Evidence map›Paper›PMID 34532083›Full record

ArticleJournal of gastrointestinal oncology2021

Evaluating prognostic value and relevant gene signatures of tumor microenvironment characterization in esophageal carcinoma.

Wang Sheng, Xiaoyu Li, Jiayi Li, Yanjun Mi, Fan Li

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

Article in Journal of gastrointestinal oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Wang ShengDepartment of Medical Oncology, Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, Xiamen, China.
Xiaoyu LiDepartment of Oncology, Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Jiayi LiDepartment of Medical Oncology, Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, Xiamen, China.
Yanjun MiDepartment of Medical Oncology, Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, Xiamen, China.
Fan LiDepartment of Thoracic Surgery, Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
First Affiliated Hospital of Xiamen University · CNHuazhong University of Science and Technology · CNTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor microenvironment (TME) cells are an important part of tumor tissues. There is increasing evidence that the TME plays a vital role in tumor prognosis, and is associated with patient survival in various kinds of malignances. To date, very little research has been conducted on how to effectively use TME to better evaluate the prognosis of patients with esophageal carcinoma (EC). The concept of a "TME score" was introduced to better distinguish the prognosis of patients.

methodsWe employed bioinformatic methods to investigate the TME infiltration patterns of 160 patients with EC from the Cancer Genome Atlas (TCGA) cohort. TME clusters were identified using k-means clustering methods with 1,000 resampling times. The significance of the survival difference among patients belonging to different TME clusters was assessed by the log-rank test and Kaplan-Meier survival curves. Correlations between immune cell types and survival were calculated by a Cox regression, and the Pearson correlation coefficient (PCC) was used to measure the relationship among different immune cell types. We classified patient into 2 subtypes based on the optimal breakpoint of TME score determined by R package maxstat.

resultsTwo TME phenotypes were defined based on the immune cell type fractions, and patients with a high TME score phenotype had a better prognosis than those with a low TME score phenotype. Kaplan-Meier analysis for differentially expressed micro ribonucleic acids (RNAs) and messenger RNAs also showed that different TME score subtypes were significantly associated with the prognosis of EC. Just as tumor mutational burden can predict the efficacy of immunotherapy, the TME score can predict the efficacy of immune checkpoint inhibitors (ICIs). The genomic alterations of 2 TME score subtypes of EC further revealed that genomic instability is prevalent in TMEs, and patients with a low TME score subtype have a more unstable chromosome status than those with a high subtype.

conclusionsThus, TME score is an emerging prognostic biomarker for predicting the efficacy of ICIs.

Indexed as

Esophageal carcinoma (EC)prognosisTME scoretumor microenvironment (TME)

Identifiers

PMID34532083
PMCPMC8421893
OpenAlexW3196779457

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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.