高低转移卵巢癌细胞株差异表达基因在染色体定位及其功能

用基因芯片技术研究高（H）、低（L）转移卵巢癌细胞株（HO-8910PM和HO-8910）和正常卵巢上皮（C）基因表达谱差异,筛选与卵巢癌转移相关的基因,并利用生物信息学方法对检测结果进行差异基因在染色体定位和功能分析。结果：高、低转移卵巢癌细胞株比较表达差异2倍以上共有409个基因,其中表达上调（信号比的对数值[SLR]≥1）有271个,表达下调（SLR≤-1）有138个。从表达差异的基因在染色体定位分析,发现除1个基因未知其定位外,其余所有差异表达基因散在分布于各条染色体上,但以1号染色体最多有43个（占10．7％）。其次是6号染色体有39个（占9．6％）,第三是2号染色体有29个（占7．1％）。第四是17号染色体有28个（占6．9％）。第五是3号染色体有25个（占6．2％）。第6是5号和11号染色体各有24个（各占5．9％）。而差异表达的基因发生在染色体短臂（q）的有264个（占64．7％）,在13,14,15,21和22号仅发现在q都有异常表达。从表达差异基因的分子功能分类看,属于酶和酶调控子基因为最多（104个,占25．4％）,其次是信号传导基因（43个,占10．5％）。第3类是核酸结合基因（42个,占10．3％）。第4类是蛋白结合基因（34个,占8．3％）。以上4大类共占基因总数54．5％。还有功能未知的基因有76个,占18．6％。高、低转移卵巢癌细胞株差异表达基因散在分布在各条染色体上,但以1、6、2、17、3、5和11号染色体差异表达基因居多。肿瘤的转移是多基因共同作用的结果。4大类（酶和酶调控子、信号传导、核酸结合和蛋白结合）相关基因异常是我们今后研究卵巢癌转移的重要基因。     

用基因芯片筛选高转移卵巢癌细胞系转移相关基因

用标准化的Affymetrix公司生产U133A基因芯片技术研究高(H)转移卵巢癌细胞株(HO-8910PM)和正常卵巢上皮(C)基因表达谱差异,筛选与卵巢癌转移相关的基因及其在染色体的定位和功能。结果发现高转移卵巢癌细胞株和正常卵巢上皮比较表达差异8倍以上共有1,237个基因,其中表达上调(信号比的对数值SLR≥3)有597个,表达下调(SLR≤-3)有640个。从表达差异的基因在染色体定位分析,发现除1个基因未知其定位外,其余所有差异表达基因散在分布在各条染色体上,但以1号染色体最多,有115个(9.3%)。其次是2号染色体有94个(7.6%),第三是12号染色体有88个(7.1%)。第四是11号染色体有76个(6.1%)。第五是X染色体有71个(5.7%)。第6是17号染色体有69个(5.6%)。而差异表达的基因发生在染色体短臂(q)上有805个(占65.1%),在13,14,15,21和22号仅发现在q上有差异表达基因。从表达差异的基因分子功能分类看,属于酶和酶调控子基因最多(306个,占24.7%),其次是核酸结合基因(144个,占11.6%)。第三类是信号传导基因(137个,占11.1%)。第四类是蛋白结合基因(116个,占9.4%)。以上4大类共占基因总数56.8%。还有功能未知的基因有207个,占16.7%。结论:高转移卵巢癌细胞株差异表达基因散在分布在各条染色体上,但以1、2、12、11、17和X染色体差异表达基因居多,肿瘤的转移是多基因共同作用的结果。4大类(酶和酶调控子活性、核酸结合活性、信号传导活性、蛋白结合活性)差异表达基因是我们今后研究卵巢癌转移相关的重要基因。     

胃癌差异表达基因在染色体上的定位及其功能分析

利用标准化的Affymetrix公司生产的U133A基因芯片检测胃癌（T）与切缘正常胃黏膜（C）基因表达谱差异,并利用生物信息学方法对检测结果进行差异基因在染色体定位和功能分析。结果表明：胃癌与正常胃黏膜比较差异8倍以上共有270个基因,其中表达上调[信号比的对数值（SLR）≥3]有157个,表达下调（SLR≤-3）有113个。从表达差异的基因在染色体定位分析,发现除4个基因未知其定位外,其余所有差异表达基因散在分布和各条染色体上,但以1号染色体为最多,有26个（占9．8％）,其次是11和19号染色体上分别有24个（各占9．1％）。而差异表达的基因发生在染色体短臂（q）上有173个（占65％）。从表达差异的基因功能分类看,属于酶和酶调控子基因最多（67个,24．8占％）,其次是信号传导基因（43个,占15．9％）,第3类是核酸结合基因（17个,占6．3％）,第4类是转运子基因（15个,占5．5％）,第5类是蛋白结合基因（12个,占4．4％）,还有功能未知的基因有50个,占18．5％。以上5大类共占基因总数56．9％。胃癌差异表达基因散在分布在各条染色体上,但以1、11、19号染色体差异表达基因居多。这5大类（酶和酶调控子、信号传导、核酸结合、转运子、蛋白结合）相关基因异常是今后研究胃癌的重要基因。     

