Immune Microenvironment Of Melanoma Research Articles

An update on methods for detection of prognostic and predictive biomarkers in melanoma.

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

Extracellular RNA in melanoma: Advances, challenges, and opportunities.

Melanoma, a malignant mass lesion that originates in melanocytes and has a high rate of malignancy, metastasis, and mortality, is defined by these characteristics. Malignant melanoma is a kind of highly malignant tumor that produces melanin and has a high mortality rate. Its incidence accounts for 1%-3% of all malignant tumors and shows an obvious upward trend. The discovery of biomolecules for the diagnosis and treatment of malignant melanoma has important application value. So far, the exact molecular mechanism of melanoma development relevant signal pathway still remains unclear. According to previous studies, extracellular RNAs (exRNAs) have been implicated in tumorigenesis and spread of melanoma. They can influence the proliferation, invasion and metastasis of melanoma by controlling the expression of target genes and can also influence tumor progression by participating in signal transduction mechanisms. Therefore, understanding the relationship between exRNA and malignant melanoma and targeting therapy is of positive significance for its prevention and treatment. In this review, we did an analysis of extracellular vesicles of melanoma which focused on the role of exRNAs (lncRNAs, miRNAs, and mRNAs) and identifies several potential therapeutic targets. In addition, we discuss the typical signaling pathways involved in exRNAs, advances in exRNA detection and how they affect the tumor immune microenvironment in melanoma.

Exosomal miR-211-5p regulates glucose metabolism, pyroptosis, and immune microenvironment of melanoma through GNA15

Despite the unprecedented advancement of cancer treatment, the prognosis for patients with metastatic stage of cancer remains poor. The challenge that underlines this clinical dilemma is the complexity of metastasis. The conventional experiment-driven discovery approaches (the “wet lab”) yield overly simplified one-to-one mechanistic relationships that are inept of elucidating the complexity of metastasis. Metastasis research also suffers from the knowledge and skill deficiency of the individual investigators. The importance of the present study is the demonstration that the “dry-lab-driven discovery and wet-lab validation” approach can improve the efficiency of studying complex biological behaviors, and can yield more reliable, objective and comprehensive mechanistic findings that are have clinical significance. Specifically, we applied this approach to study the mechanisms that underline the involvement of exosomal miRNAs in transferring the metastatic capability between heterogenous melanoma cancer cells. We show that the highly metastatic melanoma tumor cells (POL) can transfer their metastatic competency to the low-metastatic melanoma tumor cells (OL) by exosomal miR-211-5p. The oncogenic activity of miR-211-5p is mediated by the target gene guanine nucleotide-binding protein subunit alpha-15 (GNA15) through modifying the immune function of the tumor microenvironment extrinsically; as well as through inhibiting pyroptosis and augmenting glycolysis within OL cells intrinsically. In addition, we show that exosomal sorting of miR-211-5p is like selective and is subjected to regulation by a transcriptional feedback loop between miR-211-5p and zinc finger FYVE-type containing 26 (ZFYVE26). Furthermore, the “8-genes pyroptosis Risk model” derived from LASSO regression analysis was verified as an independent prognostic factor for melanoma.

Fibroblast growth factor receptor family mutations as a predictive biomarker for immune checkpoint inhibitors and its correlation with tumor immune microenvironment in melanoma.

