Whole mitochondrial genome sequencing highlights mitochondrial impact in gastric cancer

Mitochondrial variants of complex I genes associated with leprosy clinical subtypes

Leprosy is a chronic bacterial infection mainly caused by Mycobacterium leprae that primarily affects skin and peripheral nerves. Due to its ability to absorb carbon from the host cell, the bacillus became dependent on energy production, mainly through oxidative phosphorylation. In fact, variations in genes of Complex I of oxidative phosphorylation encoded by mtDNA have been associated with several diseases in humans, including bacterial infections, which are possible influencers in the host response to leprosy. Here, we investigated the presence of variants in the mtDNA genes encoding Complex I regarding leprosy, as well as the analysis of their pathogenicity in the studied cohort. We found an association of 74 mitochondrial variants with either of the polar forms, Pole T (Borderline Tuberculoid) or Pole L (Borderline Lepromatous and Lepromatous) of leprosy. Notably, six variants were exclusively found in both clinical poles of leprosy, including m.4158A>G and m.4248T>C in MT-ND1, m.13650C>A, m.13674T>C, m.12705C>T and m.13263A>G in MT-ND5, of which there are no previous reports in the global literature. Our observations reveal a substantial number of mutations among different groups of leprosy, highlighting a diverse range of consequences associated with mutations in genes across these groups. Furthermore, we suggest that the six specific variants exclusively identified in the case group could potentially play a crucial role in leprosy susceptibility and its clinical differentiation. These variants are believed to contribute to the instability and dysregulation of oxidative phosphorylation during the infection, further emphasizing their significance.

Whole mitogenome sequencing uncovers a relation between mitochondrial heteroplasmy and leprosy severity

BACKGROUND

In recent years, the mitochondria/immune system interaction has been proposed, so that variants of mitochondrial genome and levels of heteroplasmy might deregulate important metabolic processes in fighting infections, such as leprosy.

METHODS

We sequenced the whole mitochondrial genome to investigate variants and heteroplasmy levels, considering patients with different clinical forms of leprosy and household contacts. After sequencing, a specific pipeline was used for preparation and bioinformatics analysis to select heteroplasmic variants.

RESULTS

We found 116 variants in at least two of the subtypes of the case group (Borderline Tuberculoid, Borderline Lepromatous, Lepromatous), suggesting a possible clinical significance to these variants. Notably, 15 variants were exclusively found in these three clinical forms, of which five variants stand out for being missense (m.3791T > C in MT-ND1, m.5317C > A in MT-ND2, m.8545G > A in MT-ATP8, m.9044T > C in MT-ATP6 and m.15837T > C in MT-CYB). In addition, we found 26 variants shared only by leprosy poles, of which two are characterized as missense (m.4248T > C in MT-ND1 and m.8027G > A in MT-CO2).

CONCLUSION

We found a significant number of variants and heteroplasmy levels in the leprosy patients from our cohort, as well as six genes that may influence leprosy susceptibility, suggesting for the first time that the mitogenome might be involved with the leprosy process, distinction of clinical forms and severity. Thus, future studies are needed to help understand the genetic consequences of these variants.

A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

BACKGROUND

Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis.

METHODS

Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes.

RESULTS

Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages.

CONCLUSIONS

These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Mitochondria in Mycobacterium Infection: From the Immune System to Mitochondrial Haplogroups

In humans, mitochondria play key roles in the regulation of cellular functions, such as the regulation of the innate immune response and are targets of several pathogenic viruses and bacteria. Mycobacteria are intracellular pathogens that infect cells important to the immune system of organisms and target mitochondria to meet their energy demands. In this review, we discuss the main mechanisms by which mitochondria regulate the innate immune response of humans to mycobacterial infection, especially those that cause tuberculosis and leprosy. Notably, the importance of mitochondrial haplogroups and ancestry studies for mycobacterial diseases is also discussed.

