Beyond comparing means: the usefulness of analyzing interindividual variation in gene expression for identifying genes associated with cancer development

Identifying genes associated with cancer development is typically accomplished by comparing mean expression values in normal and tumor tissues, which identifies differentially expressed (DE) genes. Interindividual variation (IV) in gene expression is indirectly included in DE gene identification because given the same absolute differences in means, genes with lower variance tend to have lower p-values. We explored the direct use of IV in gene expression to identify candidate genes associated with cancer development. We focused on prostate (PCa) and lung (LC) cancers and compared IV in the expression level of genes shown to be cancer related with that in all other genes in the human genome. Compared with all those other genes, cancer-related genes tended to have greater IV in normal tissues and a greater increase in IV during the transition from normal to tumorous tissue. Genes without significantly different mean expression values between tumor and normal tissues but with greater IV in tumor than in normal tissue (note: the DE-based approach completely ignores those genes) had stronger associations with clinically important features like Gleason score in PCa or tumor histology in LC than all other genes were. Our results suggest that analyzing IV in gene expression level is useful in identifying novel candidate genes associated with cancer development.     

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues

A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.     

Integrated analysis of miRNA and mRNA expression in childhood medulloblastoma compared with neural stem cells

Medulloblastoma (MB) is the most common malignant brain tumor in children and a leading cause of cancer-related mortality and morbidity. Several molecular sub-types of MB have been identified, suggesting they may arise from distinct cells of origin. Data from animal models indicate that some MB sub-types arise from multipotent cerebellar neural stem cells (NSCs). Hence, microRNA (miRNA) expression profiles of primary MB samples were compared to CD133+ NSCs, aiming to identify deregulated miRNAs involved in MB pathogenesis. Expression profiling of 662 miRNAs in primary MB specimens, MB cell lines, and human CD133+ NSCs and CD133- neural progenitor cells was performed by qRT-PCR. Clustering analysis identified two distinct sub-types of MB primary specimens, reminiscent of sub-types obtained from their mRNA profiles. 21 significantly up-regulated and 12 significantly down-regulated miRNAs were identified in MB primary specimens relative to CD133+ NSCs (p<0.01). The majority of up-regulated miRNAs mapped to chromosomal regions 14q32 and 17q. Integration of the predicted targets of deregulated miRNAs with mRNA expression data from the same specimens revealed enrichment of pathways regulating neuronal migration, nervous system development and cell proliferation. Transient over-expression of a down-regulated miRNA, miR-935, resulted in significant down-regulation of three of the seven predicted miR-935 target genes at the mRNA level in a MB cell line, confirming the validity of this approach. This study represents the first integrated analysis of MB miRNA and mRNA expression profiles and is the first to compare MB miRNA expression profiles to those of CD133+ NSCs. We identified several differentially expressed miRNAs that potentially target networks of genes and signaling pathways that may be involved in the transformation of normal NSCs to brain tumor stem cells. Based on this integrative approach, our data provide an important platform for future investigations aimed at characterizing the role of specific miRNAs in MB pathogenesis.     

Identification of LINC01615 as potential metastasis-related long noncoding RNA in hepatocellular carcinoma

Hepatocellular carcinoma is one of the most prevalent and fatal cancers. Studying the long noncoding RNA (lncRNA) alterations in hepatocellular carcinoma may lead to new therapeutic strategies. We checked whether there were correlations between The Cancer Genome Atlas expression profiles of the differentially expressed lncRNAs and their DNA methylation status or the copy number variations for hepatocellular carcinoma. We obtained 41 lncRNAs that were differentially expressed between tumor and normal samples, and their DNA methylation status was negatively correlated with the expression levels. We identified five lncRNAs that were recurrently amplified or deleted in tumor samples, but none of them were associated with the messenger RNA (mRNA) expression levels. To obtain the biological function of these lncRNAs, the coexpressed mRNAs in the hepatocellular carcinoma were figured out. A total of 10 lncRNAs were highly correlated with at least one gene. Six out of the ten lncRNAs were already known to be related with cancer previously. LINC01615 had 72 coexpressed genes, and we carried out the gene ontology (GO) term enrichment for these protein-coding genes. The results suggested that these lncRNAs were associated with extracellular matrix organization. To summarize, we identified 41 potentially cancer-related lncRNAs. In particular, we proposed that LINC01615 potentially affected the extracellular matrix and had further impacts on the metastasis of hepatocellular carcinoma.     

