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pmid:29671412

Possible Molecular Markers for the Diagnosis of Pancreatic Ductal Adenocarcinoma.

Quan Shen · Miao Yu · Jiang-Kun Jia · Wen-Xi Li · Yu-Wei Tian · Huan-Zhou Xue

Medical science monitor : international medical journal of experimental and clinical research · 2018 doi:10.12659/msm.906313

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:29671412
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title
Possible Molecular Markers for the Diagnosis of Pancreatic Ductal Adenocarcinoma.
doi
10.12659/msm.906313
pmid
29671412
authors array · 6 items
[0]
Quan Shen
[1]
Miao Yu
[2]
Jiang-Kun Jia
[3]
Wen-Xi Li
[4]
Yu-Wei Tian
[5]
Huan-Zhou Xue
journal
Medical science monitor : international medical journal of experimental and clinical research
year
2018
abstract
BACKGROUND We aimed to identify pivotal genes and pathways involved in pancreatic ductal adenocarcinoma (PDAC), and explore possible molecular markers for the early diagnosis of the disease. MATERIAL AND METHODS The array data of GSE74629, including 34 PDAC samples and 16 healthy samples, was downloaded from GEO (Gene Expression Omnibus) database. Then, the DEGs (differentially expressed genes) in PDAC samples were compared with healthy samples using limma (linear models for microarray). Gene functional interaction networks were analyzed with Cytoscape and ReactomeFIViz. PPI networks were constructed with Cytoscape software. In addition, PPI (protein-protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS A total of 630 upregulated and 1,002 downregulated DEGs were identified in PDAC samples compared with healthy samples. Some ribosomal protein genes with higher average correlation in module 0 were enriched in the ribosome pathway. NUP107 (nucleoporin 107 kDa) and NUP160 (nucleoporin 160 kDa) were enriched in module 3. HNRNPU (heterogeneous nuclear ribonucleoprotein U) with higher average correlation in module 8 was enriched in the spliceosome pathway. The ribosome pathway and the spliceosome pathway were significantly enriched in cluster 1 and cluster 2, respectively. CONCLUSIONS Ribosomal protein genes Nup170, Nup160, and HNRNPU, and the ribosome pathway as well as the spliceosome pathway may play important roles in PDAC progression. In addition, ribosomal protein genes Nup170, Nup160, and HNRNPU may be used as possible molecular markers for the early diagnosis of the disease.
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The DEGs in PDAC samples compared with healthy samples were analyzed with limma. The array data of GSE74629 was downloaded from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/) database with the platform of GPL10558 (Illumina HumanHT-12 V4.0 expression beadchip, Jaen, Spain).
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The DEGs in PDAC samples compared with healthy samples were analyzed with limma.
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The array data of GSE74629 was downloaded from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/) database with the platform of GPL10558 (Illumina HumanHT-12 V4.0 expression beadchip, Jaen, Spain).
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The array data of GSE74629 was downloaded from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/) database with the platform of GPL10558 (Illumina HumanHT-12 V4.0 expression beadchip, Jaen, Spain). A total of 34 PDAC samples and 16 healthy samples were included in this study.
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The array data of GSE74629 was downloaded from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/) database with the platform of GPL10558 (Illumina HumanHT-12 V4.0 expression beadchip, Jaen, Spain). A total of 34 PDAC samples and 16 healthy samples were included in this study.
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The study used limma to analyze GSE74629 microarray data downloaded from GEO and identified 630 upregulated and 1,002 downregulated DEGs in PDAC samples compared with healthy samples.
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The array data of GSE74629, including 34 PDAC samples and 16 healthy samples, was downloaded from GEO (Gene Expression Omnibus) database.
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Then, the DEGs (differentially expressed genes) in PDAC samples were compared with healthy samples using limma (linear models for microarray).
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A total of 630 upregulated and 1,002 downregulated DEGs were identified in PDAC samples compared with healthy samples.
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The study used limma to analyze GSE74629 microarray data downloaded from GEO and identified 630 upregulated and 1,002 downregulated DEGs in PDAC samples compared with healthy samples.
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title
Transcriptome profile of peripheral blood from pancreatic ductal adenocarcinoma patients
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2026-11-01T15:39:55Z
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The DEGs in PDAC samples compared with healthy samples were analyzed with limma. The array data of GSE74629 was downloaded from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/geo/) database with the platform of GPL10558 (Illumina HumanHT-12 V4.0 expression beadchip, Jaen, Spain).
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althy samples using limma (linear models for microarray). Gene functional interaction networks were
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29671412", "kind": "science-record", "revision": 9, "content_hash": "sha256:99cf6c79b06f7fd9dac194a6d43129999d687a16aad313f429994f1a249d02ec", "created_at": "2026-11-01T15:40:33Z", "updated_at": "2026-11-01T22:43:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Possible Molecular Markers for the Diagnosis of Pancreatic Ductal Adenocarcinoma.", "doi": "10.12659/msm.906313", "pmid": "29671412", "authors": ["Quan Shen", "Miao Yu", "Jiang-Kun Jia", "Wen-Xi Li", "Yu-Wei Tian", "Huan-Zhou Xue"], "journal": "Medical science monitor : international medical journal of experimental and clinical research", "year": 2018, "abstract": "BACKGROUND We aimed to identify pivotal genes and pathways involved in pancreatic ductal adenocarcinoma (PDAC), and explore possible molecular markers for the early diagnosis of the disease. MATERIAL AND METHODS The array data of GSE74629, including 34 PDAC samples and 16 healthy samples, was downloaded from GEO (Gene Expression Omnibus) database. Then, the DEGs (differentially expressed genes) in PDAC samples were compared with healthy samples using limma (linear models for microarray). Gene functional interaction networks were analyzed with Cytoscape and ReactomeFIViz. PPI networks were constructed with Cytoscape software. In addition, PPI (protein-protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS A total of 630 upregulated and 1,002 downregulated DEGs were identified in PDAC samples compared with healthy samples. Some ribosomal protein genes with higher average correlation in module 0 were enriched in the ribosome pathway. NUP107 (nucleoporin 107 kDa) and NUP160 (nucleoporin 160 kDa) were enriched in module 3. HNRNPU (heterogeneous nuclear ribonucleoprotein U) with higher average correlation in module 8 was enriched in the spliceosome pathway. The ribosome pathway and the spliceosome pathway were significantly enriched in cluster 1 and cluster 2, respectively. CONCLUSIONS Ribosomal protein genes Nup170, Nup160, and HNRNPU, and the ribosome pathway as well as the spliceosome pathway may play important roles in PDAC progression. In addition, ribosomal protein genes Nup170, Nup160, and HNRNPU may be used as possible molecular markers for the early diagnosis of the disease.", "claims": [{"id": "claim-method", "statement": "The DEGs in PDAC samples compared with healthy samples were analyzed with limma. 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