immune Active (IA), Immune Desert (ID), and Immune Suppressed (IS). The final classifier was evaluated in four independent clinical cohorts to test whether TME subtype could predict response to anti-angiogenic agents and immunotherapies across gastric, ovarian, and melanoma datasets.ResultsThe TME subtypes represent stromal phenotypes defined by angiogenesis and immune biological axes. The model yields clear boundaries between biomarker-positive and -negative and showed 1.6-to-7-fold enrichment of clinical benefit for multiple therapeutic hypotheses. The Panel performed better across all criteria compared to a null model for gastric and ovarian anti-angiogenic datasets. It also outperformed PD-L1 combined positive score (>1) in accuracy, specificity, and positive predictive value (PPV), and microsatellite-instability high (MSI-H) in sensitivity and negative predictive value (NPV) for the gastric immunotherapy cohort.DiscussionThe TME Panel’s strong performance on diverse datasets suggests it may be amenable for use as a clinical diagnostic for varied cancer types and therapeutic modalities.

【 授权许可】

Unknown   
Copyright © 2023 Uhlik, Pointing, Iyer, Ausec, Štajdohar, Cvitkovič, Žganec, Culm, Santos, Pytowski, Malafa, Liu, Krieg, Lee, Rosengarten and Benjamin