Bioinformatic Analysis Reveals Central Role for Tumor-Infiltrating Immune Cells in Uveal Melanoma Progression

Recent Advances in Molecular and Genetic Research on Uveal Melanoma

Uveal melanoma (UM), a distinct subtype of melanoma, presents unique challenges in its clinical management due to its complex molecular landscape and tendency for liver metastasis. This review highlights recent advancements in understanding the molecular pathogenesis, genetic alterations, and immune microenvironment of UM, with a focus on pivotal genes, such as GNAQ/11, BAP1, and CYSLTR2, and delves into the distinctive genetic and chromosomal classifications of UM, emphasizing the role of mutations and chromosomal rearrangements in disease progression and metastatic risk. Novel diagnostic biomarkers, including circulating tumor cells, DNA and extracellular vesicles, are discussed, offering potential non-invasive approaches for early detection and monitoring. It also explores emerging prognostic markers and their implications for patient stratification and personalized treatment strategies. Therapeutic approaches, including histone deacetylase inhibitors, MAPK pathway inhibitors, and emerging trends and concepts like CAR T-cell therapy, are evaluated for their efficacy in UM treatment. This review identifies challenges in UM research, such as the limited treatment options for metastatic UM and the need for improved prognostic tools, and suggests future directions, including the discovery of novel therapeutic targets, immunotherapeutic strategies, and advanced drug delivery systems. The review concludes by emphasizing the importance of continued research and innovation in addressing the unique challenges of UM to improve patient outcomes and develop more effective treatment strategies.

Immunohistochemistry assessment of tissue neutrophil-to-lymphocyte ratio predicts outcomes in melanoma patients treated with anti-programmed cell death 1 therapy

Elevated neutrophil-to-lymphocyte ratio (NLR) is associated with diminished immunotherapy response in metastatic melanoma. Although NLR assessment in peripheral blood is established, tissue dynamics remain insufficiently explored. This study aimed to evaluate tissue NLR (tNLR)'s predictive potential through immunohistochemistry in immunotherapy-treated melanoma. Fifty melanoma patients who underwent anti-programmed cell death 1 (PD-1) therapy were assessed. Hematological, clinical and tumor features were collected from medical records. Responses were categorized using the Response Evaluation Criteria in Solid Tumors for immunotherapy (iRECIST) guidelines. Immunohistochemistry for tumor-infiltrating T cells (cluster differentiation 3) and neutrophils (myeloperoxidase) was performed on formalin-fixed paraffin-embedded tumor samples. NLR, derived NLR (dNLR) and tNLR were calculated. Overall survival (OS) and survival following immunotherapy (SFI) were calculated from diagnosis or immunotherapy start to loss of follow-up or death. Patients with high tNLR presented improved OS ( P =  0.038) and SFI with anti-PD-1 therapy ( P =  0.006). Both NLR and dNLR were associated with OS ( P =  0.038 and P =  0.046, respectively) and SFI ( P =  0.001 and P =  0.019, respectively). NLR was also associated with immunotherapy response ( P =  0.007). In conclusion, tNLR emerged as a novel potential biomarker of enhanced survival post anti-PD-1 therapy, in contrast to classical NLR and dNLR markers.

Identification and validation of an immune-relevant risk signature predicting survival outcome and immune infiltration in uveal melanoma

PURPOSE

The current study aimed to reveal a novel immune-related signature to evaluate immune infiltration status and the survival outcome for patients with uveal melanoma (UM).

METHODS

Based on 80 UM samples from the Cancer Genome Atlas, the transcriptome gene expression and clinical characteristics were analyzed to identify immune-related genes that contributed most to prognosis based on LASSO Cox regression. By combining the gene expression level with the corresponding regression coefficient, a risk score was calculated and all patients were divided into high- and low-risk groups. Survival, tumor-infiltrating immune cell abundance, dysregulated signaling pathways, immunophenoscore and tumor mutation burden were compared between two groups. Validation of the risk signature was performed in GSE22138 and GSE44295 cohort. For evaluating the immunotherapy efficacy, 348 advanced urothelial cancer patients treated with immune checkpoint inhibitor (ICI) were used for external validation.

