In:
Journal of Oncology, Hindawi Limited, Vol. 2022 ( 2022-2-15), p. 1-16
Abstract:
Background. Pancreatic cancer (PC) has a high mortality and dismal prognosis, predicting to be the second most lethal malignancy. 5-Methylcytosine (m5C) and long noncoding RNAs (lncRNAs) are both crucial in the prognostic outcome and immunotherapeutic effect for PC patients. Therefore, we aimed to create an m5C-related lncRNA signature (m5C-LS) for PC patients’ prognosis and treatment. Methods. Clinicopathological information and RNAseq data were acquired from The Cancer Genome Atlas (TCGA) database. Pearson’s correlation analysis was used to extract m5C-related lncRNAs in PC. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were adopted to build an m5C-LS. Kaplan–Meier (K-M), principal component analysis (PCA), and nomogram were utilized to assess model accuracy. In addition, we explored the model’s possible immunotherapeutic responses and drug sensitivity targets. Results. Three m5C-related lncRNAs were finally established to construct the risk signature, which has a good and independent predictive ability for PC patients. Based on the m5C-LS, patients were classified into the low- and high-m5C-LS group, with the latter having a worse prognosis. Furthermore, the m5C-LS allowed us to better discriminate the immunotherapeutic responses of PC patients in different subgroups. Conclusions. Our study constructed an m5C-LS and established a nomogram model that accurately predicted the prognosis of PC patients, as well as provides promising immunotherapeutic strategies in the future.
Type of Medium:
Online Resource
ISSN:
1687-8469
,
1687-8450
DOI:
10.1155/2022/7467797
Language:
English
Publisher:
Hindawi Limited
Publication Date:
2022
detail.hit.zdb_id:
2461349-6
