Evidence map›Paper›PMID 39816360›Full record

ArticleHeliyon2024

A five-gene prognosis model based on lysine β-hydroxybutyrylation site genes to predict the survival and therapy response in pancreatic adenocarcinoma.

Fangfang Hu, Zhibin Bai, Kai Yan, Zheng Zhang, Jiahua Zhou

Abstract 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
–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

4 citing papers in PubMed.

  1. Article
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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

5 authors.

Fangfang HuDepartment of Hepatobiliary and Pancreatic Surgery, Zhongda Hospital, Medical School, Southeast University, Nanjing, Jiangsu, 210009, China.
Zhibin BaiCenter of interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, Jiangsu, 210009, China.
Kai YanDepartment of Hepatobiliary and Pancreatic Surgery, Zhongda Hospital, Medical School, Southeast University, Nanjing, Jiangsu, 210009, China.
Zheng ZhangMedical School, Southeast University, Nanjing, Jiangsu, 210009, China.
Jiahua ZhouDepartment of Hepatobiliary and Pancreatic Surgery, Zhongda Hospital, Medical School, Southeast University, Nanjing, Jiangsu, 210009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pancreatic adenocarcinoma (PAAD) is one of the most malignancy diseases. Lysine β-hydroxybutyrylation (Kbhb) has been reported to involve various metabolism and cancer progression. Methods: Data from online databases (TCGA and GEO) were retrieved for the selection of differential expressed Kbhb site genes (DTRGs). Univariate cox and LASSO analysis were performed to identify the prognostic DTRGs. Based on the optimal DTRGs, a prognostic risk score model was established. Kaplan-Meier and Receiver operator characteristic analysis were conducted to evaluate the predicting ability of the prognosis model. Generated with clinical data, independent analysis and nomogram model were performed. Finally, the differences of survival, immune cell levels, immunotherapy response, drug sensitivity between high- and low-risk groups were explored. Results: A total of 63 DTRGs were identified in PAAD, and these genes were related to cell division and apoptosis biological functions. Through univariate cox regression and LASSO analysis, 30 DTRGs were selected to be related to prognosis and five ( Conclusion: A five-gene prognosis risk model which exhibit promising predictive ability in survival is constructed for patients with PAAD.

Indexed as

ButyrylationLysine β-hydroxybutyrylationMetabolismPancreatic adenocarcinomaPrognosis

Identifiers

PMID39816360
PMCPMC11734053

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.