Reconstruction of an Integrated Genome-Scale Co-Expression Network Reveals Key Modules Involved in Lung Adenocarcinoma

Bidkhori, Gholamreza; Narimani, Zahra; Ashtiani, Saman Hosseini; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi‐Nejad, Ali

doi:10.1371/journal.pone.0067552

Cited by 94 publications

(77 citation statements)

References 98 publications

(108 reference statements)

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“…SMC-4 is an indispensable factor involved in chromosome condensation which has been implicated in several malignancies (Lu et al, 2004;Kulawiec et al, 2008;Takahashi et al, 2012;Zhou et al, 2012;Bidkhori et al, 2013). Abnormal SMC-4 expression in tumor tissues suggests that SMC-4 is significant in cancer pathogenesis and progression.…”

Section: Discussionmentioning

confidence: 99%

“…SMC-4 also known as chromosome-associated polypeptide C (CAP-C) or XCAP-C homolog, it is a protein that in humans is encoded by the SMC-4 gene which is located on chromosome 3q26.1 (Nishiwaki et al, 1999). Recent studies have indicated SMC-4 is up-regulated and play an important role in many malignancies, including primary liver cancer (Zhou et al, 2012), epithelial ovarian cancer (Lu et al, 2004), glioma (Takahashi et al, 2012, breast (Kulawiec et al, 2008) and lung cancers (Bidkhori et al, 2013). However, its expression and potential role in the pathogenesis in CRC remain unknown.…”

Section: Introductionmentioning

confidence: 99%

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Structural Maintenance of Chromosomes 4 is a Predictor of Survival and a Novel Therapeutic Target in Colorectal Cancer

Feng

Song²,

Li³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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Asian Pac J Cancer Prev, 15 (21), 9459-9465 IntroductionColorectal cancer (CRC) is one of the most frequent malignances in the world. It is the third most common cancer and the third leading cause of cancer death in the United State (Siegel et al., 2014). Although dramatic reduction in cancer mortality and prolong patient survival with surgical resection and chemotherapy has been achieved clinically (Yan et al., 2010). However, tumor recurrence and the chemoresistance is the main factor for the failure of therapy (Chang, 2011). CRC arises through the progressive accumulation of mutations in oncogenes and tumor-suppressor genes (Sansom et al., 2007; Petrova et al., 2008). Despite several genes have being proved that relate to genesis of CRC, the exact mechanisms underlying he development and progression CRC are still poorly understood (Goel and Boland, 2010). Throughout the articles relate to CRC in the journal ACJCP over the past two years, it is not difficult to find that the novel molecular markers with potential of treatment and prognosis have captured more and more attention (Chen et al., 2013; Zhu et al., 2013). Given this consideration, it is imperative to seek out a key gene associated with the progression and pathogenesis.Structural maintenance of chromosomes (SMC)

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structural Maintenance of Chromosomes 4 is a Predictor of Survival and a Novel Therapeutic Target in Colorectal Cancer

Feng

Song²,

Li³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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“…There are so many studies that show PRKAR2A gene is upregulated. For example; Bidkhori and et al (24) show that PRKAR2A is overexpressed in lung adenocarcinoma in their study in 2013. In 2004, Neben and at al.…”

Section: Discussionmentioning

confidence: 89%

Investigation of ErbB and Insulin Signaling Pathways in the Pathogenesis of Multiple Myeloma

Öztürk¹,

Çoşkunpınar²,

Osmanbaşoğlu³

et al. 2018

Haseki

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Introduction:Analysis of genes that play roles in Multiple myeloma pathogenesis and their pathways are current research topics. We aim to detect expression of some genes of ErbB and insulin signaling pathways.Methods:Bone marrows were taken from three healthy volunteers and 17 untreated patients, firstly RNA isolation was made and then cDNA were synthesized. There are eight genes that are related to ErbB and Insulin signaling pathways, after that specific primers for these genes were designed. Gene expression analysis was performed by Real-Time PCR method.Results:In the patient group, expressions of MTOR, RPTOR, PIK3CA, AKT1, ErbB4, PRKAR2A and PRKACB genes were detected to be 3-10 times up-regulated than control group. There were not differences in the expression levels of RICTOR and GYS1 genes between control group and patient group. GYS1, PRKACB and PRKAR2A genes have been analyzed for the first time.Conclusion:In this study, PRKAR2A and PRKACB genes expressions were detected to be upregulated and this hasn't been reported in literature before. MTOR, RPTOR, PIK3CA, AKT1, ErbB4 genes expression were detected to be upregulated as had reported in the literature before. All these results will be useful to understand thepathogenesis of the multiple myeloma. Keywords: Multiple myeloma, qRT-PCR, insulin signaling pathway, ErbBAmaç:Multipl miyeloma patogenezinde rol oynayan genlerin ve ilgili yolakların moleküler düzeyde incelenmesi güncel bir araştırma alanıdır. ErbB ve insülin sinyal yolağında bulunan bazı genlerin ekspresyon çalışmasının yapılması amaçlandı.Yöntemler: Üç sağlıklı gönüllü ve 17 tedavisiz hastadan kemik iliği alındı, ilk olarak RNA izolasyonu yapıldı ve daha sonra cDNA sentezi yapıldı.ErbB ve insülin sinyal yolakları ile ilgili sekiz gen vardır, bu genler için spesifik primerler dizayn edilmiştir. Gen ekspresyon analizi, RealTime PCR yöntemi ile gerçekleştirilmiştir. Bulgular: Hasta grubunda MTOR, RPTOR, PIK3CA, AKT1, ErbB4, PRKAR2A ve PRKACB genlerinin ekspresyonu kontrol grubuna göre 3-10 kat arttı. Kontrol grubu ile hasta grubu arasında RICTOR ve GYS1 genlerinin ekspresyon düzeylerinde farklılıklar gözlenmedi. GYS1, PRKACB ve PRKAR2A genleri ilk kez analiz edilmiştir.Sonuç: Bu çalışmada, PRKAR2A ve PRKACB gen ekspresyonlarının arttığı saptanmış ve daha önce literatürde bildirilmemiştir. MTOR, RPTOR, PIK3CA, AKT1, ErbB4 gen ekspresyonunun daha önce literatürde bildirildiği gibi ekspresyonlarının arttığı tespit edildi. Tüm bu sonuçlar Multipl miyelomun patogenezini anlamak için faydalı olacaktır.Anahtar Sözcükler: Multipl miyelom, qRT-PCR, insulin sinyal yolağı, ErbB

