Biological and functional analysis of statistically significant pathways deregulated in colon cancer by using gene expression profiles

Gene expression profiling offers a great opportunity for studying multi-factor diseases and for understanding the key role of genes in mechanisms which drive a normal cell to a cancer state. Single gene analysis is insufficient to describe the complex perturbations responsible for cancer onset, progression and invasion. A deeper understanding of the mechanisms of tumorigenesis can be reached focusing on deregulation of gene sets or pathways rather than on individual genes. We apply two known and statistically well founded methods for finding pathways and biological processes deregulated in pathological conditions by analyzing gene expression profiles. In particular, we measure the amount of deregulation and assess the statistical significance of predefined pathways belonging to a curated collection (Molecular Signature Database) in a colon cancer data set. We find that pathways strongly involved in different tumors are strictly connected with colon cancer. Moreover, our experimental results show that the study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. Our study shows the importance of using gene sets rather than single genes for understanding the main biological processes and pathways involved in colorectal cancer. Our analysis evidences that many of the genes involved in these pathways are strongly associated to colorectal tumorigenesis. In this new perspective, the focus shifts from finding differentially expressed genes to identifying biological processes, cellular functions and pathways perturbed in the phenotypic conditions by analyzing genes co-expressed in a given pathway as a whole, taking into account the possible interactions among them and, more importantly, the correlation of their expression with the phenotypical conditions.     

Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network

One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes as disease genes for quite a long time, while the latter has been widely used to study the mechanism of diseases. With the existing protein-protein interaction data from STRING (Search Tool for the Retrieval of Interacting Genes), a weighted functional protein association network was constructed. By means of the mRMR (Maximum Relevance Minimum Redundancy) approach, six genes were identified that can distinguish the colorectal tumors and normal adjacent colonic tissues from their gene expression profiles. Meanwhile, according to the shortest path approach, we further found an additional 35 genes, of which some have been reported to be relevant to colorectal cancer and some are very likely to be relevant to it. Interestingly, the genes we identified from both the gene expression profiles and the functional protein association network have more cancer genes than the genes identified from the gene expression profiles alone. Besides, these genes also had greater functional similarity with the reported colorectal cancer genes than the genes identified from the gene expression profiles alone. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying colorectal cancer genes. It has not escaped our notice that the method can be applied to identify the genes of other diseases as well.     

Hmga1 null mouse embryonic fibroblasts display downregulation of spindle assembly checkpoint gene expression associated to nuclear and karyotypic abnormalities

The High Mobility Group A1 proteins (HMGA1) are nonhistone chromatinic proteins with a critical role in development and cancer. We have recently reported that HMGA1 proteins are able to increase the expression of spindle assembly checkpoint (SAC) genes, thus impairing SAC function and causing chromosomal instability in cancer cells. Moreover, we found a significant correlation between HMGA1 and SAC genes expression in human colon carcinomas. Here, we report that mouse embryonic fibroblasts null for the Hmga1 gene show downregulation of Bub1, Bub1b, Mad2l1 and Ttk SAC genes, and present several features of chromosomal instability, such as nuclear abnormalities, binucleation, micronuclei and karyotypic alterations. Interestingky, also MEFs carrying only one impaired Hmga1 allele present karyotypic alterations. These results indicate that HMGA1 proteins regulate SAC genes expression and, thereby, genomic stability also in embryonic cells.     

Comprehensive evaluation of isoprenoid biosynthesis regulation in Saccharomyces cerevisiae utilizing the Genome Reporter Matrix

Gene expression profiling is rapidly becoming a mainstay of functional genomic studies. However, there have been relatively few studies of how the data from expression profiles integrate with more classic approaches to examine gene expression. This study used gene expression profiling of a portion of the genome of Saccharomyces cerevisiae to explore the impact of blocks in the isoprenoid biosynthetic pathway on the expression of genes and the regulation of this pathway. Approximately 50% of the genes whose expression was altered by blocks in isoprenoid biosynthesis were genes previously known to participate in the pathway. In contrast to this simple correspondence, the regulatory patterns revealed by different blocks, and in particular by antifungal azoles, was complex in a manner not anticipated by earlier studies.     

Let-7 Prevents Early Cancer Progression by Suppressing Expression of the Embryonic Gene HMGA2

The microRNA let-7 regulates late embryonic development by suppressing expression of a number of genes such as c-myc and RAS as well as the embryonic gene high mobility group, A2 (HMGA2). We now demonstrate that HMGA2 is more efficiently targeted by let-7 than RAS. Its expression inversely correlates with the expression of let-7 in the NCI60 cells lines, and the expression of RAS does not change when amounts of let-7 that efficiently silence expression of HMGA2 are introduced into tumor cells. We did not find a difference in the expression of HMGA2 between primary ovarian cancer samples and matching metastases, suggesting that the expression of HMGA2 represents an early event during cancer progression. The late repression of HMGA2 by let-7 during embryonic development, and the early reexpression of HMGA2 during cancer development, is in line with the hypothesis that cancer development represents a case of reverse embryogenesis.     

