Immune marker signature helps to predict survival in uveal melanoma

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.

Pervasive structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programs

Glioblastoma multiforme (GBM) encompasses brain malignancies marked by phenotypic and transcriptional heterogeneity thought to render these tumors aggressive, resistant to therapy, and inevitably recurrent. However, little is known about how the spatial organization of GBM genomes underlies this heterogeneity and its effects. Here, we compile a cohort of 28 patient-derived glioblastoma stem cell-like lines (GSCs) known to reflect the properties of their tumor-of-origin; six of these were primary-relapse tumor pairs from the same patient. We generate and analyze 5 kbp-resolution chromosome conformation capture (Hi-C) data from all GSCs to systematically map thousands of standalone and complex structural variants (SVs) and the multitude of neoloops arising as a result. By combining Hi-C, histone modification, and gene expression data with chromatin folding simulations, we explain how the pervasive, uneven, and idiosyncratic occurrence of neoloops sustains tumor-specific transcriptional programs via the formation of new enhancer-promoter contacts. We also show how even moderately recurrent neoloops can relate to patient-specific vulnerabilities. Together, our data provide a resource for dissecting GBM biology and heterogeneity, as well as for informing therapeutic approaches.

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.

Identification and validation of immunogenic cell death-related score in uveal melanoma to improve prediction of prognosis and response to immunotherapy

BACKGROUND

Immunogenic cell death (ICD) could activate innate and adaptive immune response. In this work, we aimed to develop an ICD-related signature in uveal melanoma (UVM) patients and facilitate assessment of their prognosis and immunotherapy.

METHODS

A set of machine learning methods, including non-negative matrix factorization (NMF) method and least absolute shrinkage and selection operator (LASSO) logistic regression model, and bioinformatics analytic tools were integrated to construct an ICD-related risk score (ICDscore). CIBERSORT and ESTIMATE algorithms were used to evaluate the infiltration of immune cells. The Genomics of Drug Sensitivity in Cancer (GDSC), cellMiner and tumor immune dysfunction and exclusion (TIDE) databases were used for therapy sensitivity analyses. The predictive performance between ICDscore with other mRNA signatures was also compared.

RESULTS

The ICDscore could predict the prognosis of UVM patients in both the training and four validating cohorts. The ICDscore outperformed 19 previously published signatures. Patients with high ICDscore exhibited a substantial increase in immune cell infiltration and expression of immune checkpoint inhibitor-related genes, leading to a higher response rate to immunotherapy. Furthermore, the downregulation of poly (ADP-ribose) polymerase family member 8 (PARP8), a critical gene involved in the development of the ICDscore, resulted in decreased cell proliferation and slower migration of UVM cells.

CONCLUSION

In conclusion, we developed a robust and powerful ICD-related signature for evaluating the prognosis and benefits of immunotherapy that could serve as a promising tool to guide decision-making and surveillance for UVM patients.