Evidence map›Paper›PMID 18834532›Full record

ArticleBMC cancer2008

Performance of mitochondrial DNA mutations detecting early stage cancer.

John P Jakupciak, Samantha Maragh, Maura E Markowitz, Alissa K Greenberg, Mohammad O Hoque, Anirban Maitra, Peter E Barker, Paul D Wagner, William N Rom, Sudhir Srivastava and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 69 citations in OpenAlex.

  1. Article
  2. Roles of Mitochondrial DNA Damage in Kidney Diseases: A New Biomarker.International journal of molecular sciences · 2022
    Review
  3. Article
  4. Review
  5. Detection of novel mitochondrial mutations in cytochrome C oxidase subunit 1 (COX1) in patients with familial adenomatous polyposis (FAP).Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020
    Article
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  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Mitochondria and cancer: past, present, and future.BioMed research international · 2013
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 2 countries.

John P JakupciakBiochemical Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA. johnjakupciak@verizon.net
Samantha Maragh
Maura E Markowitz
Alissa K Greenberg
Mohammad O Hoque
Anirban Maitra
Peter E Barker
Paul D Wagner
William N Rom
Sudhir Srivastava
David Sidransky
Catherine D O'Connell
Johns Hopkins University · USNational Cancer Institute · USNational Institute of Standards · EGNational Institute of Standards and Technology · USTetracore (United States) · US

Funding

NYU Lung Cancer Biomarker CenterU01CA086137 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ROM, WILLIAM N · 2000 to 2015
$15.3M
NCI NIH HHS U01 CA086137NCI NIH HHS UO1 CA86137NCI NIH HHS Y1CN2020NCI NIH HHS Y1CN5001-01
6 · The paper itself

Abstract

backgroundMutations in the mitochondrial genome (mtgenome) have been associated with cancer and many other disorders. These mutations can be point mutations or deletions, or admixtures (heteroplasmy). The detection of mtDNA mutations in body fluids using resequencing microarrays, which are more sensitive than other sequencing methods, could provide a strategy to measure mutation loads in remote anatomical sites.

methodsWe determined the mtDNA mutation load in the entire mitochondrial genome of 26 individuals with different early stage cancers (lung, bladder, kidney) and 12 heavy smokers without cancer. MtDNA was sequenced from three matched specimens (blood, tumor and body fluid) from each cancer patient and two matched specimens (blood and sputum) from smokers without cancer. The inherited wildtype sequence in the blood was compared to the sequences present in the tumor and body fluid, detected using the Affymetrix Genechip Human Mitochondrial Resequencing Array 1.0 and supplemented by capillary sequencing for noncoding region.

resultsUsing this high-throughput method, 75% of the tumors were found to contain mtDNA mutations, higher than in our previous studies, and 36% of the body fluids from these cancer patients contained mtDNA mutations. Most of the mutations detected were heteroplasmic. A statistically significantly higher heteroplasmy rate occurred in tumor specimens when compared to both body fluid of cancer patients and sputum of controls, and in patient blood compared to blood of controls. Only 2 of the 12 sputum specimens from heavy smokers without cancer (17%) contained mtDNA mutations. Although patient mutations were spread throughout the mtDNA genome in the lung, bladder and kidney series, a statistically significant elevation of tRNA and ND complex mutations was detected in tumors.

conclusionOur findings indicate comprehensive mtDNA resequencing can be a high-throughput tool for detecting mutations in clinical samples with potential applications for cancer detection, but it is unclear the biological relevance of these detected mitochondrial mutations. Whether the detection of tumor-specific mtDNA mutations in body fluidsy this method will be useful for diagnosis and monitoring applications requires further investigation.

Indexed as

MutationAdultAgedAged, 80 and overDNA, MitochondrialDNA, NeoplasmGenome, HumanGenome, MitochondrialHumansLung NeoplasmsMiddle AgedNeoplasmsNeoplasm StagingPolymerase Chain ReactionSequence Analysis, DNASmokingDNA, MitochondrialDNA, Neoplasm

Identifiers

PMID18834532
PMCPMC2572633
OpenAlexW2134637121

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.