Mutational landscape of gastric adenocarcinoma in Latin America: A genetic approach for precision medicine

Latin-America (LATAM) is the second region in gastric cancer incidence; gastric adenocarcinoma (GA) represents 95% of all cases. We provide a mutational landscape of GA highlighting a) germline pathogenic variants associated with hereditary GA, b) germline risk variants associated with sporadic GA, and c) somatic variants present in sporadic GA in LATAM, and analyze how this landscape can be applied for precision medicine. We found that Brazil, Chile, Colombia, Mexico, Peru, and Venezuela are the countries with more published studies from LATAM explicitly related to GA. Our analysis displayed that different germline pathogenic variants for the CDH1 gene have been identified for hereditary GA in Brazilian, Chilean, Colombian, and Mexican populations. An increased risk of developing somatic GA is associated with the following germline risk variants: IL-4, IL-8, TNF-α, PTGS2, NFKB1, RAF1, KRAS and MAPK1 in Brazilian; IL-10 in Chilean; IL-10 in Colombian; EGFR and ERRB2 in Mexican, TCF7L2 and Chr8q24 in Venezuelan population. The path from mutational landscape to precision medicine requires four development levels: 1) Data compilation, 2) Data analysis and integration, 3) Development and approval of clinical approaches, and 4) Population benefits. Generating local genomic information is the initial padlock to overcome to generate and apply precision medicine.

Application of next-generation sequencing in the diagnosis of gastric cancer

Objectives: Gastric cancer (GC) is a disease with high mortality, poor prognosis and numerous risk factors. GC has an asymptomatic nature in early stages of the diseases, making timely diagnosis complicated using common conventional approaches, namely pathological examinations and imaging tests. Recently, molecular profiling of GC using next generation sequencing (NGS) has opened new doors to efficient prognostic, diagnostic, and therapeutic strategies. The current review aims to thoroughly discuss and compare the current NGS techniques and commercial platforms utilized for GC diagnosis and treatment, highlighting the most recent NGS-based GC studies. Furthermore, this review addresses the challenges of clinical implementation of NGS in GC.Materials and methods: This review was conducted according to the eligible studies identified via search of Web of Science, PubMed, Scopus, Embase and the Cochrane Library. In the present study, data on gastric cancer patients and NGS methods used to diagnose the disease were reviewed.Conclusion: Given the ever-rising advancements in NGS technologies, bioinformatics, healthcare guidelines and refined classifications, it is hoped that these technologies can actualize their advantages and optimize GC patients' experience.

Identification of Mitochondrial DNA Variants Associated With Risk of Neuroblastoma

Neuroblastoma is a childhood cancer that originates in the developing sympathetic nervous system. We previously reported a crucial role of mitochondrial DNA haplogroups in the pathology of neuroblastoma. To pinpoint mitochondrial DNA variants associated with neuroblastoma risk, we applied a mitochondrial genome imputation pipeline to the single nucleotide polymorphisms array data of 2 pediatric cohorts containing a total of 2404 neuroblastoma patients and 9310 cancer-free controls. All statistical tests were 2-sided. The single nucleotide variant, rs2853493, was statistically significantly associated with neuroblastoma risk in the discovery cohort (odds ratio = 0.62, 95% confidence interval = 0.53 to 0.72, P < .001) and further confirmed in the replication cohort (odds ratio = 0.75, 95% confidence interval = 0.62 to 0.90, P = .002). Further, expression quantitative trait loci analysis indicated genotypes of rs2853493 were associated with expression levels of MT-CYB gene expression in neuroblastoma cells, suggesting rs2853493 may confer risk to neuroblastoma via regulating the expression level of its nearby genes.

