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:This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs.
| S-EPMC9499749 | biostudies-literature
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.
| S-EPMC7668584 | biostudies-literature
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.
| S-EPMC8040875 | biostudies-literature
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.
| S-EPMC9258069 | biostudies-literature
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.
| S-EPMC8582397 | biostudies-literature
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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Project description:PurposeUveal melanoma is a rare melanoma variant with no effective therapies once metastases develop. Although durable cancer regression can be achieved in metastatic cutaneous melanoma with immunotherapies that augment naturally existing antitumor T-cell responses, the role of these treatments for metastatic uveal melanoma remains unclear. We sought to define the relative immunogenicity of these two melanoma variants and determine whether endogenous antitumor immune responses exist against uveal melanoma.Experimental designWe surgically procured liver metastases from uveal melanoma (n = 16) and cutaneous melanoma (n = 35) patients and compared the attributes of their respective tumor cell populations and their infiltrating T cells (TIL) using clinical radiology, histopathology, immune assays, and whole-exomic sequencing.ResultsDespite having common melanocytic lineage, uveal melanoma and cutaneous melanoma metastases differed in their melanin content, tumor differentiation antigen expression, and somatic mutational profile. Immunologic analysis of TIL cultures expanded from these divergent forms of melanoma revealed cutaneous melanoma TIL were predominantly composed of CD8(+) T cells, whereas uveal melanoma TIL were CD4(+) dominant. Reactivity against autologous tumor was significantly greater in cutaneous melanoma TIL compared with uveal melanoma TIL. However, we identified TIL from a subset of uveal melanoma patients which had robust antitumor reactivity comparable in magnitude with cutaneous melanoma TIL. Interestingly, the absence of melanin pigmentation in the parental tumor strongly correlated with the generation of highly reactive uveal melanoma TIL.ConclusionsThe discovery of this immunogenic group of uveal melanoma metastases should prompt clinical efforts to determine whether patients who harbor these unique tumors can benefit from immunotherapies that exploit endogenous antitumor T-cell populations. Clin Cancer Res; 22(9); 2237-49. ©2015 AACR.
| S-EPMC4854785 | biostudies-literature
Project description:Melanoma of the uveal tract accounts for approximately 5% of all melanomas and represents the most common primary intraocular malignancy. Despite improvements in diagnosis and more effective local therapies for primary cancer, the rate of metastatic death has not changed in the past forty years. In the present study, we made use of bioinformatics to analyze the data obtained from three public available microarray datasets on uveal melanoma in an attempt to identify novel putative chemotherapeutic options for the liver metastatic disease. We have first carried out a meta-analysis of publicly available whole-genome datasets, that included data from 132 patients, comparing metastatic vs. non metastatic uveal melanomas, in order to identify the most relevant genes characterizing the spreading of tumor to the liver. Subsequently, the L1000CDS2 web-based utility was used to predict small molecules and drugs targeting the metastatic uveal melanoma gene signature. The most promising drugs were found to be Cinnarizine, an anti-histaminic drug used for motion sickness, Digitoxigenin, a precursor of cardiac glycosides, and Clofazimine, a fat-soluble iminophenazine used in leprosy. In vitro and in vivo validation studies will be needed to confirm the efficacy of these molecules for the prevention and treatment of metastatic uveal melanoma.
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Project description:Introduction: Stroke, of which ischemic stroke (IS) is the major type, is the second leading cause of disability and death worldwide. Circular RNAs (circRNAs) are reported to play important role in the physiology and pathology of IS. CircRNAs often act as competing endogenous RNA (ceRNA) to regulate gene expression by acting as miRNA sponges. However, whole transcriptome-wide screenings of circRNA-mediated ceRNA networks associated with IS are still lacking. In the present study, we constructed a circRNA-miRNA-mRNA ceRNA network by whole transcriptome-wide analysis. Methods: CircRNAs, miRNAs and mRNAs expression profiles were downloaded from the Gene Expression Omnibus (GEO) datasets. We identified differentially expressed (DE) circRNAs, miRNAs, and mRNAs in IS patients. StarBase and CircBank databases were used to predict the miRNA targets of DEcircRNAs, and mirDIP database was used to predict the mRNA targets of DEmiRNAs. CircRNA-miRNA pairs and miRNA-mRNA pairs were established. Then, we identified hub genes via protein-protein interaction analysis and constructed a core ceRNA sub-network. Results: In total, 276 DEcircRNAs, 43 DEmiRNAs, and 1926 DEmRNAs were explored. The ceRNA network included 69 circRNAs, 24 miRNAs, and 92 mRNAs. The core ceRNA subnetwork included hsa_circ_0011474, hsa_circ_0023110, CDKN1A, FHL2, RPS2, CDK19, KAT6A, CBX1, BRD4, and ZFHX3. Discussion: In conclusion, we established a novel hsa_circ_0011474 - hsa-miR-20a-5p/hsa-miR-17-5p - CDKN1A ceRNA regulatory axis associated with IS. Our findings provide new insights into the pathogenesis of IS and offer promising diagnostic and predictive biomarkers.
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