Affymetrix基因表达谱芯片在新疆维吾尔族与汉族胰腺癌组织样本间差异表达基因筛选中的运用

目的:运用基因表达谱芯片筛选并分析新疆维吾尔族与汉族胰腺癌组织样本间的差异表达基因。方法:收集我院2014年1月至2016年6月间行手术切除的维吾尔族与汉族胰腺导管细胞癌组织并提取总RNA,选取经Nanodrop 2000与Agilent 2100仪器质检合格的样本总RNA采用Affymetrix基因表达谱芯片筛选出差异表达基因并绘制统计图,运用基因本体(GO)分析及信号通路(Pathway)分析对这些差异表达基因的生物信息进行汇总分析。结果:通过基因表达谱芯片分析,新疆维吾尔族与汉族胰腺癌组织样本间共检测到1063个基因存在差异表达,在维吾尔族胰腺癌标本中显著上调表达的基因共281个,差异表达倍数最高的为IGLV1-44基因(差异倍数:9.99)下调表达的基因共782个,差异表达倍数最高的为CPB1基因(差异倍数:33.76);在Gene Ontology数据库中共检索到815个上述差异表达基因具有明确的GO分类,差异表达倍数最高的为CPB1基因(差异倍数:33.76);Pathway分析中共检测到30条信号通路包含有上述差异表达基因,共涉及196个基因,其中以FAK信号通路差异表达基因富集程度最高,差异表达倍数最高的基因为COL11A1基因(差异倍数:5.02)。结论:基因表达谱芯片分析结果显示,在新疆维吾尔族与汉族胰腺癌组织样本间存在大量的差异表达基因,这些基因与胰腺癌的增殖分化、侵袭转移及多药耐药等特性密切相关,且参与了多条生物体内重要信号转导通路的调控。     

Differential gene expression of the key signalling pathway in para‐carcinoma,carcinoma and relapse human pancreatic cancer

Pancreatic cancer (PC) has a high rate of mortality and a poorly understood mechanism of progression. Investigation of the molecular mechanism of PC and exploration of the specific markers for early diagnosis and specific targets of therapy are key points to prevent and treat PC effectively and to improve their prognosis. In our study, expression profiles experiment of para‐carcinoma, carcinoma and relapse human PC was performed using Agilent human whole genomic oligonucleotide microarrays with 45 000 probes. Differentially expressed genes related with PC were screened and analysed further by Gene Ontology term analysis and Kyoto encyclopaedia of genes and genomes pathway analysis. Our results showed that there were 3853 differentially expressed genes associated with pancreatic carcinogenesis and relapse. In addition, our study found that PC was related to the Jak–STAT signalling pathway, PPAR signalling pathway and Calcium signalling pathway, indicating their potential roles in pancreatic carcinogenesis and progress. Copyright © 2013 John Wiley & Sons, Ltd.     

Identification of a potential ovarian cancer stem cell gene expression profile from advanced stage papillary serous ovarian cancer

Identification of gene expression profiles of cancer stem cells may have significant implications in the understanding of tumor biology and for the design of novel treatments targeted toward these cells. Here we report a potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma. Affymetrix U133 Plus 2.0 microarrays were used to interrogate the differentially expressed genes between side population (SP) and main population (MP), and the results were analyzed by paired T-test using BRB-ArrayTools. We identified 138 up-regulated and 302 down-regulated genes that were differentially expressed between all 10 SP/MP pairs. Microarray data was validated using qRT-PCR and17/19 (89.5%) genes showed robust correlations between microarray and qRT-PCR expression data. The Pathway Studio analysis identified several genes involved in cell survival, differentiation, proliferation, and apoptosis which are unique to SP cells and a mechanism for the activation of Notch signaling is identified. To validate these findings, we have identified and isolated SP cells enriched for cancer stem cells from human ovarian cancer cell lines. The SP populations were having a higher colony forming efficiency in comparison to its MP counterpart and also capable of sustained expansion and differentiation in to SP and MP phenotypes. 50,000 SP cells produced tumor in nude mice whereas the same number of MP cells failed to give any tumor at 8 weeks after injection. The SP cells demonstrated a dose dependent sensitivity to specific γ-secretase inhibitors implicating the role of Notch signaling pathway in SP cell survival. Further the generated SP gene list was found to be enriched in recurrent ovarian cancer tumors.     