RESULTS

Nine immune-related prognostic genes were identified under the LASSO Cox regression in the TCGA cohort; they are ACKR2, AREG, CCL5, CLEC11A, IGKV1-33, IL36B, NROB1, TRAV8-4 and TRBV28. Better prognosis, elevated immune cell infiltration, decreased immune-suppressive cell infiltration, immune response-related pathways and higher immunophenoscore were found in low-risk patients, with better ICI treatment response rate.

CONCLUSION

The identified immune risk signature was demonstrated to be associated with the favorable immune infiltration, prognosis and immunotherapeutic efficacy, which may provide clues for survival evaluation and immune treatment.

Tryptophan metabolism-related gene expression patterns: unveiling prognostic insights and immune landscapes in uveal melanoma

Uveal melanoma (UVM) remains the leading intraocular malignancy in adults, with a poor prognosis for those with metastatic disease. Tryptophan metabolism plays a pivotal role in influencing cancerous properties and modifying the tumor's immune microenvironment. In this study, we explore the relationship between tryptophan metabolism-related gene (TRMG) expression and the various features of UVM, including prognosis and tumor microenvironment. Our analysis included 143 patient samples sourced from public databases. Using K-means clustering, we categorized UVM patients into two distinct clusters. Further, we developed a prognostic model based on five essential genes, effectively distinguishing between low-risk and high-risk patients. This distinction underscores the importance of TRMGs in UVM prognostication. Combining TRMG data with gender to create nomograms demonstrated exceptional accuracy in predicting UVM patient outcomes. Moreover, our analysis reveals correlations between risk assessments and immune cell infiltrations. Notably, the low-risk group displayed a heightened potential response to immune checkpoint inhibitors. In conclusion, our findings underscore the dynamic relationship between TRMG expression and various UVM characteristics, presenting a novel prognostic framework centered on TRMGs. The deep connection between TRMGs and UVM's tumor immune microenvironment emphasizes the crucial role of tryptophan metabolism in shaping the immune landscape. Such understanding paves the way for designing targeted immunotherapy strategies for UVM patients.

Clinical significance and immune landscape of a novel ferroptosis-related prognosis signature in osteosarcoma

BACKGROUND

Osteosarcoma is a malignant tumor that usually occurs in adolescents aged 10-20 years and is associated with poor prognosis. Ferroptosis is an iron-dependent cell death mechanism that plays a vital role in cancer.

METHODS

Osteosarcoma transcriptome data were downloaded from the public database TARGET and from previous studies. A prognostic risk score signature was constructed using bioinformatics analysis, and its efficacy was determined by analyzing typical clinical features. The prognostic signature was then validated with external data. Differences in immune cell infiltration between high- and low-risk groups were analyzed. The potential of the prognostic risk signature as a predictor of immunotherapy response was evaluated using the GSE35640 (melanoma) dataset. Five key genes expression were measured by real-time PCR and western blot in human normal osteoblasts and osteosarcoma cells. Moreover, malignant biological behaviors of osteosarcoma cells were tested by modulating gene expression level.

RESULTS

We obtained 268 ferroptosis-related genes from the online database FerrDb and published articles. Transcriptome data and clinical information of 88 samples in the TARGET database were used to classify genes into two categories using clustering analysis, and significant differences in survival status were identified. Differential ferroptosis-related genes were screened, and functional enrichment showed that they were associated with HIF-1, T cells, IL17, and other inflammatory signaling pathways. Prognostic factors were identified by univariate Cox regression and LASSO analysis, and a 5-factor prognostic risk score signature was constructed, which was also applicable for external data validation. Experimental validation indicated that the mRNA and protein expression level of MAP3K5, LURAP1L, HMOX1 and BNIP3 decreased significantly, though meanwhile MUC1 increased in MG-63 and SAOS-2 cells compared with hFOB1.19 cells. Cell proliferation and migration ability of SAOS-2 were affected based on alterations of signature genes.

