Predicting clinical outcomes of cancer patients with a p53 deficiency gene signature

• Published in: Scientific reports Vol. 12; no. 1; p. 1317
• Main Authors: Schaafsma, Evelien, Takacs, Eric M., Kaur, Sandeep, Cheng, Chao, Kurokawa, Manabu
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 25-01-2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/114/2114; 631/67; 692/53; 692/53/2422; Cancer; Clinical outcomes; Computer applications; Drug Resistance, Neoplasm - genetics; Gene Expression Profiling - methods; Gene Expression Regulation, Neoplastic; Genes, p53; Genomics - methods; Heterogeneity; Humanities and Social Sciences; Humans; Inactivation; Kaplan-Meier Estimate; multidisciplinary; Mutation; Mutation Rate; Neoplasms - genetics; Neoplasms - metabolism; Neoplasms - mortality; p53 Protein; Patients; Prognosis; Science; Science (multidisciplinary); Survival Rate; Transcriptome - genetics; Tumor cell lines; Tumor microenvironment; Tumor Microenvironment - genetics; Tumor suppressor genes; Tumor Suppressor Protein p53 - deficiency; Tumor Suppressor Protein p53 - genetics; Tumors
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-05243-6

The tumor suppressor p53, encoded by the
TP53
gene, is mutated or nullified in nearly 50% of human cancers. It has long been debated whether
TP53
mutations can be utilized as a biomarker to predict clinical outcomes of cancer patients. In this study, we applied computational methods to calculate p53 deficiency scores (PDSs) that reflect the inactivation of the p53 pathway, instead of
TP53
mutation status. Compared to
TP53
mutation status, the p53 deficiency gene signature is a powerful predictor of overall survival and drug sensitivity in a variety of cancer types and treatments. Interestingly, the PDSs predicted clinical outcomes more accurately than drug sensitivity in cell lines, suggesting that tumor heterogeneity and/or tumor microenvironment may play an important role in predicting clinical outcomes using p53 deficiency gene signatures.