Function and Chromosome Location of Differentially Expressed Genes in Gastric Cancer

Using Affymetrix U133A oligonucleotide microarrays, screening was done for genes that were differentially expressed in gastric cancer (T) and normal gastric mucosa (C), and their chromosome location was characterized by bioinformatics. A total of 270 genes were found to have a difference in expression levels of more than eight times. Of them 157 were up-regulated (Signal Log Ratio [SLR]≥3), and 113 were down-regulated (SLR≤-3). Except for, four genes with unknown localization, a vast majority of the genes were sporadically distributed over every chromosome. However, chromosome 1 contained the most differentially expressed genes (26 genes, or 9.8%), followed by chromosomes 11 and 19 (both 24 genes, or 9.1%). These genes were also more likely to be on the short-arm of the chromosome (q), which had 173 (65%). When these genes were classified according to their functions, it was found that most (67 genes, 24.8%) belonged to the enzymes and their regulators groups. The next group was the signal transduction genes group (43 genes, 15.9%). The rest of the top three groups were nucleic acid binding genes (17, 6.3%), transporter genes (15, 5.5%), and protein binding genes (12, 4.4%). These made up 56.9% of all the differentially expressed genes. There were also 50 genes of unknown function (18.5%). Therefore it was concluded that differentially expressed genes in gastric cancer seemed to be sporadically distributed across the genome, but most were found on chromosomes 1, 11 and 19. The five groups associated genes abnormality were important genes for further study on gastric cancer.     

Proteomics-based strategy to delineate the molecular mechanisms of the metastasis suppressor gene BRMS1

The breast cancer metastasis suppressor 1 (BRMS1) gene has been shown to suppress metastasis without affecting the growth of the primary tumor in mouse models. It has also been shown to suppress the metastasis of tumors derived from breast, melanoma, and, more recently, ovarian carcinoma (see ref 1). However, how BRMS1 exerts its metastasis suppressor function remains unknown. To shed light into its metastatic mechanism of action, the sensitive 2D-DIGE analysis coupled with MS has been used to identify proteins differentially expressed by either overexpressing (Mel-BRMS1) or silencing BRMS1 (sh635) in a melanoma cell line. After comparison of the protein profiles from WT, Mel-BRMS1, and sh635 cells, 79 spots were found to be differentially expressed. Mass spectrometry analysis allowed the unambiguous identification of 55 polypeptides, corresponding to 43 different proteins. Interestingly, more than 75% of the identified proteins were down-regulated in Mel-BRMS1 cells compared to WT. In contrast, all the identified proteins in sh635 cells extracts were up-regulated compared to WT. Most of the deregulated proteins are involved in cell growth/maintenance and signal transduction among other cell processes. Six differentially expressed proteins (Hsp27, Alpha1 protease inhibitor, Cofilin1, Cathepsin D, Bone morphogenetic protein receptor2, and Annexin2) were confirmed by immunoblot and functional assays. Excellent correlation was found between DIGE analysis and immunoblot results, indicating the reliability of the analysis. Available evidence on the reported functions of the identified proteins supports the emerging role of BRMS1 as negative regulator of the metastasis development. This work opens an avenue for the molecular mechanisms' characterization of metastasis suppressor genes with the aim to understand their roles.     

杨盘二孢菌诱导的杨树差异表达基因的功能分析和染色体定位

利用cDNA芯片技术从含有2,952个克隆的杨树芯片中筛选出1,160个受杨盘二孢菌诱导的基因。功能分析表明,该1,160个基因分别属于11个功能类别,除了功能未知基因外,参与新陈代谢、防御反应、信号传导及转录调控的基因最多,这4大类基因约占基因总数的42%。1,160个差异表达基因中有926个基因被定位于19条染色体上,其中被定位于第Ⅱ条染色体上的差异基因最多,共102个(11.0%),其次是第Ⅰ条染色体,共93个(10%),被定位到第ⅩⅦ条染色体上的差异基因最少,仅有11个,基因在染色体上的分布则表现为在部分染色体的末端区域存在大量的聚集,在中间区段则相对较少和排列稀疏,基因的这种分布情况与植物抗病的关系有待进一步研究。     

