Computational approaches in cancer multidrug resistance research: Identification of potential biomarkers, drug targets and drug-target interactions.

Like physics in the 19th century, biology and molecular biology in particular, has been fertilized and enhanced like few other scientific fields, by the incorporation of mathematical methods. In the last decades, a whole new scientific field, bioinformatics, has developed with an output of over 30,000 papers a year (Pubmed search using the keyword "bioinformatics"). Huge databases of mass throughput data have been established, with ArrayExpress alone containing more than 2.7 million assays (October 2019). Computational methods have become indispensable tools in molecular biology, particularly in one of the most challenging areas of cancer research, multidrug resistance (MDR). However, confronted with a plethora of different algorithms, approaches, and methods, the average researcher faces key questions: Which methods do exist? Which methods can be used to tackle the aims of a given study? Or, more generally, how do I use computational biology/bioinformatics to bolster my research? The current review is aimed at providing guidance to existing methods with relevance to MDR research. In particular, we provide an overview on: a) the identification of potential biomarkers using expression data; b) the prediction of treatment response by machine learning methods; c) the employment of network approaches to identify gene/protein regulatory networks and potential key players; d) the identification of drug-target interactions; e) the use of bipartite networks to identify multidrug targets; f) the identification of cellular subpopulations with the MDR phenotype; and, finally, g) the use of molecular modeling methods to guide and enhance drug discovery. This review shall serve as a guide through some of the basic concepts useful in MDR research. It shall give the reader some ideas about the possibilities in MDR research by using computational tools, and, finally, it shall provide a short overview of relevant literature.

DECO: decompose heterogeneous population cohorts for patient stratification and discovery of sample biomarkers using omic data profiling.

MOTIVATION: Patient and sample diversity is one of the main challenges when dealing with clinical cohorts in biomedical genomics studies. During last decade, several methods have been developed to identify biomarkers assigned to specific individuals or subtypes of samples. However, current methods still fail to discover markers in complex scenarios where heterogeneity or hidden phenotypical factors are present. Here, we propose a method to analyze and understand heterogeneous data avoiding classical normalization approaches of reducing or removing variation. RESULTS: DEcomposing heterogeneous Cohorts using Omic data profiling (DECO) is a method to find significant association among biological features (biomarkers) and samples (individuals) analyzing large-scale omic data. The method identifies and categorizes biomarkers of specific phenotypic conditions based on a recurrent differential analysis integrated with a non-symmetrical correspondence analysis. DECO integrates both omic data dispersion and predictor-response relationship from non-symmetrical correspondence analysis in a unique statistic (called h-statistic), allowing the identification of closely related sample categories within complex cohorts. The performance is demonstrated using simulated data and five experimental transcriptomic datasets, and comparing to seven other methods. We show DECO greatly enhances the discovery and subtle identification of biomarkers, making it especially suited for deep and accurate patient stratification. AVAILABILITY AND IMPLEMENTATION: DECO is freely available as an R package (including a practical vignette) at Bioconductor repository (http://bioconductor.org/packages/deco/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions.

BACKGROUND: Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes. RESULTS: The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal. CONCLUSIONS: PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download.

JAMI: a Java library for molecular interactions and data interoperability.

BACKGROUND: A number of different molecular interactions data download formats now exist, designed to allow access to these valuable data by diverse user groups. These formats include the PSI-XML and MITAB standard interchange formats developed by Molecular Interaction workgroup of the HUPO-PSI in addition to other, use-specific downloads produced by other resources. The onus is currently on the user to ensure that a piece of software is capable of read/writing all necessary versions of each format. This problem may increase, as data providers strive to meet ever more sophisticated user demands and data types. RESULTS: A collaboration between EMBL-EBI and the University of Cambridge has produced JAMI, a single library to unify standard molecular interaction data formats such as PSI-MI XML and PSI-MITAB. The JAMI free, open-source library enables the development of molecular interaction computational tools and pipelines without the need to produce different versions of software to read different versions of the data formats. CONCLUSION: Software and tools developed on top of the JAMI framework are able to integrate and support both PSI-MI XML and PSI-MITAB. The use of JAMI avoids the requirement to chain conversions between formats in order to reach a desired output format and prevents code and unit test duplication as the code becomes more modular. JAMI's model interfaces are abstracted from the underlying format, hiding the complexity and requirements of each data format from developers using JAMI as a library.