The emergence of immune checkpoint inhibitors (ICIs) has significantly improved the clinical outcomes of patients with metastatic melanoma. However, survival benefits are only observed in a subset of patients. The fibroblast growth factor receptor (FGFR) family genes are frequently mutated in melanoma, yet their impacts on the efficacy of ICIs remain unclear. Our study aimed to explore the association of FGFR mutations with ICIs efficacy in metastatic melanoma. The Cancer Genome Atlas (TCGA) data (PanCancer Atlas, skin cutaneous melanoma (SKCM), n = 448) in cBioPortal were collected as a TCGA cohort to investigate the association between FGFR mutations and prognosis of melanoma patients. To explore the impact of FGFR mutations on the efficacy of ICIs in melanoma, clinical and tumor whole-exome sequencing (WES) data of four ICI-treated studies from cBioPortal were consolidated as an ICIs-treated cohort. Moreover, the relationship between FGFR mutations and immunogenicity (tumor mutation burden (TMB), neo-antigen load (NAL), mismatch repair (MMR)-related genes and DNA damage repair (DDR)-related genes) of melanoma was evaluated utilizing data from the ICIs-treated cohort. The influence of FGFR mutations on the tumor immune microenvironment (TIME) of melanoma was also analyzed using the TCGA cohort. In the TCGA cohort, survival in melanoma patients with or without FGFR mutations was nearly equivalent. In the ICIs-treated cohort, patients with FGFR mutations had better survival than those without (median overall survival: 60.00 vs. 31.00 months; hazard ratio: 0.58, 95% CI: 0.42-0.80; P = 0.0051). Besides, the objective response rate was higher for patients harboring FGFR mutations (55.56%) compared to wild-type patients (22.40%) (P = 0.0076). Mechanistically, it was revealed that FGFR mutations correlated with increased immunogenicity (e.g., TMB, NAL, MMR-related gene mutations and DDR-related gene mutations). Meanwhile, FGFR mutant melanoma tended to exhibit an enhanced antitumor TIME compared with its wild-type counterparts. Our study demonstrated that FGFR mutations is a promising biomarker in stratifying patients with advanced melanoma who might benefit from ICIs therapy.

Comprehensive characterisation of immunogenic cell death in melanoma revealing the association with prognosis and tumor immune microenvironment.

Increasing evidence has highlighted the critical functions of immunogenic cell death (ICD) within many tumors. However, the therapeutic possibilities and mechanism of utilizing ICD in melanoma are still not well investigated. Melanoma samples involved in our study were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. First, pan-cancer analysis of ICD systematically revealed its expression characteristics, prognostic values, mutation information, methylation level, pathway regulation relationship in multiple human cancers. The non-negative matrix factorization clustering was utilized to separate the TCGA-melanoma samples into two subtypes (i.e. C1 and C2) with different prognosis and immune microenvironment based on the expression traits of ICD. Then, LASSO-Cox regression analysis was utilized to determine an ICD-dependent risk signature (ICDRS) based on the differentially expressed genes (DEGs) between the two subtypes. Principal component analysis and t-distributed stochastic neighbor embedding analysis of ICDRS showed that high- and low-risk subpopulations could be clearly distinguished. Survival analysis and ROC curves in the training, internal validation, and external validation cohorts highlighted the accurate prognosis evaluation of ICDRS. The obvious discrepancies of immune microenvironment between the different risk populations might be responsible for the different prognoses of patients with melanoma. These findings revealed the close association of ICD with prognosis and tumor immune microenvironment. More importantly, ICDRS-based immunotherapy response and targeted drug prediction might be beneficial to different risk subpopulations of patients with melanoma. The innotative ICDRS could function as a marker to determine the prognosis and tumor immune microenvironment in melanoma. This will aid in patient classification for individualized melanoma treatment.

Comprehensive transcriptomic analysis of immune-related eRNAs associated with prognosis and immune microenvironment in melanoma

Recent evidence suggests that enhancer RNAs (eRNAs) play key roles in cancers. Identification of immune-related eRNAs (ireRNAs) in melanoma can provide novel insights into the mechanisms underlying its genesis and progression, along with potential therapeutic targets. To establish an ireRNA-related prognostic signature for melanoma and identify potential drug candidates. The ireRNAs associated with the overall survival (OS-ireRNAs) of melanoma patients were screened using data from The Cancer Genome Atlas (TCGA) via WGCNA and univariate Cox analysis. A prognostic signature based on these OS-ireRNAs was then constructed by performing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The immune landscape associated with the prognostic model was evaluated by the ESTIMATE algorithm and CIBERSORT method. Finally, the potential drug candidates for melanoma were screened through the cMap database. A total of 24 OS-ireRNAs were obtained, of which 7 ireRNAs were used to construct a prognostic signature. The ireRNAs-related signature performed well in predicting the overall survival (OS) of melanoma patients. The risk score of the established signature was further verified as an independent risk factor, and was associated with the unique tumor microenvironment in melanoma. We also identified several potential anti-cancer drugs for melanoma, of which corticosterone ranked first. The ireRNA-related signature is an effective prognostic predictor and provides reliable information to better understand the mechanism of ireRNAs in the progression of melanoma.

