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Background: Epithelial ovarian cancer (EOC) heavily relies on oxidative phosphorylation (OXPHOS) and exhibits distinct mitochondrial metabolic reprogramming. Up to now, the evolutionary pattern of somatic mitochondrial DNA (mtDNA) mutations in EOC tissues and their potential roles in metabolic remodelling have not been systematically elucidated., Methods: Based on a large somatic mtDNA mutation dataset from private and public EOC cohorts (239 and 118 patients, respectively), we most comprehensively characterised the EOC-specific evolutionary pattern of mtDNA mutations and investigated its biological implication., Results: Mutational profiling revealed that the mitochondrial genome of EOC tissues was highly unstable compared with non-cancerous ovary tissues. Furthermore, our data indicated the delayed heteroplasmy accumulation of mtDNA control region (mtCTR) mutations and near-complete absence of mtCTR non-hypervariable segment (non-HVS) mutations in EOC tissues, which is consistent with stringent negative selection against mtCTR mutation. Additionally, we observed a bidirectional and region-specific evolutionary pattern of mtDNA coding region mutations, manifested as significant negative selection against mutations in complex V (ATP6/ATP8) and tRNA loop regions, and potential positive selection on mutations in complex III (MT-CYB). Meanwhile, EOC tissues showed higher mitochondrial biogenesis compared with non-cancerous ovary tissues. Further analysis revealed the significant association between mtDNA mutations and both mitochondrial biogenesis and overall survival of EOC patients., Conclusions: Our study presents a comprehensive delineation of EOC-specific evolutionary patterns of mtDNA mutations that aligned well with the specific mitochondrial metabolic remodelling, conferring novel insights into the functional roles of mtDNA mutations in EOC tumourigenesis and progression., (© 2024 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)

Mitochondrial DNA (mtDNA) somatic mutations play important roles in the initiation and progression of cancer. Although next-generation sequencing (NGS) of paired tumor and control samples has become a common practice to identify tumor-specific mtDNA mutations, the unique nature of mtDNA and NGS-associated sequencing bias could cause false-positive/-negative somatic mutation calling. Additionally, there are clinical scenarios where matched control tissues are unavailable for comparison. Therefore, a novel approach for accurately identifying somatic mtDNA variants is greatly needed, particularly in the absence of matched controls. In this study, the ground truth mtDNA variants orthogonally validated by triple-paired tumor, adjacent nontumor, and blood samples were used to develop mitoSomatic, a random forest-based machine learning tool. We demonstrated that mitoSomatic achieved area under the curve (AUC) values over 0.99 for identifying somatic mtDNA variants without paired control in three tumor types. In addition, mitoSomatic was also applicable in nontumor tissues such as adjacent nontumor and blood samples, suggesting the flexibility of mitoSomatic's classification capability. Furthermore, analysis of triple-paired samples identified a small group of variants with uncertain somatic/germline origin, whereas application of mitoSomatic significantly facilitated the prediction of their possible source. Finally, a control-free evaluation of the public pan-cancer NGS dataset with mitoSomatic revealed a substantial number of variants that were probably misclassified by conventional tumor-control comparison, further emphasizing the usefulness of mitoSomatic in application. Taken together, our study demonstrates that mitoSomatic is valuable for accurately identifying somatic mtDNA variants in mtDNA NGS data without paired controls, applicable for both tumor and nontumor tissues., (© 2022 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Rationale: Mitochondrial dysfunction caused by mitochondrial DNA (mtDNA) mutations and subsequent metabolic defects are closely involved in tumorigenesis and progression in a cancer-type specific manner. To date, the mutational pattern of mtDNA somatic mutations in colorectal cancer (CRC) tissues and its clinical implication are still not completely clear. Methods: In the present study, we generated a large mtDNA somatic mutation dataset from three CRC cohorts (432, 1,015, and 845 patients, respectively) and then most comprehensively characterized the CRC-specific evolutionary pattern and its clinical implication. Results: Our results showed that the mtDNA control region (mtCTR) with a high mutation density exhibited a distinct mutation spectrum characterizing a high enrichment