MicroRNA (miR)-203 and miR-205 expression patterns identify subgroups of prognosis in cutaneous squamous cell carcinoma.

BACKGROUND: Cutaneous squamous cell carcinoma (CSCC) is the second most widespread cancer in humans and its incidence is rising. These tumours can evolve as diseases of poor prognosis, and therefore it is important to identify new markers to better predict its clinical evolution. OBJECTIVES: We aimed to identify the expression pattern of microRNAs (miRNAs or miRs) at different stages of skin cancer progression in a panel of murine skin cancer cell lines. Owing to the increasing importance of miRNAs in the pathogenesis of cancer, we considered the possibility that miRNAs could help to define the prognosis of CSCC and aimed to evaluate the potential use of miR-203 and miR-205 as biomarkers of prognosis in human tumours. METHODS: Seventy-nine human primary CSCCs were collected at the University Hospital of Salamanca in Spain. We identified differential miRNA expression patterns at different stages of CSCC progression in a well-established panel of murine skin cancer cell lines, and then selected miR-205 and miR-203 to evaluate their association with the clinical prognosis and evolution of human CSCC. RESULTS: miR-205 was expressed in tumours with pathological features recognized as indicators of poor prognosis such as desmoplasia, perineural invasion and infiltrative growth pattern. miR-205 was mainly expressed in undifferentiated areas and in the invasion front, and was associated with both local recurrence and the development of general clinical events of poor evolution. miR-205 expression was an independent variable selected to predict events of poor clinical evolution using the multinomial logistic regression model described in this study. In contrast, miR-203 was mainly expressed in tumours exhibiting the characteristics associated with a good prognosis, was mainly present in well-differentiated zones, and rarely expressed in the invasion front. Therefore, the expression and associations of miR-205 and miR-203 were mostly mutually exclusive. Finally, using a logistic biplot we identified three clusters of patients with differential prognosis based on miR-203 and miR-205 expression, and pathological tumour features. CONCLUSIONS: miR-205 and miR-203 tended to exhibit mutually exclusive expression patterns in human CSCC. This work highlights the utility of miR-205 and miR-203 as prognostic markers in CSCC.

miRNA cargo within exosome-like vesicle transfer influences metastatic bone colonization.

Bone metastasis represents one of the most deleterious clinical consequences arising in the context of many solid tumors. Severe osteolysis results from tumor cell colonization of the bone compartment, a process which entails reciprocal exchange of soluble signals between tumor cells and their osseous microenvironment. Recent evidence indicates that tumor-intrinsic miRNAs are pleiotropic regulators of gene expression. But they are also frequently released in exosome-like vesicles (ELV). Yet the functional relevance of the transference of tumor-derived ELV and their miRNA cargo to the extracellular milieu during osseous colonization is unknown. Comparative transcriptomic profiling using an in vivo murine model of bone metastasis identified a repressed miRNA signature associated with high prometastatic activity. Forced expression of single miRNAs identified miR-192 that markedly appeased osseous metastasis in vivo, as shown by X-ray, bioluminescence imaging and microCT scans. Histological examination of metastatic lesions revealed impaired tumor-induced angiogenesis in vivo, an effect that was associated in vitro with decreased hallmarks of angiogenesis. Isolation and characterization of ELV by flow cytometry, Western blot analysis, transmission electron microscopy and nanoparticle tracking analysis revealed the ELV cargo enrichment in miR-192. Consistent with these findings, fluorescent labeled miR-192-enriched-ELV showed the in vitro transfer and release of miR-192 in target endothelial cells and abrogation of the angiogenic program by repression of proangiogenic IL-8, ICAM and CXCL1. Moreover, in vivo infusion of fluorescent labeled ELV efficiently targeted cells of the osseous compartment. Furthermore, treatment with miR-192 enriched ELV in a model of in vivo bone metastasis pre-conditioned osseous milieu and impaired tumor-induced angiogenesis, thereby reducing the metastatic burden and tumor colonization. Changes in the miRNA-cargo content within ELV represent a novel mechanism heavily influencing bone metastatic colonization, which is most likely relevant in other target organs. Mechanistic mimicry of this phenomenon by synthetic nanoparticles could eventually emerge as a novel therapeutic approach.

