Abstract 32P
Background
Small cell lung cancer (SCLC) is a heterogeneous malignancy with dismal prognosis. As molecular subtyping of SCLC with distinct genomic and transcriptional profiles have been identified, the treatment of SCLC has entered the era of precision medicine. However, few studies have conducted on the heterogeneity among SCLC patients from the perspective of metabolism. Therefore, in the present study, we aimed to identify SCLC classifications in terms of untargeted metabolomics and lipidomics. We also compared the survival and the immunotherapy responses among these subgroups.
Methods
Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS) analysis was performed in a total of 191 SCLC serum samples from our cohort. Distinct subtypes of SCLC were identified by consensus clustering algorithm using partioning around medoids (pam) based on untargeted metabolomics and lipidomics. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was conducted to identify different metabolic pathways in each subgroup. Kaplan Meier was conducted to compare survival among different subgroups.
Results
Four distinct subtypes of SCLC were identified. We have revealed that specific contributions of metabolic pathways to each SCLC subtype. Subgroup 2 was linked with the longest survival whereas Subgroup 1 had the shortest survival, with marked survival difference. Subtype 2 benefited most from immunotherapy in terms of OS, as in sharp contrast to Subtype 3 with shortest survival.
Conclusions
Our study revealed the metabolic heterogeneity in SCLC and identified four subtypes with distinct metabolic features. It indicates promising therapeutic and prognostic value that may guide treatment for SCLC. The subtype-specific clinical trials may be designed and would be instructive for drug development.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Special Funds for Taishan Scholars Project (Grant No. tsqn201812149), Academic promotion program of Shandong First Medical University (2019RC004).
Disclosure
All authors have declared no conflicts of interest.