Identification of a ferroptosis-related gene signature for predicting the prognosis of cholangiocarcinoma

ABSTRACT

Background

Cholangiocarcinoma (CCA) is a highly intractable malignancy with poor prognosis. Ferroptosis, a newly explored type of programmed cell death, plays a critical role in the initiation and progression of a tumor. Herein, we aimed to identify a ferroptosis-related risk model to evaluate the prognosis of CCA.

Methods

Differentially expressed genes (DEGs) were retrieved from three GEO cohorts. Univariate and LASSO analysis were employed to build a ferroptosis-related gene signature. Next, the predictive value was assessed in a training and a validation cohort. Metascape Online analysis, ESTIMATE and CIBERSORT algorithms, and ssGSEA were employed to perform the functional analysis between different risk groups. Finally, the expression of prognostic genes was validated with RT-qPCR.

Results

We identified 51 differentially expressed ferroptosis genes and established the prognostic signature containing five ferroptosis-related genes. The K-M curves and the ROC curves revealed a favorable predictive efficacy of the prognostic signature. Functional enrichment analysis indicated that immune-related responses were greatly enriched between different risk groups. Five prognostic genes were also differentially expressed in CCA cell lines.

Conclusions

We developed a novel ferroptosis-related gene signature for CCA with high predictive accuracy. The analysis of the immune infiltration status may provide a potential therapeutic alternative to CCA.

KEYWORDS:

• Cholangiocarcinoma
• ferroptosis
• risk signature
• immune cell infiltration

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

Conception or design were provided by X Li and Z Wang. Acquisition, analysis, or interpretation of data were supplied by Y Chen and S Liu. Drafting of the manuscript was done by Z Wang. Critical revision of the manuscript for important intellectual content was imparted by Y Zhang. Collection and assembly of data was supplied by S Liu. Statistical analysis was contributed by Z Wang and Y Zhang. Administrative, technical, or material support was provided by C Li. All authors have given the final approval of the manuscript for submission and publication.

Availability of data and materials

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This study was supported by the National Science Foundation of China (NSFC) (81700572 and 81670570); the Natural Science Foundation of Jiangsu Province, China (BK20171077); and the Key research and development program of Jiangsu Province (BE2016789).