A gene signature of bone metastatic colonization sensitizes for tumor-induced osteolysis and predicts survival in lung cancer.

Bone metastasis of lung adenocarcinoma (AC) is a frequent complication of advanced disease. The purpose of this study was to identify key mediators conferring robust prometastatic activity with clinical significance. We isolated highly metastatic subpopulations (HMS) using a previously described in vivo model of lung AC bone metastasis. We performed transcriptomic profiling of HMS and stringent bioinformatics filtering. Functional validation was assessed by overexpression and lentiviral silencing of single, double and triple combination in vivo and in vitro. We identified HDAC4, PITX1 and ROBO1 that decreased bone metastatic ability after their simultaneous abrogation. These effects were solely linked to defects in osseous colonization. The molecular mechanisms related to bone colonization were mediated by non-cell autonomous effects that include the following: (1) a marked decrease in osteoclastogenic activity in vitro and in vivo, an effect associated with reduced pro-osteoclastogenic cytokines IL-11 and PTHrP expression levels, as well as decreased in vitro expression of stromal rankl in conditions mimicking tumor-stromal interactions; (2) an abrogated response to TGF-ß signaling by decreased phosphorylation and levels of Smad2/3 in tumor cells and (3) an impaired metalloproteolytic activity in vitro. Interestingly, coexpression of HDAC4 and PITX1 conferred high prometastatic activity in vivo. Further, levels of both genes correlated with patients at higher risk of metastasis in a clinical lung AC data set and with a poorer clinical outcome. These findings provide functional and clinical evidence that this metastatic subset is an important determinant of osseous colonization. These data suggest novel therapeutic targets to effectively block lung AC bone metastasis.

Genome-wide profiling of methylation identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes.

Gene expression profiling signatures may be used to classify the subtypes of Myelodysplastic syndrome (MDS) patients. However, there are few reports on the global methylation status in MDS. The integration of genome-wide epigenetic regulatory marks with gene expression levels would provide additional information regarding the biological differences between MDS and healthy controls. Gene expression and methylation status were measured using high-density microarrays. A total of 552 differentially methylated CpG loci were identified as being present in low-risk MDS; hypermethylated genes were more frequent than hypomethylated genes. In addition, mRNA expression profiling identified 1005 genes that significantly differed between low-risk MDS and the control group. Integrative analysis of the epigenetic and expression profiles revealed that 66.7% of the hypermethylated genes were underexpressed in low-risk MDS cases. Gene network analysis revealed molecular mechanisms associated with the low-risk MDS group, including altered apoptosis pathways. The two key apoptotic genes BCL2 and ETS1 were identified as silenced genes. In addition, the immune response and micro RNA biogenesis were affected by the hypermethylation and underexpression of IL27RA and DICER1. Our integrative analysis revealed that aberrant epigenetic regulation is a hallmark of low-risk MDS patients and could have a central role in these diseases.

Identification of a novel recurrent gain on 20q13 in chronic lymphocytic leukemia by array CGH and gene expression profiling.

BACKGROUND: The presence of genetic changes is a hallmark of chronic lymphocytic leukemia (CLL). The most common cytogenetic abnormalities with independent prognostic significance in CLL are 13q14, ATM and TP53 deletions and trisomy 12. However, CLL displays a great genetic and biological heterogeneity. The aim of this study was to analyze the genomic imbalances in CLL cytogenetic subsets from both genomic and gene expression perspectives to identify new recurrent alterations. PATIENTS AND METHODS: The genomic imbalances and expression levels of 67 patients were analyzed. The novel recurrent abnormalities detected with bacterial artificial chromosome array were confirmed by FISH and oligonucleotide microarrays. In all cases, gene expression profiling was assessed. RESULTS: Copy number alterations were identified in 75% of cases. Overall, the results confirmed FISH studies for the regions frequently involved in CLL and also defined a new recurrent gain on chromosome 20q13.12, in 19% (13/67) of the CLL patients. Oligonucleotide expression correlated with the regions of loss or gain of genomic material, suggesting that the changes in gene expression are related to alterations in copy number. CONCLUSION: Our study demonstrates the presence of a recurrent gain in 20q13.12 associated with overexpression of the genes located in this region, in CLL cytogenetic subgroups.

