Evidence map›Paper›PMID 28177904›Full record

ArticleOncotarget2017

Genome-scale analysis identifies GJB2 and ERO1LB as prognosis markers in patients with pancreatic cancer.

Tao Zhu, Yuan-Feng Gao, Yi-Xin Chen, Zhi-Bin Wang, Ji-Ye Yin, Xiao-Yuan Mao, Xi Li, Wei Zhang, Hong-Hao Zhou, Zhao-Qian Liu

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

38 citing papers in PubMed, 63 citations in OpenAlex.

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  16. Genome-Scale Analysis Identified NID2, SPARC, and MFAP2 as Prognosis Markers of Overall Survival in Gastric Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2021
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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.

Tao ZhuDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Yuan-Feng GaoDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Yi-Xin ChenDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Zhi-Bin WangDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Ji-Ye YinDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Xiao-Yuan MaoDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Xi LiDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Wei ZhangDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Hong-Hao ZhouDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Zhao-Qian LiuDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Central South University · CNXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is a complex and heterogeneous disease with the etiology largely unknown. The deadly nature of pancreatic cancer, with an extremely low 5-year survival rate, renders urgent a better understanding of the molecular events underlying it. The aim of this study is to investigate the gene expression module of pancreatic adenocarcinoma and to identify differentially expressed genes (DEGs) with prognostic potentials. Transcriptome microarray data of five GEO datasets (GSE15471, GSE16515, GSE18670, GSE32676, GSE71989), including 117 primary tumor samples and 73 normal pancreatic tissue samples, were utilized to identify DEGs. The five sets of DEGs had an overlapping subset consisting of 98 genes (90 up-regulated and 8 down-regulated), which were probably common to pancreatic cancer. Gene ontology (GO) analysis of the 98 DEGs showed that cell cycle and cell adhesion were the major enriched processes, and extracellular matrix (ECM)-receptor interaction and p53 signaling pathway were the most enriched pathways according to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Elevated expression of gap junction protein beta 2 (GJB2) and reduced endoplasmic reticulum oxidoreductase 1-like beta (ERO1LB) expression were validated in an independent cohort. Kaplan-Meier survival analysis revealed that GJB2 and ERO1LB levels were significantly associated with the overall survival of pancreatic cancer patients. GJB2 and ERO1LB are implicated in pancreatic cancer progression and can be used to predict patient survival. Therapeutic strategies targeting GJB2 and facilitating ERO1LB expression may deserve evaluation to improve prognosis of pancreatic cancer patients.

Indexed as

AdultAgedBiomarkers, TumorCluster AnalysisConnexin 26ConnexinsFemaleGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansKaplan-Meier EstimateMaleMembrane GlycoproteinsMiddle AgedOligonucleotide Array Sequence AnalysisBiomarkers, TumorConnexin 26ConnexinsERO1B protein, humanGJB2 protein, humanMembrane GlycoproteinsOxidoreductases Acting on Sulfur Group DonorsERO1LBGJB2pancreatic cancerprognosis

Identifiers

PMID28177904
PMCPMC5400583
OpenAlexW2584623346

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.