Amplification of extrachromosomal MYC paralogs shapes immunosuppressive tumor microenvironment in small cell lung cancer

Abstract Purpose: Immunotherapy has demonstrated promise in small cell lung cancer (SCLC), but certain patients encounter limited benefits, highlighting the need for immunosuppressive biomarkers. Extrachromosomal circular DNA (ecDNA) promotes amplification of MYC-paralogs (MYC, MYCN and MYCL), driving cross-resistance in SCLC. Here, we aim to investigate whether ecDNA-mediated MYC-paralogs amplification (ecMYC+) represents immunosuppressive features in SCLC. Experimental Design: Bulk RNA sequencing data were retrieved from public database and paraffin-embedded samples. The overexpression and amplification of MYC-paralogs were identified using immunohistochemistry and fluorescence in situ hybridization. Imaging mass cytometry and multiplex immunohistochemistry were used to characterize spatial distribution of tumor immune microenvironment (TIME). The copy number of MYC-paralogs was investigated using real-time polymerase chain reaction. RNA-sequencing and flow cytometry were performed in SCLC cell lines. Results: The mean copy number of ecDNAs and the frequency of ecMYC+ cell lines were higher in SCLC than that in the other lineages (SCLC 22/47 vs others 15/282). In ecMYC+ SCLC, multiple immune-related pathways were downregulated while nucleotide metabolism processes were upregulated. Inhibition of nucleotide metabolism induced ecDNA elimination, along with activated antigen presenting pathways. Highly dispersed MYC-paralogs amplifications were detected in resected treatment-naïve SCLC samples. Through the resolution of 103,341 cells from 24 pathological regions, we observed higher expression of MKI67, VEGFA, FAP and FOXP3 and reduced T cell infiltration in ecMYC+ samples. Moreover, ecMYC+ samples exhibited elevated cellular neighborhoods dominated by Ki67+ tumors, with reduced spatial interaction with immune cells. Conclusions: Extrachromosomal amplification of MYC-paralogs shapes suppressive TIME, identifying potential subgroup of immunotherapy resistant patients.