NRDE2 deficiency impairs homologous recombination repair and sensitizes hepatocellular carcinoma to PARP inhibitors.

To identify novel susceptibility genes for hepatocellular carcinoma (HCC), we performed a rare-variant association study in Chinese populations consisting of 2,750 cases and 4,153 controls. We identified four HCC-associated genes, including NRDE2, RANBP17, RTEL1, and STEAP3. Using NRDE2 (index rs199890497 [p.N377I], p = 1.19 × 10-9) as an exemplary candidate, we demonstrated that it promotes homologous recombination (HR) repair and suppresses HCC. Mechanistically, NRDE2 binds to the subunits of casein kinase 2 (CK2) and facilitates the assembly and activity of the CK2 holoenzyme. This NRDE2-mediated enhancement of CK2 activity increases the phosphorylation of MDC1 and then facilitates the HR repair. These functions are eliminated almost completely by the NRDE2-p.N377I variant, which sensitizes the HCC cells to poly(ADP-ribose) polymerase (PARP) inhibitors, especially when combined with chemotherapy. Collectively, our findings highlight the relevance of the rare variants to genetic susceptibility to HCC, which would be helpful for the precise treatment of this malignancy.

Mitochondrial DNA Haplogroups and SNPs: Risk Factors in Multiple Cancers Based on a Cross-Tumor Analysis in Chinese Population.

BACKGROUND: Mitochondrial DNA's (mtDNA) haplogroups and SNPs were associated with the risk of different cancer. However, there is no evidence that the same haplogroup or mitochondrial SNP (mtSNP) exhibits the pleiotropic effect on multiple cancers. METHODS: We recruited 2,489 participants, including patients with colorectal, hepatocellular, lung, ovarian, bladder, breast, pancreatic, and renal cell carcinoma. In addition, 715 healthy individuals from Northern China served as controls. Next, cross-tumor analysis was performed to determine whether mtDNA variation is associated with multiple cancers. RESULTS: Our results revealed a significant decrease in the occurrence risk of multiple cancers among individuals belonging to haplogroup A [OR = 0.553, 95% confidence interval (CI) = 0.375-0.815, P = 0.003]. Furthermore, we identified 11 mtSNPs associated with multiple cancers and divided the population into high-risk and low-risk groups. Low-risk groups showed a significantly reduced risk of occurrence compared with high-risk groups (OR = 0.614, 95% CI = 0.507-0.744, P < 0.001). Furthermore, using interaction analysis, we identified a special group of individuals belonging to haplogroup A/M7 and the low-risk population, who exhibit a lower risk of multiple cancers compared with other populations (OR = 0.195, 95% CI = 0.106-0.359, P < 0.001). Finally, gene set enrichment analysis confirmed that haplogroup A/M7 patients had lower expression levels of cancer-related pathway genes compared with haplogroup D patients. CONCLUSIONS: We found that specific mtDNA haplogroups and mtSNPs may play a role in predicting multiple cancer predisposition in Chinese populations. IMPACT: This may provide a potential tool for early screening in clinical settings for individuals in the Chinese population.

Mutational profiling of mitochondrial DNA reveals an epithelial ovarian cancer-specific evolutionary pattern contributing to high oxidative metabolism.

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.

Endothelial MICU1 alleviates diabetic cardiomyopathy by attenuating nitrative stress-mediated cardiac microvascular injury.

