Evidence map›Paper›PMID 36338964›Full record

ArticleFrontiers in genetics2022

An immunogenic cell death-associated classification predictions are important for breast invasive carcinoma prognosis and immunotherapy.

Xinghe Liao, Hui Liu, Zhe Zhang, Jing Zhang, Chenyue Zhang, Weiwei Zhao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. 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
0.6field-weighted citation impact, top 30% 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, 6 citations in OpenAlex.

  1. Review
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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

6 authors at 3 institutions in 1 country.

Xinghe LiaoDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Hui LiuDepartment of Neurology, Renmin Hospital of Wuhan University, Wuhan, China.
Zhe ZhangDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Jing ZhangDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Chenyue ZhangDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Weiwei ZhaoDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Fudan University Shanghai Cancer Center · CNRenmin Hospital of Wuhan University · CNShanghai Medical College of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a type of regulated cell death (RCD), immunogenic cell death (ICD) can initiate the adaptive immune responses. Numerous reports highlight the capacity of ICD to alter the tumor immune microenvironment by releasing Damage-Associated Molecular Patterns (DAMP) or danger signals to boost the efficacy of immunotherapy. Therefore, identification of the ICD-associated biomarkers is crucial for the prediction of ICD-induced immune responses. In this report, the consensus clustering technique was used to identify two subcategories (subtypes) linked to ICD. In comparison to the ICD-low subcategory, the ICD-high subcategory showed longer survival and more immune cell infiltration. Then, a novel ICD-associated prognostic model was developed and validated for predicting the survival of patients with breast invasive carcinomas (BRCA) and is linked to the tumor immune microenvironment. To conclude, a novel ICD-based BRCA classification scheme was designed. For individuals with BRCA, this categorization will be crucial for directing the assessment of prognosis and treatment.

Indexed as

biomarkerbreast invasive carcinomaimmunogenic cell deathprognosistumor immune microenvironment

Identifiers

PMID36338964
PMCPMC9630734
OpenAlexW4306928734

What OpenQuestion holds

Textmetadata
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.