Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data

ABSTRACT

Objective

The purpose of this study was to explore the composition of tumor-infiltrating immune cells (TIIC) and prognostic significance of tumor-infiltrating mast cells (TIMC) in adrenocortical carcinoma (ACC).

Methods

The gene expression profiles of ACC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE90713, GSE12368). The abundance of TIICs in ACC samples was calculated by CIBERSORT algorithm and immunohistochemistry was used to identify mast cells of 39 tumor samples from Fudan University Shanghai Cancer Center (FUSCC). Differentially expressed genes (DEGs) were analyzed by LIMMA package using R software. Survival analysis was analyzed by Kaplan-Meier method and Cox regression models.

Results

The abundance of mast cells (p = .008) was positively correlated with ACC patients’ outcome in TCGA cohort and was also positively correlated with both overall survival (p < .05) and progression-free survival (p < .05) in FUSCC cohort. Different TIMC infiltrations showed significant changes in signaling pathways including DNA replication, nuclear chromosome segregation, and meiotic cell cycle process of ACC. In addition, elevated expression of eight hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) related to the abundance of TIMC in ACC was significantly correlated with the poor prognosis of the patients.

Conclusion

In conclusion, higher TIMC infiltration was positively correlated with ACC patients’ outcome in both TCGA and FUSCC cohort. Lower TIMC infiltration and elevated expression of hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) are markedly correlated with aggressive progression and poor prognosis, which might shed lights on novel targets for treatment strategies.

KEYWORDS:

• Adrenocortical carcinoma
• tumor infiltrating immune cells
• tumor infiltrating mast cells
• CIBERSORT
• differentially expressed genes

Abbreviations

Table

Acknowledgments

We thank the TCGA databases and GEO (ID: GSE90713, GSE12368) for providing ACC gene expression profiles.

Disclosure of potential conflicts of interest

No potential conflicts of interest were disclosed.

Ethics approval and consent to participate

The Ethics approval and consent to participate in the current study were approved and consented by the ethics committee of Fudan University Shanghai Cancer center.

Availability of data and material

The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.

Authors’ contributions

The work presented here was carried out in collaboration with all authors. YDW, ZHL, and QYY defined the theme of the study and discussed analysis, interpretation, and presentation. TX, XWH, and WYC drafted the manuscript, analyzed the data, developed the algorithm, and explained the results. Aihetaimujiang, WHK and WFN, participated in the collection of relevant data and helped draft the manuscript. ZY and CDL helped to perform the statistical analysis. ZYP and SGH helped revise the manuscript and provided guiding suggestions. All the authors read and approved the final manuscript.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Funding

This work is supported by Grants from the National Key Research and Development Project (No.2019YFC1316000) and National Natural Science Foundation of China (No.81772706 and No.81802525).