Work

116P A novel cytoband-mediated copy number alteration model for predicting clinical outcomes among pan-cancer

Year: 2025

Type: article

Abstract: Copy number alterations (CNAs) have emerged as promising biomarkers for predicting prognosis and therapeutic response in cancer. However, integrating CNA data from diverse gene panel-based sequencing platforms has posed a considerable challenge. This study aimed to develop a novel cytoband-mediated CNA algorithm capable of reliably predicting outcomes across multiple cancer types, no matter what gene panel was used.

Source: ESMO Open

DOI: 10.1016/j.esmoop.2025.104277

Authors: D. Wang, E.Y-L. Ko, W. Dai, B. Zhang, A. El-Helali

Institutions: University of Hong Kong, Chinese Academy of Medical Sciences & Peking Union Medical College

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,910