Evidence map›Paper›PMID 39664386›Full record

ArticleFrontiers in immunology2024

Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer.

Yang Cui, Weihang Zhang, Xin Zeng, Yitao Yang, Sung-Joon Park, Kenta Nakai

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors.

Yang CuiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.
Weihang ZhangDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.
Xin ZengDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.
Yitao YangDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.
Sung-Joon ParkHuman Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
Kenta NakaiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tumor microenvironment (TME) plays a crucial role in tumor progression and immunoregulation. Major histocompatibility complex class II (MHC-II) is essential for immune surveillance within the TME. While MHC-II genes are typically expressed by professional antigen-presenting cells, they are also expressed in tumor cells, potentially facilitating antitumor immune responses. To understand the role of MHC-II-expressing tumor cells, we analyzed triple-negative breast cancer (TNBC), an aggressive subtype with poor prognosis and limited treatment options, using public bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics datasets. Our analysis revealed a distinct tumor subpopulation that upregulates MHC-II genes and actively interacts with immune cells. We implicated that this subpopulation is preferentially present in proximity to regions in immune infiltration of TNBC patient cohorts with a better prognosis, suggesting the functional importance of MHC-II-expressing tumor cells in modulating the immune landscape and influencing patient survival outcomes. Remarkably, we identified a prognostic signature comprising 40 significant genes in the MHC-II-expressing tumors in which machine leaning models with the signature successfully predicted patient survival outcomes and the degree of immune infiltration. This study advances our understanding of the immunological basis of cancer progression and suggests promising new directions for therapeutic strategies.

Indexed as

Computational BiologyGene Expression Regulation, NeoplasticHistocompatibility Antigens Class IITriple Negative Breast NeoplasmsTumor MicroenvironmentBiomarkers, TumorFemaleGene Expression ProfilingHumansPrognosisTranscriptomeBiomarkers, TumorHistocompatibility Antigens Class IIbreast cancermachine learningMHC-II pathwaymulti-omics data integrationtumor microenvironment

Identifiers

PMID39664386
PMCPMC11631845

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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.