Evidence map›Paper›PMID 37941546›Full record

ArticleFrontiers in oncology2023

Identification and characterization of interferon-γ signaling-based personalized heterogeneity and therapeutic strategies in patients with pancreatic cancer.

Xu Chen, Qihang Yuan, Hewen Guan, Xueying Shi, Jiaao Sun, Zhiqiang Wu, Jie Ren, Shilin Xia, Dong Shang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-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

4 citing papers in PubMed, 3 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.

Xu Chen *Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Qihang Yuan *Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Hewen Guan *Department of Dermatology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Xueying ShiDepartment of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Jiaao SunDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Zhiqiang WuDepartment of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Jie RenDepartment of Oncology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Shilin XiaDepartment of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Dong ShangDepartment of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
First Affiliated Hospital of Dalian Medical University · CNDalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Interferon-γ (IFN-γ) is a key cytokine with diverse biological functions, including antiviral defense, antitumor activity, immune regulation, and modulation of cellular processes. Nonetheless, its role in pancreatic cancer (PC) therapy remains debated. Therefore, it is worthwhile to explore the role of Interferon-γ related genes (IFN-γGs) in the progression of PC development. Methodology: Transcriptomic data from 930 PC were sourced from TCGA, GEO, ICGC, and ArrayExpress, and 93 IFN-γGs were obtained from the MSigDB. We researched the characteristics of IFN-γGs in pan-cancer. Subsequently, the cohort of 930 PC was stratified into two distinct subgroups using the NMF algorithm. We then examined disparities in the activation of cancer-associated pathways within these subpopulations through GSVA analysis. We scrutinized immune infiltration in both subsets and probed classical molecular target drug sensitivity variations. Finally, we devised and validated a novel IFN-γ related prediction model using LASSO and Cox regression analyses. Furthermore, we conducted RT-qPCR and immunohistochemistry assays to validate the expression of seven target genes included in the prediction model. Results: We demonstrated the CNV, SNV, methylation, expression levels, and prognostic characteristics of IFN-γGs in pan-cancers. Notably, Cluster 2 demonstrated superior prognostic outcomes and heightened immune cell infiltration compared to Clusters 1. We also assessed the IC50 values of classical molecular targeted drugs to establish links between IFN-γGs expression levels and drug responsiveness. Additionally, by applying our prediction model, we segregated PC patients into high-risk and low-risk groups, identifying potential benefits of cisplatin, docetaxel, pazopanib, midostaurin, epothilone.B, thapsigargin, bryostatin.1, and AICAR for high-risk PC patients, and metformin, roscovitine, salubrinal, and cyclopamine for those in the low-risk group. The expression levels of these model genes were further verified through HPA website data and qRT-PCR assays in PC cell lines and tissues. Conclusion: This study unveils IFN-γGs related molecular subsets in pancreatic cancer for the first time, shedding light on the pivotal role of IFN-γGs in the progression of PC. Furthermore, we establish an IFN-γGs related prognostic model for predicting the survival of PC, offering a theoretical foundation for exploring the precise mechanisms of IFN-γGs in PC.

Indexed as

IFN-γ-related genesinterferon-γ (IFN-γ) signaling pathwaypan-cancerpancreatic cancerprediction model

Identifiers

PMID37941546
PMCPMC10628740
OpenAlexW4387938582

What OpenQuestion holds

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LicenceCC BY
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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.