Unraveling the Relevance of ARL GTPases in Cutaneous Melanoma Prognosis through Integrated Bioinformatics Analysis.
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ABSTRACT:
SUBMITTER: Brito C
PROVIDER: S-EPMC8431576 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Multiple types of genetic, epigenetic, and genomic changes have been implicated in cutaneous melanoma prognosis. Many of the existing studies are limited in analyzing a single type of omics measurement and cannot comprehensively describe the biological processes underlying prognosis. As a result, the obtained prognostic models may be less satisfactory, and the identified prognostic markers may be less informative. The recently collected TCGA (The Cancer Genome Atlas) data have a high quality and comprehensive omics measurements, making it possible to more comprehensively and more accurately model prognosis. In this study, we first describe the statistical approaches that can integrate multiple types of omics measurements with the assistance of variable selection and dimension reduction techniques. Data analysis suggests that, for cutaneous melanoma, integrating multiple types of measurements leads to prognostic models with an improved prediction performance. Informative individual markers and pathways are identified, which can provide valuable insights into melanoma prognosis.
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Project description:The rising incidence and mortality rate associated with the metastatic ability of cutaneous melanoma represent a major public health concern. Cutaneous melanoma is one of the most invasive human cancers, but the molecular mechanisms are poorly understood. Moreover, currently available therapies are not efficient in avoiding melanoma lethality. In this context, new biomarkers of prognosis, metastasis, and response to therapy are necessary to better predict the disease outcome. Additionally, the knowledge about the molecular alterations and dysregulated pathways involved in melanoma metastasis may provide new therapeutic targets. Members of the Ras superfamily of small GTPases regulate various essential cellular activities, from signaling to membrane traffic and cytoskeleton dynamics. Therefore, it is not surprising that they are differentially expressed, and their functions subverted in several types of cancer, including melanoma. Indeed, Ras small GTPases were found to regulate melanoma progression and invasion. Hence, a better understanding of the mechanisms regulated by Ras small GTPases that are involved in melanoma tumorigenesis and progression may provide new therapeutic strategies to block these processes. Here, we review the current knowledge on the role of Ras small GTPases in melanoma aggressiveness and the molecular mechanisms involved. Furthermore, we summarize the known involvement of these proteins in melanoma metastasis and how these players influence the response to therapy.
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Project description:The American Joint Committee on Cancer staging system for cutaneous melanoma is based on primary tumor thickness and the presence of ulceration, mitoses, lymph node spread, and distant metastases as determinants of prognosis. Although this cutaneous melanoma staging system has evolved over time to more accurately reflect patient prognosis, improvements are still needed, because current understanding of the particular factors (genetic mutation, expression alteration, host response, etc) that are critical for predicting patient outcomes is incomplete. Given the clinical and biologic heterogeneity of primary melanomas, new prognostic tools are needed to more precisely identify patients who are most likely to develop advanced disease. Such tools would affect clinical surveillance strategies and aid in patient selection for adjuvant therapy. The authors reviewed the literature on prognostic molecular and immunologic markers in primary cutaneous melanoma, their associations with clinicopathologic and survival outcomes, and their potential for incorporation into current staging models. Overall, the studies considered in this review did not define prognostic markers that could be readily incorporated into the current staging system. Therefore, efforts should be continued in these and other directions to maximize the likelihood of identifying clinically useful prognostic biomarkers for cutaneous melanoma.
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Project description:BackgroundSkin cutaneous malignant melanoma (SKCM) is a deadly mutated malignancy that arises from melanocytes in the basal layer of the skin. This study sought to identify effective treatment targets that could serve as prospective therapeutic targets to improve patient outcomes.MethodsThe GSE83583, GSE111766, and GSE104849 data sets from the GPL10558 platform in the Gene Expression Omnibus (GEO) were used in this study. The candidate genes were identified using the GEO2R tool and a Venn diagram. The Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Gene and Genome (KEGG) preliminary analyses of the differentially expressed genes (DEGs) were conducted using the Database for Annotation, Visualization and Integrated Discovery, and R software. The protein-protein interaction (PPI) network was examined using Cytoscape software. The survminer package was used to examine the overall survival of patients with the identified genes. The Human Protein Atlas (HPA) was used to verify the protein levels of significant genes with poor prognosis. The highly expressed genes in the melanoma tissues were visualized using the ggplot2 package.ResultsIn total, 160 DEGs from 124 melanoma tissues and 9 normal melanocyte tissues were examined in this study. Cytoscape displayed 19 central nodes from the 160 DEGs. The re-analysis showed that the cytochrome P450 family 1 subfamily B member 1 (CYP1B1) and protein kinase C beta (PRKCB) were significantly enriched in the micro ribonucleic acids (RNAs) in cancer.ConclusionsCYP1B1 and PRKCB were overexpressed in and correlated with the poor prognosis of SKCM. Our findings might help explore the prognosis and diagnostic markers of SKCM.
