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Abdulghani M, Song G, Kaur H, Walley JW, Tuteja G. Comparative Analysis of the Transcriptome and Proteome during Mouse Placental Development. J Proteome Res 2019; 18:2088-2099. [PMID: 30986076 DOI: 10.1021/acs.jproteome.8b00970] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The condition of the placenta is a determinant of the short- and long-term health of the mother and the fetus. However, critical processes occurring in early placental development, such as trophoblast invasion and establishment of placental metabolism, remain poorly understood. To gain a better understanding of the genes involved in regulating these processes, we utilized a multiomics approach, incorporating transcriptome, proteome, and phosphoproteome data generated from mouse placental tissue collected at two critical developmental time points. We found that incorporating information from both the transcriptome and proteome identifies genes associated with time point-specific biological processes, unlike using the proteome alone. We further inferred genes upregulated on the basis of the proteome data but not the transcriptome data at each time point, leading us to identify 27 genes that we predict to have a role in trophoblast migration or placental metabolism. Finally, using the phosphoproteome data set, we discovered novel phosphosites that may play crucial roles in the regulation of placental transcription factors. By generating the largest proteome and phosphoproteome data sets in the developing placenta, and integrating transcriptome analysis, we uncovered novel aspects of placental gene regulation.
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Affiliation(s)
- Majd Abdulghani
- Interdepartmental Genetics and Genomics , Iowa State University , Ames , Iowa 50011-1079 , United States.,Department of Genetics, Development, and Cell Biology , Iowa State University , Ames , Iowa 50011-1079 , United States
| | - Gaoyuan Song
- Department of Plant Pathology and Microbiology , Iowa State University , Ames , Iowa 50011-1079 , United States
| | - Haninder Kaur
- Department of Genetics, Development, and Cell Biology , Iowa State University , Ames , Iowa 50011-1079 , United States
| | - Justin W Walley
- Interdepartmental Genetics and Genomics , Iowa State University , Ames , Iowa 50011-1079 , United States.,Department of Plant Pathology and Microbiology , Iowa State University , Ames , Iowa 50011-1079 , United States
| | - Geetu Tuteja
- Interdepartmental Genetics and Genomics , Iowa State University , Ames , Iowa 50011-1079 , United States.,Department of Genetics, Development, and Cell Biology , Iowa State University , Ames , Iowa 50011-1079 , United States
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52
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Hao S, Lv J, Yang Q, Wang A, Li Z, Guo Y, Zhang G. Identification of Key Genes and Circular RNAs in Human Gastric Cancer. Med Sci Monit 2019; 25:2488-2504. [PMID: 30948703 PMCID: PMC6463957 DOI: 10.12659/msm.915382] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background Globally, gastric cancer (GC) is the third most common source of cancer-associated mortality. The aim of this study was to identify key genes and circular RNAs (circRNAs) in GC diagnosis, prognosis, and therapy and to further explore the potential molecular mechanisms of GC. Material/Methods Differentially expressed genes (DEGs) and circRNAs (DE circRNAs) between GC tissues and adjacent non-tumor tissues were identified from 3 mRNA and 3 circRNA expression profiles. Functional analyses were performed, and protein–protein interaction (PPI) networks were constructed. The significant modules and key genes in the PPI networks were identified. Kaplan-Meier analysis was performed to evaluate the prognostic value of these key genes. Potential miRNA-binding sites of the DE circRNAs and target genes of these miRNAs were predicted and used to construct DE circRNA–miRNA–mRNA networks. Results A total of 196 upregulated and 311 downregulated genes were identified in GC. The results of functional analysis showed that these DEGs were significantly enriched in a variety of functions and pathways, including extracellular matrix-related pathways. Ten hub genes (COL1A1, COL3A1, COL1A2, COL5A2, FN1, THBS1, COL5A1, SPARC, COL18A1, and COL11A1) were identified via PPI network analysis. Kaplan-Meier analysis revealed that 7 of these were associated with a poor overall survival in GC patients. Furthermore, we identified 2 DE circRNAs, hsa_circ_0000332 and hsa_circ_0021087. To reveal the potential molecular mechanisms of circRNAs in GC, DE circRNA–microRNA–mRNA networks were constructed. Conclusions Key candidate genes and circRNAs were identified, and novel PPI and circRNA–microRNA–mRNA networks in GC were constructed. These may provide useful information for the exploration of potential biomarkers and targets for the diagnosis, prognosis, and therapy of GC.
