Bioinformatic Analysis And Functional Prediction Of Prostate Cancer Metastasis Related Genes

Prostate cancer is one of the most common cancer among men and second in cancer-related deaths in the United States.As the age indication increases,the dietary ingredient changes, aging of the population and improved diagnosis,the incidence of prostate cancer in China although much lower than Western countries, but in recent twenty years showed significant growth trend.Prostate cancer rarely causes symptoms early in the course of the disease because the majority of adenocarcinomas arise in the periphery of the gland distant from the urethra. The presence of symptoms as a result of prostate cancer suggests locally advanced or metastatic disease.In the case of disease progression,cancer cells first spread to the regional lymph nodes and then primarily to bone.In patients with localized prostate cancer, the5-year survival rate approximates100%; however, in patients in whom distant metastases have occurred, the5-year survival rate drops to29%.From a clinical standpoint, the development of bone metastases is the cause of significant morbidity and mortality and overall greatly affect the quality of life of prostate cancer patients, Indeed, in the United States, it has been estimated that>80%of men who die from prostate cancer develop bone metastases. Skeletal-related events are commonly associated with bone metastases, often causing severe pain, pathologic bone fracture and spinal cord compression, increasing mortality and reducing quality of life, as well as imposing a burden on healthcare resources. Bone metastases can be diagnosed with imaging such as x-ray, computerised tomography (CT) and magnetic resonance imaging (MRI). In prostate cancer, the gold-standard approach is by bone scan, also known as bone scintigraphy. Scintigraphy involves a radioactive tracer being given intravenously. The tracer has an affinity for bone and abnormal bone activity, and a subsequent bone scan allows for abnormal bone activity to be identified. Such a scan is often carried out as an initial assessment where metastases are suspected and in men with prostate cancer who develop signs and symptoms of metastases further on in their cancer pathway, such as a rise in prostate-specific antigen despite treatment or bone pain. When metastasised, classic anti-androgen therapy is the first-line treatment. The androgen receptor (AR) plays a central role in prostate cancer development, and androgen deprivation therapy is still the standard systemic treatment for metastatic prostate cancer.The majority of patients treated with androgen deprivation therapies, which suppress testicular androgen production [surgical castration or administration of luteinizing hormone-releasing hormone (LHRH) agonists] or block AR directly by treatment with AR antagonists, show clinical improvement and have decreases in serum PSA levels. Unfortunately, Metastatic prostate cancer is incurable, so the aim is to control disease progression, reduce associated symptoms and optimise patients’quality of life,treatment remains a significant clinical challenge.Therefore, it is important to investigate the molecular mechanisms underlying the progression and metastasis of prostate cancer to provide better strategies for the prevention and therapy of prostate cancer.Metastasis of prostate cancer is a complex process which multi-gene and multi-factor interact and influence mutually like other malignancies, and is also a trouble problem in tumor prevention and therapy. Metastasis is a complex process comprising multiple steps, including dissemination of cells from a primary tumor into blood or lymph vessels, survival of the cells in these vessels, arrest and extravasation into a new organ,initiation and maintenance of growth, and vascularization of the metastatic tumor. Even before dissemination, the tumor cells may secrete growth factors and cytokines that induce systemic changes and prime the distant site for metastasis. The early steps in metastasis occur efficiently, in contrast to later steps, where only a small subset of cancer cells at a secondary site initiate growth and form pre-angiogenic micrometastases, and, of these, only a tiny proportion continue to become vascularized and progressively growing macrometastases. The ability to grow at a distant site is largely dictated by molecular interactions of the cancer cells with the new microenvironment, which may have an even greater impact on cell behavior at a distant site than at the primary tumor location. Only when metastasis successfully blocked, the complete cure of malignant tumor can be reached. In the course of tumor development, some tumor cells acquire invasive and metastatic potency which were induced by genetic alteration of tumor cells. It is a hot spot of research to search for the metastasis