Multi-region exome sequencing reveals the intratumoral heterogeneity of surgically resected small cell lung cancer
Small cell lung cancer (SCLC) is a highly malignant tumor which is eventually refractory to any treatment. Intratumoral heterogeneity (ITH) may contribute to treatment failure. However, the extent of ITH in SCLC is still largely unknown. Here, we subject 120 tumor samples from 40 stage I-III SCLC pa...
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Veröffentlicht in: | Nature communications 2021-09, Vol.12 (1), p.5431-5431, Article 5431 |
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Zusammenfassung: | Small cell lung cancer (SCLC) is a highly malignant tumor which is eventually refractory to any treatment. Intratumoral heterogeneity (ITH) may contribute to treatment failure. However, the extent of ITH in SCLC is still largely unknown. Here, we subject 120 tumor samples from 40 stage I-III SCLC patients to multi-regional whole-exome sequencing. The most common mutant genes are TP53 (88%) and RB1 (72%). We observe a medium level of mutational heterogeneity (0.30, range 0.0~0.98) and tumor mutational burden (TMB, 10.2 mutations/Mb, range 1.1~51.7). Our SCLC samples also exhibit somatic copy number variation (CNV) across all patients, with an average CNV ITH of 0.49 (range 0.02~0.99). In terms of mutation distribution, ITH, TMB, mutation clusters, and gene signatures, patients with combined SCLC behave roughly the same way as patients with pure SCLC. This condition also exists in smoking patients and patients with EGFR mutations. A higher TMB per cluster is associated with better disease-free survival while single-nucleotide variant ITH is linked to worse overall survival, and therefore these features may be used as prognostic biomarkers for SCLC. Together, these findings demonstrate the intratumoral genetic heterogeneity of surgically resected SCLC and provide insights into resistance to treatment.
Multi-region sequencing of small cell lung cancers (SCLC) can improve our understanding of the disease. Here the authors analyse 120 multi-region samples from 40 SCLC patients with whole exome sequencing and characterise their mutational burden, evolution, heterogeneity, and potential prognostic biomarkers. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-021-25787-x |