Development and Validation of An Immune Gene Set-Based Prognostic Signature in Cutaneous Melanoma

Abstract

We aimed to fully understand the landscape of the skin cutaneous melanoma (SKCM) microenvironment and develop an immune prognostic signature that can predict the prognosis for SKCM patients. RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases. The immune-prognostic signature was constructed by LASSO Cox regression analysis. We calculated the relative abundance of 29 immune-related gene sets based on the mRNA expression profiles of 314 SKCM patients in the Cancer Genome Atlas training set. Hierarchical clustering was performed to classify SKCM patients into three clusters: immunity-high, -medium and -low. The values of our prognostic model in predicting disease progression, metastasis and immunotherapeutic responses were also validated. In conclusion, the prognostic model demonstrated a powerful ability to distinguish and predict SKCM patients’ prognosis.

Lay abstract

Skin cutaneous melanoma (SKCM) is one of the most aggressive skin cancers, with an increasing incidence worldwide. The introduction of immunotherapy has dramatically improved overall survival, but the identification of patients who will benefit from immunotherapy and the determination of the best treatment choice remain crucial. The immediate surroundings of the tumor (the tumor microenvironment) are closely related to the response to cancer immunotherapy. The objective of this study was to comprehensively understand the tumor microenvironment of SKCM and to develop a model that can predict the prognosis of SKCM patients. Based on genetic data of 314 SKCM patients, we classified SKCM patients into three groups: immunity-high, -medium and -low. Immune cells, molecules and cellular signaling were overexpressed in the immunity-high cluster. Our immune-related prognostic model consists of five core genes and has been confirmed to be an ideal biomarker for predicting the survival of SKCM patients. Furthermore, the value of our prognostic model in predicting disease progression, metastasis and response to immunotherapy were also validated. In summary, the immune-related five-gene prognostic model demonstrated a powerful ability to stratify and predict SKCM patients’ prognosis. Prospective clinical studies are needed to further validate the accuracy in its clinical application.

Keywords:

• cutaneous melanoma
• GEO
• immunotherapeutic response
• prognosis
• TCGA
• tumor microenvironment

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.tandfonline.com/doi/suppl/10.2217/fon-2021-0104

Acknowledgments

The authors wish to thank the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) for their open access databases.

Data availability statement

The results here are based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga and GEO database (http://www.ncbi.nlm.nih.gov/geo/). The main codes and parameters used in this study can be downloaded from the following link: (https://github.com/tianqi930119/Prognostic-Signature).

Financial & competing interests disclosure

This study was supported by International Cooperation Foundation Project of Shaanxi Province (No. 2019KW-033) and Clinical Research Project of the First Affiliated Hospital of Xi'an Jiaotong University (XJTU1AF-CRF-2016-020). The authors have no other 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 apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

This study was supported by International Cooperation Foundation Project of Shaanxi Province (No. 2019KW-033) and Clinical Research Project of the First Affiliated Hospital of Xi'an Jiaotong University (XJTU1AF-CRF-2016-020). The authors have no other 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 apart from those disclosed