as a possible novel predictive biomarker of chemotherapy response and death in pediatric B-cell ALL.

Although B-cell acute lymphoblastic leukemia (B-cell ALL) survival rates have improved in recent years, Hispanic children continue to have poorer survival rates. There are few tools available to identify at the time of diagnosis whether the patient will respond to induction therapy. Our goal was to identify predictive biomarkers of treatment response, which could also serve as prognostic biomarkers of death, by identifying methylated and differentially expressed genes between patients with positive minimal residual disease (MRD+) and negative minimal residual disease (MRD-).

Long Noncoding RNA TALAM1 Is a Transcriptional Target of the RUNX2 Transcription Factor in Lung Adenocarcinoma.

Background: Lung cancer is the leading cause of cancer death worldwide. It has been reported that genetic and epigenetic factors play a crucial role in the onset and evolution of lung cancer. Previous reports have shown that essential transcription factors in embryonic development contribute to this pathology.

Lung Cancer Gene Regulatory Network of Transcription Factors Related to the Hallmarks of Cancer.

The transcriptomic analysis of microarray and RNA-Seq datasets followed our own bioinformatic pipeline to identify a transcriptional regulatory network of lung cancer. Twenty-six transcription factors are dysregulated and co-expressed in most of the lung cancer and pulmonary arterial hypertension datasets, which makes them the most frequently dysregulated transcription factors. Co-expression, gene regulatory, coregulatory, and transcriptional regulatory networks, along with fibration symmetries, were constructed to identify common connection patterns, alignments, main regulators, and target genes in order to analyze transcription factor complex formation, as well as its synchronized co-expression patterns in every type of lung cancer.

Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells.

The use of a new bioinformatics pipeline allowed the identification of deregulated transcription factors (TFs) coexpressed in lung cancer that could become biomarkers of tumor establishment and progression. A gene regulatory network (GRN) of lung cancer was created with the normalized gene expression levels of differentially expressed genes (DEGs) from the microarray dataset GSE19804. Moreover, coregulatory and transcriptional regulatory network (TRN) analyses were performed for the main regulators identified in the GRN analysis.

Prog-Plot - a visual method to determine functional relationships for false discovery rate regression methods.

Multiple test corrections are a fundamental step in the analysis of differentially expressed genes, as the number of tests performed would otherwise inflate the false discovery rate (FDR). Recent methods for P-value correction involve a regression model in order to include covariates that are informative of the power of the test. Here, we present Progressive proportions plot (Prog-Plot), a visual tool to identify the functional relationship between the covariate and the proportion of P-values consistent with the null hypothesis.

Uncovering anthocyanin diversity in potato landraces (Solanum tuberosum L. Phureja) using RNA-seq.

Potato (Solanum tuberosum L.) is the third largest source of antioxidants in the human diet, after maize and tomato. Potato landraces have particularly diverse contents of antioxidant compounds such as anthocyanins.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis.

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer.

Identification of Two Exosomal miRNAs in Circulating Blood of Cancer Patients by Using Integrative Transcriptome and Network Analysis.

Exosomes carry molecules of great biological and clinical interest, such as miRNAs. The contents of exosomes vary between healthy controls and cancer patients. Therefore, miRNAs and other molecules transported in exosomes are considered a potential source of diagnostic and prognostic biomarkers in cancer.

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions.

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods.

Coexpression network analysis identified lncRNAs-mRNAs with potential relevance in African ancestry prostate cancer.

Aim: This study aims to investigate similarities and differences using lncRNA and mRNA coexpression network analysis in African ancestry (AA) and European ancestry (EA) among prostate cancer (PCa) patients.

Methods: We performed weighted gene coexpression network analysis of the expression from 49 of AA and 49 of EA to identify lncRNAs-mRNAs.

Results: 27 lncRNAs and 36 mRNAs were highly expressed in patients of AA.

Temporal Changes of the Epiphytic Bacteria Community From the Marine Macroalga Ulva lactuca (Santa Marta, Colombian-Caribbean).

Microbial communities live on macroalgal surfaces. The identity and abundance of the bacteria making these epiphytic communities depend on the macroalgal host and the environmental conditions. Macroalgae rely on epiphytic bacteria for basic functions (spore settlement, morphogenesis, growth, and protection against pathogens).

Identification of common differentially expressed genes in Turner (45,X) and Klinefelter (47,XXY) syndromes using bioinformatics analysis.

Background: Analysis of patients with chromosomal abnormalities, including Turner syndrome and Klinefelter syndrome, has highlighted the importance of X-linked gene dosage as a contributing factor for disease susceptibility. Escape from X-inactivation and X-linked imprinting can result in transcriptional differences between normal men and women as well as in patients with sex chromosome abnormalities.

Objective: To identify differentially expressed genes among patients with Turner (45,X) and Klinefelter (46,XXY) syndrome using bioinformatics analysis.

