Evidence map›Paper›PMID 40593408›Full record

ArticleDiscover oncology2025

Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer.

Hao Yu, Quan Yuan, Liu-Xing Feng, Jia-Huan Xu, Shen-Yuan Zhan, Zhi-Min Li, Shuang-Jia Wang

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Hao Yu *Department of Hepato-Biliary-Pancreatic and Vascular Surgery, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China.
Quan Yuan *Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.
Liu-Xing Feng *Department of Hepato-Biliary-Pancreatic and Vascular Surgery, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China.
Jia-Huan XuDepartment of Basic Medical Sciences, Putian University, Putian, Fujian, China.
Shen-Yuan ZhanShengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.
Zhi-Min LiDepartment of Hepato-Biliary-Pancreatic and Vascular Surgery, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China. lizhimin@sina.com.
Shuang-Jia WangDepartment of Hepato-Biliary-Pancreatic and Vascular Surgery, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China. abian-03@163.com.

Funding

Plan Project of Natural Science Foundation of Fujian Province 2021J011345
6 · The paper itself

Abstract

Pancreatic cancer (PC), often referred to as the "king of cancers", has demonstrated limited success with immunotherapies, many of which are still under development. Psoriasis, a common hereditary skin disorder involving genetic, immune, and environmental factors, is only partially understood and has been linked to an elevated risk of various cancers, including PC. However, the precise mechanisms through which psoriasis may influence PC progression remain unclear. A comparative analysis of the immune microenvironments in both diseases revealed that tertiary lymphoid structures (TLS) are downregulated in both conditions. Gene expression profiles from public databases were analyzed, and TLS-associated genes were subjected to Cox regression and Kaplan-Meier analyses. Machine learning algorithms identified GBP2 as a risk factor and ZNF814 as a protective factor. The TLS pathway was underexpressed in PC, and GBP2, PARP9, ESRP1, FERMT1, and ZNF814 were identified as critical determinants of survival outcomes. GBP2 was linked to poor prognosis, while ZNF814 was associated with favorable outcomes. Clinical risk plots, ROC curves, and Kaplan-Meier analyses were used to assess model performance. Additionally, qPCR experiments validated the expression of these genes in pancreatic cancer cell lines. These results offer valuable insights into PC progression, providing a foundation for improved clinical management and future research.

Indexed as

Machine learningPancreatic cancerPsoriasisTertiary lymphoid structures

Identifiers

PMID40593408
PMCPMC12214077

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.