Evidence map›Paper›PMID 33318305›Full record

ArticleAging2020

Identification of long non-coding RNA signatures for squamous cell carcinomas and adenocarcinomas.

Suyan Tian, Mingbo Tang, Jialin Li, Chi Wang, Wei Liu

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 59% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
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 2 countries.

Suyan TianDivision of Clinical Research, First Hospital of Jilin University, Changchun 130021, Jilin, P.R. China.
Mingbo TangDepartment of Thoracic Surgery, First Hospital of Jilin University, Changchun 130021, Jilin, China.
Jialin LiDepartment of Thoracic Surgery, First Hospital of Jilin University, Changchun 130021, Jilin, China.
Chi WangDepartment of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY 40536, USA.
Wei LiuDepartment of Thoracic Surgery, First Hospital of Jilin University, Changchun 130021, Jilin, China.
First Hospital of Jilin University · CNJilin University · CNUniversity of Kentucky · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies have demonstrated that both squamous cell carcinomas (SCCs) and adenocarcinomas (ACs) possess some common molecular characteristics. Evidence has accumulated to support the theory that long non-coding RNAs (lncRNAs) serve as novel biomarkers and therapeutic targets in complex diseases such as cancer. In this study, we aimed to identify pan lncRNA signatures that are common to squamous cell carcinomas or adenocarcinomas with different tissues of origin. With the aid of elastic-net regularized regression models, a 35-lncRNA pan discriminative signature and an 11-lncRNA pan prognostic signature were identified for squamous cell carcinomas, whereas a 6-lncRNA pan discriminative signature and a 5-lncRNA pan prognostic signature were identified for adenocarcinomas. Among them, many well-known cancer relevant genes such as MALAT1 and PVT1 were included. The identified pan lncRNA lists can help experimental biologists generate research hypotheses and adopt existing treatments for less prevalent cancers. Therefore, these signatures warrant further investigation.

Indexed as

Gene Expression Regulation, NeoplasticAdenocarcinomaBiomarkers, TumorCarcinoma, Squamous CellGene Expression ProfilingHumansLung NeoplasmsRNA, Long NoncodingBiomarkers, TumorRNA, Long Noncodingadenocarcinoma (AC)gene signaturelong non-coding RNA (lncRNA)pan-cancer analysissquamous cell carcinoma (SCC)

Identifiers

PMID33318305
PMCPMC7880362
OpenAlexW3204229026

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.