Evidence map›Paper›PMID 34815705›Full record

ArticleInternational journal of general medicine2021

A Novel Autophagy-Related Long Non-Coding RNA Signature to Predict Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma.

Xiaobo Shi, Xiaoxiao Liu, Shupei Pan, Yue Ke, Yuxing Li, Wei Guo, Yuchen Wang, Qinli Ruan, Xiaozhi Zhang, Hongbing Ma

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 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
1.7field-weighted citation impact, top 16% 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, 22 citations in OpenAlex.

  1. Article
  2. lncRNA FENDRR Predicts Adverse Prognosis and Regulates the Development of Esophageal Squamous Cell Carcinoma Through Negatively Modulating miR-495-3p.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2025
    Article
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  4. NClinical and translational medicine · 2024
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  14. Ferroptosis and its emerging role in esophageal cancer.Frontiers in molecular biosciences · 2022
    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

10 authors at 2 institutions in 1 country.

Xiaobo ShiDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.ORCID 0000-0002-0391-5076
Xiaoxiao LiuDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.ORCID 0000-0001-5582-9084
Shupei PanDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Yue KeDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Yuxing LiDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Wei GuoDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Yuchen WangDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Qinli RuanDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Xiaozhi ZhangDepartment of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Hongbing MaDepartment of Radiation Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Second Affiliated Hospital of Xi'an Jiaotong University · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConsidering the significance of autophagy and long non-coding RNAs (lncRNAs) in the biology of esophageal squamous cell carcinoma (ESCC), the present study aimed to identify a new autophagy-related lncRNA signature to forecast the clinical outcomes of ESCC patients and to guide individualized treatment.

methodsThe expression profiles were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. We extracted autophagy-related genes from the Human Autophagy Database and identified autophagy-related lncRNAs through Spearman correlation analysis. Univariate, least absolute shrinkage and selection operator and multivariate Cox regression analyses were performed on GSE53625 to construct an autophagy-related lncRNAs prognostic signature. The model was subjected to bootstrap internal validation, and the expression levels of lncRNAs were verified by TCGA database. The potential molecular mechanism of the model was explored by gene set enrichment analysis (GSEA). Spearman correlation coefficient examined the correlation between risk score and ferroptosis-associated genes as well as the response to immunotherapy and chemotherapy.

resultsWe identified and validated an autophagy-related lncRNAs prognostic signature in 179 patients with ESCC. The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (

conclusionIn brief, we constructed a novel autophagy-related lncRNAs signature (LINC02024, LINC01711, LINC01419, LCAL1, FENDRR, ADAMTS9-AS1, AC025244.1, AC015908.6 and AC011997.1), which could improve the prediction of clinical outcomes and guide individualized treatment of ESCC patients.

Indexed as

autophagyesophageal squamous cell carcinomalncRNAprognosistherapeutic response

Identifiers

PMID34815705
PMCPMC8605829
OpenAlexW3213498449

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.