Tissue of origin determines cancer-associated CpG island promoter hypermethylation patterns

Background

Aberrant CpG island promoter DNA hypermethylation is frequently observed in cancer and is believed to contribute to tumor progression by silencing the expression of tumor suppressor genes. Previously, we observed that promoter hypermethylation in breast cancer reflects cell lineage rather than tumor progression and occurs at genes that are already repressed in a lineage-specific manner. To investigate the generality of our observation we analyzed the methylation profiles of 1,154 cancers from 7 different tissue types.

Results

We find that 1,009 genes are prone to hypermethylation in these 7 types of cancer. Nearly half of these genes varied in their susceptibility to hypermethylation between different cancer types. We show that the expression status of hypermethylation prone genes in the originator tissue determines their propensity to become hypermethylated in cancer; specifically, genes that are normally repressed in a tissue are prone to hypermethylation in cancers derived from that tissue. We also show that the promoter regions of hypermethylation-prone genes are depleted of repetitive elements and that DNA sequence around the same promoters is evolutionarily conserved. We propose that these two characteristics reflect tissue-specific gene promoter architecture regulating the expression of these hypermethylation prone genes in normal tissues.

Conclusions

As aberrantly hypermethylated genes are already repressed in pre-cancerous tissue, we suggest that their hypermethylation does not directly contribute to cancer development via silencing. Instead aberrant hypermethylation reflects developmental history and the perturbation of epigenetic mechanisms maintaining these repressed promoters in a hypomethylated state in normal cells.     

Metabolomic profiling of lung and prostate tumor tissues by capillary electrophoresis time-of-flight mass spectrometry

Metabolic microenvironment of tumor cells is influenced by oncogenic signaling and tissue-specific metabolic demands, blood supply, and enzyme expression. To elucidate tumor-specific metabolism, we compared the metabolomics of normal and tumor tissues surgically resected pairwise from nine lung and seven prostate cancer patients, using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Phosphorylation levels of enzymes involved in central carbon metabolism were also quantified. Metabolomic profiles of lung and prostate tissues comprised 114 and 86 metabolites, respectively, and the profiles not only well distinguished tumor from normal tissues, but also squamous cell carcinoma from the other tumor types in lung cancer and poorly differentiated tumors from moderately differentiated tumors in prostate cancer. Concentrations of most amino acids, especially branched-chain amino acids, were significantly higher in tumor tissues, independent of organ type, but of essential amino acids were particularly higher in poorly differentiated than moderately differentiated prostate cancers. Organ-dependent differences were prominent at the levels of glycolytic and tricarboxylic acid cycle intermediates and associated energy status. Significantly high lactate concentrations and elevated activating phosphorylation levels of phosphofructokinase and pyruvate kinase in lung tumors confirmed hyperactive glycolysis. We highlighted the potential of CE-TOFMS-based metabolomics combined with phosphorylated enzyme analysis for understanding tissue-specific tumor microenvironments, which may lead to the development of more effective and specific anticancer therapeutics.     

Mirna expression profiles identify drivers in colorectal and pancreatic cancers

Background and Aim

Altered expression of microRNAs (miRNAs) hallmarks many cancer types. The study of the associations of miRNA expression profile and cancer phenotype could help identify the links between deregulation of miRNA expression and oncogenic pathways.

Methods

Expression profiling of 866 human miRNAs in 19 colorectal and 17 pancreatic cancers and in matched adjacent normal tissues was investigated. Classical paired t-test and random forest analyses were applied to identify miRNAs associated with tissue-specific tumors. Network analysis based on a computational approach to mine associations between cancer types and miRNAs was performed.

Results

The merge between the two statistical methods used to intersect the miRNAs differentially expressed in colon and pancreatic cancers allowed the identification of cancer-specific miRNA alterations. By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers.

Conclusion

MiRNA expression profiles may identify cancer-specific signatures and potentially useful biomarkers for the diagnosis of tissue specific cancers. miRNA-network analysis help identify altered miRNA regulatory networks that could play a role in tumor pathogenesis.     

Telomere Length Influences Cancer Cell Differentiation In Vivo

Limitless reproductive potential is one of the hallmarks of cancer cells. This ability is due to the maintenance of telomeres, erosion of which causes cellular senescence or death. While most cancer cells activate telomerase, a telomere-elongating enzyme, it remains elusive as to why cancer cells often maintain shorter telomeres than the cells in the surrounding normal tissues. Here, we show that forced telomere elongation in cancer cells promotes their differentiation in vivo. We elongated the telomeres of human prostate cancer cells that possess short telomeres by enhancing their telomerase activity. The resulting cells had long telomeres and retained the ability to form tumors in nude mice. Strikingly, these tumors exhibited many duct-like structures and reduced N-cadherin expression, reminiscent of well-differentiated adenocarcinoma. These changes were caused by telomere elongation and not by enhanced telomerase activity. Gene expression profiling revealed that tumor formation was accompanied by the expression of innate immune system-related genes, which have been implicated in maintaining tumor cells in an undifferentiated state and poor-prognosis cancers. In tumors derived from the telomere-elongated cells, upregulation of such gene sets is not observed. Our observations suggest a functional contribution of short telomeres to tumor malignancy by regulation of cancer cell differentiation.     

