Histone demethylase UTX regulates glioblastoma progression through affecting periostin expression

The histone H3K27 demethylase UTX participates in regulating multiple cancer types. However, less is known about the UTX function in glioblastoma (GBM). This study aims to define the effect of UTX on GBM. GEPIA2 database analysis showed that UTX expression was significantly increased in GBM and inversely correlated with survival. Knockdown UTX inhibited GBM cell proliferation, migration, and invasion while promoting apoptosis. Moreover, knockdown UTX also hampered tumor growth in the heterotopic xenograft model. RNA-seq combined with qRT-PCR and ChIP-qPCR were used to identify the target genes. The results showed that the UTX-mediated genes were strongly associated with tumor progression and the extracellular environment. Protein-protein interaction analysis suggested that periostin (POSTN) interacted with most of the other UTX-mediated genes. POSTN supplement abolished the effect of UTX knockdown in GBM cells. Furthermore, silencing UTX exhibited similar antitumor effect in patient-derived glioblastoma stem-like cells, while UTX functions were partially restored after exposing POSTN. Our findings may reveal a new insight into the onset of gliomagenesis and progression, providing a promising therapeutic strategy for GBM treatment.

Download Full-text

NUSAP1 Promotes Gastric Cancer Progression Through Regulation of Yap Stability

10.21203/rs.3.rs-33883/v1 ◽

2020 ◽

Author(s):

Hui Guo ◽

Jianping Zou ◽

Ling Zhou ◽

Yan He ◽

Miao Feng ◽

...

Keyword(s):

Gastric Cancer ◽

Cancer Progression ◽

Target Genes ◽

Hippo Pathway ◽

Critical Role ◽

Xenograft Model ◽

Migration And Invasion

Abstract Background:Nucleolar and spindle associated protein (NUSAP1) is involved in tumor initiation, progression and metastasis. However, there are limited studies regarding the role of NUSAP1 in gastric cancer (GC). Methods: The expression profile and clinical significance of NUSAP1 in GC were analysed in online database using GEPIA, Oncomine and KM plotter, which was further confirmed in clinical specimens.The functional role of NUSAP1 were detected utilizing in vitro and in vivo assays. Western blotting, qRT-PCR, the cycloheximide-chase, immunofluorescence staining and Co-immunoprecipitaion (Co-IP) assays were performed to explore the possible molecular mechanism by which NUSAP1 stabilizes YAP protein. Results:In this study, we found that the expression of NUSAP1 was upregulated in GC tissues and correlates closely with progression and prognosis. Additionally, abnormal NUSAP1 expression promoted malignant behaviors of GC cells in vitro and in a xenograft model. Mechanistically, we discovered that NUSAP1 physically interacts with YAP and furthermore stabilizes YAP protein expression, which induces the transcription of Hippo pathway downstream target genes. Furthermore, the effects of NUSAP1 on GC cell growth, migration and invasion were mainly mediated by YAP. Conclusions:Our data demonstrates that the novel NUSAP1-YAP axis exerts an critical role in GC tumorigenesis and progression, and therefore could provide a novel therapeutic target for GC treatment.

Download Full-text

Pan-cancer analysis reveals complex tumor-specific alternative polyadenylation

10.1101/160960 ◽

2017 ◽

Author(s):

Zhuyi Xue ◽

René L Warren ◽

Ewan A Gibb ◽

Daniel MacMillan ◽

Johnathan Wong ◽

...

Keyword(s):

Alternative Polyadenylation ◽

Length Change ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Rna Seq ◽

Multiple Cancer ◽

Tissue Samples ◽

Cancer Genome Atlas ◽

Specific Alternative ◽

Cancer Types

AbstractAlternative polyadenylation (APA) of 3’ untranslated regions (3’ UTRs) has been implicated in cancer development. Earlier reports on APA in cancer primarily focused on 3’ UTR length modifications, and the conventional wisdom is that tumor cells preferentially express transcripts with shorter 3’ UTRs. Here, we analyzed the APA patterns of 114 genes, a select list of oncogenes and tumor suppressors, in 9,939 tumor and 729 normal tissue samples across 33 cancer types using RNA-Seq data from The Cancer Genome Atlas, and we found that the APA regulation machinery is much more complicated than what was previously thought. We report 77 cases (gene-cancer type pairs) of differential 3’ UTR cleavage patterns between normal and tumor tissues, involving 33 genes in 13 cancer types. For 15 genes, the tumor-specific cleavage patterns are recurrent across multiple cancer types. While the cleavage patterns in certain genes indicate apparent trends of 3’ UTR shortening in tumor samples, over half of the 77 cases imply 3’ UTR length change trends in cancer that are more complex than simple shortening or lengthening. This work extends the current understanding of APA regulation in cancer, and demonstrates how large volumes of RNA-seq data generated for characterizing cancer cohorts can be mined to investigate this process.