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Affiliation(s)
- Shuhong Hao
- Department of Hematology and Oncology, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland)
| | - Junfeng Lv
- Department of Radiology, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland)
| | - Qiwei Yang
- Medical Research Center, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland)
| | - Ao Wang
- Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland)
| | - Zhaoyan Li
- Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland)
| | - Yuchen Guo
- Department of Gastrointestinal Surgery, The First Hospital of Jilin University, Changchun, Jilin, China (mainland)
| | - Guizhen Zhang
- Medical Research Center, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland).,Department of Orthopedics, The Second Hospital of Jilin University, Changchun, Jilin, China (mainland)
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53
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Gu HY, Yang M, Guo J, Zhang C, Lin LL, Liu Y, Wei RX. Identification of the Biomarkers and Pathological Process of Osteoarthritis: Weighted Gene Co-expression Network Analysis. Front Physiol 2019; 10:275. [PMID: 30941059 PMCID: PMC6433881 DOI: 10.3389/fphys.2019.00275] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 02/28/2019] [Indexed: 11/29/2022] Open
Abstract
Osteoarthritis (OA) is a joint disease resulting in high rates of disability and low quality of life. The initial site of OA (bone or cartilage) is uncertain. The aim of the current study was to explore biomarkers and pathological processes in subchondral bone samples. The gene expression profile GSE51588 was downloaded from the Gene Expression Omnibus database. Fifty subchondral bone [knee lateral tibial (LT) and medial tibial (MT)] samples from 40 OA and 10 non-OA subjects were analyzed. After data preprocessing, 5439 genes were obtained for weighted gene co-expression network analysis. Highly correlated genes were divided into 19 modules. The yellow module was found to be highly correlated with OA (r = 0.71, p = 1e-08) and the brown module was most associated with the differences between the LT and MT regions (r = 0.77, p = 1e-10). Gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment indicated that the yellow module was enriched in a variety of components including proteinaceous extracellular matrix and collagen trimers, involved in protein digestion and absorption, axon guidance, ECM-receptor interaction, and the PI3K-Akt signaling pathway. In addition, the brown module suggests that the differences between the early (LT) and end (MT) stage of OA are associated with extracellular processes and lipid metabolism. Finally, 45 hub genes in the yellow module (COL24A1, COL5A2, COL3A1, MMP2, COL6A1, etc.) and 72 hub genes in the brown module (LIPE, LPL, LEP, SLC2A4, FABP4, ADH1B, ALDH4A1, ADIPOQ, etc.) were identified. Hub genes were validated using samples from cartilage (GSE57218). In summary, 45 hub genes and 72 hub genes in two modules are associated with OA. These hub genes could provide new biomarkers and drug targets in OA. Further studies focusing on subchondral bone are required to validate these hub genes and better understand the pathological process of OA.