Identification of candidate miRNAs in early-onset and late-onset prostate cancer by network analysis.

The incidence of patients under 55 years old diagnosed with Prostate Cancer (EO-PCa) has increased during recent years. The molecular biology of PCa cancer in this group of patients remains unclear. Here, we applied weighted gene coexpression network analysis of the expression of miRNAs from 24 EO-PCa patients (38-45 years) and 25 late-onset PCa patients (LO-PCa, 71-74 years) to identify key miRNAs in EO-PCa patients.

Joint Transcriptomic Analysis of Lung Cancer and Other Lung Diseases.

Epidemiological and clinical evidence points cancer comorbidity with pulmonary chronic disease. The acquisition of some hallmarks of cancer by cells affected with lung pathologies as a cell adaptive mechanism to a shear stress, suggests that could be associated with the establishment of tumoral processes. To propose a bioinformatic pipeline for the identification of all deregulated genes and the transcriptional regulators (TFs) that are coexpressed during lung cancer establishment, and therefore could be important for the acquisition of the hallmarks of cancer.

Multivariate Method for Inferential Identification of Differentially Expressed Genes in Gene Expression Experiments.

Microarray technology is widely recognized as one of the most important tools when it comes to understanding genetic expression in biological processes. In light of the thousands of gene expression level measurements (including measurements across a number of conditions), identifying differentially expressed genes necessarily implies data mining or large-scale multiple testing procedures. To date, advances with regard to this field have been multivariate-descriptive or inferential-univariate in nature and therefore have important limitations regarding the biological validity of detected genes.

RUNX family: Oncogenes or tumor suppressors (Review).

Runt‑related transcription factor (RUNX) proteins belong to a transcription factors family known as master regulators of important embryonic developmental programs. In the last decade, the whole family has been implicated in the regulation of different oncogenic processes and signaling pathways associated with cancer. Furthermore, a suppressor tumor function has been also reported, suggesting the RUNX family serves key role in all different types of cancer.

Gene expression analysis in peripheral blood cells of patients with hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC): identification of NRF2 pathway activation.

Hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC) is a very rare disease that is inherited in an autosomal dominant manner. Affected patients may develop from cutaneous and uterine leiomyomas to type 2 papillary renal cell carcinoma (Schmidt and Linehan, Int J Nephrol Renovasc Dis 7:253-260, 2014). HLRCC is caused by germline mutations in the FH gene, which produces the fumarate hydratase protein that participates in the tricarboxylic acid cycle during the conversion of fumarate to malate.

[Influence of lifestyle, diet and vitamin D on atopy in a population of Afro-descendant Colombian children].

Background: Allergic conditions have shown an increase in the past few decades. Hygiene, changes in lifestyle, diet and vitamin D have been blamed for this increase.

Objective: To determine the role of environment, diet and vitamin D in atopic diseases in a population of Colombian Afro-descendant children.

Co-expressed miRNAs in gastric adenocarcinoma.

Co-expression networks may provide insights into the patterns of molecular interactions that underlie cellular processes. To obtain a better understanding of miRNA expression patterns in gastric adenocarcinoma and to provide markers that can be associated with histopathological findings, we performed weighted gene correlation network analysis (WGCNA) and compare it with a supervised analysis. Integrative analysis of target predictions and miRNA expression profiles in gastric cancer samples was also performed.

Regulatory network reconstruction reveals genes with prognostic value for chronic lymphocytic leukemia.

Background: The clinical course of chronic lymphocytic leukemia (CLL) is highly variable; some patients follow an indolent course, but others progress to a more advanced stage. The mutational status of rearranged immunoglobulin heavy chain variable (IGVH) genes in CLL is a feature that is widely recognized for dividing patients into groups that are related to their prognoses. However, the regulatory programs associated with the IGVH statuses are poorly understood, and markers that can precisely predict survival outcomes have yet to be identified.

Draft genome sequences of clostridium strains native to Colombia with the potential to produce solvents.

Genomes from four Clostridium sp. strains considered to be mesophilic anaerobic bacteria, isolated from crop soil in Colombia, with a strong potential to produce alcohols like 1,3-propanediol, were analyzed. We present the draft genome of these strains, which will be useful for developing genetic engineering strategies.

Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

Gene expression data (microarrays and RNA-sequencing data) as well as other kinds of genomic data can be extracted from publicly available genomic data. Here, we explain how to apply multivariate cluster and classification methods on gene expression data. These methods have become very popular and are implemented in freely available software in order to predict the participation of gene products in a specific functional category of interest.

Algorithm for the Construction of a Global Enzymatic Network to be Used for Gene Network Reconstruction.

Relationships between genes are best represented using networks constructed from information of different types, with metabolic information being the most valuable and widely used for genetic network reconstruction. Other types of information are usually also available, and it would be desirable to systematically include them in algorithms for network reconstruction. Here, we present an algorithm to construct a global metabolic network that uses all available enzymatic and metabolic information about the organism.