Download Full-text

Perturbation of Interaction Networks for Application to Cancer Therapy

Cancer Informatics ◽

10.1177/117693510700500005 ◽

2007 ◽

Vol 5 ◽

pp. 117693510700500 ◽

Cited By ~ 5

Author(s):

Adrian P. Quayle ◽

Asim S. Siddiqui ◽

Steven J. M. Jones

Keyword(s):

Protein Interaction ◽

Experimental Testing ◽

Cell Types ◽

Drug Combinations ◽

Interaction Networks ◽

Data Sources ◽

Model Organisms ◽

Multiple Cancer ◽

Protein Protein Interaction ◽

Cancer Types

We present a computational approach for studying the effect of potential drug combinations on the protein networks associated with tumor cells. The majority of therapeutics are designed to target single proteins, yet most diseased states are characterized by a combination of many interacting genes and proteins. Using the topology of protein-protein interaction networks, our methods can explicitly model the possible synergistic effect of targeting multiple proteins using drug combinations in different cancer types. The methodology can be conceptually split into two distinct stages. Firstly, we integrate protein interaction and gene expression data to develop network representations of different tissue types and cancer types. Secondly, we model network perturbations to search for target combinations which cause significant damage to a relevant cancer network but only minimal damage to an equivalent normal network. We have developed sets of predicted target and drug combinations for multiple cancer types, which are validated using known cancer and drug associations, and are currently in experimental testing for prostate cancer. Our methods also revealed significant bias in curated interaction data sources towards targets with associations compared with high-throughput data sources from model organisms. The approach developed can potentially be applied to many other diseased cell types.

Download Full-text

miR-206 Inhibits Cell Proliferation, Migration, and Invasion by Targeting BAG3 in Human Cervical Cancer

Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics ◽

10.3727/096504017x15143731031009 ◽

2018 ◽

Vol 26 (6) ◽

pp. 923-931 ◽

Cited By ~ 12

Author(s):

Yingying Wang ◽

Yongjie Tian

Keyword(s):

Cervical Cancer ◽

Cell Proliferation ◽

Protein Expression ◽

Xenograft Model ◽

Migration And Invasion ◽

Normal Tissues ◽

Bax Protein ◽

Cancer Types

miR-206 and Bcl-2-associated athanogene 3 (BAG3) have been suggested as important regulators in various cancer types. However, the biological role of miR-206 and BAG3 in cervical cancer (CC) remains unclear. We investigated the expressions and mechanisms of miR-206 and BAG3 in CC using in vitro and in vivo assays. In the present study, miR-206 expression was expressed at a lower level in CC tissues and cells than adjacent normal tissues and NEECs. By contrast, BAG3 mRNA and protein were expressed at higher levels in CC tissues and cells. Furthermore, miR-206 overexpression repressed cell proliferation, migration, and invasion in vitro, and the 3′-untranslated region (3′-UTR) of BAG3 was a direct target of miR-206. miR-206 overexpression also inhibited EGFR, Bcl-2, and MMP2/9 protein expression, but promoted Bax protein expression. Besides, BAG3 overexpression partially abrogated miR-206-inhibited cell proliferation and invasion, while BAG3 silencing enhanced miR-206-mediated inhibition. In vivo assay revealed that miR-206 repressed tumor growth in nude mice xenograft model. In conclusion, miR-206 inhibits cell proliferation, migration, and invasion by targeting BAG3 in human CC. Thus, miR-206-BAG3 can be used as a useful target for CC.

Download Full-text

NUSAP1 Promotes Gastric Cancer Tumorigenesis and Progression by Stabilizing the YAP1 Protein

Frontiers in Oncology ◽

10.3389/fonc.2020.591698 ◽

2021 ◽

Vol 10 ◽

Author(s):

Hui Guo ◽

Jianping Zou ◽

Ling Zhou ◽

Min Zhong ◽

Yan He ◽

...

