Evidence map›Paper›PMID 25407022›Full record

ArticleBMC cancer2014

Increased coagulation activity and genetic polymorphisms in the F5, F10 and EPCR genes are associated with breast cancer: a case-control study.

Mari Tinholt, Marte Kathrine Viken, Anders Erik Dahm, Hans Kristian Moen Vollan, Kristine Kleivi Sahlberg, Oystein Garred, Anne-Lise Børresen-Dale, Anne Flem Jacobsen, Vessela Kristensen, Ida Bukholm and 6 more

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

25 citing papers in PubMed, 42 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. The association between two genetic polymorphisms inSaudi journal of biological sciences · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Identification ofBioMed research international · 2020
    Article
  18. Article
  19. Observational
  20. Review
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

16 authors at 4 institutions in 2 countries.

Mari Tinholt
Marte Kathrine Viken
Anders Erik Dahm
Hans Kristian Moen Vollan
Kristine Kleivi Sahlberg
Oystein Garred
Anne-Lise Børresen-Dale
Anne Flem Jacobsen
Vessela Kristensen
Ida Bukholm
Rolf Kåresen
Ellen Schlichting
Grethe Skretting
Benedicte Alexandra Lie
Per Morten Sandset
Nina IversenDepartment of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway. nina.iversen@medisin.uio.no.
Oslo University Hospital · NOUniversity of Oslo · NOBreast Cancer Research Foundation · USAkershus University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe procoagulant state in cancer increases the thrombotic risk, but also supports tumor progression. To investigate the molecular mechanisms controlling cancer and hemostasis, we conducted a case-control study of genotypic and phenotypic variables of the tissue factor (TF) pathway of coagulation in breast cancer.

methods366 breast cancer patients and 307 controls were genotyped for SNPs (n = 41) in the F2, F3 (TF), F5, F7, F10, TFPI and EPCR genes, and assayed for plasma coagulation markers (thrombin generation, activated protein C (APC) resistance, D-dimer, antithrombin, protein C, protein S, and TF pathway inhibitor (TFPI)). Associations with breast cancer were evaluated using logistic regression to obtain odds ratios (ORs) and 95% confidence intervals (CIs), or the chi-square test.

resultsFour SNPs in F5 (rs12120605, rs6427202, rs9332542 and rs6427199), one in F10 (rs3093261), and one in EPCR (rs2069948) were associated with breast cancer. EPCR rs2069948 was associated with estrogen receptor (ER) and progesterone receptor (PR) positivity, while the SNPs in F5 appeared to follow hormone receptor negative and triple negative patients. The prothrombotic polymorphisms factor V Leiden (rs6025) and prothrombin G20210A (rs1799963) were not associated with breast cancer. High APC resistance was associated with breast cancer in both factor V Leiden non-carriers (OR 6.5, 95% CI 4.1-10.4) and carriers (OR 38.3, 95% CI 6.2-236.6). The thrombin parameters short lag times (OR 5.8, 95% CI 3.7-9.2), short times to peak thrombin (OR 7.1, 95% CI 4.4-11.3), and high thrombin peak (OR 6.1, 95% CI 3.9-9.5) predicted presence of breast cancer, and high D-dimer also associated with breast cancer (OR 2.0, 95% CI 1.3-3.3). Among the coagulation inhibitors, low levels of antithrombin associated with breast cancer (OR 5.7, 95% CI 3.6-9.0). The increased coagulability was not explained by the breast cancer associated SNPs, and was unaffected by ER, PR and triple negative status.

conclusionsA procoagulant phenotype was found in the breast cancer patients. Novel associations with SNPs in F5, F10 and EPCR to breast cancer susceptibility were demonstrated, and the SNPs in F5 were confined to hormone receptor negative and triple negative patients. The study supports the importance of developing new therapeutic strategies targeting coagulation processes in cancer.

Indexed as

Polymorphism, GeneticAdultAgedAged, 80 and overAllelesAntigens, CDBlood CoagulationBreast NeoplasmsCase-Control StudiesEndothelial Protein C ReceptorFactor VFactor XFemaleGenetic Association StudiesGenetic Predisposition to DiseaseHaplotypesAntigens, CDEndothelial Protein C ReceptorFactor VFactor XPROCR protein, humanReceptors, Cell SurfaceThromboplastin

Identifiers

PMID25407022
PMCPMC4251949
OpenAlexW2082791534

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.