Newly identified tumor-associated role of human Sharpin

In order to discover previously unidentified cancer-associated genes, we analyzed genome-wide differences in gene expression between tumor biopsies and normal tissues. Among those differentially regulated genes, we identified Sharpin (Shank-associated RH domain-interacting protein) as a commonly up-regulated gene in multiple human cancer types. Although rat Sharpin is reported to interact with Shank1, a multidomain scaffold protein localized in postsynaptic densities, its exact roles are unknown. Whereas human Sharpin homologue was primarily localized in the cytosol of cultured cells, they were detected in both cytosol and nucleus of the cells from ovarian and liver cancer tissues using immunohistochemical staining. In addition, Chinese ovary hamster cells over-expressing Sharpin exhibited enhanced cancer-specific phenotypes in multiple in vitro tumor assays. Taken together, the results suggest that Sharpin is not an inert scaffold protein, but may play tumor-associated roles during cancer biogenesis.     

Identification and cloning of genes displaying elevated expression as a consequence of metastatic progression in human melanoma cells by rapid subtraction hybridization

Although extensively investigated, the complete repertoire of genes associated with and causative of metastasis remain largely unknown. We developed an efficient approach for identifying differentially expressed genes that involves rapid subtraction hybridization (RaSH) of cDNA clones prepared from two cell populations, a driver and a tester. This RaSH approach has previously documented high sensitivity and effectiveness in identifying genes that are differentially expressed as a function of induction of terminal differentiation in human melanoma cells, resistance or sensitivity to human immunodeficiency virus-1 (HIV-1) infection of human T cells and perturbation in gene expression in normal human fetal astrocytes infected with HIV-1 or treated with HIV-1 gp120 viral envelope glycoprotein or tumor necrosis factor-alpha (TNF-alpha). In the present study, RaSH has been applied to a metastatic melanoma model, which mimics the early events of metastasis in humans, comprising weakly metastatic vs. immunosuppressed newborn rat-selected highly metastatic variants. This has now resulted in the identification of eight genes displaying elevated expression in the high metastatic variants vs. normal immortal melanocytes or weakly metastatic parental clones. These include six known genes, 67-kDa laminin receptor (67LR), endothelin receptor B (ENDRB), Na+/K+-ATPase, Ku antigen, interleukin-receptor-associated kinase-1 (IRAK-1) and ribosomal protein RPLA, which may contribute to the complex process of melanoma metastasis. Additionally, two unknown genes (not reported in current databases) that may also impact on the metastatic phenotype have also been identified. These studies provide additional support of the use of the RaSH approach, in this application in the context of closely related variant cell lines with different metastatic potential, for effective differential gene identification and elucidate eight previously unrecognized genes whose role in melanoma progression to metastatic competence can now be scrutinized.     

Joint analysis of WES and RNA-Seq identify signature genes related to metastasis in prostate cancer

Prostate cancer (PCa) has a certain degree of heritability, and metastasis occurs as cancer progresses. However, its underlying mechanism remains largely unknown. We sequenced four cases of cancer without metastasis, four metastatic cancer, and four benign hyperplasia tissues as controls. A total of 1839 damaging mutations were identified. Pathway analysis, gene clustering, and weighted gene co-expression network analysis were employed to find characteristics associated with metastasis. Chr19 had the most mutation density and 1p36 had the highest mutation frequency across the genome. These mutations occurred in 1630 genes, including the most frequently mutated genes TTN and PLEC, and dozens of metastasis-related genes, such as FOXA1, NCOA1, CD34, and BRCA2. Ras signalling and arachidonic acid metabolism were uniquely enriched in metastatic cancer. Gene programmes 10 and 11 showed the signatures indicating the occurrence of metastasis better. A module (135 genes) was specifically associated with metastasis. Of them, 67.41% reoccurred in program 10, with 26 genes further retained as the signature genes related to PCa metastasis, including AGR3, RAPH1, SOX14, DPEP1, and UBL4A. Our study provides new molecular perspectives on PCa metastasis. The signature genes and pathways could be served as potential therapeutic targets for metastasis or cancer progression.     

