Evidence map›Paper›PMID 33869009›Full record

ArticleFrontiers in oncology2021

Identification of IFN-Induced Transmembrane Protein 1 With Prognostic Value in Pancreatic Cancer Using Network Module-Based Analysis.

Lingyun Wu, Xinli Zhu, Danfang Yan, Mengmeng Tang, Chiyuan Ma, Senxiang Yan

Abstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Lingyun WuDepartment of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xinli ZhuDepartment of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Danfang YanDepartment of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Mengmeng TangDepartment of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Chiyuan MaDepartment of Orthopedic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Senxiang YanDepartment of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite improvements reported in diagnosis and treatments in recent decades, pancreatic cancer is still characterized by poor prognosis and low survival rate among solid tumors. Intensive interests have grown in exploring novel predictive biomarkers, aiming to enhance the efficiency in early detection and treatment prognosis. In this study, we identified the differentially expressed genes (DEGs) in pancreatic cancer by analyzing five gene expression profiles and established the functional modules according to the functional interaction (FI) network between the DEGs. A significant upregulation of the selected DEG, interferon (IFN)-induced transmembrane protein 1 (IFITM1), was evaluated in several bioinformatics online tools and verified with immunohistochemistry staining from samples of 90 patients with pancreatic cancer. Prognostic data showed that high expression of IFITM1 associated with poor survival, and multivariate Cox regression analysis showed IFITM1 was one of the independent prognostic factors for overall survival. Meanwhile, significant correlations of the expression of IFITM1 and the infiltration of immune cells were found by TIMER. Furthermore, a higher level of IFITM1 was assessed in pancreatic cancer cell lines compared to normal human pancreatic duct epithelial cells, and silencing IFITM1 in tumor cells remarkedly inhibited cancer tumorigenicity. Collectively, our findings suggested that IFITM1 might have promising utility for pancreatic cancer.

Indexed as

functional interaction networkIFITM1IFN-induced transmembrane protein 1pancreatic cancerprognostic biomarkertissue microarray detection

Identifiers

PMID33869009
PMCPMC8044951

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