An integrated mRNA-lncRNA signature for overall survival prediction in cholangiocarcinoma

Derong Xu, Lili Wei, Liping Zeng, Robert Mukiibi, Hongbo Xin, Feng Zhang

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The combination of mRNA and lncRNA profiles for establishing an integrated mRNA-lncRNA prognostic signature has remained unexplored in cholangiocarcinoma (CCA) patients. We utilized a training dataset of 36 samples from The Cancer Genome Atlas dataset and a validation cohort (GSE107943) of 30 samples from Gene Expression Omnibus. Two mRNAs (CFHR3 and PIWIL4) and 2 lncRNAs (AC007285.1 and AC134682.1) were identified to construct the integrated signature through a univariate Cox regression (P-value = 1.35E-02) and a multivariable Cox analysis (P-value = 3.07E-02). Kaplan-Meier curve showed that patients with low risk scores had notably prolonged overall survival than those with high risk scores (P-value = 4.61E-03). Subsequently, the signature was validated in GSE107943 cohort with an area under the curve of 0.750 at 1-year and 0.729 at 3-year. The signature was not only independent from diverse clinical features (P-value = 3.07E-02), but also surpassed other clinical characteristics as prognostic biomarkers with area under the curve of 0.781 at 3-year. Moreover, the weighted gene co-expression network analysis and gene enrichment analyses found that the integrated signature were associated with metabolic-related biological process and lipid metabolism pathway, which has been implicated in the pathogenesis of CCA. Taken together, we developed an integrated mRNA-lncRNA signature that had an independent prognostic value in the risk stratification of patients with CCA.

Original languageEnglish
Article numbere35348
Pages (from-to)1-11
Number of pages11
JournalMedicine
Volume102
Issue number39
Early online date29 Sept 2023
DOIs
Publication statusPublished - 29 Sept 2023

Keywords / Materials (for Non-textual outputs)

  • cholangiocarcinoma
  • proportional hazards models
  • risk assessment
  • survival

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