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Affiliation(s)
- Hui-Yun Gu
- Department of Orthopedic, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Min Yang
- Department of Orthopedic, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Jia Guo
- Department of Plastic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Chao Zhang
- Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Lu-Lu Lin
- Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Yang Liu
- Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Ren-Xiong Wei
- Department of Orthopedic, Zhongnan Hospital of Wuhan University, Wuhan, China
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54
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Liu B, Huang G, Zhu H, Ma Z, Tian X, Yin L, Gao X, He X. Analysis of gene co‑expression network reveals prognostic significance of CNFN in patients with head and neck cancer. Oncol Rep 2019; 41:2168-2180. [PMID: 30816522 PMCID: PMC6412593 DOI: 10.3892/or.2019.7019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 02/07/2019] [Indexed: 01/20/2023] Open
Abstract
In patients with head and neck cancer (HNC), lymph node (N) metastases are associated with cancer aggressiveness and poor prognosis. Identifying meaningful gene modules and representative biomarkers relevant to the N stage helps predict prognosis and reveal mechanisms underlying tumor progression. The present study used a step-wise approach for weighted gene co-expression network analysis (WGCNA). Dataset GSE65858 was subjected to WGCNA. RNA sequencing data of HNC downloaded from the Cancer Genome Atlas (TCGA) and dataset GSE39366 were utilized to validate the results. Following data preprocessing, 4,295 genes were screened, and blue and black modules associated with the N stage of HNC were identified. A total of 16 genes [keratinocyte differentiation associated protein, suprabasin, cornifelin (CNFN), small proline rich protein 1B, desmoglein 1 (DSG1), chromosome 10 open reading frame 99, keratin 16 pseudogene 3, gap junction protein β2, dermokine, LY6/PLAUR domain containing 3, transmembrane protein 79, phospholipase A2 group IVE, transglutaminase 5, potassium two pore domain channel subfamily K member 6, involucrin, kallikrein related peptidase 8] that had a negative association with the N-stage in the blue module, and two genes (structural maintenance of chromosomes 4 and mutS homolog 6) that had a positive association in the black module, were identified to be candidate hub genes. Following further validation in TCGA and dataset GSE65858, it was identified that CNFN and DSG1 were associated with the clinical stage of HNC. Survival analysis of CNFN and DSG1 was subsequently performed. Patients with increased expression of CNFN displayed better survival probability in dataset GSE65858 and TCGA. Therefore, CNFN was selected as the hub gene for further verification in the Gene Expression Profiling Interactive Analysis database. Finally, functional enrichment and gene set enrichment analyses were performed using datasets GSE65858 and GSE39366. Three gene sets, namely ‘P53 pathway’, ‘estrogen response early’ and ‘estrogen response late’, were enriched in the two datasets. In conclusion, CNFN, identified via the WGCNA algorithm, may contribute to the prediction of lymph node metastases and prognosis, probably by regulating the pathways associated with P53, and the early and late estrogen response.
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Affiliation(s)
- Baoling Liu
- Department of Physiology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Guanhong Huang
- Department of Radiotherapy, No. 2 People's Hospital of Lianyungang, Lianyungang, Jiangsu 222000, P.R. China
| | - Hongming Zhu
- Department of Radiotherapy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210000, P.R. China
| | - Zhaoming Ma
- Department of Radiotherapy, No. 2 People's Hospital of Lianyungang, Lianyungang, Jiangsu 222000, P.R. China
| | - Xiaokang Tian
- Department of Radiotherapy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210000, P.R. China
| | - Li Yin
- Department of Radiotherapy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210000, P.R. China
| | - Xingya Gao
- Department of Physiology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China
| | - Xia He
- Department of Radiotherapy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210000, P.R. China
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55
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Towner RA, Smith N, Saunders D, Brown CA, Cai X, Ziegler J, Mallory S, Dozmorov MG, Coutinho De Souza P, Wiley G, Kim K, Kang S, Kong DS, Kim YT, Fung KM, Wren JD, Battiste J. OKN-007 Increases temozolomide (TMZ) Sensitivity and Suppresses TMZ-Resistant Glioblastoma (GBM) Tumor Growth. Transl Oncol 2019; 12:320-335. [PMID: 30468988 PMCID: PMC6251232 DOI: 10.1016/j.tranon.2018.10.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 09/28/2018] [Accepted: 10/01/2018] [Indexed: 02/06/2023] Open
Abstract