of L-strand C > T mutations, which was contrary to the H-strand C > T mutational bias observed in the mtDNA coding region (mtCDR) ( P < 0.001). Further analysis clearly confirmed the relaxed evolutionary selection of mtCTR mutations, which was mainly characterized by the similar distribution of hypervariable region (HVS) and non-HVS mutation density. Moreover, significant negative selection was identified in mutations of mtDNA complex V (ATP6/ATP8) and tRNA loop regions. Although our data showed that oxidative metabolism was commonly increased in CRC cells, mtDNA somatic mutations in CRC tissues were not closely associated with mitochondrial biogenesis, oxidative metabolism, and clinical progression, suggesting a cancer-type specific relationship between mtDNA mutations and mitochondrial metabolic functions in CRC cells. Conclusion: Our study identified the CRC-specific evolutionary mode of mtDNA mutations, which is possibly matched to specific mitochondrial metabolic remodeling and confers new mechanic insight into CRC tumorigenesis., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Background: Mitochondrial DNA (mtDNA) mutations alter mitochondrial function in oxidative metabolism and play an important role in tumorigenesis. A series of studies have demonstrated that the mtDNA control region (mtCTR), which is essential for mtDNA replication and transcription, represents a mutational hotspot in human tumors. However, a comprehensive pan-cancer evolutionary pattern analysis of mtCTR mutations is urgently needed., Methods: We generated a comprehensive combined dataset containing 10026 mtDNA somatic mutations from 4664 patients, covering 20 tumor types based on public and private next-generation sequencing data., Findings: Our results demonstrated a significantly higher and much more variable mutation rate in mtCTR than in the coding region across different tumor types. Moreover, our data showed a remarkable distributional bias of tumor somatic mutations between the hypervariable segment (HVS) and non-HVS, with a significantly higher mutation density and average mutation sites in HVS. Importantly, the tumor-specific mutational pattern between mtCTR HVS and non-HVS was identified, which was classified into three evolutionary selection types (relaxed, moderate, and strict constraint types). Analysis of substitution patterns revealed that the prevalence of C H > T H in non-HVS greatly contributed to the mutational selection pattern of mtCTR across different tumor types. Furthermore, we found that the mutational pattern of mtCTR in the four tumor types was clearly associated with mitochondrial biogenesis, mitochondrial oxidative metabolism, and the overall survival of patients., Interpretation: Our results suggest that somatic mutations in mtCTR may be shaped by tumor-specific selective pressure and are involved in tumorigenesis., Fundings: National Natural Science Foundation of China [grants 82020108023, 81830070, 81872302], and Autonomous Project of State Key Laboratory of Cancer Biology, China [grants CBSKL2019ZZ06, CBSKL2019ZZ27]., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Next-generation sequencing (NGS) of mitochondrial DNA (mtDNA) has widespread applications in aging and cancer studies. However, cross-contamination of mtDNA constitutes a major concern. Previous methods for the detection of mtDNA contamination mainly focus on haplogroup-level phylogeny, but neglect haplotype-level differences, leading to limited sensitivity and accuracy. In our study, we present mitoDataclean, a random-forest-based machine learning package for accurate identification of cross-contamination, evaluation of contamination levels and detection of contamination-derived variants in mtDNA NGS data. Comprehensive optimization of mitoDataclean revealed that training simulation with mixtures of small haplogroup distance and low polymorphic difference was critical for optimal modeling. Compared to existing methods, mitoDataclean exhibited significantly improved sensitivity and accuracy for the detection of sample contamination in simulated data. In addition, mitoDataclean achieved area under the curve values of 0.91 and 0.97 for discerning genuine and contamination-derived mtDNA variants in a simulated Western dataset and private sequencing contamination data, respectively, suggesting that this tool may be applicable for different populations and samples with different sources of contamination. Finally, mitoDataclean was further evaluated in several private and public datasets and showed a robust ability for contamination detection. Altogether, our study demonstrates that mitoDataclean may be used for accurate detection of contaminated samples and contamination-derived variants in mtDNA NGS data., (© 2022 UICC.)

