Evidence map›Paper›PMID 40640432›Full record

ArticleDiscover oncology2025

Unveiling the therapeutic potential of senescence-related IQGAP2 in pancreatic Cancer through post-GWAS genomic and scRNA-seq analyses.

Zilong Bai, Jiale Liang, Yuanhua Nie, Shilong Wang, Dongmin Chang

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Zilong BaiDepartment of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, China.
Jiale LiangDepartment of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, China.
Yuanhua NieDepartment of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, China.
Shilong WangDepartment of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, China.
Dongmin ChangDepartment of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, China. sdmqqw@126.com.

Funding

the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University, China NO. XJTU1AF2021CRF-009
6 · The paper itself

Abstract

backgroundPancreatic cancer (PC) is a highly aggressive tumor with a poor prognosis and few treatment options available. While cellular senescence has been linked to the advancement of various cancers, its specific role in PC is not well understood.

methodWe employed Mendelian randomization (MR) alongside single-cell RNA sequencing (scRNA-seq) to explore the involvement of senescence-associated genes (SAGs) in PC. A summary-data-based MR (SMR) analysis was performed to evaluate the connection between SAG expression and the risk of developing PC, using HEIDI test and colocalization analysis to reduce confounding variables. Additionally, scRNA-seq data were used to further examine SAG expression within pancreatic cancer cells and assess their potential as therapeutic targets.

resultsThe SMR analysis revealed a significant correlation between IQGAP2 expression levels and the risk of PC (P_

conclusionThere is a strong association between IQGAP2 and the risk factors for the progression of PC, positioning it as an attractive candidate for targeted therapies. This investigation sheds new light on mechanisms underlying PC while paving the way for precision-targeted treatment strategies.

Indexed as

Cellular senescenceDrug targetIQGAP2Pancreatic cancerscRNA-seqSummary-data-based MR

Identifiers

PMID40640432
PMCPMC12245744

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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.