Evidence map›Paper›PMID 33193628›Full record

ArticleFrontiers in genetics2020

The Key Genes for Perineural Invasion in Pancreatic Ductal Adenocarcinoma Identified With Monte-Carlo Feature Selection Method.

Jin-Hui Zhu, Qiu-Liang Yan, Jian-Wei Wang, Yan Chen, Qing-Huang Ye, Zhi-Jiang Wang, Tao Huang

Open access · goldAbstract read
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Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

13 citing papers in PubMed, 17 citations in OpenAlex.

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  11. TGF-β1-induced RAP2 regulates invasion in pancreatic cancer.Acta biochimica et biophysica Sinica · 2022
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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

7 authors at 3 institutions in 1 country.

Jin-Hui ZhuDepartment of General Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Qiu-Liang YanDepartment of General Surgery, Jinhua People's Hospital, Jinhua, China.
Jian-Wei WangDepartment of Surgical Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yan ChenDepartment of General Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Qing-Huang YeDepartment of General Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zhi-Jiang WangDepartment of General Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Tao HuangShanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
Second Affiliated Hospital of Zhejiang University · CNJinhua Academy of Agricultural Sciences · CNShanghai Institute of Nutrition and Health · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPancreatic ductal adenocarcinoma (PDAC) is the most aggressive form of pancreatic cancer. Its 5-year survival rate is only 3-5%. Perineural invasion (PNI) is a process of cancer cells invading the surrounding nerves and perineural spaces. It is considered to be associated with the poor prognosis of PDAC. About 90% of pancreatic cancer patients have PNI. The high incidence of PNI in pancreatic cancer limits radical resection and promotes local recurrence, which negatively affects life quality and survival time of the patients with pancreatic cancer.

objectivesTo investigate the mechanism of PNI in pancreatic cancer, we analyzed the gene expression profiles of tumors and adjacent tissues from 50 PDAC patients which included 28 patients with perineural invasion and 22 patients without perineural invasion.

methodUsing Monte-Carlo feature selection and Incremental Feature Selection (IFS) method, we identified 26 key features within which 15 features were from tumor tissues and 11 features were from adjacent tissues.

resultsOur results suggested that not only the tumor tissue, but also the adjacent tissue, was informative for perineural invasion prediction. The SVM classifier based on these 26 key features can predict perineural invasion accurately, with a high accuracy of 0.94 evaluated with leave-one-out cross validation (LOOCV).

conclusionThe in-depth biological analysis of key feature genes, such as TNFRSF14, XPO1, and ATF3, shed light on the understanding of perineural invasion in pancreatic ductal adenocarcinoma.

Indexed as

incremental feature selectionMonte-Carlo feature selectionpancreatic ductal adenocarcinomaperineural invasionsupport vector machine

Identifiers

PMID33193628
PMCPMC7593847
OpenAlexW3093004857

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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.