Evidence map›Paper›PMID 35614413›Full record

SynthesisBMC cancer2022

TP73-AS1 as a predictor of clinicopathological parameters and prognosis in human malignancies: a meta and bioinformatics analysis.

Caizhi Chen, Jingjing Wang, Yeqian Feng, Ye Liang, Yan Huang, Wen Zou

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 47% 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, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  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

6 authors at 2 institutions in 1 country.

Caizhi ChenDepartment of Oncology, The Second Xiangya Hospital of Central South University, Changsha, 410000, Hunan, China.
Jingjing WangDepartment of Oncology, The Second Xiangya Hospital of Central South University, Changsha, 410000, Hunan, China.
Yeqian FengDepartment of Oncology, The Second Xiangya Hospital of Central South University, Changsha, 410000, Hunan, China.
Ye LiangDepartment of Oncology, The Second Xiangya Hospital of Central South University, Changsha, 410000, Hunan, China.
Yan HuangDepartment of Oncology, The Second Xiangya Hospital of Central South University, Changsha, 410000, Hunan, China.
Wen ZouDepartment of Oncology, The Second Xiangya Hospital of Central South University, Changsha, 410000, Hunan, China. zouwen29w@csu.edu.cn.
Central South University · CNSecond Xiangya Hospital of Central South University · CN

Funding

Development and Reform Commission of Hunan Province (2019)412Wu Jieping Medical Foundation 320.6750.18540
6 · The paper itself

Abstract

backgroundLong non-coding RNA P73 antisense RNA 1 T (non-protein coding), also known as Lnc RNA TP73-AS1, is dysregulated in various tumors but the correlation between its expression and clinicopathological parameters and/or prognoses in cancer patients is inconclusive. Here, we performed a meta-analysis to evaluate the prognostic value of Lnc RNA TP73-AS1 for malignancies.

methodsWe systematically searched four online databases including PubMed, the Web of Science, Embase, and the Cochrane Library for eligible articles published up to June 29/2020. Odds ratios (ORs) and Pooled hazard ratios (HRs) with 95% confidence intervals (95% CIs) were used to assess the association of TP73-AS1 expression with prognostic and clinicopathological parameters. We further validated TP73-AS1 expression in various malignancies and its potential prognostic value using the GEPIA online database. We predicted potential biological processes and relevant signal mechanisms through the public databases.

resultsA total of 26 studies examining 14 cancers were analyzed to evaluate the relationship between TP73-AS1 expression, clinicopathological features and prognostic indicators. The results indicated that TP73-AS1 expression markedly correlates with TNM stage (OR = 3.27,95% CI:2.43-4.39, P < 0.00001), tumor size (OR = 3.00, 95%CI:2.08-4.35, P < 0.00001), lymph node metastasis (OR = 2.77, 95%CI:1.42-5.38,P < 0.00001) and distant metastasis (OR = 4.50,95%CI:2. 62-7.73,P < 0.00001). No correlation with age (OR = 1.12,95%CI:0.77-1.64, P > 0.05), gender (OR = 1.08, 95%CI:0.84-1.38, P > 0.05) or differentiation (OR = 1.39, 95%CI:0.71-2.70, P = 0.340) was observed. TP73-AS1 overexpression was a biomarker of poor Overall survival(OS)(HR = 1.85,95%CI:1.53-2.22, P < 0.00001) and Disease-Free-Survival (DFS) (HR = 1.57,95%CI:1.03-2.42, P < 0.05). Dysregulated TP73-AS1 expression and its prognostic value in various cancers was validated based on The Cancer Genome Atlas (TCGA). Further biological function predictions indicated that TP73-AS1 was involved in pro-oncogenic signaling.

conclusionsThe upregulation of Lnc RNA TP73-AS1 was related to detrimental clinicopathological parameters and can be considered an indicator of poor prognosis for cancer malignancies.

Indexed as

NeoplasmsRNA, Long NoncodingBiomarkers, TumorComputational BiologyHumansLymphatic MetastasisPrognosisTumor Protein p73Biomarkers, TumorRNA, Long NoncodingTumor Protein p73BioinformaticsClinicopathological parametersLnc RNA TP73-AS1malignanciesMeta-analysisPrognosis

Identifiers

PMID35614413
PMCPMC9134685
OpenAlexW4281485902

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.