Evidence map›Paper›PMID 32047513›Full record

ArticleFrontiers in genetics2019

Development of an Immune-Related Prognostic Signature in Breast Cancer.

Peiling Xie, Yuying Ma, Shibo Yu, Rui An, Jianjun He, Huimin Zhang

Abstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

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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

27 citing papers in PubMed.

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  12. A CD8Journal of mammary gland biology and neoplasia · 2022
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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.

Peiling XieDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yuying MaDepartment of Structural Heart Disease, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Shibo YuDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Rui AnDepartment of Anesthesiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Jianjun HeDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Huimin ZhangDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough increased early detection, diagnosis and treatment have improved the outcome of breast cancer patients, prognosis estimation still poses challenges due to the disease heterogeneity. Accumulating data indicated an evident correlation between tumor immune microenvironment and clinical outcomes.

objectiveTo construct an immune-related signature that can estimate disease prognosis and patient survival in breast cancer.

methodsGene expression profiles and clinical data of breast cancer patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, which were further divided into a training set (n = 499), a testing set (n = 234) and a Meta-validation set (n = 519). In the training set, immune-related genes were recognized using combination of gene expression data and ESTIMATE algorithm-derived immune scores. An immune-related prognostic signature was generated with LASSO Cox regression analysis. The prognostic value of the signature was validated in the testing set and the Meta-validation set.

resultsA total of 991 immune-related genes were identified. Twelve genes with non-zero coefficients in LASSO analysis were used to construct an immune-related prognostic signature. The 12-gene signature significantly stratified patients into high and low immune risk groups in terms of overall survival independent of clinical and pathologic factors. The signature also significantly stratified overall survival in clinical defined groups, including stage I/II disease. Several biological processes, such as immune response, were enriched among genes in the immune-related signature. The percentage of M

conclusionWe developed a 12-gene prognostic signature, providing novel insights into the identification of breast cancer with a high risk of death and assessment of the possibility of immunotherapy incorporation in personalized breast cancer management.

Indexed as

breast cancerimmune systemmodel statisticalprognosissurvival

Identifiers

PMID32047513
PMCPMC6997532

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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.