Abstract 213P
Background
Therapeutic management of small cell lung cancer (SCLC) remains a major challenge for clinicians, with few treatment options significantly impacting patient survival. One of the barriers to advancing the treatment of patients with SCLC has been identified as the lack of detailed molecular characterization. A recent large real-world data reveals genomic characterization of predominantly Caucasian SCLC patients. However, little is known about that in Chinese SCLC patients.
Methods
Here, we analyzed whole-exome sequencing data based on 178 Chinese SCLC patients to understand the genomic characteristics of Chinese patients, and compare them with those of Caucasian patients. Univariate Cox regression analysis was performed to figure out the correlation between gene mutation and prognosis. CCLE database was used to predict drug responses in SCLC cells with different mutation status.
Results
The top ten frequently mutated genes in Chinese SCLC patients were TP53, TTN, RB1 MUC16, USH2A, FSIP2, ZFHX4, SYNE1 CSMD3 and OBSCN. And the top ten frequently genes with copy number amplifications/deletions were SDHA, NKX2-1, PSIP1, SRSF2, CALR PTPN6, SUZ16, PABPC1, MAP2K4, and MSI2. PKD1L1 mutation was found to be associated with worse prognosis in both Chinese and Caucasian SCLC patients, and analyses based on the CCLE dataset found that SCLC cell lines with PKD1L1 mutation were more sensitive to small molecular inhibitors targeting the MYC and mTOR signaling pathways.
Conclusions
Compared with Caucasian, the genetic alterations of Chinese SCLC patients presented different patterns, and we identified a common gene, PKD1L1, associated with poor prognosis in patients from different populations, and this gene may be a predictive marker of drug reactivity targeting the MYC and/or mTOR signaling pathways.
Legal entity responsible for the study
The authors.
Funding
Special Funds for Taishan Scholars Project (grant no. tsqn201812149), China Lung Cancer Immunotherapy Research Foundation, Shandong Provincial Natural Science Foundation, China (grant no. ZR2023MH065).
Disclosure
Z. Huang, T. Sun, W. Su: Financial Interests, Institutional, Full or part-time Employment: Amoy Diagnostics Co., Ltd. All other authors have declared no conflicts of interest.