Characterization of the treatment-naive immune microenvironment in melanoma with BRAF mutation

BackgroundPatients with BRAF-mutant and wild-type melanoma have different response rates to immune checkpoint blockade therapy. However, the reasons for this remain unknown. To address this issue, we investigated the precise...

Construction of a Ferroptosis-Related Gene Signature for Predicting Survival and Immune Microenvironment in Melanoma Patients.

ObjectiveIn this research, we studied the genes associated with ferroptosis to develop a prognostic model and find out an association with tumor immune microenvironment in skin cutaneous melanoma (SKCM) patients.MethodsTo find SKCM-related ferroptosis genes, we used Cox regression and LASSO approach on 60 genes related to ferroptosis and SKCM-related RNA-seq. Following that, a ferroptosis-related gene signature was created. Time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its capability of prediction. Besides, several assessments were used to evaluate overall survival (OS), accompanied by the creation of a nomogram for the clinicopathologic factors and the ferroptosis-related gene signature we established. We also investigated the relationship between ferroptosis-related gene signature with three immune checkpoints and immune cell infiltration.ResultsOur prognostic model included two genes (ALOX5, CHAC1). In both TCGA and GEO cohorts, OS was lower in high-risk category. Using our gene signature, we can reliably predict OS. Additionally, our gene signature can predict immune cell infiltration and SKCM immunotherapy response.ConclusionOur gene signature has shown to be a reliable predictor of OS, reflect the immune microenvironment, and predict the effectiveness of immunotherapy for SKCM patients.

Coexpressed Genes That Promote the Infiltration of M2 Macrophages in Melanoma Can Evaluate the Prognosis and Immunotherapy Outcome.

Purpose To improve immunotherapy efficacy for melanoma, a coexpression network and key genes of M2 macrophages in melanoma were explored. A prognostic risk assessment model was established for M2-related coexpressed genes, and the role of M2 macrophages in the immune microenvironment of melanoma was elucidated. Method We obtained mRNA data from melanoma and peritumor tissue samples from The Cancer Genome Atlas-skin cutaneous melanoma (TCGA-SKCM). Then, we used CIBERSORT to calculate the proportion of M2 macrophage cells. A coexpression module most related to M2 macrophages in TCGA-SKCM was determined by analyzing the weighted gene coexpression network, and a coexpression network was established. After survival analysis, factors with significant results were incorporated into a Cox regression analysis to establish a model. The model's essential genes were analyzed using functional enrichment, GSEA, and subgroup and total carcinoma. Finally, external datasets GSE65904 and GSE78220 were used to verify the prognostic risk model. Results The yellow-green module was the coexpression module most related to M2 macrophages in TCGA-SKCM; NOTCH3, DBN1, KDELC2, and STAB1 were identified as the essential genes that promoted the infiltration of M2 macrophages in melanoma. These genes are concentrated in antigen treatment and presentation, chemokine, cytokine, the T cell receptor pathway, and the IFN-γ pathway. These factors were analyzed for survival, and factors with significant results were included in a Cox regression analysis. According to the methods, a model related to M2-TAM coexpressed gene was established, and the formula was risk score = 0.25∗NOTCH3 + 0.008∗ DBN1 − 0.031∗KDELC2 − 0.032∗STAB1. The new model was used to perform subgroup evaluation and external queue validation. The results showed good prognostic ability. Conclusion We proposed a Cox proportional hazards regression model associated with coexpression genes of melanoma M2 macrophages that may provide a measurement method for generating prognosis scores in patients with melanoma. Four genes coexpressed with M2 macrophages were associated with high levels of infiltration of M2 macrophages. Our findings may provide significant candidate biomarkers for the treatment and monitoring of melanoma.