Identification of two molecular subtypes of dysregulated immune lncRNAs in ovarian cancer

Long non-coding RNA (lncRNA) has increasingly been identified as a key regulator in pathologies such as cancer. Multiple platforms were used for comprehensive analysis of ovarian cancer to identify molecular subgroups. However, lncRNA and its role in mapping the ovarian cancer subpopulation are still largely unknown. RNA-sequencing and clinical characteristics of ovarian cancer were acquired from The Cancer Genome Atlas database (TCGA). A total of 52 lncRNAs were identified as aberrant immune lncRNAs specific to ovarian cancer. We redefined two different molecular subtypes, C1(188) and C2(184 samples), in “iClusterPlus” R package, among which C2 grouped ovarian cancer samples have higher survival probability and longer median survival time (P <0.05) with activated IFN-gamma response, Wound Healing and Cytotoxic lymphocytes signal; 456 differentially expressed genes were acquired in C1 and C2 subtypes using limma (3.40.6) package, among which 419 were up-regulated and 37 were down-regulated, in TCGA dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis revealed that these genes were actively involved in ECM-receptor interaction, PI3K-Akt signaling pathway interaction KEGG pathway. Compared with the existing immune subtype, the Cluster2 sample showed a substantial increase in the proportion of the existing C2 immune subtype, accounting for 81.37%, which was associated with good prognosis. Our C1 subtype contains only 56.49% of the existing immune C1 and C4, which also explains the poor prognosis of C1. Furthermore, 52 immune-related lncRNAs were used to divide the TCGA-endometrial cancer and cervical cancer samples into two categories, and C2 had a good prognosis. The differentially expressed genes were highly correlated with immune-cell-related pathways. Based on lncRNA, two molecular subtypes of ovarian cancer were identified and had significant prognostic differences and immunological characteristics.     

Retracted: KDM6B promotes ovarian cancer cell migration and invasion by induced transforming growth factor-β1 expression

KDM6B, also known as JMJD3, is a member of the family of histone lysine demethylase (KDMs), which is closely related to many types of cancers. However, its role and the underlying mechanisms in ovarian cancer remain unknown. Here we show that KDM6B is elevated in epithelial ovarian cancer and its expression level is closely related with metastasis and invasion. In addition, survival analysis showed that high expression of KDM6B was associated with low overall survival in ovarian cancer patients. Overexpression of KDM6B in epithelial ovarian cancer cells promoted proliferation, epithelial-mesenchymal transition (EMT), migration and invasion in vitro, and enhanced metastatic capacities in vivo. On the contrary, silencing KDM6B in invasive and metastatic ovarian cancer cells inhibited these processes. Mechanistically, we found that KDM6B exerts its function by modulating the transforming growth factor-β1 (TGF-β1) expression, and TGF-β1 signal pathway inhibitor LY2157299 significantly inhibited KDM6B-induced proliferation, migration, metastasis, and EMT in ovarian cancer cells. Our findings, for the first time, reveal the pivotal role of KDM6B in the invasion and metastatic behavior of epithelial ovarian cancer. Thus, targeting KDM6B may be a useful strategy to interfere with these behaviors of epithelial ovarian cancer.     

Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis

This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pre‐treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis‐related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up‐regulated and 60 were down‐regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K‐Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K‐Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis.     

Suppression of lung cancer cell invasion and metastasis by connexin43 involves the secretion of follistatin-like 1 mediated via histone acetylation

Although connexin has been recognized as a tumor suppressor in many types of cancer, the underlying mechanisms are poorly understood. We have previously shown that transfection of connexin43 (Cx43) cDNA retarded the growth of a highly metastatic human pulmonary giant cell carcinoma cell line, PG, both in vitro and in vivo. Here, we further demonstrate that the metastasis and invasion, but not the migration, of PG cells are also inhibited following Cx43 transfection. The diminishment of metastasis and invasion is associated with down-regulation of genes including MMP-2, S100A, LAMA4, and HDAC10, as well as up-regulation of genes such as MTSS1 and FSTL1 as revealed by gene chip analysis. Interestingly, the suppression effects of Cx43 are related to secreted factor(s), which are blocked by FSTL1 antibody treatment in a dose-dependent manner. Furthermore, the FSTL1 promoter was shown to be associated with acetylated histones H3 and H4 upon Cx43 transfection. These data suggest that Cx43 inhibits the invasion and metastasis of PG cells by modulating the secretion of FSTL1, which is regulated by histone acetylation. Cx43 may act as a "histone deacetylase inhibitor" to modulate gene expression and subsequent cellular functions in PG cells.     

