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Landscape of somatic mutations and clonal evolution in mantle cell lymphoma

ABSTRACT: Mantle cell lymphoma (MCL) is an aggressive tumor, but a subset of patients may follow an indolent clinical course. To understand the mechanisms underlying this biological heterogeneity, we performed whole-genome and/or whole-exome sequencing on 29 MCL cases and their respective matched normal DNA, as well as 6 MCL cell lines. Recurrently mutated genes were investigated by targeted sequencing in an independent cohort of 172 MCL patients. We identified 25 significantly mutated genes, including known drivers such as ataxia-telangectasia mutated (ATM), cyclin D1 (CCND1), and the tumor suppressor TP53; mutated genes encoding the anti-apoptotic protein BIRC3 and Toll-like receptor 2 (TLR2); and the chromatin modifiers WHSC1, MLL2, and MEF2B. We also found NOTCH2 mutations as an alternative phenomenon to NOTCH1 mutations in aggressive tumors with a dismal prognosis. Analysis of two simultaneous or subsequent MCL samples by whole-genome/whole-exome (n = 8) or targeted (n = 19) sequencing revealed subclonal heterogeneity at diagnosis in samples from different topographic sites and modulation of the initial mutational profile at the progression of the disease. Some mutations were predominantly clonal or subclonal, indicating an early or late event in tumor evolution, respectively. Our study identifies molecular mechanisms contributing to MCL pathogenesis and offers potential targets for therapeutic intervention.

OTHER RELATED OMICS DATASETS IN: PRJNA203212

PROVIDER: EGAS00001000510 | EGA |

REPOSITORIES: EGA

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Project description:Intratumoral heterogeneity (ITH) arises from distinct subclonal expansion following genetic or epigenetic alterations, and profoundly influences how tumors response to their immune microenvironment. Tumor progression trees based on single-cell mutational profiles have made it possible to trace subclonal evolution; however, conventional tree-building methods can incorporate only a limited number of cells and mutations, restricting their application to larger single-cell data. To investigate the effect of ITH on the therapeutic response of melanoma, we have developed Trisicell (https://trisicell.rtfd.io), a computational toolkit for scalable inference of mutational ITH through assessment of single-cell genomic variant data. By applying Trisicell to genetically matched mouse melanoma datasets, we found that expressed mutations are sufficient to effectively drive subclonal evolution. On single-cell, full-length RNA sequencing data of mouse melanoma from preclinical immune checkpoint blockade (ICB) studies, the analysis showed that the subtree-seeding mutations in the trees identified distinct subclones associated with a specific developmental state and neural crest lineage markers. Using the tree to trace cell lineages, we found that neoantigens depleted by ICB were predominantly expressed in minor subclones, suggesting that post-treatment recurrence is driven by immunoediting. Moreover, these neoantigens were enriched with those derived from frameshift mutations and mutated nuclear genes. Importantly, recurrently mutated genes in ICB-responding human melanoma exhibited the same features. We next used Trisicell to analyze single-cell, full-length RNA data of brain metastases (BM) from melanoma patients treated with ICB, and discovered that relapsing BM from ICB-responding patients exhibited subclones that also expressed a higher fraction of frameshift mutations and were associated with elevated levels of infiltrated T cells. Notably, they also exhibited more mutated HLA genes and expressed high level of the novel immune checkpoint HLA-G, a putative local immunosuppressive mechanism. In summary, applying Trisicell to single-cell transcriptomic analyses allowed us to identify novel features of ICB-responding melanoma neoantigens and distinct mechanisms for adapting to immunotherapy at different sites. These results have important implications for both melanoma evolution and target identification for immunotherapies, including ICB and cancer vaccines. This is the first study to trace subclonal evolution of neoantigens at single-cell resolution, demonstrating that Trisicell and our datasets represent important resources for the field.

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Landscape of somatic mutations and clonal evolution in mantle cell lymphoma

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