Binary classification of copy number alteration profiles in liquid biopsy with potential clinical impact in advanced NSCLC

• Published in: Scientific reports Vol. 14; no. 1; pp. 18545 - 12
• Main Authors: Tosello, Valeria, Grassi, Angela, Rose, Dominic, Bao, Loc Carlo, Zulato, Elisabetta, Dalle Fratte, Chiara, Polano, Maurizio, Del Bianco, Paola, Pasello, Giulia, Guarneri, Valentina, Indraccolo, Stefano, Bonanno, Laura
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09-08-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 631/1647; 692/4028; 692/53; Aged; Aged, 80 and over; Biopsy; Carcinoma, Non-Small-Cell Lung - drug therapy; Carcinoma, Non-Small-Cell Lung - genetics; Carcinoma, Non-Small-Cell Lung - pathology; Classification; Copy number; Copy number alterations; DNA Copy Number Variations; DNA sequencing; Female; Genetic analysis; High-Throughput Nucleotide Sequencing - methods; Humanities and Social Sciences; Humans; Immune checkpoint inhibitors; Immune Checkpoint Inhibitors - therapeutic use; Immunotherapy; Liquid biopsy; Liquid Biopsy - methods; Liver cancer; Lung cancer; Lung diseases; Lung Neoplasms - drug therapy; Lung Neoplasms - genetics; Lung Neoplasms - pathology; Machine learning; Male; Metastases; Middle Aged; multidisciplinary; Next-generation sequencing; Non-small cell lung carcinoma; Patients; Retrospective Studies; Science; Science (multidisciplinary); Small cell lung carcinoma; Support Vector Machine; Tumor fraction; Whole genome sequencing; Liquid biopsy; Copy number alterations; Tumor fraction; Immunotherapy; Machine learning
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-68229-6

Liquid biopsy has recently emerged as an important tool in clinical practice particularly for lung cancer patients. We retrospectively evaluated cell-free DNA analyses performed at our Institution by next generation sequencing methodology detecting the major classes of genetic alterations. Starting from the graphical representation of chromosomal alterations provided by the analysis software, we developed a support vector machine classifier to automatically classify chromosomal profiles as stable (SCP) or unstable (UCP). High concordance was found between our binary classification and tumor fraction evaluation performed using shallow whole genome sequencing. Among clinical features, UCP patients were more likely to have ≥ 3 metastatic sites and liver metastases. Longitudinal assessment of chromosomal profiles in 33 patients with lung cancer receiving immune checkpoint inhibitors (ICIs) showed that only patients that experienced early death or hyperprogressive disease retained or acquired an UCP within 3 weeks from the beginning of ICIs. UCP was not observed following ICIs among patients that experienced progressive disease or clinical benefit. In conclusion, our binary classification, applied to whole copy number alteration profiles, could be useful for clinical risk stratification during systemic treatment for non-small cell lung cancer patients.