Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations

Tian Gen Chang*, Yingying Cao, Eldad D. Shulman, Uri Ben-David, Alejandro A. Schäffer, Eytan Ruppin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores—the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)—to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs.

Original languageEnglish
Article number54
Journalnpj Precision Oncology
Volume7
Issue number1
DOIs
StatePublished - Dec 2023

Funding

FundersFunder number
National Institutes of Health
American Association for Cancer Research
National Cancer Institute

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