{"id":224446,"date":"2025-11-03T20:03:19","date_gmt":"2025-11-04T02:03:19","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/11\/functionally-dominant-hotspot-mutations-of-mitochondrial-ribosomal-rna-genes-in-cancer"},"modified":"2025-11-03T20:03:19","modified_gmt":"2025-11-04T02:03:19","slug":"functionally-dominant-hotspot-mutations-of-mitochondrial-ribosomal-rna-genes-in-cancer","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/11\/functionally-dominant-hotspot-mutations-of-mitochondrial-ribosomal-rna-genes-in-cancer","title":{"rendered":"Functionally dominant hotspot mutations of mitochondrial ribosomal RNA genes in cancer"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/functionally-dominant-hotspot-mutations-of-mitochondrial-ribosomal-rna-genes-in-cancer.jpg\"><\/a><\/p>\n<p>To study selection for somatic single nucleotide variants (SNVs) in tumor mtDNA, we identified somatic mtDNA variants across primary tumors from the GEL cohort (<i>n<\/i> = 14,106). The sheer magnitude of the sample size in this dataset, in conjunction with the high coverage depth of mtDNA reads (mean = 15,919\u00d7), enabled high-confidence identification of mtDNA variants to tumor heteroplasmies of 5%. In total, we identified 18,104 SNVs and 2,222 indels (Supplementary Table <a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"https:\/\/share.google\/articles\/s41588-025-02374-0#MOESM2\">1<\/a>), consistent with previously reported estimates of approximately one somatic mutation in every two tumors<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" title=\"Gorelick, A. N. et al. Respiratory complex and tissue lineage drive recurrent mutations in tumour mtDNA. Nat. Metab. 3558&ndash;570 (2021).\" href=\"https:\/\/share.google\/s3JTq43EQv4dTKha4#ref-CR1\" id=\"ref-link-section-d68958645e886\">1<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" title=\"Ju, Y. S. et al. Origins and functional consequences of somatic mitochondrial DNA mutations in human cancer. eLife 3, e02935 (2014).\" href=\"https:\/\/share.google\/s3JTq43EQv4dTKha4#ref-CR2\" id=\"ref-link-section-d68958645e886_1\">2<\/a>,<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 3\" title=\"Yuan, Y. et al. Comprehensive molecular characterization of mitochondrial genomes in human cancers. Nat. Genet. 52342&ndash;352 (2020).\" href=\"https:\/\/share.google\/articles\/s41588-025-02374-0#ref-CR3\" id=\"ref-link-section-d68958645e889\">3<\/a><\/sup>. The identified mutations exhibited a strand-specific mutation signature, with a predominant occurrence of CT mutations on the heavy strand and TC on the light strand in the non-control region that was reversed in the control region<sup><a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 2\" title=\"Ju, Y. S. et al. Origins and functional consequences of somatic mitochondrial DNA mutations in human cancer. eLife 3, e02935 (2014).\" href=\"https:\/\/share.google\/articles\/s41588-025-02374-0#ref-CR2\" id=\"ref-link-section-d68958645e893\">2<\/a><\/sup> (Extended Data Fig. <a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"https:\/\/share.google\/articles\/s41588-025-02374-0#Fig5\">1a, b<\/a>). These mutations occur largely independently of known nuclear driver mutations, with the exception of a co-occurrence of <i>TP53<\/i> mutation and mtDNA mutations in breast cancer (<i>Q<\/i> = 0.031, odds ratio (OR) = 1.43, chi-squared test) (Extended Data Fig. <a data-track=\"click\" data-track-label=\"link\" data-track-action=\"figure anchor\" href=\"https:\/\/share.google\/articles\/s41588-025-02374-0#Fig6\">2a<\/a> and Supplementary Table <a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"https:\/\/share.google\/articles\/s41588-025-02374-0#MOESM2\">4<\/a>).<\/p>\n<p>Although the landscape of hotspot mutations in nuclear-DNA-encoded genes is relatively well described, a lack of statistical power has impeded an analogous, comprehensive analysis in mtDNA<sup>16,17<\/sup>. To do so, we applied a hotspot detection algorithm that identified mtDNA loci demonstrating a mutation burden in excess of the expected background mutational processes in mtDNA (Methods). In total, we recovered 138 unique statistically significant SNV hotspots (Q 0.05) across 21 tumor lineages (Fig. 1a, b and Supplementary Table 2) and seven indel hotspots occurring at homopolymeric sites in complex I genes, as previously described by our group (Extended Data Fig. 2b and Supplementary Table 3). SNV hotspots affected diverse genetic elements, including protein-coding genes (n = 96 hotspots, 12 of 13 distinct genes), tRNA genes (n = 8 hotspots, 6 of 22 distinct genes) and rRNA genes (n = 34 hotspots, 2 of 2 genes) (Fig. 1b, c, e).<\/p>\n","protected":false},"excerpt":{"rendered":"<p>To study selection for somatic single nucleotide variants (SNVs) in tumor mtDNA, we identified somatic mtDNA variants across primary tumors from the GEL cohort (n = 14,106). The sheer magnitude of the sample size in this dataset, in conjunction with the high coverage depth of mtDNA reads (mean = 15,919\u00d7), enabled high-confidence identification of mtDNA [\u2026]<\/p>\n","protected":false},"author":511,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,412,41,873],"tags":[],"class_list":["post-224446","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-genetics","category-information-science","category-nuclear-energy"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/224446","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/511"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=224446"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/224446\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=224446"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=224446"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=224446"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}