143P Association of PTPRT mutation with survival of immune checkpoint inhibitor in patients with cancer. (15th December 2019)

• Record Type: Journal Article
• Authors: Li, A; Lin, D; Yu, Y; Gu, Y; Ou, Q; Zhang, W; Chen, Y; Liu, R; Tan, Y; Xu, H; Li, L; Yao, H
• Is Part Of: Annals of oncology. Volume 30(2019)Supplement 11
• Publication Date: 2019-12-15
• Subjects: Oncology -- Periodicals; 616.992
• DOI: 10.1093/annonc/mdz452.014
• Languages: English
• ISSNs: 0923-7534

Abstract

Abstract: Background: Mutation in the gene encoding Protein Tyrosine Phosphatase Receptor T (PTPRT) has been shown to influence survival outcomes in cancers. However, the association of PTPRT mutation with clinical outcomes of immune checkpoint inhibitor (ICI) remains unclear. Here we performed comprehensive analysis of PTPRT mutation frequency and clinically validated PTPRT mutation as a predictive biomarker of ICI in patients with cancer. Methods: This study analyzed cancer genomic data from the cBioPortal database. All patients treated with ICI were included. Nonsynonymous mutations of PTPRT were considered. Kaplan-Meier survival analysis and logistic regression models were applied. Primary outcomes were overall survival (OS) and progression-free survival (PFS). Results: Among 2129 patients with non–small cell lung cancer (NSCLC) (n = 510), melanoma (n = 596), and other tumor types (n = 1, 023), the tumor mutation burden of patients with PTPRT mutation was significantly higher than in those without the mutations in NSCLC, melanoma, and pancancer (Wilcoxon rank sum test, all P < 0.0001). Among patients receiving ICI, PTPRT mutation compared with PTPRT wild-type was associated with better OS in melanoma [hazard ratio (HR) 0.66, 95% CI 0.50 to 0.88] and in pancancer (HR 0.63, 95% CI 0.52 to 0.77), and was associated with better PFS in NSCLC (HR 0.55, 95% CI 0.35 to 0.87). Conclusion: We demonstrated that PTPRT mutation can predict survival benefit from cancer ICI therapy. PTPRT mutation might be an important component of the immunogenetic landscape and should be integrated into predictive biomarker panels for ICI therapy and be validated in future prospective clinical trials. Legal entity responsible for the study: Herui Yao. Funding: This study was supported by grants from the National Natural Science Foundation of China (81372819, 81572596, U1601223), the Natural Science Foundation of Guangdong Province (2017A030313828), the Guangzhou Science and Technology Program (201704020131), the Sun Yat-Sen University Clinical Research 5010 Program (2018007). Disclosure: All authors have declared no conflicts of interest.