CONCLUSIONS

Significant differences in immune cell infiltration between high- and low-risk groups indicated that the five ferroptosis-related prognostic signature was constructed and could be used to predict the response to immunotherapy in osteosarcoma.

A Novel Glycolysis-Related Signature for Predicting the Prognosis and Immune Infiltration of Uveal Melanoma

INTRODUCTION

As the most common aggressive intraocular cancer in adults, uveal melanoma (UVM) threatens the survival and vision of many people. Glycolysis is a novel hallmark of cancer, but the role of glycolysis-related genes in UVM prognosis remains unknown. The purpose of the study was to establish a glycolysis-related gene signature (GRGS) to predict UVM prognosis.

METHODS

Raw data were obtained from TCGA-UVM and GSE22138 datasets. The GRGS was established by univariate, LASSO, and multivariate Cox regression analyses. Kaplan-Meier survival and time-dependent receiver operating characteristic curves were used to evaluate the predictive ability of the GRGS. The relationships of the GRGS with infiltrating immune cell levels and mutations were analyzed with CIBERSORT and maftools.

RESULTS

A novel GRGS (risk score = 0.690861*ISG20 + 0.070991*MET - 0.227520*SDC2 + 0.690223*FBP1 + 0.048008*CLN6 - 0.128520*SDC3) was developed for predicting UVM prognosis. The GRGS had robust predictive stability in UVM. Enrichment annotation suggested that the high-risk group had stronger adaptive immune responses and that the low-risk group had more innate immune cell infiltration. Moreover, BAP1 mutation was related to high risk, and SF3B1 mutation was related to low risk.

CONCLUSIONS

This study developed and validated a novel GRGS to predict UVM prognosis and immune infiltration. The signature revealed an association between glycolysis-related genes and the tumor microenvironment, providing new insights into the role of glycolysis in UVM.

Digital Quantification of Intratumoral CD8+ T-Cells Predicts Relapse and Unfavorable Outcome in Uveal Melanoma

Although it is a disease that occurs mainly in the Caucasian population, uveal melanoma (UM) is the most common primary intraocular tumor in adults. Here, we used digital pathology and image analysis for the diagnosis of UM and the prediction of the prognosis. Our retrospective study included a total of 404 histopathological slides from 101 patients. A digital image acquisition and quantitative analysis of tissue immune biomarkers (CD4, CD8, CD68, CD163) were performed. A negative impact of the intratumoral CD8 positive cell density higher than 13.3 cells/mm² was detected for both RFS (HR 2.08, 95% Cl 1.09 to 3.99, p = 0.027) and OS (HR 3.30, 95% CI 1.58 to 6.88, p = 0.001). Moreover, we confirmed that older age and stage III were independent negative prognostic factors for both RFS and OS. Our results suggest that a specific distribution profile of CD8 in UM might predict the risk of relapse and death, with potential implications for determining which subgroups of UMs are amenable to specific pharmacological treatment regimens.

Uveal Melanoma Metastasis

Uveal melanoma (UM) is characterized by relatively few, highly incident molecular alterations and their association with metastatic risk is deeply understood. Nevertheless, this knowledge has so far not led to innovative therapies for the successful treatment of UM metastases or for adjuvant therapy, leaving survival after diagnosis of metastatic UM almost unaltered in decades. The driver mutations of UM, mainly in the G-protein genes GNAQ and GNA11, activate the MAP-kinase pathway as well as the YAP/TAZ pathway. At present, there are no drugs that target the latter and this likely explains the failure of mitogen activated kinase kinase inhibitors. Immune checkpoint blockers, despite the game changing effect in cutaneous melanoma (CM), show only limited effects in UM probably because of the low mutational burden of 0.5 per megabase and the unavailability of antibodies targeting the main immune checkpoint active in UM. The highly pro-tumorigenic microenvironment of UM also contributes to therapy resistance. However, T-cell redirection by a soluble T-cell receptor that is fused to an anti-CD3 single-chain variable fragment, local, liver specific therapy, new immune checkpoint blockers, and YAP/TAZ specific drugs give new hope to repeating the success of innovative therapy obtained for CM.