Evidence map›Paper›PMID 34762599›Full record

ArticleAging2021

Establishment of a tumor immune microenvironment-based molecular classification system of breast cancer for immunotherapy.

Xiaobo Zheng, Li Li, Chune Yu, Jiqiao Yang, Yujie Zhao, Chao Su, Jing Yu, Mingqing Xu

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Aging, 2021. 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
0.4field-weighted citation impact, top 34% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  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

8 authors at 2 institutions in 1 country.

Xiaobo ZhengDepartment of Liver Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Li LiInstitute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Chune YuLaboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast Disease, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Jiqiao YangLaboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast Disease, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Yujie ZhaoLaboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast Disease, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Chao SuLaboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast Disease, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Jing YuLaboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast Disease, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Mingqing XuDepartment of Liver Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Sichuan University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antitumor immunotherapy can enable promising and durable responses following their clinical application. However, heterogeneity in the tumor immune microenvironment leads to differences in the individual response rates. In this study, we identified novel immune-related molecular subclasses of breast cancer using a non-negative matrix factorization analysis. We enrolled 4184 patients with breast cancer, including 1104 patients from The Cancer Genome Atlas as a training cohort and 3080 patients from another four independent datasets as validation cohorts. In the training cohort, 36.9% of patients who exhibited significantly higher immunocyte infiltration and enrichment of immune response-associated signatures were categorized into an immune class, which was confirmed by probing the expression of immunocyte markers (CD3, CD19, and CD163). Within the immune class, 53.3% of patients belonged to an immune-suppressed subclass, characterized by the activation of stroma-related signatures and immune-suppressive cells. The remaining patients in the immune class were allocated to an immune-activated subclass. The interferon-γ and granzyme B levels were higher in the immune-activated subclass, whereas the transforming growth factor-β1 and programmed cell death-1 (PD-1) levels were higher in the immune-suppressed subclass. The established molecular classification system was recapitulated in validation cohorts. The immune-activated subclass was predicted to have a better response to anti-PD-1 immunotherapy. The immune-related subclasses were associated with differences in copy number alterations, tumor mutation burden, neoantigens, tumor-infiltrating lymphocyte enrichment, PD-1/programmed death-ligand 1 expression, mutation landscape, and various infiltration immunocytes. Overall, we established a novel immune-related molecular classification of breast cancer, which may be used to select candidate patients for immunotherapy.

Indexed as

Breast NeoplasmsImmunotherapyTumor MicroenvironmentFemaleHumansImmune Checkpoint InhibitorsMiddle AgedImmune Checkpoint Inhibitorsbreast cancercancer immunotherapyimmune-related subtypenon-negative matrix factorizationtumor microenvironment

Identifiers

PMID34762599
PMCPMC8610112
OpenAlexW3212095872

What OpenQuestion holds

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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.