Dominant Expression of DCLK1 in Human Pancreatic Cancer Stem Cells Accelerates Tumor Invasion and Metastasis

Patients with pancreatic cancer typically develop tumor invasion and metastasis in the early stage. These malignant behaviors might be originated from cancer stem cells (CSCs), but the responsible target is less known about invisible CSCs especially for invasion and metastasis. We previously examined the proteasome activity of CSCs and constructed a real-time visualization system for human pancreatic CSCs. In the present study, we found that CSCs were highly metastatic and dominantly localized at the invading tumor margins in a liver metastasis model. Microarray and siRNA screening assays showed that doublecortin-like kinase 1 (DCLK1) was predominantly expressed with histone modification in pancreatic CSCs with invasive and metastatic potential. Overexpression of DCLK1 led to amoeboid morphology, which promotes the migration of pancreatic cancer cells. Knockdown of DCLK1 profoundly suppressed in vivo liver metastasis of pancreatic CSCs. Clinically, DCLK1 was overexpressed in the metastatic tumors in patients with pancreatic cancer. Our studies revealed that DCLK1 is essential for the invasive and metastatic properties of CSCs and may be a promising epigenetic and therapeutic target in human pancreatic cancer.     

Increased Secretory Leukocyte Protease Inhibitor (SLPI) Production by Highly Metastatic Mouse Breast Cancer Cells

The precise molecular mechanisms enabling cancer cells to metastasize from the primary tumor to different tissue locations are still largely unknown. Secretion of some proteins by metastatic cells could facilitate metastasis formation. The comparison of secreted proteins from cancer cells with different metastatic capabilities in vivo might provide insight into proteins involved in the metastatic process. Comparison of the secreted proteins from the mouse breast cancer cell line 4T1 and its highly metastatic 4T1.2 clone revealed a prominent differentially secreted protein which was identified as SLPI (secretory leukocyte protease inhibitor). Western blotting indicated higher levels of the protein in both conditioned media and whole cell lysates of 4T1.2 cells. Additionally higher levels of SLPI were also observed in 4T1.2 breast tumors in vivo following immunohistochemical staining. A comparison of SLPI mRNA levels by gene profiling using microarrays and RT-PCR did not detect major differences in SLPI gene expression between the 4T1 and 4T1.2 cells indicating that SLPI secretion is regulated at the protein level. Our results demonstrate that secretion of SLPI is drastically increased in highly metastatic cells, suggesting a possible role for SLPI in enhancing the metastatic behavior of breast cancer cell line 4T1.     

Molecular mechanisms of ovarian carcinoma metastasis: Key genes and regulatory microRNAs

Metastasis of primary tumors progresses stepwise — from change in biochemistry, morphology, and migratory patterns of tumor cells to the emergence of receptors on their surface that facilitate directional migration to target organs followed by the formation of a specific microenvironment in a target organ that helps attachment and survival of metastatic cells. A set of specific genes and signaling pathways mediate this process under control of microRNA. The molecular mechanisms underlying biological processes associated with tumor metastasis are reviewed in this publication using ovarian cancer, which exhibits high metastatic potential, as an example. Information and data on the genes and regulatory microRNAs involved in the formation of cancer stem cells, epithelial–mesenchymal transition, reducing focal adhesion, degradation of extracellular matrix, increasing migration activity of cancer cells, formation of spheroids, apoptosis, autophagy, angiogenesis, formation of metastases, and development of ascites are presented. Clusters of microRNAs (miR-145, miR-31, miR-506, miR-101) most essential for metastasis of ovarian cancer including the families of microRNAs (miR-200, miR-214, miR-25) with dual role, which is different in different histological types of ovarian cancer, are discussed in detail in a section of the review.     

Identification of NDRG1-regulated genes associated with invasive potential in cervical and ovarian cancer cells

N-myc downstream regulated gene 1 (NDRG1) is an important gene regulating tumor invasion. In this study, shRNA technology was used to suppress NDRG1 expression in CaSki (a cervical cancer cell line) and HO-8910PM (an ovarian cancer cell line). In vitro assays showed that NDRG1 knockdown enhanced tumor cell adhesion, migration and invasion activities without affecting cell proliferation. cDNA microarray analysis revealed 96 deregulated genes with more than 2-fold changes in both cell lines after NDRG1 knockdown. Ten common upregulated genes (LPXN, DDR2, COL6A1, IL6, IL8, FYN, PTP4A3, PAPPA, ETV5 and CYGB) and one common downregulated gene (CLCA2) were considered to enhance tumor cell invasive activity. BisoGenet network analysis indicated that NDRG1 regulated these invasion effector genes/proteins in an indirect manner. Moreover, NDRG1 knockdown also reduced pro-invasion genes expression such as MMP7, TMPRSS4 and CTSK. These results suggest that regulation of invasion and metastasis by NDRG1 is a highly complicated process.