Benchmarking the Effectiveness and Accuracy of Multiple Mitochondrial DNA Variant Callers: Practical Implications for Clinical Application

Mitochondrial DNA (mtDNA) mutations contribute to human disease across a range of severity, from rare, highly penetrant mutations causal for monogenic disorders to mutations with milder contributions to phenotypes. mtDNA variation can exist in all copies of mtDNA or in a percentage of mtDNA copies and can be detected with levels as low as 1%. The large number of copies of mtDNA and the possibility of multiple alternative alleles at the same DNA nucleotide position make the task of identifying allelic variation in mtDNA very challenging. In recent years, specialized variant calling algorithms have been developed that are tailored to identify mtDNA variation from whole-genome sequencing (WGS) data. However, very few studies have systematically evaluated and compared these methods for the detection of both homoplasmy and heteroplasmy. A publicly available synthetic gold standard dataset was used to assess four mtDNA variant callers (Mutserve, mitoCaller, MitoSeek, and MToolBox), and the commonly used Genome Analysis Toolkit “best practices” pipeline, which is included in most current WGS pipelines. We also used WGS data from 126 trios and calculated the percentage of maternally inherited variants as a metric of calling accuracy, especially for homoplasmic variants. We additionally compared multiple pathogenicity prediction resources for mtDNA variants. Although the accuracy of homoplasmic variant detection was high for the majority of the callers with high concordance across callers, we found a very low concordance rate between mtDNA variant callers for heteroplasmic variants ranging from 2.8% to 3.6%, for heteroplasmy thresholds of 5% and 1%. Overall, Mutserve showed the best performance using the synthetic benchmark dataset. The analysis of mtDNA pathogenicity resources also showed low concordance in prediction results. We have shown that while homoplasmic variant calling is consistent between callers, there remains a significant discrepancy in heteroplasmic variant calling. We found that resources like population frequency databases and pathogenicity predictors are now available for variant annotation but still need refinement and improvement. With its peculiarities, the mitochondria require special considerations, and we advocate that caution needs to be taken when analyzing mtDNA data from WGS data.

Mitochondria in tumour progression: a network of mtDNA variants in different types of cancer

Background

Mitochondrial participation in tumorigenesis and metastasis has been studied for many years, but several aspects of this mechanism remain unclear, such as the association of mitochondrial DNA (mtDNA) with different cancers. Here, based on two independent datasets, we modelled an mtDNA mutation-cancer network by systematic integrative analysis including 37 cancer types to identify the mitochondrial variants found in common among them.

Results

Our network showed mtDNA associations between gastric cancer and other cancer types, particularly kidney, liver, and prostate cancers, which is suggestive of a potential role of such variants in the metastatic processes among these cancer types. A graph-based interactive web tool was made available at www2.lghm.ufpa.br/mtdna. We also highlighted that most shared variants were in the MT-ND4, MT-ND5 and D-loop, and that some of these variants were nonsynonymous, indicating a special importance of these variants and regions regarding cancer progression, involving genomic and epigenomic alterations.

Conclusions

This study reinforces the importance of studying mtDNA in cancer and offers new perspectives on the potential involvement of different mitochondrial variants in cancer development and metastasis.

Downregulation of lncRNA ZNF582-AS1 due to DNA hypermethylation promotes clear cell renal cell carcinoma growth and metastasis by regulating the N(6)-methyladenosine modification of MT-RNR1

Background

Emerging evidence confirms that lncRNAs (long non-coding RNAs) are potential biomarkers that play vital roles in tumors. ZNF582-AS1 is a novel lncRNA that serves as a potential prognostic marker of cancers. However, the specific clinical significance and molecular mechanism of ZNF582-AS1 in ccRCC (clear cell renal cell carcinoma) are unclear.

Methods

Expression level and clinical significance of ZNF582-AS1 were determined by TCGA-KIRC data and qRT-PCR results of 62 ccRCCs. DNA methylation status of ZNF582-AS1 promoter was examined by MSP, MassARRAY methylation and demethylation analysis. Gain-of-function experiments were conducted to investigate the biological roles of ZNF582-AS1 in the phenotype of ccRCC. The subcellular localization of ZNF582-AS1 was detected by RNA FISH. iTRAQ, RNA pull-down and RIP-qRT-PCR were used to identify the downstream targets of ZNF582-AS1. rRNA MeRIP-seq and MeRIP-qRT-PCR were utilized to examine the N(6)-methyladenosine modification status. Western blot and immunohistochemistry assays were used to determine the protein expression level.

