Background: Small cell lung cancer (SCLC) is the most aggressive lung cancer subtype, with more than 70% of patients having metastatic disease and a poor prognosis. However, no integrated multi-omics analysis has been performed to explore novel differentially expressed genes (DEGs) or significantly mutated genes (SMGs) associated with lymph node metastasis (LNM) in SCLC.
Methods: In this study, whole-exome sequencing (WES) and RNA-sequencing were performed on tumor specimens to investigate the association between genomic and transcriptome alterations and LNM in SCLC patients with (N+, n=15) or without (N0, n=11) LNM.
Results: The results of WES revealed that the most common mutations occurred in TTN (85%) and TP53 (81%). The SMGs, including ZNF521, CDH10, ZNF429, POLE, and FAM135B, were associated with LNM. Cosmic signature analysis showed that mutation signatures 2, 4, and 7 were associated with LNM. Meanwhile, DEGs, including MAGEA4, FOXI3, RXFP2, and TRHDE, were found to be associated with LNM. Furthermore, we found that the messenger RNA (mRNA) levels of RB1 (P=0.0087), AFF3 (P=0.058), TDG (P=0.05), and ANKRD28 (P=0.042) were significantly correlated with copy number variants (CNVs), and ANKRD28 expression was consistently lower in N+ tumors than in N0 tumors. Further validation in cBioPortal revealed a significant correlation between LNM and poor prognosis in SCLC (P=0.014), although there was no significant correlation between LNM and overall survival (OS) in our cohort (P=0.75).
Conclusions: To our knowledge, this is the first integrative genomics profiling of LNM in SCLC. Our findings are particularly important for early detection and the provision of reliable therapeutic targets.
Keywords: RNA-sequencing; Small cell lung cancer (SCLC); lymph node metastasis (LNM); multi-omics analysis; whole-exome sequencing (WES).
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