associated genes and reveal the molecular mechanisms of metastasis.The genechip technology and bioinformatics developed in recent years shows their superiority in the analysis of diseases.The genechip is a major technique in bioscience field,which has the outstanding of high-throughput and rapid detection. genechip technology has been widely used in gene expression profile analysis, discovery of new genes and gene mutations, polymorphism analysis, genomic library construction, disease diagnosis, disease prediction, drug screening, gene sequencing and other fields. But when you get the genechip results, it does not mean that you have accessed to the knowledge. How to interpret the information on genechip, and how to link the great amount of genechip data to specific life activities are very important in data analysis.With the development of high-throughput genechip technology and DNA sequencing, enormous data has been generated. Biological information is now being accumulated at an astonishing speed. In order to analyze and to make full use of the vast ocean of data and to help the wide sharing of these data,several databases have been developed.The Gene Expression Omnibus(GEO)at the National Center for Biotechnology Information (NCBI) is the largest one and is a fully public repository of such data,generated mostly from genechip studies globally. The database has a flexible and open access design that allows the submission, storage and retrieval of many data formats. With comprehensive resources and timely updating,GEO database is easy to use and open to the public and scientific community. It provides a useful platform for subsequent data mining and distributing of these important information.Bioinformatics is all interdisciplinary subject which began to develop with the great increase of genome sequencing data at the end of1980s. Following the fast development of biology and medicine, especially the successful implement of the Human Genome Project,mass biological data were generated. There is plenty of biological knowledge underlying these data.How to take full advantage of the information has become a great challenge to biologists and mathematicians.Concretely, bioinformatics began to take shape by the infiltration and intersection of many different subjects including medical science,modem biology,computer science,biostatistics,informatics and mathematics. By acquiring, processing, storing, managing, searching, distributing, analyzing, explaining biological experimental information, and making use of mathematics, computer and biological instruments,bioinformatics can help us understand the biological connotations in the data. Nowadays, bioinformatics has already been extensively used in different research fields of life science such as discovery and identify of functional genes of human diseases,functions of genes and proteins. It also plays a key role in other researches,for example,drug design,gene polymorphism analyses,gene expression control,identify of disease related genes,prediction of the structure and function of gene,gene evolution,epidemiology based on genetics and genetic mechanism of cancers, etc.It is an important approach to obtain cancer-related genes and their regulatory networks by gene-chip technologies and bioinformatics,which can integrate the gene expression network of tumors from the genome level.It is obviously superior to the past pattern of single gene studies.In this study,157gene expression profiling datesets related to the prostate cancer metastasis (GSM152931-GSM152991, CSM152856-GSM152880, GSM799468-GSM799489and CSM799490-GSM799518),which were downloaded from gene expression omnibus(GEO), were used in this study. BRB-ArrayTools4.3.0 Beta software was used to idemify the differential expressed genes between the primary tumors and metastatic tumors of prostate cancer,and bioinformatics tools and data mining were used to analyze the relationship of the differential genes,which found two prostate cancer metastasis-associated genes SPP1and VCAN,and then their structures and functions were studied by a set of bioinformatics tools, which provide a new idea for the pathogenesis metastasis of prostate cancer, and lay the foundation for the molecular diagnosis and individualized treatment of metastatic prostate cancer.There are four parts in this study:Part1:Bioinformatic analysis of genes related to metastatic prostate cancer.We downloaded the gene expression profile data from GEO database, including61primary prostate tumor samples and25Metastatic prostate tumor samples, and the differentially expressed genes of metastatic prostate cancer were analyzed with a set of bioinformatic tools including BRB-Array Tools4.3.0Beta3、STRING、ToppGene、 GOEAST and DAVID. BRB-ArrayTools4.3.0Beta3analysis results showed There were210genes significantly differentially expressed by BRB-ArrayTools4.3.0Beta, including84up-regulated genes and126down-regulated genes,Bioinformatic analysis results suggested that AR、FOS、JUN、ACTB、FN1、MYL9、MYH11、 MYLK and SPP1played essential roles in such important biological processes as Cytoskeletal regulation by Rho GTPase、Integrin signalling pathway, Cadherin signaling pathway and Wnt signaling pathway。