Keyword(s):

Gastric Cancer ◽

Target Genes ◽

Hippo Pathway ◽

Therapeutic Targets ◽

Xenograft Model ◽

Migration And Invasion ◽

Aberrant Expression ◽

Downstream Target ◽

Tumorigenesis And Progression

The Yes-associated protein (YAP1) is a main effector of the canonical Hippo pathway, which contributes greatly to tumor initiation, progression, and metastasis in multiple cancers, including gastric cancer (GC). Due to limited knowledge of YAP1 upregulation in cancer, it is a great challenge of therapeutic targets toward the Hippo–YAP1 pathway. Here, we identify nucleolar spindle-associated protein 1 (NUSAP1) as a novel binding partner of YAP1. The upregulation of NUSAP1 is associated with unfavorable clinical outcomes in GC patients, and NUSAP1 depletion impairs its oncogenic properties in vitro and in a xenograft model. Mechanistically, we discovered that NUSAP1 functions as a positive regulator of YAP1 protein stability, thereby inducing the transcription of Hippo pathway downstream target genes, such as CTGF and CYR61. More interestingly, we find that the cancer-promoting effects of NUSAP1 on GC cell growth, migration, and invasion are mainly mediated by YAP1. Furthermore, aberrant expression of NUSAP1 and YAP1 is highly correlated in GC cell lines and tissues. We herein clarify the role of the oncogenic NUSAP1–YAP1 axis in GC tumorigenesis and progression and, therefore, provide novel therapeutic targets for GC treatment.

Download Full-text

StrongestPath: a Cytoscape application for protein-protein interaction analysis

10.1101/2020.11.12.380600 ◽

2020 ◽

Author(s):

Zaynab Mousavian ◽

Mehran Khodabandeh ◽

Ali Sharifi-Zarchi ◽

Alireza Nadafian ◽

Alireza Mahmoudi

Keyword(s):

Protein Interaction ◽

Target Genes ◽

Interaction Analysis ◽

Confidence Score ◽

Signaling Network ◽

Easy Access ◽

Protein Protein Interaction ◽

Or Groups ◽

User Friendly ◽

Short Time

ABSTRACTBackgroundStrongestPath is a Cytoscape 3 application that enables to look for one or more cascades of interactions connecting two single or groups of proteins in a collection of protein-protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, it is able to process them and identify the cascade of interactions having the highest total confidence score. Given a set of proteins, StrongestPath can extract and show the network of interactions among them from the given databases, and expand the network by adding new proteins having the most interactions with highest total confidence to the current proteins. The application can also identify any activation or inhibition regulatory paths between two distinct sets of transcription factors and target genes. This application can be either used with a set of built-in human and mouse PPI or signaling databases, or any user-provided database for some organism.ResultsOur results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in the middle of the pathway by finding the strongest path(s) in the PPI or signaling network.ConclusionEasy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform and providing a user-friendly graphical interface make the StrongestPath easy to use.

Download Full-text

3506 PRMT5 is a novel therapeutic target to enhance radiation therapy for cancer treatment

Journal of Clinical and Translational Science ◽

10.1017/cts.2019.257 ◽

2019 ◽

Vol 3 (s1) ◽

pp. 112-112

Author(s):

Jake L Owens ◽

Elena Beketova ◽

Samantha Tinsley ◽

Andrew Asberry ◽

Xuehong Deng ◽

...

Keyword(s):

