VECTOR: An Integrated Correlation Network Database for the Identification of CeRNA Axes in Uveal Melanoma.
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ABSTRACT:
SUBMITTER: Barbagallo C
PROVIDER: S-EPMC8305227 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundUveal melanoma (UM) is the most common primary intraocular malignancy in adults. Many previous studies have demonstrated that the infiltrating of immune and stromal cells in the tumor microenvironment contributes significantly to prognosis.MethodsDataset TCGA-UVM, download from TCGA portal, was taken as the training cohort, and GSE22138, obtained from GEO database, was set as the validation cohort. ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to initial screen for potential prognostic genes. Then these genes entered into the validation cohort for validation using the same methods as that in the training cohort. Moreover, we conducted correlation analyses between the genes obtained in the validation cohort and the status of chromosome 3, chromosome 8q, and tumor metastasis to get prognosis genes. At last, the immune infiltration analysis was performed between the prognostic genes and 6 main kinds of tumor-infiltrating immune cells (TICs) for understanding the role of the genes in the tumor microenvironment.Results959 intersection DEGs were found in the UM microenvironment. Kaplan-Meier and Cox analysis was then performed in the training and validation cohorts on these DEGs, and 52 genes were identified with potential prognostic value. After comparing the 52 genes to chromosome 3, chromosome 8q, and metastasis, we obtained 21 genes as the prognostic genes. The immune infiltration analysis showed that Neutrophil had the potential prognostic ability, and almost every prognostic gene we had identified was correlated with abundances of Neutrophil and CD8+ T Cell.ConclusionsIdentifying 21 prognosis genes (SERPINB9, EDNRB, RAPGEF3, HFE, RNF43, ZNF415, IL12RB2, MTUS1, NEDD9, ZNF667, AZGP1, WARS, GEM, RAB31, CALHM2, CA12, MYEOV, CELF2, SLCO5A1, ISM1, and PAPSS2) could accurately identify patients' prognosis and had close interactions with Neutrophil in the tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.
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Project description:Uveal melanoma (UM) is a comparatively rare cancer but requires serious consideration since patients with developing metastatic UM survive only for about 6-12 months. Fortunately, increasingly large multi-omics databases allow us to further understand cancer initiation and development. Moreover, previous studies have observed that associations between copy number aberrations (CNA) or methylation (MET) versus messenger RNA (mRNA) expression have affected these processes. From that, we decide to explore the effect of these associations on a case study of UM. Also, the current subtypes of UM display its weak association with biological phenotypes and its lack of therapy suggestions. Therefore, the re-identification of molecular subtypes is a pressing need. In this study, we recruit three omics profiles, including CNA, MET, and mRNA, in a UM cohort from The Cancer Genome Atlas (TCGA). Firstly, we identify two sets of genes, CNAexp and METexp, whose CNA and MET significantly correlated with their corresponding mRNA, respectively. Then, single and integrative analyses of the three data types are performed using the PINSPlus tool. As a result, we discover two novel integrative subgroups, IntSub1 and IntSub2, which could be a useful alternative classification for UM patients in the future. To further explore molecular events behind each subgroup, we identify their subgroup-specific genes computationally. Accordingly, the highest expressed genes among IntSub1-specific genes are mostly enriched with immune-related processes. On the other hand, IntSub2-specific genes are highly associated with cellular cation homeostasis, which responds effectively to chemotherapy using ion channel inhibitor drugs. In addition, we detect that the two integrative subgroups show different age-related risks and survival rates. These discoveries can influence the frequency of metastatic surveillance and support medical practitioners to choose an appropriate treatment regime.
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Project description:Melanoma is an extremely malignant tumor with early metastasis and high mortality. Little is known about the process of by which melanoma occurs, as its mechanism is very complex and only limited data are available on its long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs). The purpose of this study was to screen out potential prognostic molecules and identify a ceRNA network related to the occurrence of melanoma. We screened 169 differentially expressed mRNAs (DEmRNAs) from E-MTAB-1862 and GSE3189; gene ontology (GO) enrichment analysis showed that these genes were closely related to the development of skin. In the protein-protein interaction network, we screened out a total of 19 hub genes. Furthermore, we predicted the microRNAs (miRNAs) that regulate hub genes using the miRWalk database and then intersected these with GSE35579, resulting in nine DEmiRNAs. We also predicted the lncRNAs that regulate the miRNAs using the LncBasev.2 database. According to the ceRNA hypothesis, and based on the intersection of the DElncRNAs with merged GTEx and TCGA data, we obtained 20 DElncRNAs. A total of four DEmRNAs, nine DEmiRNAs, and 20 DElncRNAs were included in the ceRNA network. Based on Cox stepwise regression and survival analysis, we identified five biomarkers, ZSCAN16-AS1, LINC00520, XIST, DTL, and let-7a-5p, and obtained risk scores. The results showed that most of the differentially expressed genes were related to epithelial-mesenchymal transition (EMT) in melanoma. Finally, we obtained a LINC00520/let-7a-5p/DTL molecular regulatory network. These results suggest that ceRNA networks have an important role in evaluating the prognosis of patients with melanoma and provide a new experimental basis for exploring the EMT process in the development of melanoma.