Determination of hypoxia signature to predict prognosis and the tumor immune microenvironment in melanoma

Melanoma is one of the highly malignant skin tumors, the incidence and death of which continue to increase. The hypoxic microenvironment drives tumor growth, progression, and heterogeneity; it also triggers a cascade of immunosuppressive responses and affects the levels of T cells, macrophages, and natural killer cells. Here, we aim to develop a hypoxia-based gene signature for prognosis evaluation and help evaluate the status of hypoxia and the immune microenvironment in melanoma. Based on the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, we performed integrated bioinformatics to analyze the hypoxia-related genes. Using Lasso Cox regression, a hypoxia model was constructed. The receiver operating characteristic and the Kaplan-Meier curve were used to evaluate the predictive capacity of the model. With the CIBERSORT algorithm, the abundance of 22 immune cells in the melanoma microenvironment was analyzed. A total of 20 hypoxia-related genes were significantly related to prognosis in the log-rank test. Lasso regression showed that FBP1, SDC3, FOXO3, IGFBP1, S100A4, EGFR, ISG20, CP, PPARGC1A, KIF5A, and DPYSL4 displayed the best features. Based on these genes, a hypoxia model was established, and the area under the curve for the model was 0.734. Furthermore, the hypoxia score was identified as an independent prognostic factor. Besides, the hypoxia score could also predict the immune microenvironment in melanoma. Down-regulated activated CD4 memory T cells, CD8 T cells, and M1-like macrophages, and up-regulated Tregs were observed in patients with a high hypoxia score. The hypoxia-related genes were identified, and the hypoxia score was found to be a prognostic factor for overall survival and a predictor for the immune microenvironment. Our findings provide new ideas for evaluation and require further validation in clinical practice.

Integrated Analysis of the ETS Family in Melanoma Reveals a Regulatory Role of ETV7 in the Immune Microenvironment.

The ETS family modulates immune response and drug efficiency to targeted therapies, but their role in melanoma is largely unclear. In this study, the ETS family was systematically analyzed in multiple public data sets. Bioinformatics tools were used to characterize the function of ETV7 in melanoma. A prognostic model was constructed using the LASSO Cox regression method. We found that ETV7 was the only differentially expressed gene with significant prognostic relevance in melanoma. Enrichment analysis of seven independent data sets indicated ETV7 participation in various immune-related pathways. ETV7 particularly showed a strong positive correlation with CD8+ T cell infiltration. The prognostic model based on ETV7 and its hub genes showed a relatively good predictive value in training and testing data sets. Thus, ETV7 can potentially regulate the immune microenvironment in melanoma.

Tertiary lymphoid structures improve immunotherapy and survival in melanoma.

Checkpoint blockade therapies that reactivate tumour-associated T cells can induce durable tumour control and result in the long-term survival of patients with advanced cancers1. Current predictive biomarkers for therapy response include high levels of intratumour immunological activity, a high tumour mutational burden and specific characteristics of the gut microbiota2,3. Although the role of T cells in antitumour responses has thoroughly been studied, other immune cells remain insufficiently explored. Here we use clinical samples of metastatic melanomas to investigate the role of Bcells in antitumour responses, and find that the co-occurrence of tumour-associated CD8+ T cells and CD20+ Bcells is associated with improved survival, independently of other clinical variables. Immunofluorescence staining of CXCR5 and CXCL13 in combination with CD20 reveals the formation of tertiary lymphoid structures in these CD8+CD20+ tumours. We derived a gene signature associated with tertiary lymphoid structures, which predicted clinical outcomes in cohorts of patients treated with immunecheckpoint blockade. Furthermore, B-cell-rich tumours were accompanied by increased levels of TCF7+ naive and/or memory T cells. This was corroborated by digital spatial-profiling data, in which T cells in tumours without tertiary lymphoid structures had a dysfunctional molecular phenotype. Our results indicate that tertiary lymphoid structures have a key role in the immune microenvironment in melanoma, by conferring distinct T cell phenotypes. Therapeutic strategies to induce the formation of tertiary lymphoid structures should be explored to improve responses to cancer immunotherapy.

