Networking of differentially expressed genes in human cancer cells resistant to methotrexate

BACKGROUND: The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). METHODS: Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. RESULTS: Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. CONCLUSIONS: Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX.

Networking of differentially expressed genes in human cancer cells resistant to methotrexate

BACKGROUND: The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). METHODS: Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. RESULTS: Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. CONCLUSIONS: Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX.

Passive modernization? the new human development index and its components in Italy’s regions (1871-2007)

The article presents and discusses estimates of social and economic indicators for Italy’s regions in benchmark years roughly from Unification to the present day: life expectancy, education, GDP per capita at purchasing power parity, and the new Human Development Index (HDI). A broad interpretative hypothesis, based on the distinction between passive and active modernization, is proposed to account for the evolution of regional imbalances over the long-run. In the lack of active modernization, Southern Italy converged thanks to passive modernization, i.e., State intervention: however, this was more effective in life expectancy, less successful in education, expensive and as a whole ineffective in GDP. As a consequence, convergence in the HDI occurred from the late XIX century to the 1970s, but came to a sudden halt in the last decades of the XX century.

Bilinear models for spatio-temporal point distribution analysis: application to extrapolation of left ventricular, biventricular and whole heart cardiac dynamics

In this work we describe the usage of bilinear statistical models as a means of factoring the shape variability into two components attributed to inter-subject variation and to the intrinsic dynamics of the human heart. We show that it is feasible to reconstruct the shape of the heart at discrete points in the cardiac cycle. Provided we are given a small number of shape instances representing the same heart atdifferent points in the same cycle, we can use the bilinearmodel to establish this. Using a temporal and a spatial alignment step in the preprocessing of the shapes, around half of the reconstruction errors were on the order of the axial image resolution of 2 mm, and over 90% was within 3.5 mm. From this, weconclude that the dynamics were indeed separated from theinter-subject variability in our dataset.

Insulin degradation by adipose tissue is increased in human obesity

White adipose tissue samples from obese and lean patients were used for the estimation ofinsulin protease and insulin:glutathione transhydrogenase using 1251-labeled insulin. There was no activity detected in the absence of reduced glutathione, which indicates that insulin is cleaved in human adipose "tissue through reduction of the disulfide bridge between the chains. O bese patients showed higher transhydrogenase activity (per U tissue protein wt, per U tissue wt, and in the total adipose tissue mass) than the lean group. There is a significant correlation between the activity per U tissue wt, and protein and total activity in the whole adipose tissue with respect to body mass index, with a higher activity in obese patients. The potential ofinsulin cleavage by adipose tissue in obese patients was a mean 5.6-fold higher than that in controla. The coexistence of high insulinemia and high cleavage capability implies that insulin secretion and turnover are increased in the o bese. Thus, white adipose tissue may be crucial in the control of energy availability through modulation ofinsulin cleavage.

Different effects of hyperlipidic diets in human lactation and adulthood: growth versus the development of obesity

After birth, the body shifts from glucose as primary energy substrate to milk-derived fats, with sugars from lactose taking a secondary place. At weaning, glucose recovers its primogeniture and dietary fat role decreases. In spite of human temporary adaptation to a high-fat (and sugars and protein) diet during lactation, the ability to thrive on this type of diet is lost irreversibly after weaning. We could not revert too the lactating period metabolic setting because of different proportions of brain/muscle metabolism in the total energy budget, lower thermogenesis needs and capabilities, and absence of significant growth in adults. A key reason for change was the limited availability of foods with high energy content at weaning and during the whole adult life of our ancestors, which physiological adaptations remain practically unchanged in our present-day bodies. Humans have evolved to survive with relatively poor diets interspersed by bouts of scarcity and abundance. Today diets in many societies are largely made up from choice foods, responding to our deeply ingrained desire for fats, protein, sugars, salt etc. Consequently our diets are not well adjusted to our physiological needs/adaptations but mainly to our tastes (another adaptation to periodic scarcity), and thus are rich in energy roughly comparable to milk. However, most adult humans cannot process the food ingested in excess because our cortical-derived craving overrides the mechanisms controlling appetite. This is produced not because we lack the biochemical mechanisms to use this energy, but because we are unprepared for excess, and wholly adapted to survive scarcity. The thrifty mechanisms compound the effects of excess nutrients and damage the control of energy metabolism, developing a pathologic state. As a consequence, an overflow of energy is generated and the disease of plenty develops.