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Project description:BACKGROUND: This study investigated survival probabilities and prognostic factors in sentinel lymph node biopsy (SLNB) staged patients with cutaneous melanoma (CM) with the aim of defining subgroups of patients who are at higher risk for recurrences and who should be considered for adjuvant clinical trials. METHODS: Patients with primary CM who underwent SLNB in the Department of Dermatology, University of Tuebingen, Germany, between 1996 and 2009 were included into this study. Survival probabilities and prognostic factors were evaluated by Kaplan-Meier and multivariate Cox proportional hazard models. RESULTS: 1909 SLNB staged patients were evaluated. Median follow-up time was 44 months. Median tumor thickness was 1.8 mm, ulceration was present in 31.8% of cases. The 5-year Overall Survival (OS) was 90.3% in SLNB negative patients (IB 96.2%, IIA 87.0%, IIB 78.1%, IIC 72.6%). Patients with micrometastases (stage IIIA/B) had a 5-year OS rate of 70.9% which was clearly less favorable than for stages I-II. Multivariate analysis revealed tumor thickness, ulceration, body site, histopathologic subtype and SLNB status as independent significant prognostic factors. CONCLUSION: Survival rates of patients with primary CM in stages I-II were shown to be much more favorable than previously reported from non sentinel node staged collectives. For future clinical trials, sample size calculations should be adapted using survival probabilities based on sentinel node staging.
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Project description:Rho GTPases control cell division, motility, adhesion, vesicular trafficking and phagocytosis, which may affect progression and/or prognosis of cancers. Here, we investigated associations between genetic variants of Rho GTPases-related genes and cutaneous melanoma-specific survival (CMSS) by re-analyzing a published melanoma genome-wide association study (GWAS) and validating the results in another melanoma GWAS. In the single-locus analysis of 36,018 SNPs in 129 Rho-related genes, 427 SNPs were significantly associated with CMSS (p?<?0.050 and false-positive report probability <0.2) in the discovery dataset, and five SNPs were replicated in the validation dataset. Among these, four SNPs (i.e., RHOU rs10916352 G?>?C, ARHGAP22 rs3851552 T?>?C, ARHGAP44 rs72635537 C?>?T and ARHGEF10 rs7826362 A?>?T) were independently predictive of CMSS (a meta-analysis derived p?=?9.04 × 10-4 , 9.58 × 10-4 , 1.21 × 10-4 and 8.47 × 10-4 , respectively). Additionally, patients with an increasing number of unfavorable genotypes (NUGs) of these loci had markedly reduced CMSS in both discovery dataset and validation dataset (ptrend =1.47 × 10-7 and 3.12 × 10-5 ). The model including the NUGs and clinical variables demonstrated a significant improvement in predicting the five-year CMSS. Moreover, rs10916352C and rs3851552C alleles were significantly associated with an increased mRNA expression levels of RHOU (p?=?1.8 × 10-6 ) and ARHGAP22 (p?=?5.0 × 10-6 ), respectively. These results may provide promising prognostic biomarkers for CM personalized management and treatment.
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Project description:ObjectiveMelanoma accounts for 80% of skin cancer deaths. The pathogenesis of melanoma is regulated by gene networks. Thus, we aimed here to identify gene networks and hub genes associated with melanoma and to further identify their underlying mechanisms.MethodsGTEx (normal skin) and TCGA (melanoma tumor) RNA-seq datasets were employed for this purpose. We conducted weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with melanoma. Log-rank analysis and multivariate Cox model analysis were performed to identify prognosis genes, which were validated using two independent melanoma datasets. We also evaluated the correlation between prognostic gene and immune cell infiltration.ResultsThe blue module was the most relevant for melanoma and was thus considered the key module. Intersecting genes were identified between this module and differentially expressed genes (DEGs). Finally, 72 genes were identified and verified as hub genes using the Oncomine database. Log-rank analysis and multivariate Cox model analysis identified 13 genes that were associated with the prognosis of the metastatic melanoma group, and RTP4 was validated as a prognostic gene using two independent melanoma datasets. RTP4 was not previously associated with melanoma. When we evaluated the correlation between prognostic gene and immune cell infiltration, we discovered that RTP4 was associated with immune cell infiltration. Further, RTP4 was significantly associated with genes encoding components of immune checkpoints (PDCD1, TIM-3, and LAG3).ConclusionsRTP4 is a novel prognosis-related hub gene in cutaneous melanoma. The novel gene RTP4 identified here will facilitate the exploration of the molecular mechanism of the pathogenesis and progression of melanoma and the discovery of potential new target for drug therapy.