IL4-induced gene 1 promotes tumor growth by shaping the immune microenvironment in melanoma

ABSTRACTAmino acid catabolizing enzymes emerged as a crucial mechanism used by tumors to dampen immune responses. The L-phenylalanine oxidase IL-4 induced gene 1 (IL4I1) is expressed by tumor-associated myeloid cells of most solid tumors, including melanoma. We previously provided the only evidence that IL4I1 accelerates tumor growth by limiting the CD8+ T cell mediated immune response, in a mouse model of melanoma cell transplantation. Here, we explored the role of IL4I1 in Ret mice, a spontaneous model of melanoma. We found that IL4I1 was expressed by CD11b+ myeloid cells and that its activity correlated with disease aggressiveness. IL4I1 did not enhance tumor cell proliferation or angiogenesis, but orchestrated the remodeling of the immune compartment within the primary tumor. Indeed, the inactivation of IL4I1 limited the recruitment of polymorphonuclear myeloid-derived suppressor cells and enhanced the infiltration by Th1 and cytotoxic T cells, thus delaying tumor development and metastatic dissemination. Accordingly, human primary melanomas that were poorly infiltrated by IL4I1+ cells exhibited a higher density of CD8+ T cells. Collectively, our findings strengthen the rationale for therapeutic targeting of IL4I1 as one of the key immune regulators.

Abstract 5126: The link between therapy-induced senescence and anti-tumor immune microenvironment in melanoma

Abstract Tumor cell senescence is often induced by cancer therapeutics. Senescent cells secrete many proteins that may affect both malignant and non-malignant components of the tumor. The goal of this study was to determine how therapy-induced senescence (TIS) affects the immune microenvironment in melanoma. We used inhibitors of cell cycle kinases AURKA and CDK4/6 (AURKAi, CDK4/6i) to induce senescence in melanoma tumors. RNA sequencing analysis of AURKAi-treated syngeneic mouse tumors demonstrated that response to AURKA inhibition was strongly associated with induction of an immune transcriptome (p = 3.5E-29). Immunofluorescent staining and flow cytometric analysis of digested tumors showed correlation between the numbers of tumor-infiltrating leukocytes (TILs) and AURKAi response (Spearman r = -0.87, p<0.001). T cells were among the TILs recruited into AURKAi-sensitive tumors. Therapeutic benefit of AURKAi was limited in immunodeficient host (67% of tumors regressed in immunocompetent mice vs 0% in immunodeficient mice, p = 0.01) suggesting that recruitment of TILs augments response to senescence-inducing therapy. We found that TILs were driven into tumors in response to chemokine CCL5 that was induced in AURKAi and CDK4/6i-treated melanoma cells (up to 20 fold, p≤0.005) on mRNA and secreted protein levels. Knockdown of CCL5 (KD) inhibited leukocyte recruitment (6.8% in KD vs 29.5% in control, p = 0.002) and response to AURKAi in vivo (p = 0.61 in KD vs p = 0.02 in control). In contrast, therapeutic benefit was greatly enhanced when senescence-inducing therapy was combined with T cell-activating immunotherapy using CD137 (4-1BB) agonist (p<0.001). We also evaluated CCL5 expression in human melanoma tumors in relation with TIS and TIL markers. Expression of CCL5 was induced by AURKAi and/or CDK4/6i in patient derived xenografts (3 patients, 3 mice each, p≤0.02), in tumors from patients who responded on AURKAi clinical trial (3 patients, before/after therapy) and was associated with expression of “Immune response” genes in The Cancer Genome Atlas (TCGA) dataset of 278 melanoma tumors (p = 1.40E-93). In conclusion, our data demonstrates that TIS promotes recruitment of TILs via the induction of CCL5 which, in turn, augment therapeutic response in melanoma. Further improvement of melanoma outcome is achieved when senescence-inducing drugs are combined with immunotherapy that promotes tumor cells killing by TILs. This study presents a novel promising approach to improve melanoma therapy by utilizing TIS to reprogram tumor immune microenvironment. Citation Format: Anna E. Vilgelm, C Andrew Johnson, Nripesh Prasad, Jinming Yang, Sheau-Chiann Chen, Gregory D. Ayers, Jeffrey A. Sosman, Jeffrey A. Ecsedy, Shyr Yu, Shawn E. Levy, Ann Richmond. The link between therapy-induced senescence and anti-tumor immune microenvironment in melanoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5126.