BACKGROUND: Myocardial microvascular injury is the key event in early diabetic heart disease. The injury of myocardial microvascular endothelial cells (CMECs) is the main cause and trigger of myocardial microvascular disease. Mitochondrial calcium homeostasis plays an important role in maintaining the normal function, survival and death of endothelial cells. Considering that mitochondrial calcium uptake 1 (MICU1) is a key molecule in mitochondrial calcium regulation, this study aimed to investigate the role of MICU1 in CMECs and explore its underlying mechanisms. METHODS: To examine the role of endothelial MICU1 in diabetic cardiomyopathy (DCM), we used endothelial-specific MICU1ecKO mice to establish a diabetic mouse model and evaluate the cardiac function. In addition, MICU1 overexpression was conducted by injecting adeno-associated virus 9 carrying MICU1 (AAV9-MICU1). Transcriptome sequencing technology was used to explore underlying molecular mechanisms. RESULTS: Here, we found that MICU1 expression is decreased in CMECs of diabetic mice. Moreover, we demonstrated that endothelial cell MICU1 knockout exacerbated the levels of cardiac hypertrophy and interstitial myocardial fibrosis and led to a further reduction in left ventricular function in diabetic mice. Notably, we found that AAV9-MICU1 specifically upregulated the expression of MICU1 in CMECs of diabetic mice, which inhibited nitrification stress, inflammatory reaction, and apoptosis of the CMECs, ameliorated myocardial hypertrophy and fibrosis, and promoted cardiac function. Further mechanistic analysis suggested that MICU1 deficiency result in excessive mitochondrial calcium uptake and homeostasis imbalance which caused nitrification stress-induced endothelial damage and inflammation that disrupted myocardial microvascular endothelial barrier function and ultimately promoted DCM progression. CONCLUSIONS: Our findings demonstrate that MICU1 expression was downregulated in the CMECs of diabetic mice. Overexpression of endothelial MICU1 reduced nitrification stress induced apoptosis and inflammation by inhibiting mitochondrial calcium uptake, which improved myocardial microvascular function and inhibited DCM progression. Our findings suggest that endothelial MICU1 is a molecular intervention target for the potential treatment of DCM.

Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations.

Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients.

Mutational signature of mtDNA confers mechanistic insight into oxidative metabolism remodeling in colorectal cancer.

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.

Downregulated mitochondrial transcription factor A enhances mycoplasma infection to promote the metastasis of hepatocellular carcinoma.

Mycoplasma is widespread in various hosts and may cause various diseases in animals. Interestingly, the occurrence of mycoplasma infection was observed in many tumor types. However, the mechanism regulating its infection is far from clear. We unexpectedly found that the knockdown of mitochondrial transcription factor A (TFAM) remarkably enhanced mycoplasma infection in hepatocellular carcinoma (HCC) cells. More importantly, we found that mycoplasma infection facilitated by TFAM knockdown significantly promoted HCC cell metastasis. Mycoplasma infection was further found to be positively correlated with poor prognosis in patients with HCC. Mechanistically, the decreased TFAM expression upregulated the transcription factor Sp1 to increase the expression level of Annexin A2 (ANXA2), which was reported to interact with membrane protein of mycoplasma. Moreover, we found that mycoplasma infection enhanced by the TFAM downregulation promoted HCC migration and invasion by activating the nuclear factor-κB signaling pathway. The downregulation of TFAM enhanced mycoplasma infection in HCC cells and promoted HCC cell metastasis. Our study contributes to the understanding of the pathological role of mycoplasma infection and provides supporting evidence that targeting TFAM could be a potential strategy for the treatment of HCC with mycoplasma infection.

Mitochondrial DNA haplogroup M7: A predictor of poor prognosis for colorectal cancer patients in Chinese population.

Haplogroups and single-nucleotide polymorphisms (SNP) of mitochondrial DNA (mtDNA) were associated with the prognosis of many types of cancer patients. However, whether mtDNA haplogroups contribute to clinical outcomes of colorectal cancer (CRC) in Chinese population remains to be determined. In this study, mtDNA of tissue samples from 445 CRC patients from Northwestern China was sequenced to evaluate the association between haplogroup and prognosis. The mtDNA sequencing data of 1015 CRC patients from Southern China were collected for validation. We found patients with mtDNA haplogroup M7 had a significantly higher death risk when compared with patients with other haplogroups in both Northwestern (Hazard ratio [HR] = 3.093, 95% CI = 1.768-5.411, p < 0.001) and Southern (HR = 1.607, 95% CI = 1.050-2.459, p = 0.029) China. Then, a haplogroup M7-based mtSNP classifier was selected by using LASSO Cox regression analysis. A nomogram comprising the mtSNP classifier and clinicopathological variables was developed to predict the prognosis of CRC patients (area under the curve [AUC] 0.735, 95% CI = 0.679-0.791). Furthermore, patients with high- and low-risk scores calculated by the haplogroup M7-based mtSNP classifier exhibited significantly different overall survival (OS) and recurrence-free survival (RFS) (all p < 0.001). Finally, RNA-seq and immunohistochemical analyses indicated the poor prognosis of patients with haplogroup M7 may be related to mitochondrial dysfunction and immune abnormalities in CRC tissues. In conclusion, the haplogroup M7 and haplogroup M7-based mtSNP classifier seems to be a practical and reliable prognostic predictor for CRC patients, which provides a potential tool of clinical decision-making for patients with haplogroup M7 in Chinese population.

mitoSomatic: a tool for accurate identification of mitochondrial DNA somatic mutations without paired controls.

