Evidence map›Paper›PMID 33948357›Full record

ArticleAmerican journal of cancer research2021

An immune-related signature that to improve prognosis prediction of breast cancer.

Yi Zhang, Xuebing Di, Guoji Chen, Jiaqi Liu, Bailin Zhang, Lin Feng, Shujun Cheng, Yipeng Wang

Open access · greenAbstract read
In one paragraph

Article in American journal of cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

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  2. International journal of molecular sciences · 2025
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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

8 authors at 1 institution in 1 country.

Yi ZhangState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Xuebing DiState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Guoji ChenDepartment of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Jiaqi LiuDepartment of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Bailin ZhangDepartment of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Lin FengState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Shujun ChengState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Yipeng WangDepartment of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the classic molecular subtype of breast cancer (BRCA) has been widely used in clinical diagnosis, as a highly heterogeneous malignant tumor, the classic scheme is not enough to accurately predict the prognosis of breast cancer patients. Immune cells in the tumor microenvironment (TME) are thought to play a paramount role in tumor development and driving poor prognosis. In this study, we aimed to develop a TME-associated, immune-related signature to improve prognosis prediction of BRCA. BRCA_OURS enriched transcriptomic RNA sequencing (RNA-seq) of tumor tissue was acquired from 43 breast cancer patients before any treatment. On the immune gene profiles of 43 patients from BRCA_OURS and 932 BRCA patients from The Cancer Genome Atlas (TCGA), we identified a robust immune-related signature including one positive coefficients gene (IL-10) and other 9 genes (C14orf79, C1orf168, C1orf226, CELSR2, FABP7, FGFBP1, KLRB1, PLEKHO1, and RAC2), of which the negative coefficients suggesting higher expression were correlated with better prognosis. Based on the expression of these genes, patients were grouped into the high- and low-risk group with significant overall survival (OS) (P<0.0001). The high-risk group was likely to have inferior outcomes related to several important cancer-associated pathways, including mobilizing more Golgi vesicle-mediated transport and intensive DNA double-strand breaking, which are closely related to the infiltration of immune cells and holds the key for further growing and metastasizing. Collectively, our results highlight that the immunological value within BRCA is an essential determinant of prognostic factor. Our signature may provide an effective risk stratification tool for clinical prognosis assessment of patients with BRCA.

Indexed as

Breast cancerimmune-related signatureRNA-seqtumor microenvironment

Identifiers

PMID33948357
PMCPMC8085862
OpenAlexW3157454380

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.