Prostate Cancer ◽

Radiation Therapy ◽

Cancer Treatment ◽

Target Genes ◽

Rna Seq ◽

Prostate Cancer Cells ◽

Dsb Repair ◽

Risk Patients ◽

Radiation Induced ◽

Cancer Types

OBJECTIVES/SPECIFIC AIMS: Prostate cancer is the second leading cause of cancer-related death among men in the U.S. and over half of all prostate cancer patients receive radiation therapy (RT). RT induces double-strand breaks (DSBs) in DNA which are lethal to cells if not repaired. While potentially curative, 10% of low-risk patients and 50% of high-risk patients treated with RT still experience tumor recurrence. Thus, identification of novel therapeutic targets to enhance RT will likely reduce prostate cancer mortality. The only clinical approach to enhance RT is androgen deprivation therapy, which targets androgen receptor (AR) signaling; however, its use is limited due to systemic side effects. We recently reported that PRMT5 epigenetically activates AR which led us to investigate if targeting PRMT5 sensitizes prostate cancer to RT. The goal of this project is to determine if PRMT5 is a therapeutic target for prostate cancer radiosensitization and analyze its mechanistic role in response to radiation. METHODS/STUDY POPULATION: To evaluate if targeting PRMT5 may sensitize prostate cancer cells to radiation, we performed a clonogenic assay of irradiated cells. To determine if PRMT5 is required for repair of radiation-induced DSBs, we performed foci analysis via immunocytochemistry. We then used RNA-seq, qPCR, western blot, and ChIP to evaluate a potential epigenetic role of PRMT5 in activating the expression of genes critical to DSB repair. To extend our findings, we analyzed clinical data from around 18,000 of cancer patients encompassing 43 cancer types to assess if PRMT5 expression correlates with the expression of its putative target genes. RESULTS/ANTICIPATED RESULTS: Targeting PRMT5 sensitizes prostate cancer cells to radiation independently of AR status. RNA-seq analysis revealed putative PRMT5 target genes including several involved in DSB repair and G2 arrest. Mechanistically, PRMT5 functions as a master epigenetic activator of DNA damage response (DDR) genes: PRMT5 maintains the basal expression of several DDR genes including BRCA1, BRCA2, and RAD51 and is recruited upon radiation to DDR gene promoters to activate their expression via histone methylation. Targeting PRMT5 decreases expression of these genes at the protein level and hinders repair of radiation-induced DSBs in multiple cancer and non-cancer cell types. Clinically, PRMT5 expression positively correlates with the expression of these DDR genes across all 43 cancer types analyzed. DISCUSSION/SIGNIFICANCE OF IMPACT: PRMT5 acts as a master epigenetic activator of genes involved in DDR and is critical for cells to survive radiation treatment. Importantly, PRMT5 epigenetically activates multiple genes that encode for well-characterized core repair proteins involved in HR (RAD51, RAD51AP1, RAD51D, BRCA1 and BRCA2) and NHEJ (NHEJ1, Ku80, XRCC4, and DNAPKcs), which may explain why PRMT5 is essential to repair IR-induced DSBs in several cell lines. As PRMT5 is overexpressed in many human cancers and its overexpression correlates with poor prognosis, our findings suggest that more efficient DSB repair via PRMT5 overexpression in these cancers may confer survival advantages particularly following DNA damaging treatments. Lastly, because targeting DSB repair is a clinically validated therapeutic approach for cancer treatment, our findings also suggest that PRMT5 targeting may be explored as a monotherapy or in combination therapy with radiation therapy or chemotherapy for cancer treatment.

Download Full-text

StrongestPath: a Cytoscape application for protein–protein interaction analysis

BMC Bioinformatics ◽

10.1186/s12859-021-04230-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Zaynab Mousavian ◽

Mehran Khodabandeh ◽

Ali Sharifi-Zarchi ◽

Alireza Nadafian ◽

Alireza Mahmoudi

Keyword(s):

Protein Interaction ◽

Target Genes ◽

Interaction Analysis ◽

Confidence Score ◽

Signaling Network ◽

Easy Access ◽

Protein Protein Interaction ◽

Or Groups ◽

User Friendly ◽

Short Time

Abstract Background StrongestPath is a Cytoscape 3 application that enables the analysis of interactions between two proteins or groups of proteins in a collection of protein–protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, the application is able to process them and identify the cascade of interactions with the highest total confidence score. Given a set of proteins, StrongestPath can extract a set of possible interactions between the input proteins, and expand the network by adding new proteins that have the most interactions with highest total confidence to the current network of proteins. The application can also identify any activating or inhibitory regulatory paths between two distinct sets of transcription factors and target genes. This application can be used on the built-in human and mouse PPI or signaling databases, or any user-provided database for some organism. Results Our results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in a pathway by finding the strongest path(s) in the PPI or signaling network. Conclusion Easy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform, and providing a user-friendly graphical interface make StrongestPath an extremely useful application.