Part2:Bioinformatic analysis of genes related to prostate cancer bone metastasis.The data of whole genomic expression profiles got from the prostate cancer bone metastasis were obtained from GEO database, a set of bioinformatics tools, such as BRB-ArrayTools4.3.0Beta3、STRING、ToppGene、GOEAST and DAVID softwares were used to accomplish the data-mining and bioinformatics analysis. BRB-ArrayTools4.3.0Beta3analysis results showed there were501differentially expressed genes in prostate cancer bone metastasis,181up-regulated and320down-regulated. Bioinformatic analysis results suggested that SPP、HBB、AR、 MMP9、AZGP1、POSTN、FN1and VCAN played essential roles in such important biological processes as collagen biosynthetic、cell adhesion、Focal adhesion、Integrin signalling pathway and ECM-receptor interaction.Part3:Bioinformatics analysis of prostate cancer metastasis related gene SPPl based on microarray.The data of whole genomic expression profiles got from the prostate cancer metastasis were obtained from GEO database, a set of bioinformatics tools, such as BRB-ArrayTools4.3.0Beta3,protparam, MotifScan,SignalP4.0, TMHMM, NetPhos2.0,PredictProtein,GO, KEGG and STRING softwares were used to accomplish the data-mining and bioinformatics analysis. After careful and vigorous screening by domain-experts,There were73Co-expressed differentially genes in prostate cancer metastasis,21up-regulated and52down-regulated. Bioinformatic analysis indicated that SPP1gene encoded314amino acids, its molecular weight was35422.7, SPP1was also contained two N-glycosylation sites%eight Casein kinase II phosphorylation sites、two N-myristoylation sites and three Protein kinase C phosphorylation sites, And a furthermore analysis suggested that SPP1played essential roles in such important biological function as cytokine activity、extracellular matrix binding、ossification、osteoblast differentiation、inflammatory response、cell adhesion、PI3K-Akt signaling pathway、Focal adhesion、Toll-like receptor signaling pathway and ECM-receptor interaction.Part4:Bioinformatics analysis of prostate cancer metastasis related gene VCAN based on microarray.The data of whole genomic expression profiles got from the prostate cancer metastasis were obtained from GEO database, a set of bioinformatics tools, such as BRB-ArrayTools4.3.0Beta3, protparam, SMART, SignalP4.0,TMHMM, NetPhos2.0, PredictProtein, SWISS-MODEL,GO,KEGG and STRING softwares were used to accomplish the data-mining and bioinformatics analysis. After careful and vigorous screening by domain-experts, There were73Co-expressed differentially genes in prostate cancer metastasis,21up-regulated and52down-regulated. Bioinformatic analysis indicated that VCAN gene encoded3396amino acids, its molecular weight was372820.0, VCAN was also contained one Immunoglobulin domain、two Hyaluronan-binding domain、one Epidermal growth factor-like domain、 one Calcium-binding EGF-like domain、one C-type lectin domain and one domain abundant in complement control proteins, And a furthermore analysis suggested that VCAN played essential roles in such important biological function as cell adhesion、hyaluronic acid binding、Calcium-binding、glycosaminoglycan binding、 extracellular matrix and Cell adhesion molecules.In summary, using microarray technology and bioinformatics can effectively analyze genes related to metastatic prostate cancer and gain the internal information. Mining the prostate cancer metastasis related genes by Bioinformatics analysis, we found that such genes as AR、FOS、JUN、ACTB、FN1、MYL9、MYH11、MYLK SPP1、HBB、MMP9、AZGP1、POSTN and VCAN may play an important role in the prostate cancer metastasis.and, Further analysis results suggested that these genes played essential roles in such important biological processes as Cytoskeletal regulation by Rho GTPase、Integrin signalling pathway, Cadherin signaling pathway、 collagen biosynthetic、cell adhesion、Focal adhesion and ECM-receptor interaction and Wnt signaling pathway in the prostate cancer metastasis. A deeper analysis of the functions of these genes would be the focus of the future work. We also predicted the structures and functions of two prostate cancer metastasis related genes named SPP1and VCAN. This might provide support and guidance for the follow up experiments. Data mining and bioinformatics analysis of prostate cancer metastasis related genes,may further our understanding on the molecular mechanisms of metastatic prostate cancer and provide novel means for clinical diagnosis and treatment.