肺癌组织和肿瘤细胞系中BRG1的表达分析

BRG1（brahma—related gene 1）是进化上高度保守的SWI／SNF染色质重塑复合物的成员之一．研究表明：BRG1具有抑瘤基因的特征,可能与肿瘤的发生发展有关．我们采用RT—PCR、Northern杂交和Western blotting证实：肺腺癌细胞系A549和鼻咽癌细胞系HNE2、HNE3、CNE1中无BRG1的表达,而肺鳞癌细胞系NCI-H520、永生化正常人支气管上皮细胞系HBE和鼻咽癌细胞系HONE1、HNE1、CNE2中有BRG1的表达．同时,通过RT—PCR检测10例肺癌组织标本．发现60％（6／10）的肺癌组织中日RGG1的mRNA水平明显下调,而配对正常肺组织中BRG1的mRNA表达未见改变．对29例肺癌组织和10例配对正常肺组织切片进行免疫组化染色,结果显示：肺癌组织中BRG1蛋白表达的阳性率为37．9％（11／29）,配对正常肺组织中BRG1蛋白表达的阳性率为90％（9／10）,两者的差异有显著性（P〈0．05）．这提示BRG1确实在肺癌组织及多种肿瘤细胞系中表达下调或缺失,在肺癌发病过程中可能起一定的作用．     

Expression Profiling of Mitochondrial Voltage-Dependent Anion Channel-1 Associated Genes Predicts Recurrence-Free Survival in Human Carcinomas

Background

Mitochondrial voltage-dependent anion channels (VDACs) play a key role in mitochondria-mediated apoptosis. Both in vivo and in vitro evidences indicate that VDACs are actively involved in tumor progression. Specifically, VDAC-1, one member of the VDAC family, was thought to be a potential anti-cancer therapeutic target. Our previous study demonstrated that the human gene VDAC1 (encoding the VDAC-1 isoform) was significantly up-regulated in lung tumor tissue compared with normal tissue. Also, we found a significant positive correlation between the gene expression of VDAC1 and histological grade in breast cancer. However, the prognostic power of VDAC1 and its associated genes in human cancers is largely unknown.

Methods

We systematically analyzed the expression pattern of VDAC1 and its interacting genes in breast, colon, liver, lung, pancreatic, and thyroid cancers. The genes differentially expressed between normal and tumor tissues in human carcinomas were identified.

Results

The expression level of VDAC1 was uniformly up-regulated in tumor tissue compared with normal tissue in breast, colon, liver, lung, pancreatic, and thyroid cancers. Forty-four VDAC1 interacting genes were identified as being commonly differentially expressed between normal and tumor tissues in human carcinomas. We designated VDAC1 and the 44 dysregulated interacting genes as the VDAC1 associated gene signature (VAG). We demonstrate that the VAG signature is a robust prognostic biomarker to predict recurrence-free survival in breast, colon, and lung cancers, and is independent of standard clinical and pathological prognostic factors.

Conclusions

VAG represents a promising prognostic biomarker in human cancers, which may enhance prediction accuracy in identifying patients at higher risk for recurrence. Future therapies aimed specifically at VDAC1 associated genes may lead to novel agents in the treatment of cancer.     

miRNA profiling in colorectal cancer highlights miR-1 involvement in MET-dependent proliferation