Results

ZNF582-AS1 was downregulated in ccRCC, and decreased ZNF582-AS1 expression was significantly correlated with advanced tumor stage, higher pathological stage, distant metastasis and poor prognosis. Decreased ZNF582-AS1 expression was caused by DNA methylation at the CpG islands within its promoter. ZNF582-AS1 overexpression inhibited cell proliferative, migratory and invasive ability, and increased cell apoptotic rate in vitro and in vivo. Mechanistically, we found that ZNF582-AS1 overexpression suppressed the N(6)-methyladenosine modification of MT-RNR1 by reducing rRNA adenine N(6)-methyltransferase A8K0B9 protein level, resulting in the decrease of MT-RNR1 expression, followed by the inhibition of MT-CO2 protein expression. Furthermore, MT-RNR1 overexpression reversed the decreased MT-CO2 expression and phenotype inhibition of ccRCC induced by increased ZNF582-AS1 expression.

Conclusions

This study demonstrates for the first time that ZNF582-AS1 functions as a tumor suppressor gene in ccRCC and ZNF582-AS1 may serve as a potential biomarker and therapeutic target of ccRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01889-8.

Monoamine Oxidase A is a Major Mediator of Mitochondrial Homeostasis and Glycolysis in Gastric Cancer Progression

Objective

Monoamine oxidase A (MAO-A) is a mitochondrial protein involved in tumourigenesis in different types of cancer. However, the biological function of MAO-A in gastric cancer development remains unknown.

Methods

We examined MAO-A expression in gastric cancer tissues and in gastric cancer cell lines by immunohistochemistry and Western blot analyses. CCK8, FACS and bromodeoxyuridine incorporation assays were performed to assess the effects of MAO-A on gastric cancer cell proliferation. The role of MAO-A in mitochondrial function was determined through MitoSOX Red staining, ATP generation and glycolysis assays.

Results

In the present study, we observed that MAO-A was significantly upregulated in gastric cancer tissues and in AGS and MGC803 cells. The observed MAO-A inhibition indicated decreased cell cycle progression and proliferation. Silencing MAO-A expression was associated with suppressed migration and invasion of gastric cancer cells in vitro. Moreover, alleviated mitochondrial damage in these cells was demonstrated by decreased levels of mitochondrial reactive oxygen species and increased ATP generation. MAO-A knockdown also regulated the expression of the glycolysis rate-limiting enzymes hexokinase 2 and pyruvate dehydrogenase. Finally, we observed that the glycolysis-mediated effect was weakened in AGS and MGC803 cells when MAO-A was blocked.

Conclusion

The findings of the present study indicate that MAO-A is responsible for mitochondrial dysfunction and aerobic glycolysis, which in turn leads to the proliferation and metastasis of human gastric tumour cells.

Complexities and pitfalls in analyzing and interpreting mitochondrial DNA content in human cancer

Mutations in the human mitochondrial genome have been observed in all types of human cancer, indicating that mutations might contribute to tumorigenesis, metastasis, recurrence, or drug response. This possibility is appealing because of the known shift from oxidative metabolism to glycolysis, known as the Warburg effect, that occurs in malignancy. Mitochondrial DNA (mtDNA) mutations could either be maternally inherited and predispose to cancer (germ line mutations) or occur sporadically in the mtDNA of specific tissues (tissue- or tumor-specific somatic mutations) and contribute to the tumor initiation and progression process. High-throughput sequencing technologies now enable comprehensive detection of mtDNA variation in tissues and bodily fluids, with the potential to be used as an early detection tool that may impact the treatment of cancer. Here, we discuss insights into the roles of mtDNA mutations in carcinogenesis, highlighting the complexities involved in the analysis and interpretation of mitochondrial genomic content, technical challenges in studying their contribution to pathogenesis, and the value of mtDNA mutations in developing early detection, diagnosis, prognosis, and therapeutic strategies for cancer.