A metabolism-relevant signature as a predictor for prognosis and therapeutic response in pancreatic cancer

Although several altered metabolic genes have been identified to be involved in the tumorigenesis and advance of pancreatic cancer (PC), their prognostic values remained unclear. The purpose of this study was to explore new targets and establish a metabolic signature to predict prognosis and chemotherapy response for optimal individualized treatment. The expression data of PC patients from two independent cohorts and metabolism-related genes from KEGG were utilized and analyzed for the establishment of the signature via lasso regression. Then, the differentially expressed candidate genes were further confirmed via online data mining platform and qRT-PCR of clinical specimens. Then, the analyses of gene set enrichment, mutation, and chemotherapeutic response were performed via R package. As results showed, 109 differentially expressed metabolic genes were screened out in PC. Then a metabolism-related five-gene signature comprising B3GNT3, BCAT1, KYNU, LDHA, and TYMS was constructed and showed excellent ability for predicting survival. A novel nomogram coordinating the metabolic signature and other independent prognostic parameters was developed and showed better predictive power in predicting survival. In addition, this metabolic signature was significantly involved in the activation of multiple oncological pathways and regulation of the tumor immune microenvironment. The patients with high risk scores had higher tumor mutation burdens and were prone to be more sensitive to chemotherapy. In summary, our work identified a new metabolic signature and established a superior prognostic nomogram which may supply more indications to explore novel strategies for diagnosis and treatment.     

家蚕5龄幼虫精巢和卵巢microRNA芯片及转录组比较分析

【目的】本研究旨在通过对家蚕Bombyx mori 5龄幼虫精巢和卵巢组织微小RNA (microRNA, miRNA)基因芯片及转录组进行分析,找到参与家蚕性腺发育相关的miRNA分子及可能的靶基因。【方法】采用新一代高通量测序平台对家蚕5龄幼虫精巢和卵巢(分别定义为Test和Control)进行miRNA基因芯片检测及转录组测序分析,根据P＜0.05且log₂(fold change, FC)≥2的标准,通过比较筛选出Test vs Control的差异表达miRNA;根据q≤0.05且|log₂(fold change)|≥1的标准,通过比较筛选出Test vs Control的差异表达基因 (differentially expressed genes, DEGs);随机选取8个上调和12个下调差异表达miRNA,对其表达及其预测的5个靶基因进行qRT-PCR验证;对DEGs以及差异表达miRNA的靶基因进行KEGG通路富集分析。【结果】从精巢和卵巢样本中(Test vs Control)分别鉴定出68个差异表达miRNA和3 991个DEGs,其中上调和下调miRNA分别为36和32个,上调和下调DEGs分别为2 033和1 958个。差异表达miRNA的qRT PCR验证结果均与芯片数据一致。KEGG通路富集分析结果显示DEGs在新陈代谢及核糖体的信号通路显著富集。对差异表达miRNA在DEGs中的可能靶基因进行预测,结果找到了4组表达趋势相反的miRNA与靶基因：分别是bmo-miR-2774a与LOC101745556;bmo-miR-92b与LOC101735954以及bmo-miR-3266与LOC733130和LOC778467;1组表达趋势一致的miRNA与靶基因：bmo-miR-3321与LOC101744895。5个靶基因的qRT-PCR验证结果与转录组测序结果一致。【结论】本研究获得了家蚕5龄幼虫精巢和卵巢转录组及miRNA芯片数据,筛选并验证了4组差异表达和1组一致表达miRNA及潜在靶基因,为探究家蚕精巢和卵巢发育差异奠定了基础。     

Identification of glycoprotein markers for pancreatic cancer CD24+CD44+ stem-like cells using nano-LC-MS/MS and tissue microarray

Pancreatic adenocarcinoma is characterized by late diagnosis due to lack of early symptoms, extensive metastasis, and high resistance to chemo/radiation therapy. Recently, a subpopulation of cells within pancreatic cancers, termed cancer stem cells (CSCs), has been characterized and postulated to be the drivers for pancreatic cancer and responsible for metastatic spread. Further studies on pancreatic CSCs are therefore of particular importance to identify novel diagnosis markers and therapeutic targets for this dismal disease. Herein, the malignant phenotype of pancreatic cancer stem-like CD24+CD44+ cells was isolated from a human pancreatic carcinoma cell line (PANC-1) and demonstrated 4-fold increased invasion ability compared to CD24-CD44+ cells. Using lectin microarray and nano LC-MS/MS, we identified a differentially expressed set of glycoproteins between these two subpopulations. Lectin microarray analysis revealed that fucose- and galactose-specific lectins, UEA-1 and DBA, respectively, exhibit distinctly strong binding to CD24+CD44+ cells. The glycoproteins extracted by multilectin affinity chromatography were consequently analyzed by LC-MS/MS. Seventeen differentially expressed glycoproteins were identified, including up-regulated Cytokeratin 8/CK8, Integrin β1/CD29, ICAM1/CD54, and Ribophorin 2/RPN2 and down-regulated Aminopeptidase N/CD13. Immunohistochemical analysis of tissue microarrays showed that CD24 was significantly associated with late-stage pancreatic adenocarcinomas, and RPN2 was exclusively coexpressed with CD24 in a small population of CD24-positive cells. However, CD13 expression was dramatically decreased along with tumor progression, preferentially present on the apical membrane of ductal cells and vessels in early stage tumors. Our findings suggest that these glycoproteins may provide potential therapeutic targets and promising prognostic markers for pancreatic cancer.     

Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes

MOTIVATION: Scanning parameters are often overlooked when optimizing microarray experiments. A scanning approach that extends the dynamic data range by acquiring multiple scans of different intensities has been developed. RESULTS: Data from each of three scan intensities (low, medium, high) were analyzed separately using multiple scan and linear regression approaches to identify and compare the sets of genes that exhibit statistically significant differential expression. In the multiple scan approach only one-third of the differentially expressed genes were shared among the three intensities, and each scan intensity identified unique sets of differentially expressed genes. The set of differentially expressed genes from any one scan amounted to < 70% of the total number of genes identified in at least one scan. The average signal intensity of genes that exhibited statistically significant changes in expression was highest for the low-intensity scan and lowest for the high-intensity scan, suggesting that low-intensity scans may be best for detecting expression differences in high-signal genes, while high-intensity scans may be best for detecting expression differences in low-signal genes. Comparison of the differentially expressed genes identified in the multiple scan and linear regression approaches revealed that the multiple scan approach effectively identifies a subset of statistically significant genes that linear regression approach is unable to identify. Quantitative RT-PCR (qRT-PCR) tests demonstrated that statistically significant differences identified at all three scan intensities can be verified. AVAILABILITY: The data presented can be viewed at http://www.ncbi.nlm.nih.gov/geo/ under GEO accession no. GSE3017.     

Identification and characterization of zebrafish ocular formation genes.

To study genes that are specifically expressed in the eyes, we employed microarray and in situ hybridization analyses to identify and characterize differentially expressed ocular genes in eyeless masterblind (mbl-/-) zebrafish (Danio rerio). Among 70 differentially expressed genes in the mbl-/- mutant identified by microarray analysis, 8 down-regulated genes were characterized, including 4 eye-specific genes, opsin 1 short-wave-sensitive 1 (opn1sw1), crystallinbetaa1b (cryba1b), crystallinbetaa2b (cryba2b), and crystallingamma M2d3 (crygm2d3); 2 eye and brain genes, ATPase, H+ transporting, lysosomal, V0 subunit c (atp6v0c) and basic leucine zipper and W2 domains 1a (bzw1a); and 2 constitutive genes, heat shock protein 8 (hspa8) and ribosomal protein L7a (rpl7a). In situ hybridization experiments confirmed down-regulation of these 8 ocular formation genes in mbl-/- zebrafish and showed their ocular and dynamic temporal expression patterns during zebrafish early development. Further, an automated literature analysis of the 70 differentially expressed genes identified a sub-network of genes with known associations, either with each other or with ocular structures or development, and shows how this study contributes to the current body of knowledge.     

基因芯片筛选新疆维吾尔妇女宫颈癌差异表达基因

新疆南部维吾尔族聚居区是宫颈癌高发区. 本文旨在利用基因芯片技术筛选与维吾尔族妇女宫颈癌发生相关的基因. 首先,分别提取5例新疆维吾尔妇女宫颈癌和5例子宫肌瘤组织(对照)的mRNA,逆转录成cDNA,并用Cy3-dUTP标记子宫肌瘤组织的cDNA,用Cy5 dUTP标记宫颈癌组织的cDNA,制成芯片杂交探针.为筛选出宫颈癌组织中差异表达的基因,上述标记探针分别与含有20 000条人类基因的Affymetrix基因芯片进行杂交,杂交信号用GeneChip Scanner 3000扫描仪扫描,并用芯片图像分析软件(SAM software)分析扫描结果.筛选出的差异表达基因经GO(Gene Ontology)分析和KEGG（Kyoto Encyclopedia of Genes and Genomes）信号通路分析,确定其在宫颈癌中的作用.基因芯片筛选结果显示,在宫颈癌组织中发现2 758个差异表达基因,其中1 326个上调基因,1 432个下调基因.GO分析和KEGG信号通路分析表明,表达差异在两倍以上的基因涉及168个信号通路,包括细胞粘附分子、细胞周期以及MAPK和mTOR信号通路等.上述结果表明,基因芯片技术筛选出大量与宫颈癌发生相关的基因,其中表达差异显著的基因涉及细胞粘附分子、细胞周期和mTOR等信号通路.     

A Meta Analysis of Pancreatic Microarray Datasets Yields New Targets as Cancer Genes and Biomarkers

The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC), which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.