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.

Down-regulation of BMAL1 by MiR-494-3p Promotes Hepatocellular Carcinoma Growth and Metastasis by Increasing GPAM-mediated Lipid Biosynthesis.

The circadian clock confers daily rhythmicity to many crucial biological processes and behaviors and its disruption is closely associated with carcinogenesis in several types of cancer. Brain and muscle arnt-like protein 1 (BMAL1) is a core circadian rhythm component in mammals and its dysregulation has been shown to contribute to aberrant metabolism in human diseases. However, the biological functions of BMAL1, especially its involvement in aberrant lipid metabolism in hepatocellular carcinoma (HCC), remain elusive. In the present study, we found that BMAL1 was frequently down-regulated in HCC cells mainly due to the up-regulation of miR-494-3p. Down-regulation of BMAL1 was significantly associated with poor survival in HCC patients. BMAL1 down-regulation promoted HCC cell growth and metastasis both in vitro and in vivo. Mechanistically, through cooperating with EZH2, BMAL1 transcriptionally suppressed the expression of glycerol-3-phosphate acyltransferase mitochondrial (GPAM), a key enzyme involved in the regulation of lipid biosynthesis, leading to reduced levels lysophosphatidic acid (LPA), which have long been known as mediator of oncogenesis. Particularly, treatment with SR8278, an activator of BMAL1, exhibited a therapeutic effect on HCC in vitro and in vivo. In conclusion, BMAL1 plays a critical anti-oncogenic role in HCC, providing strong research evidence for BMAL1 as a prospective target for HCC therapy.

A computational framework to unify orthogonal information in DNA methylation and copy number aberrations in cell-free DNA for early cancer detection.

Cell-free DNA (cfDNA) provides a convenient diagnosis avenue for noninvasive cancer detection. The current methods are focused on identifying circulating tumor DNA (ctDNA)s genomic aberrations, e.g. mutations, copy number aberrations (CNAs) or methylation changes. In this study, we report a new computational method that unifies two orthogonal pieces of information, namely methylation and CNAs, derived from whole-genome bisulfite sequencing (WGBS) data to quantify low tumor content in cfDNA. It implements a Bayes model to enrich ctDNA from WGBS data based on hypomethylation haplotypes, and subsequently, models CNAs for cancer detection. We generated WGBS data in a total of 262 samples, including high-depth (>20×, deduped high mapping quality reads) data in 76 samples with matched triplets (tumor, adjacent normal and cfDNA) and low-depth (~2.5×, deduped high mapping quality reads) data in 186 samples. We identified a total of 54 Mb regions of hypomethylation haplotypes for model building, a vast majority of which are not covered in the HumanMethylation450 arrays. We showed that our model is able to substantially enrich ctDNA reads (tens of folds), with clearly elevated CNAs that faithfully match the CNAs in the paired tumor samples. In the 19 hepatocellular carcinoma cfDNA samples, the estimated enrichment is as high as 16 fold, and in the simulation data, it can achieve over 30-fold enrichment for a ctDNA level of 0.5% with a sequencing depth of 600×. We also found that these hypomethylation regions are also shared among many cancer types, thus demonstrating the potential of our framework for pancancer early detection.

Mutational profiling of mtDNA control region reveals tumor-specific evolutionary selection involved in mitochondrial dysfunction.

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 CH > TH 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].

New insights into the diagnostic characteristics and clinical application of serum biomarkers for lung cancer, and human epididymis protein 4 as a new biomarker?

