The Landscape of mtDNA Modifications in Cancer: A Tale of Two Cities

Hertweck, Kate L.; Dasgupta, Santanu

doi:10.3389/fonc.2017.00262

“…As an easily measurable and accessible proxy for mitochondrial function, mitochondrial DNA copy number (mtDNA-CN) is increasingly used to assess the role of mitochondria in disease. Several population-based studies have shown higher levels of mtDNA-CN to be associated with decreased incidence for CVD and its component parts: coronary artery disease (CAD) and stroke 2,3 ; neurodegenerative disorders such as Parkinson's and Alzheimer's 4,5 ; as well as several types of cancer including breast, kidney, liver and colorectal [6][7][8] . Furthermore, mtDNA-CN measured from peripheral blood has consistently been shown to be higher in women, decline with age, and correlate negatively with white blood cell (WBC) count [9][10][11] .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of mitochondrial DNA copy number estimation techniques

Longchamps¹,

Castellani²,

Newcomb³

et al. 2019

Preprint

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Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10 -4 ) and silica-based column selection (p = 2.82x10 -7 ). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed.Δ Ct values >3 standard deviations from the mean of the plate. Outlier replicates were identified and excluded for samples with a Δ Ct standard deviation >0.5. The sample was excluded if the Δ Ct standard deviation remained >0.5 after replicate removal. We

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“…As an easily measurable and accessible proxy for mitochondrial function, mitochondrial DNA copy number (mtDNA-CN) is increasingly used to assess the role of mitochondria in disease. Several population-based studies have shown higher levels of mtDNA-CN to be associated with decreased incidence for CVD and its component parts: coronary artery disease (CAD) and stroke [2,3]; neurodegenerative disorders such as Parkinson's and Alzheimer's [4,5]; as well as several types of cancer including breast, kidney, liver and colorectal [6][7][8]. Furthermore, mtDNA-CN measured from peripheral blood has consistently been shown to be higher in women, decline with age, and correlate negatively with white blood cell (WBC) count [9][10][11].…”

mentioning

confidence: 99%

Evaluation of mitochondrial DNA copy number estimation techniques

Longchamps

¹

,

Castellani

²

,

Yang

³

et al. 2020

View full text Add to dashboard Cite

Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10 -4 ) and silica-based column selection (p = 2.82x10 -7 ). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed.

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“…[43], Hertweck et al . [44], as well as the MITOMAP database [45] for readers interested in potential mtDNA drivers of cancer. For example, some reports suggest that the mutational frequency was higher within the hypervariable D-Loop [25,46–48].…”

Section: Mitochondrial Dna and Cancermentioning

confidence: 99%

Roles of the mitochondrial genetics in cancer metastasis: not to be ignored any longer

Beadnell

¹

,

Scheid

²

,

Vivian

³

et al. 2018

Cancer Metastasis Rev

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Mitochondrial DNA (mtDNA) encodes for only a fraction of the proteins that are encoded within the nucleus, and therefore has typically been regarded as a lesser player in cancer biology and metastasis. Accumulating evidence, however, supports an increased role for mtDNA impacting tumor progression and metastatic susceptibility. Unfortunately, due to this delay, there is a dearth of data defining the relative contributions of specific mtDNA polymorphisms (SNP), which leads to an inability to effectively use these polymorphisms to guide and enhance therapeutic strategies and diagnosis. In addition, evidence also suggests that differences in mtDNA impact not only the cancer cells, but also the cells within the surrounding tumor microenvironment, suggesting a broad encompassing role for mtDNA polymorphisms in regulating the disease progression. mtDNA may have profound implications in the regulation of cancer biology and metastasis. However, there are still great lengths to go to understand fully its contributions. Thus, herein we discuss the recent advances in our understanding of mtDNA in cancer and metastasis, providing a framework for future functional validation and discovery.

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The Landscape of mtDNA Modifications in Cancer: A Tale of Two Cities

Cited by 68 publications

References 134 publications

Evaluation of mitochondrial DNA copy number estimation techniques

Evaluation of mitochondrial DNA copy number estimation techniques

Evaluation of mitochondrial DNA copy number estimation techniques

Roles of the mitochondrial genetics in cancer metastasis: not to be ignored any longer

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