Treatment of glioblastoma (GBM) remains a challenge using conventional chemotherapy, such as temozolomide (TMZ), and is often ineffective as a result of drug resistance. We have assessed a novel nitrone-based agent, OKN-007, and found it to be effective in decreasing tumor volumes and increasing survival in orthotopic GBM xenografts by decreasing cell proliferation and angiogenesis and increasing apoptosis. In this study, we assessed combining OKN-007 with TMZ in vivo in a human G55 GBM orthotopic xenograft model and in vitro in TMZ-resistant and TMZ-sensitive human GBM cell lines. For the in vivo studies, magnetic resonance imaging was used to assess tumor growth and vascular alterations. Percent animal survival was also determined. For the in vitro studies, cell growth, IC50 values, RNA-seq, RT-PCR, and ELISA were used to assess growth inhibition, possible mechanism-of actions (MOAs) associated with combined OKN-007 + TMZ versus TMZ alone, and gene and protein expression levels, respectively. Microarray analysis of OKN-007-treated rat F98 glioma tumors was also carried out to determine possible MOAs of OKN-007 in glioma-bearing animals either treated or not treated with OKN-007. OKN-007 seems to elicit its effect on GBM tumors via inhibition of tumorigenic TGF-β1, which affects the extracellular matrix. When combined with TMZ, OKN-007 significantly increases percent survival, decreases tumor volumes, and normalizes tumor blood vasculature in vivo compared to untreated tumors and seems to affect TMZ-resistant GBM cells possibly via IDO-1, SUMO2, and PFN1 in vitro. Combined OKN-007 + TMZ may be a potentially potent treatment strategy for GBM patients.
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Affiliation(s)
- Rheal A Towner
- Advanced Magnetic Resonance Center, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA; Department of PathologyUniversity of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | - Nataliya Smith
- Advanced Magnetic Resonance Center, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Debra Saunders
- Advanced Magnetic Resonance Center, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Chase A Brown
- Arthritis and Clinical Immunology Research Program, Division of Genomics and Data Sciences, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Xue Cai
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jadith Ziegler
- Advanced Magnetic Resonance Center, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA; Department of PathologyUniversity of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Mikhail G Dozmorov
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Graham Wiley
- Clinical Genomics Center, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Kyeongsoon Kim
- Department of Pharmaceutical Engineering, Inje University, Gimhae-si, Gyeongsangnam-do, Republic of Korea; Oblato, Inc., Princeton, NJ, USA
| | | | - Doo-Sik Kong
- Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Young-Tae Kim
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Kar-Ming Fung
- Department of PathologyUniversity of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jonathan D Wren
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Arthritis and Clinical Immunology Research Program, Division of Genomics and Data Sciences, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - James Battiste
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Department of NeurologyUniversity of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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56
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Di Y, Chen D, Yu W, Yan L. Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis. Hereditas 2019; 156:7. [PMID: 30723390 PMCID: PMC6350372 DOI: 10.1186/s41065-019-0083-y] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 01/17/2019] [Indexed: 12/31/2022] Open
Abstract
Background Bladder cancer was a malignant disease in patients, our research aimed at discovering the possible biomarkers for the diseases. Results The gene chip GSE31684, including 93samples, was downloaded from the GEO datasets and co-expression network was constructed by the data. Molecular complex detection(MCODE) was used to identify hub genes. The most significant cluster including 16 genes: CDH11, COL3A1, COL6A3, COL5A1, AEBP1, COL1A2, NTM, COL11A1, THBS2, COL8A1, COL1A1, BGN, MMP2, PXDN, THY1, and TGFB1I1 was identified. After annotated by BiNGO, they were suggested associated with collagen fibril organization and blood vessel development. In addition, the Kaplan Meier curves were obtained by UALCAN. The high expression of THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1, and TGFB1I1 indicated poor prognosis of the patients(P < 0.05). Finally, we examined genes’ expression between low and high tumor stage by the Wilcoxon test(P < 0.05), TGFB1I1 was excluded. Conclusion THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1 associated with the tumor stage as well as tumor patients’ prognosis. COL5A1, COL8A1(P < 0.01) may serve as therapeutic targets for the disease.