Segmentation of genomic and transcriptomic microarrays data reveals major correlation between DNA copy number aberrations and gene-loci expression.

DNA copy number aberrations (CNAs) are genetic alterations common in cancer cells. Their transcriptional consequences are still poorly understood. Based on the fact that DNA copy number (CN) is highly correlated with the genomic position, we have applied a segmentation algorithm to gene expression (GE) to explore its relation with CN. We have found a strong correlation between segmented CN (sCN) and segmented GE (sGE), corroborating that CNAs have clear effects on genome-wide expression. We have found out that most of the recurrent regions of sGE are common to those obtained from sCN analysis. Results for two cancer datasets confirm the known targets of aberrations and provide new candidates to study. The suggested methodology allows to find recurrent aberrations specific to sGE, revealing loci where the expression of the genes is independent from their CNs. R code and additional files are available as supplementary material.

Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression profiling.

Specific microRNA (miRNA) signatures have been associated with different cytogenetic subtypes in acute leukemias. This finding prompted us to investigate potential associations between genetic abnormalities in multiple myeloma (MM) and singular miRNA expression profiles. Moreover, global gene expression profiling was also analyzed to find correlated miRNA gene expression and select miRNA target genes that show such correlation. For this purpose, we analyzed the expression level of 365 miRNAs and the gene expression profiling in 60 newly diagnosed MM patients, selected to represent the most relevant recurrent genetic abnormalities. Supervised analysis showed significantly deregulated miRNAs in the different cytogenetic subtypes as compared with normal PC. It is interesting to note that miR-1 and miR-133a clustered on the same chromosomal loci, were specifically overexpressed in the cases with t(14;16). The analysis of the relationship between miRNA expression and their respective target genes showed a conserved inverse correlation between several miRNAs deregulated in MM cells and CCND2 expression level. These results illustrate, for the first time, that miRNA expression pattern in MM is associated with genetic abnormalities, and that the correlation of the expression profile of miRNA and their putative mRNA targets is useful to find statistically significant protein-coding genes in MM pathogenesis associated with changes in specific miRNAs.

Structural domain-domain interactions: assessment and comparison with protein-protein interaction data to improve the interactome.

Assessment and improvement of the reliability of protein-protein interaction (ppi) data is critical for the progress of the currently active research on interactomes. Some interesting questions in this respect are: How three-dimensional (3D) protein structural data is present in known ppi data?, and How this kind of information can be used to validate and improve the interactomes? To address this problem, analysis and unification of six structural domain-domain interaction (sddi) datasets is presented; followed by a comparative study of these sddi data in three ppi reference sets produced at different levels of confidence. The results show that protein structural and interactomic data are partially complementary and that a larger proportion of structural information is observed in more confident interactomes. We also present, focused on the human interactome, an analysis of the domains that are more frequently present in: (i) an interactome based on validation by at least two experimental methods versus (ii) another interactome based on validation by 3D structural interaction data. These results allow to distinguish between domain pairs associated to protein interactions supported by 3D structures and domain pairs that at present are not supported by structural information. The domain pairs exclusive of interactions without associated 3D data reveal interacting conserved modules that are probably flexible, disordered, and difficult to crystallize; and which are often found in proteins involved in signaling pathways and DNA processing.

Interleukin-12 inhibits liver-specific drug-inducible systems in vivo.

Drug-inducible systems allow modulation of the duration and intensity of cytokine expression in liver immuno-based gene therapy protocols. However, the biological activity of the transgene may influence their function. We have analyzed the kinetics of interleukin-12 (IL-12) expression controlled by the doxycycline (Dox)- and the mifepristone (Mif)-dependent systems using two long-term expressing vectors directed to liver: a plasmid administered by hydrodynamic injection and a high-capacity adenoviral vector. Daily administration of Dox or Mif was associated with a progressive loss of inducibility and a decrease of murine IL-12 production. This inhibition occurred at the transcriptional level and was probably caused by an interferon (IFN)-gamma-mediated downmodulation of liver-specific promoters that control the expression of transactivators in these systems. Genome-wide expression microarrays studies revealed a parallel downregulation of liver-specific genes in mice overexpressing murine IL-12. However, a promoter naturally induced by IL-12 was also inhibited by this cytokine when placed in a plasmid vector. Interestingly, treatment with sodium butyrate, a class I/II histone deacetylase inhibitor, was able to rescue liver-specific promoter activity solely in the vector. We conclude that biologically active IL-12 can transiently inhibit the function of drug-inducible systems in non-integrative DNA vectors by reducing promoter activity, probably through IFN-gamma and protein deacetylation-dependent mechanisms.