The value of serum tumor biomarkers used for lung cancer diagnosis is still controversial in clinical practice. This study aimed to further dissect and evaluate the clinical value of serum progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1) together with a potential new biomarker, the human epididymis protein 4 (HE4) for lung cancer diagnosis, in a large cohort of a Chinese population. Ostensibly healthy individuals, as well as those with benign non-cancerous diseases, benign tumors, lung cancers, and other types of malignancies, were enrolled in the study. Serum ProGRP, NSE, SCC-Ag, CEA, CYFRA21-1, and HE4 were analyzed using the chemiluminescence immunoassay. Data were analyzed utilizing the SPSS and GraphPad Prism software. Detailed dissection of the diagnostic characteristics of serum 6 biomarkers on lung cancer was performed. All 6 biomarkers showed capabilities in characterizing lung cancer from other diseases. ProGRP and NSE were highly specific to small cell lung cancer (SCLC); SCC-Ag was a fair biomarker for NSCLC, specifically SCC histotype; CEA showed specificity to SCLC, followed by NSCLC; CYFRA21-1 was a good biomarker for both SCLC and NSCLC; HE4 showed high specificity to SCLC. For NSCLC characterization, CYFRA21-1+HE4+CEA was the best combinatory pattern in the terms of diagnostic performance (AUC=0.8110). The best combinatory analysis for SCLC was ProGRP+NSE+HE4 (AUC=0.9282). Patients with advanced stage, larger tumor, males, and age 50 or older had higher serum biomarkers levels than those with early stage, smaller tumor, females, and age under 50. Six biomarkers had capabilities in characterizing lung cancer with high or fair diagnostic performance. HE4 is a potential biomarker for both SCLC and NSCLC diagnosis, which merits further investigation.

TFAM loss induces nuclear actin assembly upon mDia2 malonylation to promote liver cancer metastasis.

The mechanisms underlying cancer metastasis remain poorly understood. Here, we report that TFAM deficiency rapidly and stably induced spontaneous lung metastasis in mice with liver cancer. Interestingly, unexpected polymerization of nuclear actin was observed in TFAM-knockdown HCC cells when cytoskeleton was examined. Polymerization of nuclear actin is causally linked to the high-metastatic ability of HCC cells by modulating chromatin accessibility and coordinating the expression of genes associated with extracellular matrix remodeling, angiogenesis, and cell migration. Mechanistically, TFAM deficiency blocked the TCA cycle and increased the intracellular malonyl-CoA levels. Malonylation of mDia2, which drives actin assembly, promotes its nuclear translocation. Importantly, inhibition of malonyl-CoA production or nuclear actin polymerization significantly impeded the spread of HCC cells in mice. Moreover, TFAM was significantly downregulated in metastatic HCC tissues and was associated with overall survival and time to tumor recurrence of HCC patients. Taken together, our study connects mitochondria to the metastasis of human cancer via uncovered mitochondria-to-nucleus retrograde signaling, indicating that TFAM may serve as an effective target to block HCC metastasis.

Next-Generation Sequencing-Based Analysis of Urine Cell-Free mtDNA Reveals Aberrant Fragmentation and Mutation Profile in Cancer Patients.

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.

mitoDataclean: A machine learning approach for the accurate identification of cross-contamination-derived tumor mitochondrial DNA mutations.

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.

Increased mitochondrial fission drives the reprogramming of fatty acid metabolism in hepatocellular carcinoma cells through suppression of Sirtuin 1.

BACKGROUND: Mitochondria are dynamic organelles that constantly change their morphology through fission and fusion processes. Recently, abnormally increased mitochondrial fission has been observed in several types of cancer. However, the functional roles of increased mitochondrial fission in lipid metabolism reprogramming in cancer cells remain unclear. This study aimed to explore the role of increased mitochondrial fission in lipid metabolism in hepatocellular carcinoma (HCC) cells. METHODS: Lipid metabolism was determined by evaluating the changes in the expressions of core lipid metabolic enzymes and intracellular lipid content. The rate of fatty acid oxidation was evaluated by [3 H]-labelled oleic acid. The mitochondrial morphology in HCC cells was evaluated by fluorescent staining. The expression of protein was determined by real-time PCR, iimmunohistochemistry and Western blotting. RESULTS: Activation of mitochondrial fission significantly promoted de novo fatty acid synthesis in HCC cells through upregulating the expression of lipogenic genes fatty acid synthase (FASN), acetyl-CoA carboxylase1 (ACC1), and elongation of very long chain fatty acid protein 6 (ELOVL6), while suppressed fatty acid oxidation by downregulating carnitine palmitoyl transferase 1A (CPT1A) and acyl-CoA oxidase 1 (ACOX1). Consistently, suppressed mitochondrial fission exhibited the opposite effects. Moreover, in vitro and in vivo studies revealed that mitochondrial fission-induced lipid metabolism reprogramming significantly promoted the proliferation and metastasis of HCC cells. Mechanistically, mitochondrial fission increased the acetylation level of sterol regulatory element-binding protein 1 (SREBP1) and peroxisome proliferator-activated receptor coactivator 1 alpha (PGC-1α) by suppressing nicotinamide adenine dinucleotide (NAD+)/Sirtuin 1 (SIRT1) signaling. The elevated SREBP1 then upregulated the expression of FASN, ACC1 and ELOVL6 in HCC cells, while PGC-1α/PPARα suppressed the expression of CPT1A and ACOX1. CONCLUSIONS: Increased mitochondrial fission plays a crucial role in the reprogramming of lipid metabolism in HCC cells, which provides strong evidence for the use of this process as a drug target in the treatment of this malignancy.

