The Prognostic and Predictive Role of Xeroderma Pigmentosum Gene Expression in Melanoma

Sarah Fischer; Mohamed Hamed; Steffen Emmert; Olaf Wolkenhauer; Georg Fuellen; Alexander Thiem

doi:10.3389/fonc.2022.810058

The Prognostic and Predictive Role of Xeroderma Pigmentosum Gene Expression in Melanoma

Front Oncol. 2022 Jan 31:12:810058. doi: 10.3389/fonc.2022.810058. eCollection 2022.

Authors

Sarah Fischer^{1

2}, Mohamed Hamed¹, Steffen Emmert³, Olaf Wolkenhauer^{2

4}, Georg Fuellen¹, Alexander Thiem³

Affiliations

¹ Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.
² Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.
³ Clinic and Policlinic for Dermatology and Venereology, Rostock University Medical Center, Rostock, Germany.
⁴ Leibniz-Institute for Food Systems Biology, Technical University of Munich, Freising, Germany.

Abstract

Background: Assessment of immune-specific markers is a well-established approach for predicting the response to immune checkpoint inhibitors (ICIs). Promising candidates as ICI predictive biomarkers are the DNA damage response pathway genes. One of those pathways, which are mainly responsible for the repair of DNA damage caused by ultraviolet radiation, is the nucleotide excision repair (NER) pathway. Xeroderma pigmentosum (XP) is a hereditary disease caused by mutations of eight different genes of the NER pathway, or POLH, here together named the nine XP genes. Anecdotal evidence indicated that XP patients with melanoma or other skin tumors responded impressively well to anti-PD-1 ICIs. Hence, we analyzed the expression of the nine XP genes as prognostic and anti-PD-1 ICI predictive biomarkers in melanoma.

Methods: We assessed mRNA gene expression in the TCGA-SKCM dataset (n = 445) and two pooled clinical melanoma cohorts of anti-PD-1 ICI (n = 75). In TCGA-SKCM, we applied hierarchical clustering on XP genes to reveal clusters, further utilized as XP cluster scores. In addition, out of 18 predefined genes representative of a T cell inflamed tumor microenvironment, the TIS score was calculated. Besides these scores, the XP genes, immune-specific single genes (CD8A, CXCL9, CD274, and CXCL13) and tumor mutational burden (TMB) were cross-correlated. Survival analysis in TCGA-SKCM was conducted for the selected parameters. Lastly, the XP response prediction value was calculated for the two pooled anti-PD-1 cohorts by classification models.

Results: In TCGA-SKCM, expression of the XP genes was divided into two clusters, inversely correlated with immune-specific markers. A higher ERCC3 expression was associated with improved survival, particularly in younger patients. The constructed models utilizing XP genes, and the XP cluster scores outperformed the immune-specific gene-based models in predicting response to anti-PD-1 ICI in the pooled clinical cohorts. However, the best prediction was achieved by combining the immune-specific gene CD274 with three XP genes from both clusters.

Conclusion: Our results suggest pre-therapeutic XP gene expression as a potential marker to improve the prediction of anti-PD-1 response in melanoma.

Keywords: DNA damage response; RNA-seq; anti-PD-1; biomarker; gene expression; melanoma; nucleotide excision repair; xeroderma pigmentosum.