PGC-1α induces mitochondrial and myokine transcriptional programs and lipid droplet and glycogen accumulation in cultured human skeletal muscle cells

The transcriptional coactivator peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC-1α) is a chief activator of mitochondrial and metabolic programs and protects against atrophy in skeletal muscle (skm). Here we tested whether PGC-1α overexpression could restructure the transcriptome and metabolism of primary cultured human skm cells, which display a phenotype that resembles the atrophic phenotype. An oligonucleotide microarray analysis was used to reveal the effects of PGC-1α on the whole transcriptome. Fifty-three different genes showed altered expression in response to PGC-1α: 42 upregulated and 11 downregulated. The main gene ontologies (GO) associated with the upregulated genes were mitochondrial components and processes and this was linked with an increase in COX activity, an indicator of mitochondrial content. Furthermore, PGC-1α enhanced mitochondrial oxidation of palmitate and lactate to CO2, but not glucose oxidation. The other most significantly associated GOs for the upregulated genes were chemotaxis and cytokine activity, and several cytokines, including IL-8/CXCL8, CXCL6, CCL5 and CCL8, were within the most highly induced genes. Indeed, PGC-1α highly increased IL-8 cell protein content. The most upregulated gene was PVALB, which is related to calcium signaling. Potential metabolic regulators of fatty acid and glucose storage were among mainly regulated genes. The mRNA and protein level of FITM1/FIT1, which enhances the formation of lipid droplets, was raised by PGC-1α, while in oleate-incubated cells PGC-1α increased the number of smaller lipid droplets and modestly triglyceride levels, compared to controls. CALM1, the calcium-modulated δ subunit of phosphorylase kinase, was downregulated by PGC-1α, while glycogen phosphorylase was inactivated and glycogen storage was increased by PGC-1α. In conclusion, of the metabolic transcriptome deficiencies of cultured skm cells, PGC-1α rescued the expression of genes encoding mitochondrial proteins and FITM1. Several myokine genes, including IL-8 and CCL5, which are known to be constitutively expressed in human skm cells, were induced by PGC-1α.

Reconstructing native American migrations from whole-genome and whole-exome data.

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern American ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.

Finding and characterizing Partially Methylated Domains in human haematopoietic cells

DNA cytosine methylation has been demonstrated to be a central epigenetic modification that has essential roles in a myriad of cellular processes. Some examples of these include gene regulation, DNA-protein interactions, cellular differentiation, X-inactivation, maintenance of genome integrity by suppressing transposable elements and viruses, embryogenesis, genomic imprinting and tumourigenesis. This list is increasingly growing thanks to recent advances in genome-wide technologies, like Whole Genome Bisulfite Sequencing (WGBS-Seq). The development of this technology in research has allowed the identification of new features of the DNA methylation landscape that was not possible using previous technologies, like Partially Methylated Domains (PMDs). PMDs have been found in several cell lines, as well as in both healthy and cancer primary samples. They have been described as regions with high variability in methylation levels across individual CpG sites and intermediate methylation levels on average with respect to the genome. Here, we performed an extensive search of PMDs in a big dataset of different haematopoietic primary cells from both myeloid and lymphoid lineages. We found and characterized significant PMDs in plasma B cells, confirming that PMDs are a phenomenon that is restricted to certain differentiated cells. Additionally, we found loci aberrantly hypomethylated in a myeloma sample which overlapped with plasma B cell PMDs. Genome-wide comparison of the myeloma and plasma B cell sample revealed that this is probably also the case for other loci.