Evidence map›Paper›PMID 32765765›Full record

ArticleExperimental and therapeutic medicine2020

Screening potential microRNAs associated with pancreatic cancer: Data mining based on RNA sequencing and microarrays.

Jing Ma, Siwen Sun, Chen Song, Ning Li, Na Li, Lingzhi Xu, Ting Yang, Yulong Lan, Man Li

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 31% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Jing MaDepartment of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Siwen SunDepartment of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Chen SongDepartment of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Ning LiDepartment of Foreign Languages, Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Na LiDepartment of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Lingzhi XuDepartment of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Ting YangDepartment of Neurosurgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Yulong LanDepartment of Neurosurgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Man LiDepartment of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China.
Dalian Medical University · CNSecond Affiliated Hospital of Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is a malignant tumor of the digestive tract, rendering it difficult to make an accurate diagnosis. The 5 year survival rate for pancreatic cancer is <1%, and surgical resection rarely proves to be effective. Therefore, the identification of more effective methods for the early detection of pancreatic cancer is an urgent requirement. The present study aimed to explore key genes and microRNAs (miRNAs) associated with the pathogenesis of pancreatic cancer. Public databases were searched, and the data were integrated from The Cancer Genome Atlas and Gene Expression Omnibus databases, leading to the identification of 23 differentially expressed miRNAs (DE-miRNAs). A total of four of the DE-miRNAs were upregulated (hsa-miR-892b, hsa-miR-194-2, hsa-miR-200a and hsa-miR-194-1), whereas 19 downregulated DE-miRNAs (hsa-miR-424, hsa-miR-191, hsa-miR-484, hsa-miR-142, hsa-miR-15b, hsa-miR-450a-1, hsa-miR-423, hsa-miR-126, hsa-miR-505, hsa-miR-16-1, hsa-miR-342, hsa-miR-130a, hsa-miR-3613, hsa-miR-450a-2, hsa-miR-26b, hsa-miR-451, hsa-miR-19b-2, hsa-miR-106a and hsa-miR-503) were identified using the cut-off criteria of P<0.05 and |log 2FC|>1.0. Hsa-miR-3613-5p was identified as a prognostic DE-miRNA. The functional enrichment analyses demonstrated that the target genes of hsa-miR-3613-5p may be associated with the p53 signaling pathway. Survival analysis performed for genes in the p53 signaling pathway revealed that cyclin-dependent kinase 6 and ribonucleoside-diphosphate reductase subunit M2 may be the most likely to be associated with prognostic value. The integrated analysis performed in the current study demonstrated that hsa-miR-3613-5p may be used as a potential prognostic marker for pancreatic cancer.

Indexed as

bioinformatics analysisdifferentially expressed microRNAsgene expression profilepancreatic cancerRNA sequencingtargettreatment

Identifiers

PMID32765765
PMCPMC7401655
OpenAlexW3042023427

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.