Background: Many studies have demonstrated the high efficacy of cell-free nuclear DNA in cancer diagnostics. Compared to nuclear DNA, mitochondrial DNA (mtDNA) exhibits distinct characteristics, including multiple copies per cell and higher mutation frequency. However, the potential applicability of cell-free mtDNA (cf-mtDNA) in plasma and urine remains poorly investigated., Methods: Here, we comprehensively analyzed the fragmentomic and mutational characteristics of cf-mtDNA in urine and plasma samples from controls and cancer patients using next-generation sequencing., Results: Compared to plasma cf-mtDNA, urine cf-mtDNA exhibited increased copy numbers and wider spread in fragment size distributions. Based on 2 independent animal models, urine cf-mtDNA originated predominantly from local shedding and transrenal excretion. Further analysis indicated an enhanced fragmentation of urine cf-mtDNA in renal cell carcinoma (RCC) and colorectal cancer (CRC) patients. Using the mtDNA sequence of peripheral blood mononuclear cells for reference, the mutant fragments were shorter than wild-type fragments in urine cf-mtDNA. Size selection of short urine cf-mtDNA fragments (<150 bp) significantly enhanced the somatic mutation detection. Our data revealed remarkably different base proportions of fragment ends between urine and plasma cf-mtDNA that also were associated with fragment size. Moreover, both RCC and CRC patients exhibited significantly higher T-end and lower A-end proportions in urine cf-mtDNA than controls. By integrating the fragmentomic and mutational features of urine cf-mtDNA, our nomogram model exhibited a robust efficacy for cancer diagnosis., Conclusions: Our proof-of-concept findings revealed aberrant fragmentation and mutation profiles of urine cf-mtDNA in cancer patients that have diagnostic potential., (© American Association for Clinical Chemistry 2022. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Mitochondria are central eukaryotic organelles in cellular metabolism and ATP production. Mitochondrial DNA (mtDNA) alterations have been implicated in the development of colorectal cancer (CRC). However, there are few reports on the association between mtDNA haplogroups or single nucleotide polymorphisms (SNPs) and the risk of CRC. The mtDNA of 286 Northern Han Chinese CRC patients were sequenced by next-generation sequencing technology. MtDNA data from 811 Han Chinese population controls were collected from two public data sets. Then, logistic regression analysis was used to determine the effect of mtDNA haplogroup or SNP on the risk of CRC. We found that patients with haplogroup M7 exhibited a reduced risk of CRC when compared to patients with other haplogroups (odds ratio [OR] = 0.532, 95% confidence interval [CI] = 0.285-0.937, p = 0.036) or haplogroup B (OR = 0.477, 95% CI = 0.238-0.916, p = 0.030). Furthermore, haplogroup M7 was still associated with the risk of CRC when the validation and combined control cohort were used. In addition, several haplogroup M7 specific SNPs, including 199T>C, 4071C>T and 6455C>T, were significantly associated with the risk of CRC. Our results indicate the risk potential of mtDNA haplogroup M7 and SNPs in CRC in Northern China., (© 2021 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

Activation-induced cytidine deaminase (AID) initiates somatic hypermutation and class switch recombination of immunoglobulin genes in B cells, whereas off-targeted AID activity contributes to oncogenic mutations and chromosomal translocations associated with B cell malignancies. Paradoxically, only a minority of AID is allowed to access the nuclear genome, but the majority of AID is retained in the cytoplasm. It is unknown whether cytoplasmic AID can access and target the mitochondrial genome [mitochondrial DNA (mtDNA)]. To address this issue, we developed high-fidelity differential DNA denaturation PCR, which allowed the enrichment of genuine mtDNA mutations and therefore the identification of endogenous mtDNA mutation signatures in vitro. With this approach, we showed that AID targeting to mtDNA is a rare event in AID-expressing lymphoma lines. Further biochemical and microscopic analysis revealed that a fraction of cytosol AID is associated with the outer membrane of mitochondria but unable to access the mitochondrial matrix. Together, our data suggested that the mitochondrial genome is protected from AID-mediated mutagenesis by physical segregation of AID from accessing mtDNA within the mitochondrial matrix., (© 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.)

Variations in mitochondrial DNA (mtDNA) have been fundamental for understanding human evolution and are causative for a plethora of inherited mitochondrial diseases, but the mutation signatures of germline mtDNA and their value in understanding mitochondrial pathogenicity remain unknown. Here, we carried out a systematic analysis of mutation patterns in germline mtDNA based on 97,566 mtDNA variants from 45,494 full-length sequences and revealed a highly non-stochastic and replication-coupled mutation signature characterized by nucleotide-specific mutation pressure (G > T>A > C) and position-specific selection pressure, suggesting the existence of an intensive mutation-selection interplay in germline mtDNA. We provide evidence that this mutation-selection interplay has strongly shaped the mtDNA sequence during evolution, which not only manifests as an oriented alteration of amino acid compositions of mitochondrial encoded proteins, but also explains the long-lasting mystery of CpG depletion in mitochondrial genome. Finally, we demonstrated that these insights may be integrated to better understand the pathogenicity of disease-implicated mitochondrial variants.