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Affiliation(s)
- Yu Di
- 1Department of Urinary Surgery, Qilu Hospital, Jinan, Shandong province China.,Department laboratory of cardiovascular center of Shandong province, Jinan, Shandong province China
| | - Dongshan Chen
- 1Department of Urinary Surgery, Qilu Hospital, Jinan, Shandong province China.,Department laboratory of cardiovascular center of Shandong province, Jinan, Shandong province China
| | - Wei Yu
- 3Lanzhou medical college of Lanzhou University, Lanzhou, Gansu province China
| | - Lei Yan
- 1Department of Urinary Surgery, Qilu Hospital, Jinan, Shandong province China
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57
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Wang L, Chen S, Luo Y, Yuan L, Peng T, Qian K, Liu X, Xiao Y, Wang X. Identification of several cell cycle relevant genes highly correlated with the progression and prognosis of human bladder urothelial tumor. J Cell Physiol 2019; 234:13439-13451. [PMID: 30618079 DOI: 10.1002/jcp.28023] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 11/30/2018] [Indexed: 01/03/2023]
Abstract
The incidence of bladder cancer (BCa) in China is the highest among genitourinary system tumors, and its progression is affected by multitudinous pathways, of which cell cycle progress plays an important role. This study screened and enriched differentially expressed genes (DEGs) from four gene expression profiles using bioinformatics analysis methods. The enrichment and analysis of gene function showed that these genes were highly correlated with cell cycle regulation. Identification of candidate small molecules was conducted to evaluate the application of clinical transformation in these DEGs. Prognostic and stage-related expression analysis further sorted five highly expressed genes associated with worse prognosis and higher stages in patients with BCa. Further analysis revealed their interaction in cell cycle regulation and genetical alteration. Meanwhile, we validated the elevated expression of these genes through transcription and translation levels. Taking the results together, we could infer that these five genes are valuable in diagnosis, prediction, and providing candidate therapeutic targets for patients with BCa in different stages.
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Affiliation(s)
- Lu Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Song Chen
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yongwen Luo
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lushun Yuan
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Tianchen Peng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Kaiyu Qian
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Human Genetics Resource Preservation Center of Hubei Province, Wuhan, China
| | - Xuefeng Liu
- Department of Pathology, Lombardi Comprehensive Cancer Center, Georgetown University Medical School, Washington DC
| | - Yu Xiao
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Human Genetics Resource Preservation Center of Hubei Province, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinghuan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Medical Research Institute, Wuhan University, Wuhan, China
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58
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Wang Y, Chen L, Wang G, Cheng S, Qian K, Liu X, Wu CL, Xiao Y, Wang X. Fifteen hub genes associated with progression and prognosis of clear cell renal cell carcinoma identified by coexpression analysis. J Cell Physiol 2018; 234:10225-10237. [PMID: 30417363 DOI: 10.1002/jcp.27692] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 10/09/2018] [Indexed: 02/06/2023]
Abstract
Renal cell carcinoma (RCC) is the most common type of renal tumor, and the clear cell renal cell carcinoma (ccRCC) is the most frequent subtype. In this study, our aim is to identify potential biomarkers that could effectively predict the prognosis and progression of ccRCC. First, we used The Cancer Genome Atlas (TCGA) RNA-sequencing (RNA-seq) data of ccRCC to identify 2370 differentially expressed genes (DEGs). Second, the DEGs were used to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Moreover, we identified the yellow module, which was strongly related to the histologic grade and pathological stage of ccRCC. Then, the functional annotation of the yellow module and single-samples gene-set enrichment analysis of DEGs were performed and mainly enriched in cell cycle. Subsequently, 18 candidate hub genes were screened through WGCNA and protein-protein interaction (PPI) network analysis. After verification of TCGA's ccRCC data set, Gene Expression Omnibus (GEO) data set (GSE73731) and tissue validation, we finally identified 15 hub genes that can actually predict the progression of ccRCC. In addition, by using survival analysis, we found that patients of ccRCC with high expression of each hub gene were more likely to have poor prognosis than those with low expression. The receiver operating characteristic curve showed that each hub gene could effectively distinguish between localized and advanced ccRCC. In summary, our study indicates that 15 hub genes have great predictive value for the prognosis and progression of ccRCC, and may contribute to the exploration of the pathogenesis of ccRCC.
