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Boyd SS, Slawson C, Thompson JA. AMEND: active module identification using experimental data and network diffusion. BMC Bioinformatics 2023; 24:277. [PMID: 37415126 DOI: 10.1186/s12859-023-05376-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 06/02/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND Molecular interaction networks have become an important tool in providing context to the results of various omics experiments. For example, by integrating transcriptomic data and protein-protein interaction (PPI) networks, one can better understand how the altered expression of several genes are related with one another. The challenge then becomes how to determine, in the context of the interaction network, the subset(s) of genes that best captures the main mechanisms underlying the experimental conditions. Different algorithms have been developed to address this challenge, each with specific biological questions in mind. One emerging area of interest is to determine which genes are equivalently or inversely changed between different experiments. The equivalent change index (ECI) is a recently proposed metric that measures the extent to which a gene is equivalently or inversely regulated between two experiments. The goal of this work is to develop an algorithm that makes use of the ECI and powerful network analysis techniques to identify a connected subset of genes that are highly relevant to the experimental conditions. RESULTS To address the above goal, we developed a method called Active Module identification using Experimental data and Network Diffusion (AMEND). The AMEND algorithm is designed to find a subset of connected genes in a PPI network that have large experimental values. It makes use of random walk with restart to create gene weights, and a heuristic solution to the Maximum-weight Connected Subgraph problem using these weights. This is performed iteratively until an optimal subnetwork (i.e., active module) is found. AMEND was compared to two current methods, NetCore and DOMINO, using two gene expression datasets. CONCLUSION The AMEND algorithm is an effective, fast, and easy-to-use method for identifying network-based active modules. It returned connected subnetworks with the largest median ECI by magnitude, capturing distinct but related functional groups of genes. Code is freely available at https://github.com/samboyd0/AMEND .
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Affiliation(s)
- Samuel S Boyd
- Department of Biostatistics and Data Science, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS, 66103, USA
- University of Kansas Cancer Center, Kansas City, KS, USA
| | - Chad Slawson
- Department of Biochemistry, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS, 66103, USA
- University of Kansas Cancer Center, Kansas City, KS, USA
- University of Kansas Alzheimer's Disease Research Center, Fairway, KS, USA
| | - Jeffrey A Thompson
- Department of Biostatistics and Data Science, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS, 66103, USA.
- University of Kansas Cancer Center, Kansas City, KS, USA.
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Sarafidis M, Lambrou GI, Zoumpourlis V, Koutsouris D. An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer. Cancers (Basel) 2022; 14:cancers14143358. [PMID: 35884419 PMCID: PMC9319344 DOI: 10.3390/cancers14143358] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/03/2022] [Accepted: 07/06/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology. Abstract Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.
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Affiliation(s)
- Michail Sarafidis
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
- Correspondence: ; Tel.: +30-210-772-2430
| | - George I. Lambrou
- Choremeio Research Laboratory, First Department of Pediatrics, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece;
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece
| | - Vassilis Zoumpourlis
- Biomedical Applications Unit, Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vas. Konstantinou Ave., 11635 Athens, Greece;
| | - Dimitrios Koutsouris
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
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Lambrou GI, Zaravinos A, Braoudaki M. Co-Deregulated miRNA Signatures in Childhood Central Nervous System Tumors: In Search for Common Tumor miRNA-Related Mechanics. Cancers (Basel) 2021; 13:cancers13123028. [PMID: 34204289 PMCID: PMC8235499 DOI: 10.3390/cancers13123028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/09/2021] [Accepted: 06/14/2021] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Childhood tumors of the central nervous system (CNS) constitute a grave disease and their diagnosis is difficult to be handled. To gain better knowledge of the tumor’s biology, it is essential to understand the underlying mechanisms of the disease. MicroRNAs (miRNAs) are small noncoding RNAs that are dysregulated in many types of CNS tumors and regulate their occurrence and development through specific signal pathways. However, different types of CNS tumors’ area are characterized by different deregulated miRNAs. Here, we hypothesized that CNS tumors could have commonly deregulated miRNAs, i.e., miRNAs that are simultaneously either upregulated or downregulated in all tumor types compared to the normal brain tissue, irrespectively of the tumor sub-type and/or diagnosis. The only criterion is that they are present in brain tumors. This approach could lead us to the discovery of miRNAs that could be used as pan-CNS tumoral therapeutic targets, if successful. Abstract Despite extensive experimentation on pediatric tumors of the central nervous system (CNS), related to both prognosis, diagnosis and treatment, the understanding of pathogenesis and etiology of the disease remains scarce. MicroRNAs are known to be involved in CNS tumor oncogenesis. We hypothesized that CNS tumors possess commonly deregulated miRNAs across different CNS tumor types. Aim: The current study aims to reveal the co-deregulated miRNAs across different types of pediatric CNS tumors. Materials: A total of 439 CNS tumor samples were collected from both in-house microarray experiments as well as data available in public databases. Diagnoses included medulloblastoma, astrocytoma, ependydoma, cortical dysplasia, glioblastoma, ATRT, germinoma, teratoma, yoc sac tumors, ocular tumors and retinoblastoma. Results: We found miRNAs that were globally up- or down-regulated in the majority of the CNS tumor samples. MiR-376B and miR-372 were co-upregulated, whereas miR-149, miR-214, miR-574, miR-595 and miR-765 among others, were co-downregulated across all CNS tumors. Receiver-operator curve analysis showed that miR-149, miR-214, miR-574, miR-595 and miR765 could distinguish between CNS tumors and normal brain tissue. Conclusions: Our approach could prove significant in the search for global miRNA targets for tumor diagnosis and therapy. To the best of our knowledge, there are no previous reports concerning the present approach.
