Evidence map›Paper›PMID 38234923›Full record

ArticleHeliyon2024

KLK10/LIPH/PARD6B/SLC52A3 are promising molecular biomarkers for the prognosis of pancreatic cancer through a ceRNA network.

Meng Zhang, Lin Jiang, Xin-Yun Liu, Fu-Xing Liu, Hui Zhang, Yan-Juan Zhang, Xiao-Mei Tang, Yu-Shui Ma, Hui-Yi Wu, Xun Diao and 5 more

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. 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
1.1field-weighted citation impact, top 24% 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, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
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

15 authors at 4 institutions in 1 country.

Meng ZhangDepartment of Immunology, School of Medicine, Nantong University, Nantong, 226019, Jiangsu, China.
Lin JiangDepartment of Anesthesiology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, Jiangsu, 225300, China.
Xin-Yun LiuDepartment of Pathology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
Fu-Xing LiuDepartment of Pathology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
Hui ZhangInstitute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, Jiangsu, China.
Yan-Juan ZhangDepartment of Immunology, School of Medicine, Nantong University, Nantong, 226019, Jiangsu, China.
Xiao-Mei TangGeneral Surgery, Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, Shanghai, China.
Yu-Shui MaCancer Institute, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, Shanghai, China.
Hui-Yi WuDepartment of Pathology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
Xun DiaoInstitute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, Jiangsu, China.
Chun YangDepartment of Anesthesiology and Perioperative Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Ji-Bin LiuInstitute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, Jiangsu, China.
Da FuDepartment of Pathology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
Jie ZhangDepartment of Immunology, School of Medicine, Nantong University, Nantong, 226019, Jiangsu, China.
Hong YuDepartment of Pathology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
Nantong University · CNJiangsu Province Hospital · CNRuijin Hospital · CNShanghai University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic adenocarcinoma (PAAD) remains challenging to diagnose and treat clinically due to its difficult early diagnosis, low surgical resection rate, and high risk of postoperative recurrence and metastasis. SMAD4 is a classical mutated gene in pancreatic cancer and is lost in up to 60%-90 % of PAAD patients, and its mutation often predicts a poor prognosis and treatment resistance. In this study, based on the expression profile data in The Cancer Genome Atlas database, we identified a ceRNA network composed of 2 lncRNAs, 1 miRNA, and 4 mRNAs through differential expression analysis and survival prognosis analysis. Among them, high expression of KLK10/LIPH/PARD6B/SLC52A3 influenced the prognosis and overall survival of PAAD patients. We confirmed the high expression of these target genes in pancreatic tissue of pancreatic-specific SMAD4-deficient mice. In addition, immune infiltration analysis showed that the high expression of these target genes affects the tumor immune environment and contributes to the progression of PAAD. Abnormal overexpression of these target genes may be caused by hypermethylation. In conclusion, we found that KLK10/LIPH/PARD6B/SLC52A3 is a potential prognostic marker for PAAD based on a competing endogenous RNA-mediated mechanism and revealed the potential pathogenic mechanism by which deficient expression of SMAD4 promotes pancreatic cancer progression, which provides a new pathway and theoretical basis for targeted therapy or improved prognosis of pancreatic cancer. These data will help reveal potential therapeutic targets for pancreatic cancer and improve the prognosis of pancreatic cancer patients.

Indexed as

ceRNAKLK10LIPHPAADPARD6BSMAD4

Identifiers

PMID38234923
PMCPMC10792648
OpenAlexW4390650440

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.