Evidence map›Paper›PMID 39383060›Full record

ArticleeLife2024

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data.

Aurélie Anne-Gaëlle Gabriel, Julien Racle, Maryline Falquet, Camilla Jandus, David Gfeller

Abstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
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  4. Review
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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

5 authors.

Aurélie Anne-Gaëlle GabrielDepartment of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-0606-3622
Julien RacleDepartment of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-0100-0323
Maryline FalquetSwiss Cancer Center Leman (SCCL), Geneva, Switzerland.
Camilla JandusSwiss Cancer Center Leman (SCCL), Geneva, Switzerland.
David GfellerDepartment of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-3952-0930

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the microenvironment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

Indexed as

Breast NeoplasmsChromatin Immunoprecipitation SequencingChromatinFemaleHumansNeoplasmsTumor MicroenvironmentChromatinATAC-Seqbulk deconvolutioncancer biologychromatin accessibilitycomputational biologyhumansystems biologytumor microenvironment

Identifiers

PMID39383060
PMCPMC11464006

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.