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Project description:BackgroundCutaneous Melanoma (CM) is a malignant disease with increasing incidence and high mortality. Ferroptosis is a new kind of cell death and related to tumor blood and lymphatic metastasis. This study aims at using bioinformatics technology to construct a prognostic signature and identify ferroptosis-related biomarkers to improve the prognosis and treatment of cutaneous melanoma.MethodsWe used bioinformatics tools to analyze RNA sequencing expression data with clinical information from multiple databases, utilized varieties of statistical methods to construct a ferroptosis-related prognostic signature of cutaneous melanoma and screened out specific genes with independent prognostic ability.ResultsWe obtained 22 ferroptosis-related (P < 0.05) prognostic DEGs in the uniCox regression analysis, among which 10 high-expressed genes (ATG5, CHAC1, FANCD2, FBXL5, HMOX2, HSPB1, NQO1, PEBP1, PRNP, SLC3A2) were screened out by LASSO regression analysis to establish a predictive model. Meanwhile, the ferroptosis-related signature and the nomogram we drew performed an excellent performance based on Kaplan-Meier (K-M), Receiver operating characteristic (ROC) and calibration curves. Univariate and multivariable cox analyses displayed that our model was greater than other prognostic features. GO and KEGG analyses revealed that 10-biomarker signature was mainly related to epidermis differentiation and immunity. ssGSEA analysis indicated that the immune status between the two risk groups was highly different. Besides, we found that two genes (CP, ZEB1) had independent prognostic ability and can be applied for drug research. Both genes were highly related to immunity. GSEA illustrated that ZEB1 may be involved in cellular functions such as proliferation, apoptosis, and migration, while CP was closely connected to immune cell related functions.ConclusionThe present study suggested a 10-biomarker signature can be clinically used to predict the prognosis of cutaneous melanoma, which was better than conventional factors. CP and ZEB1 were independent prognostic genes and can be applied to guide treatment. In addition, ZEB1 mutation was highly related to overall survival in cutaneous melanoma, while CP may be associated with tumor progression. Our study comprehensively analyzed the relationship between iron metabolism, ferroptosis-related genes, and the prognosis of cutaneous melanoma, provided new insight for molecular mechanisms and treatment of ferroptosis and cutaneous melanoma.
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Project description:Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer‑related deaths among cancer patients. Genes correlated with the progression and prognosis of HCC are critically needed to be identified. In the present study, 3 Gene Expression Omnibus (GEO) datasets (GSE46408, GSE65372 and GSE84402) were used to analyze the differentially expressed genes (DEGs) between HCC and non‑tumor liver tissues. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to clarify the functional roles of DEGs. A protein‑protein interaction network was established to screen the hub genes associated with HCC. The prognostic values of hub genes in HCC patients were analyzed using The Cancer Genome Atlas (TCGA) database. The expression levels of hub genes were validated based on ONCOMINE, TCGA and Human Protein Atlas (HPA) databases. Notably, 56 upregulated and 33 downregulated DEGs were markedly enriched under various GO terms and four KEGG terms. Among these DEGs, 10 hub genes with high connectivity degree were identified, including cyclin B1, cyclin A2, cyclin B2, condensin complex subunit 3, PDZ binding kinase, nucleolar and spindle‑associated protein 1, aurora kinase A, ZW10 interacting kinetochore protein, protein regulator of cytokinesis 1 and kinesin family member 4A. The upregulated expression levels of these hub genes in HCC tissues were further confirmed by ONCOMINE, TCGA, and HPA databases. Additionally, the increased mRNA expression of each hub gene was related to the unfavorable disease‑free survival and overall survival of HCC patients. The present study identified ten genes associated with HCC, which may help to provide candidate targets for the diagnosis and treatment of HCC.
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