Altered expression of miRNAs is associated with development and progression of various human cancers by regulating the translation of oncogenes and tumor suppressor genes. In colorectal cancer, these regulators complement the Vogelstein multistep model of pathogenesis and have the potential of becoming a novel class of tumor biomarkers and therapeutic targets. Using quantitative real-time PCR, we measured the expression of 621 mature miRNAs in 40 colorectal cancers and their paired normal tissues and identified 23 significantly deregulated miRNAs. We subsequently evaluated their association with clinical characteristics of the samples and presence of alterations in the molecular markers of colorectal cancer progression. Expression levels of miR-31 were correlated with CA19-9 and miR-18a, miR-21, and miR-31 were associated with mutations in APC gene. To investigate the downstream regulation of the differentially expressed miRNAs identified, we integrated putative mRNA target predictions with the results of a meta-analysis of seven public gene expression datasets of normal and tumor samples of colorectal cancer patients. Many of the colorectal cancer deregulated miRNAs computationally mapped to targets involved in pathways related to progression. Here one promising candidate pair (miR-1 and MET) was studied and functionally validated. We show that miR-1 can have a tumor suppressor function in colorectal cancer by directly downregulating MET oncogene both at RNA and protein level and that reexpression of miR-1 leads to MET-driven reduction of cell proliferation and motility, identifying the miR-1 downmodulation as one of the events that could enhance colorectal cancer progression.     

Identification of potential key genes associated with osteosarcoma based on integrated bioinformatics analyses

Due to high rates of metastasis and poor clinical outcomes for patients, it is important to study the pathomechanisms of osteosarcoma. However, due to the fact that osteosarcoma shows significant interindividual variation and high heterogeneity, the identification of differentially expressed genes (DEGs) at the population level cannot answer many important questions related to osteosarcoma tumorigenesis. Therefore, a new strategy to identify dysregulated genes in osteosarcoma samples is required. The aim of this study was to improve our understanding of osteosarcoma pathogenesis by identifying genes with universal aberrant expression in osteosarcoma samples. Because the relative expression ordering of genes is stable in normal bone tissues but is disrupted in osteosarcoma tissues, we used the RankComp algorithm to identify DEGs in normal and osteosarcoma tissue samples. We then calculated the dysregulation frequency for each gene. Genes with deregulation frequencies above 80% were deemed to be universal DEGs. Next, coexpression, pathway enrichment, and protein-protein interaction network analyses were performed to characterize the functions of these genes. From 188 samples of osteosarcoma obtained from four datasets measured on different platforms, 51 universal DEGs were identified, including 4 universally upregulated genes and 47 universally downregulated genes. Genes that were differentially coexpressed with these universal DEGs were found to be enriched in 46 cancer-related pathways. In addition, functional and network analyses showed that genes with high dysregulation frequencies were involved in cancer-related functions. Thus, the commonly aberrant genes identified in osteosarcoma tissues may be important targets for osteosarcoma diagnosis and therapy.     

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.     

Comprehensive genetic analysis of cancer cells

Human cancer is viewed as a disorder of genes originating from the progeny of a single cell that has accumulated multiple genetic alterations. The genetic alterations include point mutation, chromosomal rearrangements and imbalances. Amplifications primarily involve oncogenes whose overexpression leads to growth deregulation, while deletions commonly target tumor suppressor genes that control cell cycle checkpoints and DNA repair mechanisms. With the advent of molecular cytogenetics procedures for global detection of genomic imbalances and for multicolor visualization of structural chromosome changes, as well as the completion of human genome mapping and the development of microarray technology for serial gene expression analysis of the entire genomes, a significant progress has been made in uncovering the molecular basis of cancer. The major challenge in cancer biology is to decipher the molecular anatomy of various cancers and to identify cancer-related genes that now comprise only a fraction of human genes. The complete genetic anatomy of specific cancers would allow a better understanding of the role of genetic alterations in carcinogenesis, provide diagnostic and prognostic markers and discriminate between cells at different stages of progression toward malignancy. This review highlights current technologies that are available to explore cancer cells and outlines their application to investigations in human hepatocellular carcinoma.     

Variation in gene expression patterns in human gastric cancers

Gastric cancer is the world's second most common cause of cancer death. We analyzed gene expression patterns in 90 primary gastric cancers, 14 metastatic gastric cancers, and 22 nonneoplastic gastric tissues, using cDNA microarrays representing approximately 30,300 genes. Gastric cancers were distinguished from nonneoplastic gastric tissues by characteristic differences in their gene expression patterns. We found a diversity of gene expression patterns in gastric cancer, reflecting variation in intrinsic properties of tumor and normal cells and variation in the cellular composition of these complex tissues. We identified several genes whose expression levels were significantly correlated with patient survival. The variations in gene expression patterns among cancers in different patients suggest differences in pathogenetic pathways and potential therapeutic strategies.