HMGA1 positively regulates the microtubule-destabilizing protein stathmin promoting motility in TNBC cells and decreasing tumour sensitivity to paclitaxel

High Mobility Group A1 (HMGA1) is an architectural chromatin factor involved in the regulation of gene expression and a master regulator in Triple Negative Breast Cancer (TNBC). In TNBC, HMGA1 is overexpressed and coordinates a gene network that controls cellular processes involved in tumour development, progression, and metastasis formation. Here, we find that the expression of HMGA1 and of the microtubule-destabilizing protein stathmin correlates in breast cancer (BC) patients. We demonstrate that HMGA1 depletion leads to a downregulation of stathmin expression and activity on microtubules resulting in decreased TNBC cell motility. We show that this pathway is mediated by the cyclin-dependent kinase inhibitor p27^kip1 (p27). Indeed, the silencing of HMGA1 expression in TNBC cells results both in an increased p27 protein stability and p27-stathmin binding. When the expression of both HMGA1 and p27 is silenced, we observe a significant rescue in cell motility. These data, obtained in cellular models, were validated in BC patients. In fact, we find that patients with high levels of both HMGA1 and stathmin and low levels of p27 have a statistically significant lower survival probability in terms of relapse-free survival (RFS) and distant metastasis-free survival (DMFS) with respect to the patient group with low HMGA1, low stathmin, and high p27 expression levels. Finally, we show in an in vivo xenograft model that depletion of HMGA1 chemo-sensitizes tumour cells to paclitaxel, a drug that is commonly used in TNBC treatments. This study unveils a new interaction among HMGA1, p27, and stathmin that is critical in BC cell migration. Moreover, our data suggest that taxol-based treatments may be more effective in reducing the tumour burden when tumour cells express low levels of HMGA1.Subject terms: Breast cancer, Breast cancer     

Essential Role for Activation of the Polycomb Group (PcG) Protein Chromatin Silencing Pathway in Metastatic Prostate Cancer

The Polycomb-group (PcG) gene BMI1 is required for the proliferation and self-renewal of normal and leukemic stem cells. Overexpression of the BMI1 oncogene causes neoplastic transformation of lymphocytes and plays an essential role in the pathogenesis of myeloid leukemia. Another PcG protein, Ezh2, was implicated in metastatic prostate and breast cancers, suggesting that PcG pathway activation is relevant for epithelial malignancies. Whether an oncogenic role of the BMI1 and PcG pathway activation may be extended beyond leukemia and may affect progression of solid tumors as well remains unknown. Here we demonstrate that activation of the BMI1 oncogene-associated PcG pathway plays an essential role in metastatic prostate cancer, thus mechanistically linking the pathogenesis of leukemia, self-renewal of stem cells, and prostate cancer metastasis. To characterize the functional status of the PcG pathway in metastatic prostate cancer, we utilized advanced cell- and whole animal-imaging technologies, gene and protein expression profiling, stable siRNA gene targeting, and tissue microarray (TMA) analysis in relevant experimental and clinical settings. We demonstrate that in multiple experimental models of metastatic prostate cancer both the BMI1 and Ezh2 genes are amplified and gene amplification is associated with increased expression of corresponding mRNAs and proteins. For the first time, we provide images of human prostate carcinoma metastasis precursor cells isolated from the circulation which overexpress both the BMI1 and Ezh2 oncoproteins. Consistent with the PcG pathway activation hypothesis, increased BMI1 and Ezh2 expression in metastatic cancer cells is associated with elevated levels of H2AubiK119 and H3metK27 histones. Quantitative immunofluorescence colocalization analysis and expression profiling experiments documented increased the BMI1 and Ezh2 expression in clinical prostate carcinoma samples and demonstrated that high levels of BMI1 and Ezh2 expression are associated with markedly increased likelihood of therapy failure and disease relapse after radical prostatectomy. Gene-silencing analysis reveals that activation of the PcG pathway is mechanistically linked with highly malignant behavior of human prostate carcinoma cells and is essential for in vivo growth and metastasis of human prostate cancer. We conclude that the results of experimental and clinical analyses indicate important biological role of PcG pathway activation in metastatic prostate cancer. Our work suggests that the PcG pathway activation is a common oncogenic event in pathogenesis of metastatic solid tumors and provides justification for development of small molecule inhibitors of the PcG chromatin silencing pathway as a novel therapeutic modality for treatment of metastatic prostate cancer.     

Individual-specific variation of gene expression in peripheral blood leukocytes

DNA microarray technology is used to determine gene expression profiles of various cell types, especially abnormal cells, such as cancer. By contrast, relatively little attention has been given to expression profiling of normal tissues. Here we describe studies of gene expression in peripheral blood leukocytes (PBL) from normal individuals sampled multiple times over periods ranging from several weeks up to 6 months. We demonstrate stable patterns of gene expression that differ between individuals. Among the genes whose expression varies by individual is a group of genes responsive to interferon stimulation. Certain individuals ( approximately 10-20% of those tested) showed higher baseline levels and lower inducibility of these genes in response to in vitro interferon stimulation. These studies demonstrate the feasibility of using DNA microarrays to measure the variations in gene expression of PBL from different individuals in response to environmental and genetic factors.