Research Paper Volume 15, Issue 23 pp 13710—13737
A glycosylation-related signature predicts survival in pancreatic cancer
- 1 Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
- 2 Department of Gastrointestinal Surgery, Shandong Tumor Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China
- 3 Department of Head and Neck Radiotherapy, Shandong Provincial ENT Hospital, Shandong University, Jinan 250117, China
- 4 Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China
Received: February 24, 2023 Accepted: October 19, 2023 Published: November 30, 2023
https://doi.org/10.18632/aging.205258How to Cite
Copyright: © 2023 Hu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models.
Materials and Methods: The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan–Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature.
Results: Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines.
Conclusion: This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.
Abbreviations
AUC: area under the curve; DCA: decision curve analyses; DE-GRG: differentially expressed glycosylation-related gene; FPKM: fragments per kilo base per million mapped reads; GEO: Gene Expression Omnibus; GO: Gene Ontology; GRG: glycosylation-related gene; GTEx: Genotype-Tissue Expression; ICGC: International Cancer Genome Collaboration; ICGs: immune checkpoint gene subtype; KEGG: Kyoto Encyclopedia of Genes and Genomes; OCLR: one-class logistic regression; ROC: receiver operator characteristic; TCGA: The Cancer Genome Atlas; TNM: tumor, node, and metastasis.