Single cell sequencing analysis constructed the N7-methylguanosine (m7G)-related prognostic signature in uveal melanoma

Abstract

Background: Uveal melanoma is a highly malignant tumor in the eye. Its recurrence and metastasis are common, and the prognosis is poor. Methods: The transcriptome data of UVM were downloaded from TCGA database, and the single cell sequencing dataset GSE139829 was downloaded from GEO database. Weighted co-expression network analysis was used to explore the modules associated with m7G. Lasso regression was used to construct M 7 G-related prognostic signature. Immune infiltration analysis was used to explore the significance of the model in the tumor immune microenvironment. Finally, cell assays were used to explore the function of key genes in the MUM-2B and OCM-1 cell lines of UVM. Results: The prognostic signature was constructed by Cox regression and Lasso regression. Patients could be divided into high-risk group and low-risk group by this signature, and the high-risk group had worse prognosis (P<0.05). Cell experiments showed that the proliferation, invasion and migration ability of UVM cell lines were significantly decreased after the knockdown of PAG1, a key gene in signature, which proved that PAG1 might be a potential target of UVM. Conclusions: Our study explored the significance of m 7 G in UVM, provided biomarkers for its diagnosis and treatment.

Heterogeneity and molecular landscape of melanoma: implications for targeted therapy

“…These two fields are complementary with their specific advantages and limitations. In comparison to single-cell RNA seq, Bulk RNA seq data harbor fewer noises [133,178,196,197]. Also, the relative abundance of cell types that are obtained with single cells of solid tissue is a biased duo to the cell dissociation step [197,198].…”

Single cell RNA-sequencing in uveal melanoma: advances in heterogeneity, tumor microenvironment and immunotherapy

“…Similarly, Yao Tan et al investigated the expression patterns of lipid metabolism in UM patients and established a risk model based on the genes involved with lipid metabolism which could accurately predict survival in patients with UM (28). Moreover, researchers had constructed a m7Grelated prognostic signature by integrating TCGA and GEO database and suggested PAG1 as biomarker for diagnosis and treatment of UM (29). Yunyue Li et al also developed a prognostic risk model based on basement membrane protein-related genes (30), and glycosylation-based gene signature and hypoxia-related gene signature were described as well by integrating single-cell analysis and machine learning (31,32).…”

“…investigated the expression patterns of lipid metabolism in UM patients and established a risk model based on the genes involved with lipid metabolism which could accurately predict survival in patients with UM ( 28 ). Moreover, researchers had constructed a m7G-related prognostic signature by integrating TCGA and GEO database and suggested PAG1 as biomarker for diagnosis and treatment of UM ( 29 ). Yunyue Li et al.…”

Editorial: Transcriptome analysis in tumor microenvironment and tumor heterogeneity

“…As we delve deeper into the realms of cancer research, the advent of transcriptome analysis has emerged as a powerful torchbearer, illuminating our understanding of these enigmatic facets of cancer biology [2].The tumor microenvironment (TME) has emerged as a pivotal player in cancer progression, response to therapy, and overall patient prognosis. Comprising a dynamic interplay of immune cells, stromal cells, blood vessels, and extracellular matrix components, the TME creates a nurturing niche for tumor cells to thrive [3]. Transcriptome analysis now provides us with a panoramic view of the intricate dialogues between these diverse cellular constituents.By scrutinizing the RNA profiles of the TME's inhabitants, researchers are deciphering the symphony of gene expression patterns that orchestrate the fate of tumors [4].…”

“…The tumor microenvironment (TME) has emerged as a pivotal player in cancer progression, response to therapy, and overall patient prognosis. Comprising a dynamic interplay of immune cells, stromal cells, blood vessels, and extracellular matrix components, the TME creates a nurturing niche for tumor cells to thrive [3]. Transcriptome analysis now provides us with a panoramic view of the intricate dialogues between these diverse cellular constituents.…”