Evidence map›Paper›PMID 32903590›Full record

ArticleFrontiers in oncology2020

Identification of Immune-Related Prognostic Biomarkers Based on the Tumor Microenvironment in 20 Malignant Tumor Types With Poor Prognosis.

Yu Liu, Hao Zhou, Ji Zheng, Xiaojun Zeng, Wenjing Yu, Wei Liu, Guorong Huang, Yang Zhang, Weiling Fu

Abstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  6. Integrated Analysis ofDisease markers · 2022
    Article
  7. Influencing factors of depressive symptoms in patients with malignant tumour.The Journal of international medical research · 2021
    Article
  8. Article
  9. Article
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

9 authors.

Yu LiuDepartment of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Hao ZhouDepartment of Urology, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Ji ZhengDepartment of Urology, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Xiaojun ZengDepartment of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Wenjing YuDepartment of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Wei LiuDepartment of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Guorong HuangDepartment of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Yang ZhangDepartment of Laboratory Medicine, Chongqing University Cancer Hospital, Chongqing, China.
Weiling FuDepartment of Laboratory Medicine, First Affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer, especially malignant tumors with poor prognosis, has become a major hazard to human life and health. The tumor microenvironment is gaining increasing attention from researchers, as it offers a new focus for tumor diagnosis, therapy, and prognosis. The numbers of immune and stromal cells, which are major components of the tumor microenvironment, could be determined from RNA-seq data with the Estimation of STromal and Immune cells in Malignant Tumors using Expression data (ESTIMATE) algorithm. To explore the effects of immune and stromal cells on tumor prognosis, we analyzed associations between overall survival and immune/stromal scores for 20 malignant tumor types based on The Cancer Genome Atlas (TCGA) data. For six of the 20 tumor types, we observed statistically significant associations. Furthermore, to better explain the predictive ability of these scores, differentially expressed genes (DEGs) were identified in groups of cases with high or low immune or stromal scores for each of these six malignant tumor types. In addition, a list of immune-related genes was screened to identify prognostic predictors for one or more tumor types. Thus, multi-database joint analysis can provide a new approach to the assessment of tumor prognosis and allow the identification of related genes that may be new biomarkers for tumor metastasis and prognosis.

Indexed as

immune scoreprognostic biomarkersstromal scoreTCGAtumor microenvironment

Identifiers

PMID32903590
PMCPMC7438715

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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.