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

Autor: Tian-Gen Chang, Yingying Cao, Eldad D. Shulman, Uri Ben-David, Alejandro A. Schäffer, Eytan Ruppin
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: npj Precision Oncology, Vol 7, Iss 1, Pp 1-8 (2023)
Druh dokumentu: article
ISSN: 2397-768X
DOI: 10.1038/s41698-023-00408-6
Popis: 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.
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