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Affiliation(s)
- Yejinpeng Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Liang Chen
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Gang Wang
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Human Genetics Resource Preservation Center of Hubei Province, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Songtao Cheng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Kaiyu Qian
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Human Genetics Resource Preservation Center of Hubei Province, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xuefeng Liu
- Greenebaum Cancer Center, School of Medicine, University of Maryland, Baltimore, Maryland
| | - Chin-Lee Wu
- Department of Urology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yu Xiao
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Human Genetics Resource Preservation Center of Hubei Province, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinghuan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Medical Research Institute, Wuhan University, Wuhan, China
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59
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Giulietti M, Occhipinti G, Righetti A, Bracci M, Conti A, Ruzzo A, Cerigioni E, Cacciamani T, Principato G, Piva F. Emerging Biomarkers in Bladder Cancer Identified by Network Analysis of Transcriptomic Data. Front Oncol 2018; 8:450. [PMID: 30370253 PMCID: PMC6194189 DOI: 10.3389/fonc.2018.00450] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 09/25/2018] [Indexed: 01/03/2023] Open
Abstract
Bladder cancer is a very common malignancy. Although new treatment strategies have been developed, the identification of new therapeutic targets and reliable diagnostic/prognostic biomarkers for bladder cancer remains a priority. Generally, they are found among differentially expressed genes between patients and healthy subjects or among patients with different tumor stages. However, the classical approach includes processing these data taking into consideration only the expression of each single gene regardless of the expression of other genes. These complex gene interaction networks can be revealed by a recently developed systems biology approach called Weighted Gene Co-expression Network Analysis (WGCNA). It takes into account the expression of all genes assessed in an experiment in order to reveal the clusters of co-expressed genes (modules) that, very probably, are also co-regulated. If some genes are co-expressed in controls but not in pathological samples, it can be hypothesized that a regulatory mechanism was altered and that it could be the cause or the effect of the disease. Therefore, genes within these modules could play a role in cancer and thus be considered as potential therapeutic targets or diagnostic/prognostic biomarkers. Here, we have reviewed all the studies where WGCNA has been applied to gene expression data from bladder cancer patients. We have shown the importance of this new approach in identifying candidate biomarkers and therapeutic targets. They include both genes and miRNAs and some of them have already been identified in the literature to have a role in bladder cancer initiation, progression, metastasis, and patient survival.
