Evidence map›Paper›PMID 42581999›Full record

ArticleFrontiers in oncology2026

A novel lipid droplet-related prognostic signature reveals CIDEC as a key biomarker for pancreatic adenocarcinoma.

Xuyang Shao, Jun Zhu, Xiangyu Gao, Siyu Li, Fei Zhong, Yanlong Shi

Abstract read
In one paragraph

Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xuyang Shao *Department of General Surgery, Guoyang County People's Hospital, Guoyang, Anhui, China.
Jun Zhu *Department of Oncology, Guoyang County People's Hospital, Guoyang, Anhui, China.
Xiangyu GaoDepartment of Oncology, The Fifth Affiliated Hospital of Anhui Medical University, Fuyang, Anhui, China.
Siyu LiDepartment of Oncology, The Fifth Affiliated Hospital of Anhui Medical University, Fuyang, Anhui, China.
Fei ZhongDepartment of Oncology, The Fifth Affiliated Hospital of Anhui Medical University, Fuyang, Anhui, China.
Yanlong ShiDepartment of General Surgery, The Fifth Affiliated Hospital of Anhui Medical University, Fuyang, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Reprogramming of lipid metabolism is acknowledged as a key characteristic of cancer. This research aimed to examine the potential of lipid droplet-associated genes (LDRGs) in forecasting patient outcomes and the effectiveness of immunotherapy in pancreatic adenocarcinoma (PAAD). Methods: A predictive signature was developed through LASSO Cox regression analysis. Survival predictions were assessed via Kaplan-Meier survival analysis, along with univariate and multivariate Cox regression analyses. Associations between LDRGs and tumor-immune infiltration, as well as immune checkpoints, were examined using Spearman's analysis. The pivotal gene CIDEC within the LDRGs was pinpointed, and a CIDEC-associated competing endogenous RNA (ceRNA) regulatory network was established employing comprehensive bioinformatics analysis. The pro-tumor phenotype of CIDEC was explored in PAAD cell lines through molecular experiments. Results: A signature model related to LDRGs for determining the prognosis of PAAD was constructed, based on which patients were classified into two risk groups. A nomogram accompanied by calibration curves was constructed, which proved a robust predictive value. Additional investigations revealed that these prognostic LDRGs are significantly associated with levels of immune infiltration and the expression of immune checkpoints. Through ceRNA network analysis, a regulatory axis involving LINC00365, hsa-miR-32-5p, hsa-miR-363-3p, and CIDEC was identified in PAAD. Experimental evidence indicates that elevated CIDEC expression markedly enhances proliferation, migration, and invasion capabilities in PAAD cell lines while simultaneously suppressing apoptosis. Conversely, reduced CIDEC levels produce the opposite effects. Conclusion: In conclusion, our novel prognostic signature model has promising applications in PAAD patients. Within this framework, CIDEC may serve as a valuable candidate biomarker and a potential target for therapeutic intervention, thereby providing a basis for future research. The LINC00365/hsa-miR-32-5p/hsa-miR-363-3p/CIDEC regulatory axis may be involved in the progression of PAAD.

Indexed as

CIDECcompeting endogenous RNAlipid droplet-related genespancreatic adenocarcinomaprognostic signature

Identifiers

PMID42581999
PMCPMC13456994

What Socratic holds

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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.