Evidence map›Paper›PMID 28684774›Full record

ArticleScientific reports2017

Tumoral expression of drug and xenobiotic metabolizing enzymes in breast cancer patients of different ethnicities with implications to personalized medicine.

Yan Li, Albert Steppi, Yidong Zhou, Feng Mao, Philip Craig Miller, Max M He, Tingting Zhao, Qiang Sun, Jinfeng Zhang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

36 citing papers in PubMed, 57 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Breast Cancer Exposomics.Life (Basel, Switzerland) · 2024
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Eligibility Criteria Perpetuate Disparities in Enrollment and Participation of Black Patients in Pancreatic Cancer Clinical Trials.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
    Article
  17. Can Exposure to Environmental Pollutants Be Associated with Less Effective Chemotherapy in Cancer Patients?International journal of environmental research and public health · 2022
    Review
  18. Article
  19. Article
  20. Article
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

9 authors at 5 institutions in 2 countries.

Yan LiDepartment of Breast Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Albert SteppiDepartment of Statistics, Florida State University, Tallahassee, FL, 32306, USA.
Yidong ZhouDepartment of Breast Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Feng MaoDepartment of Breast Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Philip Craig MillerUniversity of Miami Miller School of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL, 33136, USA.
Max M HeCenter for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI, 54449, USA.
Tingting ZhaoDepartment of Geography, Florida State University, Tallahassee, FL, 32306, USA.
Qiang SunDepartment of Breast Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China. sunqiangpumch@126.com.
Jinfeng ZhangDepartment of Statistics, Florida State University, Tallahassee, FL, 32306, USA. jinfeng@stat.fsu.edu.
Florida State University · USChinese Academy of Medical Sciences & Peking Union Medical College · CNPeking Union Medical College Hospital · CNCenter for Human Genetics · USUniversity of Miami · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug and xenobiotic metabolizing enzymes (DXME) play important roles in drug responses and carcinogenesis. Recent studies have found that expression of DXME in cancer cells significantly affects drug clearance and the onset of drug resistance. In this study we compared the expression of DXME in breast tumor tissue samples from patients representing three ethnic groups: Caucasian Americans (CA), African Americans (AA), and Asian Americans (AS). We further combined DXME gene expression data with eQTL data from the GTEx project and with allele frequency data from the 1000 Genomes project to identify SNPs that may be associated with differential expression of DXME genes. We identified substantial differences among CA, AA, and AS populations in the expression of DXME genes and in activation of pathways involved in drug metabolism, including those involved in metabolizing chemotherapy drugs that are commonly used in the treatment of breast cancer. These data suggest that differential expression of DXME may associate with health disparities in breast cancer outcomes observed among these three ethnic groups. Our study suggests that development of personalized treatment strategies for breast cancer patients could be improved by considering both germline genotypes and tumor specific mutations and expression profiles related to DXME genes.

Indexed as

Gene Expression Regulation, NeoplasticAllelesAntineoplastic AgentsAsian PeopleBlack or African AmericanBlack PeopleBreast NeoplasmsCytochrome P-450 Enzyme SystemDatabases, FactualFemaleGene FrequencyHealthcare DisparitiesHumansInactivation, MetabolicNeoplasm ProteinsNeoplasm StagingAntineoplastic AgentsCytochrome P-450 Enzyme SystemNeoplasm ProteinsXenobiotics

Identifiers

PMID28684774
PMCPMC5500564
OpenAlexW2733369216

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.