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Affiliation(s)
- Matteo Giulietti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona, Italy
| | - Giulia Occhipinti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona, Italy
| | - Alessandra Righetti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona, Italy
| | - Massimo Bracci
- Department of Clinical and Molecular Sciences, Polytechnic University of Marche, Ancona, Italy
| | - Alessandro Conti
- Department of Urology, Bressanone/Brixen Hospital, Bressanone, Italy
| | - Annamaria Ruzzo
- Department of Biomolecular Sciences, University of Urbino "Carlo Bo", Fano, Italy
| | - Elisabetta Cerigioni
- Unit of Pediatric and Specialistic Surgery, United Hospitals, "G.Salesi", Ancona, Italy
| | - Tiziana Cacciamani
- Department of Life and Environmental Science, Polytechnic University of Marche, Ancona, Italy
| | - Giovanni Principato
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona, Italy
| | - Francesco Piva
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, Ancona, Italy
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Yuan L, Qian G, Chen L, Wu CL, Dan HC, Xiao Y, Wang X. Co-expression Network Analysis of Biomarkers for Adrenocortical Carcinoma. Front Genet 2018; 9:328. [PMID: 30158955 PMCID: PMC6104177 DOI: 10.3389/fgene.2018.00328] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 07/31/2018] [Indexed: 01/08/2023] Open
Abstract
Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. And currently, there are no specific diagnostic biomarkers for ACC. In our study, we aimed to screen biomarkers for disease diagnosis, progression and prognosis. We firstly used the microarray data from public database Gene Expression Omnibus database to construct a weighted gene co-expression network, and then to identify gene modules associated with clinical features of ACC. Though this algorithm, a significant module with R2 = 0.64 (P = 9 × 10-5) was identified. Co-expression network and protein–protein interaction network were performed for screen the candidate hub genes. Checked by The Cancer Genome Atlas (TCGA) database, another independent dataset GSE19750, and GEPIA database, using one-way ANOVA, Pearson’s correlation, survival analysis, diagnostic capacity (ROC curve) and expression level revalidation, a total 12 real hub genes were identified. Gene ontology and KEGG pathway analysis of genes in the significant module revealed that the hub genes are significantly enriched in cell cycle regulation. Moreover, gene set enrichment analysis suggests that the samples with highly expressed hub genes are correlated with cell cycle. Taken together, our integrated analysis has identified 12 hub genes that are associated with the progression and prognosis of ACC; these hub genes might lead to poor outcomes by regulating the cell cycle.
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Affiliation(s)
- Lushun Yuan
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guofeng Qian
- Department of Endocrinology, The First Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Liang Chen
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Chin-Lee Wu
- Department of Urology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Han C Dan
- Greenebaum Cancer Center, School of Medicine, University of Maryland, Baltimore, MD, United States
| | - Yu Xiao
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinghuan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Yuan L, Zeng G, Chen L, Wang G, Wang X, Cao X, Lu M, Liu X, Qian G, Xiao Y, Wang X. Identification of key genes and pathways in human clear cell renal cell carcinoma (ccRCC) by co-expression analysis. Int J Biol Sci 2018; 14:266-279. [PMID: 29559845 PMCID: PMC5859473 DOI: 10.7150/ijbs.23574] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 01/11/2018] [Indexed: 12/13/2022] Open
Abstract
Human clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In our study, we screened differential expressed genes, and constructed protein-protein interaction (PPI) network and a weighted gene co-expression network to identify key genes and pathways associated with the progression of ccRCC (n = 56). Functional and pathway enrichment analysis demonstrated that upregulated differentially expressed genes (DEGs) were significantly enriched in response to wounding, positive regulation of immune system process, leukocyte activation, immune response and cell activation. Downregulated DEGs were significantly enriched in oxidation reduction, monovalent inorganic cation transport, ion transport, excretion and anion transport. In the PPI network, top 10 hub genes were identified (TOP2A, MYC, ALB, CDK1, VEGFA, MMP9, PTPRC, CASR, EGFR and PTGS2). In co-expression network, 6 ccRCC-related modules were identified. They were associated with immune response, metabolic process, cell cycle regulation, angiogenesis and ion transport. In conclusion, our study illustrated the hub genes and pathways involved in the progress of ccRCC, and further molecular biological experiments are needed to confirm the function of the candidate biomarkers in human ccRCC.
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Affiliation(s)
- Lushun Yuan
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Medical Research Institute, School of Medicine, Wuhan University, Wuhan, China
| | - Guang Zeng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Liang Chen
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Gang Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Medical Research Institute, School of Medicine, Wuhan University, Wuhan, China.,Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaolong Wang
- Department of Urology, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Xinyue Cao
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Mengxin Lu
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xuefeng Liu
- Department of Pathology, Lombardi Comprehensive Cancer Center, Georgetown University Medical School, Washington DC, USA
| | - Guofeng Qian
- Department of Endocrinology, The First Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Yu Xiao
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.,Laboratory of Precision Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinghuan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Medical Research Institute, School of Medicine, Wuhan University, Wuhan, China
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