Evidence map›Paper›PMID 36389299›Full record

ArticleJournal of thoracic disease2022

Development and validation of a prognostic risk signature for lung adenocarcinoma constructed by six ferroptosis, necroptosis, and pyroptosis-related lncRNAs.

Lei Peng, Jingbin Ji, Chenyu Zhang, Zhe Wu, Yuhui Sun, Kun Fan, Wenxing Du, Ao Liu, Wenjie Jiao

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. 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 at 2 institutions in 1 country.

Lei PengDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Jingbin JiDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Chenyu ZhangDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Zhe WuDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Yuhui SunDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Kun FanDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Wenxing DuDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Ao LiuDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Wenjie JiaoDepartment of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
Qingdao University · CNAffiliated Hospital of Qingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Identifying populations that benefit from immune checkpoint blockade (ICB) therapy remains a major challenge in the treatment of lung adenocarcinoma (LUAD). Existing programmed cell death (PCD) related prognostic models only consider a single mechanism, such as ferroptosis, necroptosis, and pyroptosis, and do not reflect the interaction of multiple mechanisms. This study aims to explore lncRNAs associated with multiple modes of PCD and reveal a risk signature to assess prognosis and treatment outcomes in LUAD patients. Methods: Based on expression data in The Cancer Genome Atlas (TCGA) database, ferroptosis, necroptosis, and pyroptosis-related lncRNAs (FNPRlncRNAs) were obtained by taking the intersection of ferroptosis-related lncRNAs (FRlncRNAs), necroptosis-related lncRNAs (NRlncRNAs), and pyroptosis-related lncRNAs (PRlncRNAs) differentially expressed in LUAD and normal tissues. Patients with complete survival information and expression data from TCGA database were randomly assigned to training and testing sets (1:1). Univariate, LASSO, and multivariate Cox regression analyses were performed on the training set, and a risk signature was established. Kaplan-Meier survival curves were used to verify the prognostic ability of risk signature, and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy. We then analyzed molecular and immune profile differences between high and low-risk subgroups. T-cell dysfunction and Exclusion (TIDE) scores were used to assess the response to immunotherapy in each risk subgroup. Finally, three LUAD clusters (C1, C2, and C3) were identified according to the risk signature. Results: Patients in the low-risk subgroup had higher overall survival (OS) than that in the high-risk subgroup in the K-M survival curve. The area under ROC curves (AUC) of 1-, 3-, and 5-year ROC were 0.742, 0.762, and 0.749 in the training set, and 0.672, 0.642, and 0.563 in the testing set, respectively. Compared with the high-risk subgroup, patients in the low-risk subgroup have beneficial tumor immune microenvironment and molecular characteristics, but are less likely to benefit from immunotherapy. Finally, the three LUAD clusters (C1, C2, C3) identified by risk signature had different responses to drug treatment. Conclusions: The prognosis risk signature constructed using FNPRlncRNAs is helpful to predict the prognosis of LUAD and may contribute to its individualized treatment.

Indexed as

ferroptosisimmunotherapyLung adenocarcinoma (LUAD)necroptosispyroptosis

Identifiers

PMID36389299
PMCPMC9641322
OpenAlexW4307981077

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.