Expressions of HLA Class II Genes in Cutaneous Melanoma Were Associated with Clinical Outcome: Bioinformatics Approaches and Systematic Analysis of Public Microarray and RNA-Seq Datasets

Chen, Yangyi; Chang, Wei‐An; Lin, En‐Shyh; Chen, Yi Jen; Kuo, Po‐Lin

doi:10.3390/diagnostics9020059

Cited by 19 publications

(20 citation statements)

References 60 publications

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“…This model stratified survival risk groups of the external dataset with a HR of 2.24 (p-value 0.000778). Recently, Chen et al (2019) also reported that the higher expression of HLA-class II genes enhances the survival of melanoma patients. Our analysis also revealed that, the higher expression of HLA (-A, -B, -C, -DPB1, -DQB1, -DRB1) genes, are associated with poor survival, as shown in Supplementary Table S11.…”

Section: Discussionmentioning

confidence: 98%

Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics

et al. 2020

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Human leukocyte antigen (HLA) are essential components of the immune system that stimulate immune cells to provide protection and defense against cancer. Thousands of HLA alleles have been reported in the literature, but only a specific set of HLA alleles are present in an individual. The capability of the immune system to recognize cancer-associated mutations depends on the presence of a particular set of alleles, which elicit an immune response to fight against cancer. Therefore, the occurrence of specific HLA alleles affects the survival outcome of cancer patients. In the current study, prediction models were developed, using 401 cutaneous melanoma patients, to predict the overall survival (OS) of patients using their clinical data and HLA alleles. We observed that the presence of certain favorable superalleles like HLA-B * 55 (HR = 0.15, 95% CI 0.034-0.67), HLA-A * 01 (HR = 0.5, 95% CI 0.3-0.8), is responsible for the improved OS. In contrast, the presence of certain unfavorable superalleles such as HLA-B * 50 (HR = 2.76, 95% CI 1.284-5.941), HLA-DRB1 * 12 (HR = 3.44, 95% CI 1.64-7.2) is responsible for the poor survival. We developed prediction models using key 14 HLA superalleles, demographic, and clinical characteristics for predicting high-risk cutaneous melanoma patients and achieved HR = 4.52 (95% CI 3.088-6.609, p-value = 8.01E-15). Eventually, we also provide a web-based service to the community for predicting the risk status in cutaneous melanoma patients (https://webs.iiitd.edu.in/raghava/skcmhrp/).

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Section: Discussionmentioning

confidence: 98%

Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics

et al. 2020

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Section: Discussionmentioning

confidence: 99%

“…The MHC II complex is one of the main routes for antigen presentation and immune system activation, yet expression by melanoma cells is associated with a controversial role in literature, being described as an unfavorable prognostic factor in some studies and with longer survival in others ( 18 , 24 – 28 ). Recently, MHC II expression, HLA-DR in particular, has also been correlated with response to anti-PD-1 therapy ( 13 – 16 ), nevertheless little is known about the biology behind this finding.…”

Section: Discussionmentioning

confidence: 99%

“…Upon sustained interaction with MHC II positive melanoma cells, activated lymphocytes will evolve into exhaustion, and thus become inactivated (23). These different mechanisms and the additional cofactors may explain why MHC II expression is associated with an unfavorable prognosis in some studies, but with tumor regression and longer survival in others (18,(24)(25)(26)(27)(28).…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Omics Analysis of Metastatic Melanoma Identifies a Germinal Center-Like Tumor Microenvironment in HLA-DR-Positive Tumor Areas

et al. 2021

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The emergence of immune checkpoint inhibitors has dramatically changed the therapeutic landscape for patients with advanced melanoma. However, relatively low response rates and a high incidence of severe immune-related adverse events have prompted the search for predictive biomarkers. A positive predictive value has been attributed to the aberrant expression of Human Leukocyte Antigen-DR (HLA-DR) by melanoma cells, but it remains unknown why this is the case. In this study, we have examined the microenvironment of HLA-DR positive metastatic melanoma samples using a multi-omics approach. First, using spatial, single-cell mapping by multiplexed immunohistochemistry, we found that the microenvironment of HLA-DR positive melanoma regions was enriched by professional antigen presenting cells, including classical dendritic cells and macrophages, while a more general cytotoxic T cell exhaustion phenotype was present in these regions. In parallel, transcriptomic analysis on micro dissected tissue from HLA-DR positive and HLA-DR negative areas showed increased IFNγ signaling, enhanced leukocyte adhesion and mononuclear cell proliferation in HLA-DR positive areas. Finally, multiplexed cytokine profiling identified an increased expression of germinal center cytokines CXCL12, CXCL13 and CCL19 in HLA-DR positive metastatic lesions, which, together with IFNγ and IL4 could serve as biomarkers to discriminate tumor samples containing HLA-DR overexpressing tumor cells from HLA-DR negative samples. Overall, this suggests that HLA-DR positive areas in melanoma attract the anti-tumor immune cell infiltration by creating a dystrophic germinal center-like microenvironment where an enhanced antigen presentation leads to an exhausted microenvironment, nevertheless representing a fertile ground for a better efficacy of anti-PD-1 inhibitors due to simultaneous higher levels of PD-1 in the immune cells and PD-L1 in the HLA-DR positive melanoma cells.

