Evidence map›Paper›PMID 34101077›Full record

ArticleBreast cancer research and treatment2021

Pre-diagnostic DNA methylation patterns differ according to mammographic breast density amongst women who subsequently develop breast cancer: a case-only study in the EPIC-Florence cohort.

Saverio Caini, Giovanni Fiorito, Domenico Palli, Benedetta Bendinelli, Silvia Polidoro, Valentina Silvestri, Laura Ottini, Daniela Ambrogetti, Ines Zanna, Calogero Saieva and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Breast cancer research and treatment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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

11 authors at 4 institutions in 3 countries.

Saverio Caini *Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy.
Giovanni Fiorito *Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
Domenico PalliInstitute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy. d.palli@ispro.toscana.it.ORCID http://orcid.org/0000-0002-5558-2437
Benedetta BendinelliInstitute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy.
Silvia PolidoroDepartment of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College, London, UK.
Valentina SilvestriDepartment of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
Laura OttiniDepartment of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
Daniela AmbrogettiInstitute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy.
Ines ZannaInstitute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy.
Calogero SaievaInstitute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy.
Giovanna MasalaInstitute for Cancer Research, Prevention and Clinical Network (ISPRO), Via Cosimo il Vecchio 2, 50141, Florence, Italy.
Sapienza University of Rome · ITItalian institute for Genomic Medicine · ITPrevention Institute · USUniversity of Sassari · IT

Funding

Associazione Italiana per la Ricerca sul Cancro AIRC-IG 17146
6 · The paper itself

Abstract

purposeMammographic breast density (MBD) is a marker of increased breast cancer (BC) risk, yet much remains to be clarified about the underlying mechanisms. We investigated whether DNA methylation patterns differ between high- vs. low-MBD women who developed BC during an 8.9-year median follow-up in the Florence section of the European Prospective Investigation into Cancer and Nutrition.

methodsWe analysed 96 pairs of women with BC arising on high- vs. low-MBD breasts (BI-RADS category III-IV vs. I). DNA methylation was determined on pre-diagnostic blood samples using the Illumina Infinium MethylationEPIC BeadChip assay. The statistical analysis was conducted by performing an epigenome-wide association study (EWAS), by searching differentially methylated regions (DMRs) in gene promoters (followed by functional enrichment and gene annotation analysis); and through a "candidate pathways" approach focusing on pre-defined inflammation-related pathways.

resultsIn EWAS, no single CpG site was differentially methylated between high- and low-MBD women after correction for multiple testing. A total of 140 DMRs were identified, of which 131 were hyper- and 9 hypo-methylated amongst high-MBD women. These DMRs encompassed an annotation cluster of 35 genes coding for proteins implicated in transcription regulation and DNA binding. The "apoptosis signalling" was the only inflammation-related candidate pathway differentially methylated between high- and low-MBD women.

conclusionPre-diagnostic methylation patterns differ between high- vs. low-MBD women who subsequently develop BC, particularly, in genes involved in the regulation of DNA transcription and cell apoptosis. Our study provides novel clues about the mechanisms linking MBD and BC.

Indexed as

Breast DensityBreast NeoplasmsBreastCpG IslandsDNA MethylationEpigenesis, GeneticFemaleHumansProspective StudiesBreast cancerDifferentially methylated regionsDNA methylationEpigenome-wide association studyInflammation-related pathwaysMammographic breast density

Identifiers

PMID34101077
OpenAlexW3167995690

What OpenQuestion holds

Textmetadata
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.