Download Full-text

Comprehensive Analysis of Large-Scale Transcriptomes from Multiple Cancer Types

Genes ◽

10.3390/genes12121865 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1865

Author(s):

Baoting Nong ◽

Mengbiao Guo ◽

Weiwen Wang ◽

Songyang Zhou ◽

Yuanyan Xiong

Keyword(s):

Ribosome Biogenesis ◽

Large Scale ◽

Rna Binding ◽

Workflow Management ◽

Rna Seq ◽

Contributing Factors ◽

Multiple Cancer ◽

Analysis Workflow ◽

Liver And Kidney ◽

Cancer Types

Various abnormalities of transcriptional regulation revealed by RNA sequencing (RNA-seq) have been reported in cancers. However, strategies to integrate multi-modal information from RNA-seq, which would help uncover more disease mechanisms, are still limited. Here, we present PipeOne, a cross-platform one-stop analysis workflow for large-scale transcriptome data. It was developed based on Nextflow, a reproducible workflow management system. PipeOne is composed of three modules, data processing and feature matrices construction, disease feature prioritization, and disease subtyping. It first integrates eight different tools to extract different information from RNA-seq data, and then used random forest algorithm to study and stratify patients according to evidences from multiple-modal information. Its application in five cancers (colon, liver, kidney, stomach, or thyroid; total samples n = 2024) identified various dysregulated key features (such as PVT1 expression and ABI3BP alternative splicing) and pathways (especially liver and kidney dysfunction) shared by multiple cancers. Furthermore, we demonstrated clinically-relevant patient subtypes in four of five cancers, with most subtypes characterized by distinct driver somatic mutations, such as TP53, TTN, BRAF, HRAS, MET, KMT2D, and KMT2C mutations. Importantly, these subtyping results were frequently contributed by dysregulated biological processes, such as ribosome biogenesis, RNA binding, and mitochondria functions. PipeOne is efficient and accurate in studying different cancer types to reveal the specificity and cross-cancer contributing factors of each cancer.It could be easily applied to other diseases and is available at GitHub.

Download Full-text

Characterization of the Potential Role of NTPCR in Epithelial Ovarian Cancer by Integrating Transcriptomic and Metabolomic Analysis

Frontiers in Genetics ◽

10.3389/fgene.2021.695245 ◽

2021 ◽

Vol 12 ◽

Author(s):

Hongkai Shang ◽

Huizhi Zhang ◽

Ziyao Ren ◽

Hongjiang Zhao ◽

Zhifen Zhang ◽

...

Keyword(s):

Cell Proliferation ◽

Signaling Pathways ◽

Disease Progression ◽

Target Genes ◽

Migration And Invasion ◽

Sequencing Analysis ◽

Protein Protein Interaction ◽

Skov3 Cells ◽

M Phase ◽

Cancer Tissues

BackgroundEpithelial ovarian carcinoma (EOC) is a malignant tumor with high motility in women. Our previous study found that dysregulated nucleoside-triphosphatase cancer-related (NTPCR) was associated with the prognosis of EOC patients, and thus, this present study attempted to explore the potential roles of NTPCR in disease progression.MethodsExpressed level of NTPCR was investigated in EOC tissues by RT-qPCR and Western blot analysis. NTPCR shRNA and overexpression vector were generated and transfected into OVCAR-3 or SKOV3 cells to detect the effect of NTPCR on cell proliferation, cell cycle, cell migration, and invasion. Transcriptomic sequencing and metabolite profiling analysis were performed in shNTPCR groups to identify transcriptome or metabolite alteration that might contribute to EOC. Finally, we searched the overlapped signaling pathways correlated with differential metabolites and differentially expressed genes (DEGs) by integrating analysis.ResultsComparing para-cancerous tissues, we found that NTPCR is highly expressed in cancer tissues (p < 0.05). Overexpression of NTPCR inhibited cell proliferation, migration, and invasion and reduced the proportion of S- and G2/M-phase cells, while downregulation of NTPCR showed the opposite results. RNA sequencing analysis demonstrated cohorts of DEGs were identified in shNTPCR samples. Protein–protein interaction networks were constructed for DEGs. STAT1 (degree = 43) and OAS2 (degree = 36) were identified as hub genes in the network. Several miRNAs together with target genes were predicted to be crucial genes related to disease progression, including hsa-miR-124-3p, hsa-miR-30a-5p, hsa-miR-146a-5, EP300, GATA2, and STAT3. We also screened the differential metabolites from shNTPCR samples, including 22 upregulated and 22 downregulated metabolites. By integrating transcriptomics and metabolomics analysis, eight overlapped pathways were correlated with these DEGs and differential metabolites, such as primary bile acid biosynthesis, protein digestion, and absorption, pentose, and glucuronate interconversions.ConclusionNTPCR might serve as a tumor suppressor in EOC progression. Our results demonstrated that DEGs and differential metabolites were mainly related to several signaling pathways, which might be a crucial role in the progression of NTPCR regulation of EOC.

Download Full-text