Distinct Expression Levels and Patterns of Stem Cell Marker,Aldehyde Dehydrogenase Isoform 1 (ALDH1), in Human Epithelial Cancers

Aldehyde dehydrogenase isoform 1 (ALDH1) has been proved useful for the identification of cancer stem cells. However, our knowledge of the expression and activity of ALDH1 in common epithelial cancers and their corresponding normal tissues is still largely absent. Therefore, we characterized ALDH1 expression in 24 types of normal tissues and a large collection of epithelial tumor specimens (six cancer types, n = 792) by immunohistochemical staining. Using the ALDEFUOR assay, ALDH1 activity was also examined in 16 primary tumor specimens and 43 established epithelial cancer cell lines. In addition, an ovarian cancer transgenic mouse model and 7 murine ovarian cancer cell lines were analyzed. We found that the expression levels and patterns of ALDH1 in epithelial cancers are remarkably distinct, and they correlate with their corresponding normal tissues. ALDH1 protein expression levels are positively correlated with ALDH1 enzymatic activity measured by ALDEFLUOR assay. Long-term in vitro culture doesn''t significantly affect ALDH1 activity in epithelial tumor cells. Consistent with research on other cancers, we found that high ALDH1 expression is significantly associated with poor clinical outcomes in serous ovarian cancer patients (n = 439, p = 0.0036). Finally, ALDH^br tumor cells exhibit cancer stem cell properties and are resistant to chemotherapy. As a novel cancer stem cell marker, ALDH1 can be used for tumors whose corresponding normal tissues express ALDH1 in relatively restricted or limited levels such as breast, lung, ovarian or colon cancer.     

Stanniocalcin-1 Reduces Tumor Size in Human Hepatocellular Carcinoma

Growing evidence has revealed high expression levels of stanniocalcin-1 (STC1) in different types of human cancers. Numerous experimental studies using cancer cell lines demonstrated the involvement of STC1 in inflammatory and apoptotic processes; however the role of STC1 in carcinogenesis remains elusive. Hepatocellular carcinoma (HCC) an exemplified model of inflammation-related cancer, represents a paradigm of studying the association between STC1 and tumor development. Therefore, we conducted a statistical analysis on the expression levels of STC1 using clinicopathological data from 216 HCC patients. We found that STC1 was upregulated in the tumor tissues and its expression levels was positively correlated with the levels of interleukin (IL)-6 and IL-8. Intriguingly tumors with greater expression levels of STC1 (tumor/normal ≥ 2) were significantly smaller than the lower level (tumor/normal<2) samples (p = 0.008). A pharmacological approach was implemented to reveal the functional correlation between STC1 and the ILs in the HCC cell-lines. IL-6 and IL-8 treatment of Hep3B cells induced STC1 expression. Lentiviral-based STC1 overexpression in Hep3B and MHCC-97L cells however showed inhibitory action on the pro-migratory effects of IL-6 and IL-8 and reduced size of tumor spheroids. The inhibitory effect of STC1 on tumor growth was confirmed in vivo using the stable STC1-overexpressing 97L cells on a mouse xenograft model. Genetic analysis of the xenografts derived from the STC1-overexpressing 97L cells, showed upregulation of the pro-apoptotic genes interleukin-12 and NOD-like receptor family, pyrin domain-containing 3. Collectively, the anti-inflammatory and pro-apoptotic functions of STC1 were suggested to relate its inhibitory effect on the growth of HCC cells. This study supports the notion that STC1 may be a potential therapeutic target for inflammatory tumors in HCC patients.     

Upregulation of SATB1 Is Associated with Prostate Cancer Aggressiveness and Disease Progression

Disease aggressiveness remains a critical factor to the progression of prostate cancer. Transformation of epithelial cells to mesenchymal lineage, associated with the loss of E-cadherin, offers significant invasive potential and migration capability. Recently, Special AT-rich binding protein (SATB1) has been linked to tumor progression. SATB1 is a cell-type restricted nuclear protein, which functions as a tissue-specific organizer of DNA sequences during cellular differentiation. Our results demonstrate that SATB1 plays significant role in prostate tumor invasion and migration and its nuclear localization correlates with disease aggressiveness. Clinical specimen analysis showed that SATB1 was predominantly expressed in the nucleus of high-grade tumors compared to low-grade tumor and benign tissue. A progressive increase in the nuclear levels of SATB1 was observed in cancer tissues compared to benign specimens. Similarly, SATB1 protein levels were higher in a number of prostate cancer cells viz. HPV-CA-10, DU145, DUPro, PC-3, PC-3M, LNCaP and C4-2B, compared to non-tumorigenic PZ-HPV-7 cells. Nuclear expression of SATB1 was higher in biologically aggressive subclones of prostate cancer cells with their respective parental cell lines. Furthermore, ectopic SATB1 transfection conferred increased cell motility and invasiveness in immortalized human prostate epithelial PZ-HPV-7 cells which correlated with the loss of E-cadherin expression. Consequently, knockdown of SATB1 in highly aggressive human prostate cancer PC-3M cells inhibited invasiveness and tumor growth in vivo along with increase in E-cadherin protein expression. Our findings demonstrate that SATB1 has ability to promote prostate cancer aggressiveness through epithelial-mesenchymal transition.     

