bims-cytox1 Biomed News
on Cytochrome oxidase subunit 1
Issue of 2017‒08‒06
four papers selected by
Gavin McStay
New York Institute of Technology

  1. Semin Cancer Biol. 2017 Jul 25. pii: S1044-579X(17)30192-X. [Epub ahead of print]
      As up to a fifth of all cancers worldwide, have now been linked to microbial infections, it is essential to understand the carcinogenic nature of the bacterial/host interaction. This paper reviews the bacterial targeting of mediators of mitochondrial genomic fidelity and of mitochondrial apoptotic pathways, and compares the impact of the bacterial alteration of mitochondrial function to that of cancer. Bacterial virulence factors have been demonstrated to induce mutations of mitochondrial DNA (mtDNA) and to modulate DNA repair pathways of the mitochondria. Furthermore, virulence factors can induce or impair the intrinsic apoptotic pathway. The effect of bacterial targeting of mitochondria is analogous to behavior of mitochondria in a wide array of tumours, and this strongly suggests that mitochondrial targeting of bacteria is a risk factor for carcinogenesis.
    Keywords:  Bacterial infection; Cancer; DNA repair; Microbiome; Mitochondrial function; Mitochondrial targeting; Mutations
  2. J Med Genet. 2017 Jul 28. pii: jmedgenet-2017-104615. [Epub ahead of print]
      BACKGROUND: Mitochondrial DNA (mtDNA) disorders have a high clinical variability, mainly explained by variation of the mutant load across tissues. The high recurrence risk of these serious diseases commonly results in requests from at-risk couples for prenatal diagnosis (PND), based on determination of the mutant load on a chorionic villous sample (CVS). Such procedures are hampered by the lack of data regarding mtDNA segregation in the placenta.The objectives of this report were to determine whether mutant loads (1) are homogeneously distributed across the whole placentas, (2) correlate with those in amniocytes and cord blood cells and (3) correlate with the mtDNA copy number.METHODS: We collected 11 whole placentas carrying various mtDNA mutations (m.3243A>G, m.8344A>G, m.8993T>G, m.9185T>C and m.10197G>A) and, when possible, corresponding amniotic fluid samples (AFSs) and cord blood samples. We measured mutant loads in multiple samples from each placenta (n= 6-37), amniocytes and cord blood cells, as well as total mtDNA content in placenta samples.
    RESULTS: Load distribution was homogeneous at the sample level when average mutant load was low (<20%) or high (>80%) at the whole placenta level. By contrast, a marked heterogeneity was observed (up to 43%) in the intermediate range (20%-80%), the closer it was to 40%-50% the mutant load, the wider the distribution. Mutant loads were found to be similar in amniocytes and cord blood cells, at variance with placenta samples. mtDNA content correlated to mutant load in m.3243A>G placentas only.
    CONCLUSION: These data indicate that (1) mutant load determined from CVS has to be interpreted with caution for PND of some mtDNA disorders and should be associated with/substituted by a mutant load measurement on amniocytes; (2) the m.3243A>G mutation behaves differently from other mtDNA mutations with respect to the impact on mtDNA copy number, as previously shown in human preimplantation embryogenesis.
    Keywords:  mitochondria; mitochondrial DNA; mtDNA mutations; placenta; prenatal diagnosis
  3. Oncotarget. 2017 Jul 27.
      Here, we used a data-mining and informatics approach to discover new biomarkers of resistance to hormonal therapy in breast cancer. More specifically, we investigated whether nuclear-encoded genes associated with mitochondrial biogenesis can be used to predict tumor recurrence, distant metastasis and treatment failure in high-risk breast cancer patients. Overall, this strategy allowed us to directly provide in silico validation of the prognostic value of these mitochondrial components in large and clinically relevant patient populations, with >15 years of follow-up data. For this purpose, we employed a group of 145 ER(+) luminal A breast cancer patients, with lymph-node (LN) metastasis at diagnosis, that were treated with tamoxifen, but not any chemotherapy agents. Using this approach, we identified >60 new individual mitochondrial biomarkers that predicted treatment failure and tumor recurrence, with hazard-ratios (HR) of up to 4.17 (p=2.2e-07). These include mitochondrial chaperones (HSPD1, HSPA9), membrane proteins (VDAC2, TOMM70A) and anti-oxidants (SOD2), as well as 18 different mitochondrial ribosomal proteins (MRPs) and >20 distinct components of the OXPHOS complexes. In addition, we combined 4 mitochondrial proteins (HSPD1, UQCRB, MRPL15, COX17), to generate a compact mitochondrial gene signature, associated with a HR of 5.34 (p=1e-09). This signature also successfully predicted distant metastasis and was effective in larger groups of ER(+) (N=2,447), basal (N=540) and HER2(+) (N=193) breast cancers. It was also effective in all breast cancers (N=3,180), if considered together as a single group. Based on this analysis, we conclude that mitochondrial biogenesis should be considered as a new therapeutic target for overcoming tumor recurrence, distant metastasis and treatment failure in patients with breast cancer. In summary, we identified individual mitochondrial biomarkers and 2 compact mitochondrial gene signatures that can be used to predict tamoxifen-resistance and tumor recurrence, at their initial diagnosis, in patients with advanced breast cancer. In the long-term, these mitochondrial biomarkers could provide a new companion diagnostics platform to help clinicians to accurately predict the response to hormonal therapy in ER(+) breast cancer patients, facilitating more personalized and effective treatment. Similarly, these mitochondrial markers could be used as companion diagnostics, to determine which breast cancer patients would benefit most from clinical treatments with mitochondrially-targeted anti-cancer therapeutics. Finally, we also showed that these mitochondrial markers are superior when directly compared with conventional biomarkers, such as Ki67 and PCNA.
    Keywords:  biomarkers; mitochondria; mitochondrial biogenesis; relapse; treatment failure
  4. J Theor Biol. 2017 Jul 25. pii: S0022-5193(17)30344-2. [Epub ahead of print]
      Lynn Sagan's conjecture (1967) that three of the fundamental organelles observed in eukaryote cells, specifically mitochondria, plastids and flagella were once free-living primitive (prokaryotic) cells was accepted after considerable opposition. Even though the idea was swiftly refuted for the specific case of origins of flagella in eukaryotes, the symbiosis model in general was accepted for decades as a realistic hypothesis to describe the endosymbiotic origins of eukaryotes. However, a systematic analysis of the origins of the mitochondrial proteome based on empirical genome evolution models now indicates that 97% of modern mitochondrial protein domains as well their homologues in bacteria and archaea were present in the universal common ancestor (UCA) of the modern tree of life (ToL). These protein domains are universal modular building blocks of modern genes and genomes, each of which is identified by a unique tertiary structure and a specific biochemical function as well as a characteristic sequence profile. Further, phylogeny reconstructed from genome-scale evolution models reveals that Eukaryotes and Akaryotes (archaea and bacteria) descend independently from UCA. That is to say, Eukaryotes and Akaryotes are both primordial lineages that evolved in parallel. Finally, there is no indication of massive inter-lineage exchange of coding sequences during the descent of the two lineages. Accordingly, we suggest that the evolution of the mitochondrial proteome was autogenic (endogenic) and not endosymbiotic (exogenic).