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Affiliation(s)
- George I. Lambrou
- Choremeio Research Laboratory, First Department of Pediatrics, National and Kapodistrian University of Athens, Thivon & Levadeias 8, Goudi, 11527 Athens, Greece;
| | - Apostolos Zaravinos
- Department of Life Sciences, European University Cyprus, Diogenis Str., 6, Nicosia 2404, Cyprus
- Cancer Genetics, Genomics and Systems Biology Group, Basic and Translational Cancer Research Center (BTCRC), Nicosia 1516, Cyprus
- Correspondence: (A.Z.); (M.B.); Tel.: +974-4403-7819 (A.Z.); +44-(0)-1707286503 (ext. 3503) (M.B.)
| | - Maria Braoudaki
- Department of Clinical, Pharmaceutical and Biological Science, School of Life and Medical Sciences, University of Hertfordshire, College Lane, Hatfield AL10 9AB, Hertfordshire, UK
- Correspondence: (A.Z.); (M.B.); Tel.: +974-4403-7819 (A.Z.); +44-(0)-1707286503 (ext. 3503) (M.B.)
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Wang L, Yang C, Chu M, Wang ZW, Xue B. Cdc20 induces the radioresistance of bladder cancer cells by targeting FoxO1 degradation. Cancer Lett 2020; 500:172-181. [PMID: 33290869 DOI: 10.1016/j.canlet.2020.11.052] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 11/12/2020] [Accepted: 11/30/2020] [Indexed: 12/11/2022]
Abstract
Ionizing radiation is a conventional therapy for cancer patients, but patients often experience distant metastasis and recurrence, which lead to a poor prognosis after the implementation of this treatment. Moreover, the underlying mechanisms by which radioresistance contributes to metastatic potential is still elusive. Here, we explored the molecular mechanisms that contribute to radioresistance in bladder cancer. To achieve this, we established two irradiation-resistant (IR) cell lines, T24R and 5637R, which were derived from parental bladder cancer cell lines. Cell viability was detected by CCK-8 assay, while migration and invasion abilities were examined by wound healing and Transwell chamber assays, respectively. Furthermore, the role of Cdc20 in the regulation of epithelial to mesenchymal transition (EMT) in IR cells was explored by Western blotting, immunoprecipitation and immunofluorescence staining. The IR cells exhibited EMT properties, and our data showed that Cdc20 expression was significantly elevated in IR cells. Remarkably, Cdc20 silencing reversed the EMT phenotype in IR cells. Mechanistically, Cdc20 governed IR-mediated EMT in part by governing forkhead box O1 (FoxO1) degradation. Taken together, our findings showed that the inactivation of Cdc20 or the activation of FoxO1 might be a potential strategy to overcome radioresistance in bladder cancer.
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Affiliation(s)
- Lixia Wang
- Department of Urology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China
| | - Chuanlai Yang
- Scientific Research Department, The Second Affiliated Hospital of Soochow University, China
| | - Man Chu
- Center of Scientific Research, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China; Department of Obstetrics and gynecology, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhi-Wei Wang
- Center of Scientific Research, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China; Bengbu Medical College Key Laboratory of Cancer Research and Clinical Laboratory Diagnosis, School of Laboratory Medicine, Bengbu Medical College, Bengbu, Anhui, 233030, China.
| | - Boxin Xue
- Department of Urology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China.
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