Dataset Information

Multi-Platform Omics Analysis for Identification of Molecular Characteristics and Therapeutic Targets of Uveal Melanoma.

ABSTRACT: Currently, there is no effective treatment for metastatic uveal melanoma (UVM). Here, we aimed to identify the mechanism involving intrinsic chemoresistance of metastatic UVM and the relevant therapeutic targets for UVM. We analyzed cohorts of 80 and 67 patients with primary UVM and skin cutaneous melanoma (SKCM), respectively, using The Cancer Genome Atlas dataset. Mutational burdens identified by whole exome sequencing were significantly lower in UVM than in SKCM patients. COSMIC mutational signature analysis identified that most of the mutations in UVM patients (>90%) were associated with spontaneous deamination of 5-methylcytosine or defective mismatch repair. Transcriptome analysis revealed that the MYC signature was more enriched in UVM patients, as compared to SKCM patients. Fifty-nine (73.8%) of 80 UVM patients showed gains in MYC copy number, and a high MYC copy number was associated with aggressive clinicopathological features of tumors and poor survival. Kinome-wide siRNA library screening identified several therapeutic targets, reported as synthetic lethal targets for MYC-addicted cancers. Notably, UVM cell lines showed high susceptibility to a WEE1 inhibitor (MK-1775; adavosertib) at a clinically tolerable dose. Overall, our study identified high MYC activity in UVM, and suggested G2/M checkpoint inhibitors as effective therapeutic targets for UVM.

SUBMITTER: Kim YJ

PROVIDER: S-EPMC6917695 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Multi-Platform Omics Analysis for Identification of Molecular Characteristics and Therapeutic Targets of Uveal Melanoma.

Kim Yong Joon YJ Park Seo Jin SJ Maeng Kyung Joo KJ Lee Sung Chul SC Lee Christopher Seungkyu CS

Scientific reports 20191217 1

Currently, there is no effective treatment for metastatic uveal melanoma (UVM). Here, we aimed to identify the mechanism involving intrinsic chemoresistance of metastatic UVM and the relevant therapeutic targets for UVM. We analyzed cohorts of 80 and 67 patients with primary UVM and skin cutaneous melanoma (SKCM), respectively, using The Cancer Genome Atlas dataset. Mutational burdens identified by whole exome sequencing were significantly lower in UVM than in SKCM patients. COSMIC mutational si ...[more]

PMID: 31848373

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Project description:Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

Project description:Esophageal squamous cell carcinoma (ESCC) is a major histological subtype of esophageal cancer with inferior prognosis. Here, we conducted comprehensive transcriptomic, proteomic, phosphoproteomic, and metabolomic characterization of human, treatment-naive ESCC and paired normal adjacent tissues (cohort 1, n = 24) in an effort to identify new molecular vulnerabilities for ESCC and potential therapeutic targets. Integrative analysis revealed a small group of genes that were related to the active posttranscriptional and posttranslational regulation of ESCC. By using proteomic, phosphoproteomic, and metabolomic data, networks of ESCC-related signaling and metabolic pathways that were closely linked to cancer etiology were unraveled. Notably, integrative analysis of proteomic and phosphoproteomic data pinpointed that certain pathways involved in RNA transcription, processing, and metabolism were stimulated in ESCC. Importantly, proteins with close linkage to ESCC prognosis were identified. By enrolling an ESCC patient cohort 2 (n = 41), three top-ranked prognostic proteins X-prolyl aminopeptidase 3 (XPNPEP3), bromodomain PHD finger transcription factor (BPTF), and fibrillarin (FBL) were verified to have increased expression in ESCC. Among these prognostic proteins, only FBL, a well-known nucleolar methyltransferase, was essential for ESCC cell growth in vitro and in vivo. Furthermore, a validation study using an ESCC patient cohort 3 (n = 100) demonstrated that high FBL expression predicted unfavorable patient survival. Finally, common cancer/testis antigens and established cancer drivers and kinases, all of which could direct therapeutic decisions, were characterized. Collectively, our multi-omics analyses delineated new molecular features associated with ESCC pathobiology involving epigenetic, posttranscriptional, posttranslational, and metabolic characteristics, and unveiled new molecular vulnerabilities with therapeutic potential for ESCC.

Dataset Information

Multi-Platform Omics Analysis for Identification of Molecular Characteristics and Therapeutic Targets of Uveal Melanoma.

Publications

Multi-Platform Omics Analysis for Identification of Molecular Characteristics and Therapeutic Targets of Uveal Melanoma.

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