Regional methylation of the 5' end CpG island of BRCA1 is associated with reduced gene expression in human somatic cells.

In mammalians, demethylation of specific promoter regions often correlates with gene activation; inversely, dense methylation of CpG islands leads to gene silencing, probably mediated by methyl-CpG binding proteins. In cell lines and cancers, inhibition of tissue-specific genes and tumor suppressor genes expression seems to be related to such hypermethylation. The 5' end of the breast cancer predisposition gene BRCA1 is embedded in a large CpG island of approximately 2.7 kb in length. In human sporadic breast cancers, the down-regulation of BRCA1 does not seem to be related to BRCA1 gene alterations. Southern blot analysis and the bisulfite sequencing method indicate that the BRCA1 CpG island is regionally methylated in all human tissues analyzed and unmethylated in the gametes, suggesting a role for DNA methylation in the control of gene expression. We have therefore investigated the potential role of methyl-CpG binding proteins in the regulation of BRCA1 gene expression. In vitro, partial methylation of constructs containing this region strongly inhibits gene expression in the presence of MeCP2 protein. Moreover, in the five human cell lines analyzed, chemically induced hypomethylation is associated with BRCA1 gene activation. These data suggest that methyl-CpG binding proteins might be associated with the control of BRCA1 gene expression and that methyl-DNA binding proteins may participate in the regulation of gene expression in mammalian cells.     

Array-Based Approaches for the Identification of Epigenetic Silenced Tumor Suppressor Genes

Carcinogenesis involves the inactivation or inhibition of genes that function as tumor suppressors. Deletions, mutations, or epigenetic silencing of tumor suppressor genes can lead to altered growth, differentiation, and apoptosis. DNA methylation and histone modifications are important epigenetic mechanisms of gene regulation and play essential roles both independently and cooperatively in tumor initiation and progression. Realization that many tumor suppressor genes are silenced by epigenetic mechanisms has stimulated discovery of novel tumor suppressor genes. One of the most useful of these approaches is an epigenetic reactivation screening strategy that combines treatment of cancer cells in vitro with DNA methyltransferase and/or histone deacetylase (HDAC) inhibitors, followed by global gene expression analysis using microarrays, to identify upregulated genes. This approach is most effective when complemented by microarray analyses to identify genes repressed in primary tumors. Recently, using cancer cell lines treated with a DNA methylation inhibitor and/or a HDAC inhibitor in conjunction with cDNA microarray analysis, candidate tumor suppressor genes, which are subject to epigenetic silencing, have been identified in endometrial, colorectal, esophageal, and pancreatic cancers. An increasing number of studies have utilized epigenetic reactivation screening to discover novel tumor suppressor genes in cancer. The results of some of the most recent studies are highlighted in this review.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, “RFE_Relief algorithm” was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

Human neuroblastoma tumor cell lines correspond to the arrested differentiation of chromaffin adrenal medullary neuroblasts

We have examined the hypothesis that nonhematopoietic malignancies may contain cells corresponding to those which occur during the differentiation of tissue precursors. Neuroblastoma, an embryonal tumor of the adrenal medulla, was studied because of its well described ability to differentiate both in vivo and in vitro. We examined the expression of four genes during development of the human adrenal medulla: tyrosine hydroxylase, chromagranin A, pG2, and beta-2-microglobulin. The sequential expression of these genes by adrenal neuroblasts marks successive stages during maturation of the chromaffin lineage. We also observed a population of neuroblasts during adrenal medullary development that did not express any of these four genes, suggestive of adrenal medullary cells differentiating along nonchromaffin lineage(s). We then evaluated 27 neuroblastoma cell lines for the expression of these genes and found that 24 expressed chromaffin markers, with 19 of these mimicking the pattern of gene expression found during development. Three cell lines did not express tyrosine hydroxylase, chromogranin A, or pG2, consistent with either a very undifferentiated neural crest cell or maturation along a nonchromaffin lineage. These data indicate that neuroblastoma tumor cells correspond to adrenal neuroblasts arrested during morphogenesis of the adrenal medulla and raise the possibility that malignant transformation of cells at different stages of tissue maturation may contribute to the diversity that characterizes tumors of solid tissues.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.