Evidence map›Paper›PMID 38671580›Full record

ArticleMolecular oncology2024

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer.

Thomas Fleischer, Mads Haugland Haugen, Jørgen Ankill, Laxmi Silwal-Pandit, Anne-Lise Børresen-Dale, Ingrid Hedenfalk, Thomas Hatschek, Jörg Tost, Olav Engebraaten, Vessela N Kristensen

Open access · goldAbstract read
In one paragraph

Article in Molecular oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

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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

10 authors at 4 institutions in 3 countries.

Thomas FleischerDepartment of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.ORCID 0000-0003-0985-8460
Mads Haugland HaugenDepartment of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.ORCID 0000-0002-7143-2594
Jørgen AnkillDepartment of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.ORCID 0000-0002-5752-0299
Laxmi Silwal-PanditDepartment of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
Anne-Lise Børresen-DaleDepartment of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
Ingrid HedenfalkDivision of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden.
Thomas HatschekBreast Cancer Center, Karolinska University Hospital, Stockholm, Sweden.
Jörg TostLaboratory for Epigenetics and Environment, Centre National de Recherche en Génomique Humaine, CEA - Institut de Biologie François Jacob, Université Paris Saclay, Evry, France.
Olav EngebraatenDepartment of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
Vessela N KristensenInstitute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
Oslo University Hospital · NOCommissariat à l'Énergie Atomique et aux Énergies Alternatives · FRKarolinska University Hospital · SELund University · SE

Funding

Helse Sør-Øst RHF 2017065Helse Sør-Øst RHF 2019081Helse Sør-Øst RHF 2020031K. G. Jebsen Center for Breast Cancer ResearchKreftforeningen 11003001Norges Forskningsråd 191436/V50Roche NorwaySanofi-Aventis Norway
6 · The paper itself

Abstract

Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression-methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.

Indexed as

BevacizumabBreast NeoplasmsDNA MethylationEpigenesis, GeneticNeoadjuvant TherapyFemaleGene Expression Regulation, NeoplasticHumansMiddle AgedProteomicsBevacizumabbevacizumabbreast cancerchemotherapyDNA methylationepigeneticsmultiomics

Identifiers

PMID38671580
PMCPMC11306529
OpenAlexW4395693531

What OpenQuestion holds

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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.