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“…CNA analysis also showed 54 regions of significant focal deletions, including 27 regions containing skin/cancer-related genes, and 56 significant amplifications, including 20 encompassing skin/cancer-related genes (Fig 6 and S7 Table). The elements involved in the most significant focal deletions were CDK11A (chr1p36.33; q=2.4×10-5; occurring in 6 samples), whose loss induces skin carcinogenesis [96]; the LCE cluster (chr1q21.3; q=2.4×10-6; occurring in 4 samples), including genes such as LCE2 and LCE3 , which play a role in maintaining skin barrier function and whose deletion has been associated with psoriasis [97]; and the HLA-D cluster ( HLA-DP , - DQ , and -DR , chr6p21.32; q=2×10-4; occurring in 3 samples), encoding components of major histocompatibility complex (MHC) class II molecules, whose increased expression has been associated with increased cancer immunogenicity and better prognosis in BCC, SCC and melanoma [98–104]. The skin/cancer-related genes in the most significant focally amplified regions worth mentioning are STIM2 (chr4p15.2; q=0.16; occurring in 2 samples) [105], KLRB1/CD161 (chr12p13.31; q=0.007; occurring in 2 samples) [106,107], and SPTLC3 (chr20p12.1 q=0.23; occurring in 2 samples) [108].…”

Section: Resultsmentioning

confidence: 99%

Profile of basal cell carcinoma mutations and copy number alterations - focus on gene-associated noncoding variants

Nawrocka

Galka-Marciniak

Urbanek-Trzeciak

et al. 2021

Preprint

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Basal cell carcinoma (BCC) of the skin is the most common cancer in humans, characterized by the highest mutation rate among cancers, and is mostly driven by mutations in genes involved in the hedgehog pathway. To date, almost all BCC genetic studies have focused exclusively on protein-coding sequences; therefore, the impact of noncoding variants on the BCC genome is unrecognized. In this study, with the use of whole-exome sequencing of 27 tumor/normal pairs of BCC samples, we performed an analysis of somatic mutations in both protein-coding sequences and gene-associated noncoding regions, including 5’UTRs, 3’UTRs, and exon-adjacent intron sequences. Separately, in each region, we performed hotspot identification, mutation enrichment analysis, and cancer driver identification with OncodriveFML. Additionally, we performed a whole-genome copy number alteration analysis with GISTIC2. Of the >80,000 identified mutations, ∼50% were localized in noncoding regions. The results of the analysis generally corroborated the previous findings regarding genes mutated in coding sequences, including PTCH1, TP53, and MYCN, but more importantly showed that mutations were also clustered in specific noncoding regions, including hotspots. Some of the genes specifically mutated in noncoding regions were identified as highly potent cancer drivers, of which BAD had a mutation hotspot in the 3’UTR, DHODH had a mutation hotspot in the Kozak sequence in the 5’UTR, and CHCHD2 frequently showed mutations in the 5’UTR. All of these genes are functionally implicated in cancer-related processes (e.g., apoptosis, mitochondrial metabolism, and de novo pyrimidine synthesis) or the pathogenesis of UV radiation-induced cancers. We also found that the identified BAD and CHCHD2 mutations frequently occur in melanoma but not in other cancers via The Cancer Genome Atlas analysis. Finally, we identified frequent deletion of chr9q, encompassing PTCH1, and unreported frequent copy number gain of chr9p, encompassing the genes encoding the immune checkpoint ligands PD-L1 and PD-L2. In conclusion, this study is the first systematic analysis of coding and noncoding mutations in BCC and provides a strong basis for further analyses of the variants in BCC and cancer in general.Author summaryThe study is the first systematic analysis of both coding and noncoding mutations in basal cell carcinoma (BCC), the most common and the most highly mutated human cancer. Noncoding mutations accounted for ∼50% (∼40K mutations) of all mutations detected by the standard WES approach. Among the genes frequently mutated in noncoding regions are: BAD with a hotspot in the 3’UTR, DHODH with a hotspot in the Kozak sequence, and CHCHD2 with mutations in 5’UTR, all genes functionally related to cell metabolism and apoptosis. Analysis of copy number alterations showed frequent chr9q deletion, encompassing PTCH1 (the key BCC tumor suppressor), and frequent copy number gain of chr9p, encompassing the genes of the immune checkpoint proteins PD-L1 and PD-L2.

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Expressions of HLA Class II Genes in Cutaneous Melanoma Were Associated with Clinical Outcome: Bioinformatics Approaches and Systematic Analysis of Public Microarray and RNA-Seq Datasets

Cited by 19 publications

References 60 publications

Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics

Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics

A Multi-Omics Analysis of Metastatic Melanoma Identifies a Germinal Center-Like Tumor Microenvironment in HLA-DR-Positive Tumor Areas

Profile of basal cell carcinoma mutations and copy number alterations - focus on gene-associated noncoding variants

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