Evidence map›Paper›PMID 34488540›Full record

ArticleBioengineered2021

A novel pyroptosis-related lncRNA signature for prognostic prediction in patients with lung adenocarcinoma.

Jiahang Song, Yuanyuan Sun, Hui Cao, Zhengcheng Liu, Lei Xi, Changqing Dong, Rusong Yang, Ye Shi

Abstract read
In one paragraph

Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
95citing papers in PubMed, 1 pooled it
–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

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3 · Its place in the literature

Who cites it

95 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Jiahang SongDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.
Yuanyuan SunDepartment of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Hui CaoDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.
Zhengcheng LiuDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.
Lei XiDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.
Changqing DongDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.
Rusong YangDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.
Ye ShiDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, Jiangsu, China.ORCID 0000-0001-6133-6374

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) has been the major cause of tumor-associated mortality in recent years and has a poor prognosis. Pyroptosis is regulated via the activation of inflammasomes and participates in tumorigenesis. However, the effects of pyroptosis-related lncRNAs (PRlncRNAs) on LUAD have not yet been completely elucidated. Therefore, we attempted to systematically explore patterns of cell pyroptosis to establish a novel signature for predicting LUAD survival. Based on TCGA database, we set up a prognostic model by incorporating PRlncRNAs with differential expression using Cox regression and LASSO regression. Kaplan-Meier analysis was conducted to compare the survival of LUAD patients. We further simplified the risk model and created a nomogram to enhance the prediction of LUAD prognosis. Altogether, 84 PRlncRNAs with differential expression were discovered. Subsequently, a new risk model was constructed based on five PRlncRNAs, GSEC, FAM83A-AS1, AL606489.1, AL034397.3 and AC010980.2. The proposed signature exhibited good performance in prognostic prediction and was related to immunocyte infiltration. The nomogram exactly forecasted the overall survival of patients and had excellent clinical utility. In the present study, the five-lncRNA prognostic risk signature and nomogram are trustworthy and effective indicators for predicting the prognosis of LUAD.

Indexed as

Adenocarcinoma of LungLung NeoplasmsAgedCell Line, TumorComputational BiologyDatabases, GeneticFemaleHumansMaleMiddle AgedPrognosisPyroptosisRNA, Long NoncodingTranscriptomeRNA, Long NoncodingbioinformaticslncRNALung adenocarcinomaprognostic signaturepyroptosisTCGA

Identifiers

PMID34488540
PMCPMC8806662

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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.