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Project description:BackgroundUveal melanoma (UM) is the most common primary intraocular malignancy with a strong tendency to metastasize. The prognosis is poor once metastasis occurs. The treatment remains challenging for metastatic UM, even though our understanding of UM has advanced, mostly because the complexity of the genetic and immunologic background has not been fully explored.MethodsSingle-cell sequencing data were acquired from a healthy dataset and three UM datasets. The differentially expressed genes between primary and metastatic UM in The Cancer Genome Atlas (TCGA) data were attributed to specific cell types and explained with functional annotation. The analysis for cell-cell communication was conducted by "CellChat" to understand the cell crosstalk among the cell clusters and to delineate the dysfunctional signaling pathways in metastatic UM. CCK-8, EdU and transwell assays were performed to verify the function of the genes of interest.ResultsWe revealed aberrant signaling pathways with distinct functional statuses between primary and metastatic UM by integrating multiple datasets. The crucial signals contributing most to outgoing or incoming signaling of metastasis were identified to uncover the potential targeting genes. The association of these genes with disease risk was estimated based on survival data from TCGA. The key genes associated with proliferation and metastasis were verified.ConclusionsConclusively, we discovered the potential key signals for occurrence and metastasis of UM and provided a theoretical basis for potential clinical application.
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Project description:This study reports the role played by the mutation status of Uveal Melanoma (UM) in relation to hepatic metastatic patterns as seen on imaging modalities. Radiological images were obtained from 123 patients treated at the Erasmus Medical Center Rotterdam or the Rotterdam Eye Hospital. Radiological images were derived from either computed tomography or magnetic resonance imaging. Hepatic metastatic patterns were classified by counting the number of metastases found in the liver. Miliary metastatic pattern (innumerable small metastases in the entire liver) was analyzed separately. Mutation status was determined in 85 patients. Median disease-free survival (DFS) and survival with metastases differed significantly between each of the metastatic patterns (respectively, p = 0.009, p < 0.001), both in favor of patients with less hepatic metastases. The mutation status of the primary tumor was not correlated with any hepatic tumor profiles (p = 0.296). Of the patients who had a solitary metastasis (n = 18), 11 originated from a primary BAP1-mutated tumors and one from a primary SF3B1-mutated tumor. Of the patients who had a miliary metastasis pattern (n = 24), 17 had a primary BAP1-mutated tumor and two had a primary SF3B1-mutated tumor. Chromosome 8p loss was significantly more in patients with more metastases (p = 0.045). Moreover, the primary UMs of patients with miliary metastases harbored more chromosome 8p and 1p loss, compared to patients with single solitary metastasis (p = 0.035 and p = 0.026, respectively). In conclusion, our study shows that there is an inverse correlation of the number of metastasis with the DFS and metastasized survival, indicating separate growth patterns. We also revealed that the number and type of metastases is irrelevant to the prognostic mutation status of the tumor, showing that both BAP1- and SF3B1-mutated UM can result in solitary and miliary metastases, indicating that other processes lay ground to the different metastatic patterns.
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Project description:Uveal melanoma (UM) is an uncommon but highly aggressive ocular malignancy. Poor overall survival is associated with deleterious BAP1 alterations, which frequently occur with monosomy 3 (LOH3) and a characteristic gene expression profile. Tumor DNA from a cohort of 100 UM patients from Moorfields Biobank (UK) that had undergone enucleation were sequenced for known UM driver genes (BAP1, SF3B1, EIF1AX, GNAQ, and GNA11). Immunohistochemical staining of BAP1 and interphase FISH for chromosomes 3 and 8 was performed, and cellular localization of BAP1 was correlated with BAP1 mutations. Wildtype (WT) BAP1 staining was characterized by nBAP1 expression with <10% cytoplasmic BAP1 (cBAP1). Tumors exhibited heterogeneity with respect to BAP1 staining with different percentages of nBAP1 loss: ≥25% loss of nuclear BAP1 (nBAP1) was superior to chr8q and LOH3 as a prognostic indicator. Of the successfully sequenced UMs, 38% harbored oncogenic mutations in GNA11 and 48% harbored mutations in GNAQ at residues 209 or 183. Of the secondary drivers, 39% of mutations were in BAP1, 11% were in EIF1AX, and 20% were in the SF3B1 R625 hotspot. Most tumors with SF3B1 or EIF1AX mutations retained nuclear BAP1 (nBAP1). The majority of tumor samples with likely pathogenic BAP1 mutations, regardless of mutation class, displayed ≥25% loss of nBAP1. This included all tumors with truncating mutations and 80% of tumors with missense mutations. In addition, 60% of tumors with truncating mutations and 82% of tumors with missense mutations expressed >10% cBAP1.
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Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most aggressive malignant tumors, with a poor long-term prognosis worldwide. The functional deregulations of global transcriptome were associated with the genesis and development of HCC, but lacks systematic research and validation.MethodsA total of 519 postoperative HCC patients were included. We built an interactive and visual competing endogenous RNA network. The prognostic signature was established with the least absolute shrinkage and selection operator algorithm. Multivariate Cox regression analysis was used to screen for independent prognostic factors for HCC overall survival.ResultsIn the training set, we identified a four-gene signature (PBK, CBX2, CLSPN, and CPEB3) and effectively predicted the overall survival. The survival times of patients in the high-score group were worse than those in the low-score group (p = 0.0004), and death was also more likely in the high-score group (HR 2.444, p < 0.001). The results were validated in internal validation set (p = 0.0057) and two external validation cohorts (HR 2.467 and 2.6). The signature (AUCs of 1, 2, 3 years were 0.716, 0.726, 0.714, respectively) showed high prognostic accuracy in the complete TCGA cohort.ConclusionsIn conclusion, we successfully built a more extensive ceRNA network for HCC and then identified a four-gene-based signature, enabling prediction of the overall survival of patients with HCC.
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