Laser microdissection and microarray analysis of the hippocampus of Ras-GRF1 knockout mice reveals gene expression changes affecting signal transduction pathways related to memory and learning.

We used manual macrodissection or laser capture microdissection (LCM) to isolate tissue sections of the hippocampus area of Ras-GRF1 wild type and knockout mice brains, and analyzed their transcriptional patterns using commercial oligonucleotide microarrays. Comparison between the transcriptomes of macrodissected and microdissected samples showed that the LCM samples allowed detection of significantly higher numbers of differentially expressed genes, with higher statistical rates of significance. These results validate LCM as a reliable technique for in vivo genomic studies in the brain hippocampus, where contamination by surrounding areas (not expressing Ras-GRF1) increases background noise and impairs identification of differentially expressed genes. Comparison between wild type and knockout LCM hippocampus samples revealed that Ras-GRF1 elimination caused significant gene expression changes, mostly affecting signal transduction and related neural processes. The list of 36 most differentially expressed genes included loci concerned mainly with Ras/G protein signaling and cytoskeletal organization (i.e. 14-3-3gamma/zeta, Kcnj6, Clasp2) or related, cross-talking pathways (i.e. jag2, decorin, strap). Consistent with the phenotypes shown by Ras-GRF1 knockout mice, many of these differentially expressed genes play functional roles in processes such as sensory development and function (i.e. Sptlc1, antiquitin, jag2) and/or neurological development/neurodegeneration processes affecting memory and learning. Indeed, potential links to neurodegenerative diseases such as Alzheimer disease (AD) or Creutzfeldt-Jacobs disease (CJD), have been reported for a number of differentially expressed genes identified in this study (Ptma, Aebp2, Clasp2, Hebp1, 14-3-3gamma/zeta, Csnk1delta, etc.). These data, together with the previously described role of IRS and insulin (known Ras-GRF1 activators) in AD, warrant further investigation of a potential functional link of Ras-GRF1 to neurodegenerative processes.

Gene expression profiling of B lymphocytes and plasma cells from Waldenström's macroglobulinemia: comparison with expression patterns of the same cell counterparts from chronic lymphocytic leukemia, multiple myeloma and normal individuals.

The tumoral clone of Waldenström's macroglobulinemia (WM) shows a wide morphological heterogeneity, which ranges from B lymphocytes (BL) to plasma cells (PC). By means of genome-wide expression profiling we have been able to identify genes exclusively deregulated in BL and PC from WM, but with a similar expression pattern in their corresponding cell counterparts from chronic lymphocytic leukemia (CLL) and multiple myeloma (MM), as well as normal individuals. The differentially expressed genes have important functions in B-cell differentiation and oncogenesis. Thus, two of the genes downregulated in WM-BL were IL4R, which plays a relevant role in CLL B-cell survival, and BACH2, which participates in the development of class-switched PC. Interestingly, one of the upregulated genes in WM-BL was IL6. A set of four genes was able to discriminate clonal BL from WM and CLL: LEF1 (WNT/beta-catenin pathway), MARCKS, ATXN1 and FMOD. We also found deregulation of genes involved in plasma cell differentiation such as PAX5, which was overexpressed in WM-PC, and IRF4 and BLIMP1, which were underexpressed. In addition, three of the target genes activated by PAX5 - CD79, BLNK and SYK - were upregulated in WM-PC. In summary, these results indicate that both PC and BL from WM are genetically different from the MM and CLL cell counterpart.

Transcriptional networks of knockout cell lines identify functional specificities of H-Ras and N-Ras: significant involvement of N-Ras in biotic and defense responses.

