Development of an Immune-Related Gene Signature for Prognosis in Melanoma

Zhang, Mengli; Zhou, Xu; Huang, Dan; Luan, Chao; Gu, Heng; Mei, Ju; Chen, Kun

doi:10.3389/fonc.2020.602555

Cited by 19 publications

(20 citation statements)

References 51 publications

(54 reference statements)

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“…We also identified a subset of THYM patients with overall low V-gene usage, although we could not find significant associations between this subset of patients and any clinical variables. In our hierarchical clustering analysis, we identified clusters of V-genes in each chain that had higher overall usage across the tumor types which were largely consistent with previous studies (56,57). For the IGL Vgene analysis, we found that the IGLV2-14 V-gene formed its own cluster and seems to have relatively high usage across many tumor samples.…”

Section: Discussionsupporting

confidence: 86%

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

Ravoor

Malats

et al. 2022

Front. Immunol.

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Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.

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Section: Discussionsupporting

confidence: 86%

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

Ravoor

Malats

et al. 2022

Front. Immunol.

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“…Just recently, survival prognosis in melanoma was correlated with immune-related gene signatures (70)(71)(72). Of note, Danaher et al (73) found that TIS was also highly statistically significantly prognostic in TCGA-SKCM, limiting its predictive value in melanoma patients.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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BackgroundAssessment 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.MethodsWe 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.ResultsIn 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.ConclusionOur results suggest pre-therapeutic XP gene expression as a potential marker to improve the prediction of anti-PD-1 response in melanoma.

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“…Moreover, we grouped all SKCM samples into high and low expression groups according to the median expression of the novel prognostic gene and used the ssGSEA package 27 to perform enrichment analysis of the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and MsigDB dataset (msigdb.v7.0.entrez.gmt). The ggplot2 package (version 3.3.3) was used for visualization.…”

Section: Methodsmentioning

confidence: 99%

Identification of a novel tumour microenvironment‐based prognostic biomarker in skin cutaneous melanoma

Yang

Liang

et al. 2021

J Cellular Molecular Medi

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Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)‐based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype‐Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16‐15, PRSS35, SLC7A10, IGHV1‐69D and IGHV2‐26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME‐based prognostic biomarker in SKCM, and functional analysis enriched immune‐related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.

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Development of an Immune-Related Gene Signature for Prognosis in Melanoma

Cited by 19 publications

References 51 publications

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires

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

Identification of a novel tumour microenvironment‐based prognostic biomarker in skin cutaneous melanoma

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