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“…The MCODE algorithm includes the following steps: Vertex-weighting, complex prediction and optional post-processing (29). The weighting scheme defined a measure of local density for a vertex's neighborhood.…”

Section: Construction Of a Co-expression Network And Identification Omentioning

confidence: 99%

Regulatory network of differentially expressed genes in metastatic osteosarcoma

Peng

Wang

Ding

et al. 2014

Molecular Medicine Reports

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Abstract. The present study aimed to investigate the possible molecular mechanisms underlying the pathogenesis of metastatic osteosarcoma (OS), by examining the microarray expression profiles of normal samples, and metastatic and non-metastatic OS samples. The GSE9508 gene expression profile was downloaded from the Gene Expression Omnibus database, which included 11 human metastatic OS samples, seven non-metastatic OS samples and five normal samples. Pretreatment of the data was performed using the BioConductor package in R language, and the differentially expressed genes (DEGs) were identified by a t-test. Furthermore, function and pathway enrichment analyses of the DEGs were conducted using a molecule annotation system. A differential co-expression network was also constructed, and the submodules were screened using MCODE in Cytoscape. A total of 965 genes were identified as DEGs in metastatic OS. The DEGs were shown to participate in the regulation of DNA-dependent transcription, the composition of the nucleus, cytoplasm and membrane, and protein and nucleotide binding. Furthermore, the screened DEGs were significantly associated with the ribosome, axon guidance and the cytokine-cytokine receptor interaction pathway. Certain hub genes were identified in the constructed differential co-expression network, including matrix metalloproteinase 1 (MMP1), smoothened (SMO), ewing sarcoma breakpoint region 1 (EWSR1) and fasciculation and elongation protein ζ-1 (FEZ1). Brain selective kinase 2 (BRSK2) and aldo-keto reductase family 1 member B10 (AKRIB10) were present in the screened submodules. The results of the present study suggest that genes, including MMP1, SMO, EWSR1, FEZ1, BRSK2 and AKRIB10, may be potential targets for the diagnosis and treatment of metastatic OS. IntroductionOsteosarcomas (OS) are among the most frequently occurring secondary malignancies in childhood cancer (1). OS most often originates in the metaphyses of long bones in adolescents and young adults (2). During the past 30 years, an optimal treatment strategy for OS has been developed, which consists of multi-agent chemotherapy and aggressive surgical resection of all sites of disease involvement (3). However, ~80% of patients with localized OS develop metastatic disease following surgical resection (4). Patients with primary metastatic OS are a heterogeneous group, and a five-year event-free survival rate of up to 75% is reported for patients presenting with unilateral lung metastases (5). Furthermore <20% of patients with high-grade osteosarcoma are clinically diagnosed with metastatic disease at the initial diagnosis, and long-term survival rates of patients with metastatic OS range between 10-40% (6,7). Therefore, due to the high rate of systemic spread, complete recovery following surgical treatment alone is rare (8).Recently, microarray analysis (9) has been widely used in screening for differentially expressed genes (DEGs), in order to identify potential genes that may be investigated for the treatment of various human diseases (10,11)...

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Reconstruction of an Integrated Genome-Scale Co-Expression Network Reveals Key Modules Involved in Lung Adenocarcinoma

Cited by 94 publications

References 98 publications

Structural Maintenance of Chromosomes 4 is a Predictor of Survival and a Novel Therapeutic Target in Colorectal Cancer

Structural Maintenance of Chromosomes 4 is a Predictor of Survival and a Novel Therapeutic Target in Colorectal Cancer

Investigation of ErbB and Insulin Signaling Pathways in the Pathogenesis of Multiple Myeloma

Regulatory network of differentially expressed genes in metastatic osteosarcoma

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