We characterized differential gene expression profiles of fibroblast cell lines harboring single or double-homozygous null mutations in H-ras and N-ras. Whereas the expression level of the individual H-, N- and K-ras genes appeared unaffected by the presence or absence of the other ras loci, significant differences were observed between the expression profiles of cells missing N-ras and/or H-ras. Absence of N-ras produced much stronger effects than absence of H-ras over the profile of the cellular transcriptome. N-ras(-/-) and H-ras(-/-) fibroblasts displayed rather antagonistic expression profiles and the transcriptome of H-ras(-/-) cells was significantly closer to that of wild-type fibroblasts than to that of N-ras(-/-) cells. Classifying all differentially expressed genes into functional categories suggested specific roles for H-Ras and N-Ras. It was particularly striking in N-ras(-/-) cells the upregulation of a remarkable number of immunity-related genes, as well as of several loci involved in apoptosis. Reverse-phase protein array assays demonstrated in the same N-ras(-/-) cells the overexpression and nuclear migration of tyrosine phosphorylated signal transducer and activator of transcription 1 (Stat1) which was concomitant with transcriptional activation mediated by interferon-stimulated response elements. Significantly enhanced numbers of apoptotic cells were also detected in cultures of N-ras(-/-) cells. Our data support the notion that different Ras isoforms play functionally distinct cellular roles and indicate that N-Ras is significantly involved in immune modulation/host defense and apoptotic responses.

[Bone metastases]. / Las metástasis óseas del cáncer.

Bone metastases represent a devastating clinical problem in the most frequent neoplasies, especially in multiple myeloma, tumours breast, prostate and lung. The consequences include pain which is refractory to conventional analgesics, osteolysis often leading to bone-marrow compression and pathological fractures, and metabolic disorders. Recent advances in diagnosis using imaging techniques as well as different biochemical techniques have helped accurate diagnosis and follow-up. The increase in survival has improved through a multimodal approach combining, inhibition of osteolysis, with prophylactic orthopaedic surgery and radiation therapy. Recent advances in basic research have determined the molecular metastatic that can predict its proclivity to metastasize. Basic research will improve understanding of the basic mechanisms and lead to the clarification of molecular targets that will help in the development of medicines capable of preventing, decreasing or blocking the metastatic process.

Algorithm to find gene expression profiles of deregulation and identify families of disease-altered genes.

MOTIVATION: Alteration of gene expression often results in up- or down-regulated genes and the most common analysis strategies look for such differentially expressed genes. However, molecular disease mechanisms typically constitute abnormalities in the regulation of genes producing strong alterations in the expression levels. The search for such deregulation states in the genomic expression profiles will help to identify disease-altered genes better. RESULTS: We have developed an algorithm that searches for the genes which present a significant alteration in the variability of their expression profiles, by comparing an altered state with a control state. The algorithm provides groups of genes and assigns a statistical measure of significance to each group of genes selected. The method also includes a prefilter tool to select genes with a threshold of differential expression that can be set by the user ad casum. The method is evaluated using an experimental set of microarrays of human control and cancer samples from patients with acute promyelocytic leukemia.

Calcium-dependent conformational change and thermal stability of the isolated PsbO protein detected by FTIR spectroscopy.

The structure and function of the photosystem II PsbO extrinsic protein is under intense research, being an essential part of the biomolecular engine that carries out water oxidation and oxygen production. This paper presents a structural analysis of the isolated PsbO protein by FTIR spectroscopy, reporting detailed secondary structure quantification and changes in the secondary structure content of the protein attributed to the effect of calcium (Ca(2+)). Measurements in H(2)O and D(2)O have allowed us to see the effect of calcium on the conformation of the protein. The results indicate that (i) the protein presents a major content of beta-structure (i.e., beta-sheet, beta-strands, beta-turns) as detected by the infrared bands at 1624-1625, 1678-1679, 1688-1689 cm(-1), which account for about 38% in water and 33% in heavy water, in the presence of calcium; and (ii) the amount of this beta-structure fraction increases 7-10% in the absence of calcium, with a concomitant decrease in loops and nonordered structure. The thermal denaturation profile of the protein in the presence of calcium showed low stability with T(m) approximately 56 degrees C. This profile also shows a second phase of denaturation above 60 degrees C and the appearance of aggregation signals above 70 degrees C. Our observations indicate that calcium is able to modify the conformation of the protein at least in solution and confirm that PsbO is mainly a beta-protein where beta-sheet is the major ordered secondary structure element of the protein core.