Mitochondrial fragmentation is crucial for c-Myc-driven hepatoblastoma-like liver tumors.

Hepatoblastoma is the most common liver cancer in children, and the aggressive subtype often has a poor prognosis and lacks effective targeted therapy. Although aggressive hepatoblastoma (HB) is often accompanied by abnormally high expression of the transcription factor c-Myc, the underlying mechanism remains unclear. In this study, we found that mitochondrial fragmentation was enhanced by c-Myc overexpression in human aggressive HB tissues and was associated with poor prognosis. Then, a mouse model resembling human HB was established via hydrodynamic injection of c-Myc plasmids. We observed that liver-specific knockout of the mitochondrial fusion molecule MFN1 or overexpression of mitochondrial fission molecule DRP1 promoted the occurrence of c-Myc-driven liver cancer. In contrast, when MFN1 was overexpressed in the liver, tumor formation was delayed. In vitro experiments showed that c-Myc transcriptionally upregulated the expression of DRP1 and decreased MFN1 expression through upregulation of miR-373-3p. Moreover, enhanced mitochondrial fragmentation significantly promoted aerobic glycolysis and the proliferation of HB cells by significantly increasing reactive oxygen species (ROS) production and activating the RAC-alpha serine/threonine-protein kinase (AKT)/mammalian target of rapamycin (mTOR) and nuclear factor κB (NF-κB) pathways. Taken together, our results indicate that c-Myc-mediated mitochondrial fragmentation promotes the malignant transformation and progression of HB by activating ROS-mediated multi-oncogenic signaling.

Low Expression of Phosphodiesterase 2 (PDE2A) Promotes the Progression by Regulating Mitochondrial Morphology and ATP Content and Predicts Poor Prognosis in Hepatocellular Carcinoma.

Phosphodiesterase 2 (PDE2A) modulates the levels of cAMP/cGMP and was recently found to be involved in mitochondria function regulation, closely related to multiple types of tumor progression. This study aimed to estimate the prognostic significance and biological effects of PDE2A on hepatocellular carcinoma (HCC). We comprehensively analyzed the PDE2A mRNA expression in HCC based on The Cancer Genome Atlas (TCGA) database and investigated the effects of PDE2A on the proliferation and metastatic capacity of HCC cells. PDE2A was downregulated in 25 cancer types, including HCC. Lower PDE2A expression was a protective factor in HCC and was negatively associated with serum AFP levels, tumor status, vascular invasion, histologic grade, and pathologic stage of HCC. Moreover, tumors with low PDE2A expression displayed a decreased immune function. Then, the ROC curve was used to assess the diagnostic ability of PDE2A in HCC (AUC = 0.823 in TCGA and AUC = 0.901 in GSE76427). Patients with low PDE2A expression exhibited worse outcomes compared with those with high PDE2A expression. Additionally, GO functional annotations demonstrated the involvement of PDE2A in the ECM organization, systems development, and ERK-related pathways, indicating that PDE2A might regulate HCC growth and metastasis. The in vitro experiments confirmed that overexpression of PDE2A inhibited proliferation, colony formation, migration, and invasion in two HCC cell lines (HLF and SNU-368), while inhibition of PDE2A has the opposite results. The mechanism of PDE2A's effect on HCC cells is attributed to the change of mitochondrial morphology and ATP content. These data demonstrated that PDE2A closely participated in the regulation of HCC proliferation and metastasis and can be used as a predictive marker candidate and a potential therapeutic target for HCC.