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MicroRNAs play important roles in the development of many complex diseases. Because of their importance, the analysis of signaling pathways including miRNA interactions holds the potential for unveiling the mechanisms underlying such diseases. However, current signaling pathway databases are limited to interactions between genes and ignore miRNAs. Here, we use the information on miRNA targets to build a database of miRNA-augmented pathways (mirAP), and we show its application in the contexts of integrative pathway analysis and disease subtyping. Our miRNA-mRNA integrative pathway analysis pipeline incorporates a topology-aware approach that we previously implemented. Our integrative disease subtyping pipeline takes into account survival data, gene and miRNA expression, and knowledge of the interactions among genes. We demonstrate the advantages of our approach by analyzing nine sample-matched datasets that provide both miRNA and mRNA expression. We show that integrating miRNAs into pathway analysis results in greater statistical power, and provides a more comprehensive view of the underlying phenomena. We also compare our disease subtyping method with the state-of-the-art integrative analysis by analyzing a colorectal cancer database from TCGA. The colorectal cancer subtypes identified by our approach are significantly different in terms of their survival expectation. These miRNA-augmented pathways offer a more comprehensive view and a deeper understanding of biological pathways. A better understanding of the molecular processes associated with patients’ survival can help to a better prognosis and an appropriate treatment for each subtype.
PMCID: PMC5147738  PMID: 27896992
2.  Cross-Clustering: A Partial Clustering Algorithm with Automatic Estimation of the Number of Clusters 
PLoS ONE  2016;11(3):e0152333.
Four of the most common limitations of the many available clustering methods are: i) the lack of a proper strategy to deal with outliers; ii) the need for a good a priori estimate of the number of clusters to obtain reasonable results; iii) the lack of a method able to detect when partitioning of a specific data set is not appropriate; and iv) the dependence of the result on the initialization. Here we propose Cross-clustering (CC), a partial clustering algorithm that overcomes these four limitations by combining the principles of two well established hierarchical clustering algorithms: Ward’s minimum variance and Complete-linkage. We validated CC by comparing it with a number of existing clustering methods, including Ward’s and Complete-linkage. We show on both simulated and real datasets, that CC performs better than the other methods in terms of: the identification of the correct number of clusters, the identification of outliers, and the determination of real cluster memberships. We used CC to cluster samples in order to identify disease subtypes, and on gene profiles, in order to determine groups of genes with the same behavior. Results obtained on a non-biological dataset show that the method is general enough to be successfully used in such diverse applications. The algorithm has been implemented in the statistical language R and is freely available from the CRAN contributed packages repository.
PMCID: PMC4807765  PMID: 27015427
3.  Allogeneic Hematopoietic Stem Cell Transplantation for the Treatment of High-Risk Acute Myelogenous Leukemia and Myelodysplastic Syndrome Using Reduced-Intensity Conditioning with Fludarabine and Melphalan 
Reduced-intensity conditioning has extended the use of allogeneic hematopoietic stem cell transplantation (HSCT) to patients otherwise not eligible for this treatment due to older age or frailty. One hundred twelve acute myelogenous leukemia/myelodysplastic syndromes patients received fludarabine and melphalan (FM) conditioning with allogeneic HSCT. Most patients (73%) were not in remission. Graft-versus-host disease (GVHD) prophylaxis consisted of tacrolimus and mini-methotrexate. Median age was 55 years (range, 22–74). Donors were related (53%) and unrelated (47%). Median follow-up of surviving patients (n = 43) was 29.4 months (range, 13.1–87.7). The complete remission (CR) rate was 82%. Estimates of 2-year survival were 66%, 40%, and 23% for patients in CR, with active disease without and with circulating blasts at HSCT, respectively. In multivariate analysis, survival was negatively influenced by active disease at HSCT and development of grade II–IV acute GVHD. Presence of circulating blasts at HSCT negatively influenced freedom from disease progression. Incidence of nonrelapse mortality (NRM) was significantly higher for patients with active disease, but was not influenced by patient age. Patients in CR had a day-100 and 2-year NRM of 0% and 20%, respectively. Use of unrelated donors increased the risk of NRM only among patients with active disease. FM and HSCT elicited long-term disease control in a significant fraction of this high-risk cohort.
PMCID: PMC4080636  PMID: 17382251
Leukemia; Myelodysplastic syndrome; Transplant; Aging
4.  Methods and approaches in the topology-based analysis of biological pathways 
The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as “third generation,” have the potential to better model the phenomena described by pathways. Although there is now a large variety of approaches used for this purpose, no review is currently available to offer guidance for potential users and developers. This review covers 22 such topology-based pathway analysis methods published in the last decade. We compare these methods based on: type of pathways analyzed (e.g., signaling or metabolic), input (subset of genes, all genes, fold changes, gene p-values, etc.), mathematical models, pathway scoring approaches, output (one or more pathway scores, p-values, etc.) and implementation (web-based, standalone, etc.). We identify and discuss challenges, arising both in methodology and in pathway representation, including inconsistent terminology, different data formats, lack of meaningful benchmarks, and the lack of tissue and condition specificity.
PMCID: PMC3794382  PMID: 24133454
pathway analysis; topology; signaling pathways; metabolic pathways; mathematical model; network topology; statistical significance
5.  The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways 
Bioinformatics  2011;27(15):2127-2133.
Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions.
Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and ‘wet lab’ scientists.
Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at They are implemented in Java and supported on MS Windows, Linux and OS X.
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC3137220  PMID: 21653523
6.  Effects of acute hypoventilation and hyperventilation on exhaled carbon monoxide measurement in healthy volunteers 
High levels of exhaled carbon monoxide (eCO) are a marker of airway or lung inflammation. We investigated whether hypo- or hyperventilation can affect measured values.
Ten healthy volunteers were trained to achieve sustained end-tidal CO2 (etCO2) concentrations of 30 (hyperventilation), 40 (normoventilation), and 50 mmHg (hypoventilation). As soon as target etCO2 values were achieved for 120 sec, exhaled breath was analyzed for eCO with a photoacoustic spectrometer. At etCO2 values of 30 and 40 mmHg exhaled breath was sampled both after a deep inspiration and after a normal one. All measurements were performed in two different environmental conditions: A) ambient CO concentration = 0.8 ppm and B) ambient CO concentration = 1.7 ppm.
During normoventilation, eCO mean (standard deviation) was 11.5 (0.8) ppm; it decreased to 10.3 (0.8) ppm during hyperventilation (p < 0.01) and increased to 11.9 (0.8) ppm during hypoventilation (p < 0.01). eCO changes were less pronounced than the correspondent etCO2 changes (hyperventilation: 10% Vs 25% decrease; hypoventilation 3% Vs 25% increase). Taking a deep inspiration before breath sampling was associated with lower eCO values (p < 0.01), while environmental CO levels did not affect eCO measurement.
eCO measurements should not be performed during marked acute hyperventilation, like that induced in this study, but the influence of less pronounced hyperventilation or of hypoventilation is probably negligible in clinical practice
PMCID: PMC2807848  PMID: 20030802
7.  Addition of lenalidomide to rituximab, ifosfamide, carboplatin, etoposide (RICER) in first-relapse/primary refractory diffuse large B-cell lymphoma 
British Journal of Haematology  2014;166(1):77-83.
Relapsed/refractory diffuse large B-cell lymphoma (DLBCL) is associated with a poor prognosis. Outcomes are particularly poor following immunochemotherapy failure or relapse within 12 months of induction. We conducted a Phase I/II trial of lenalidomide plus RICE (rituximab, ifosfamide, carboplatin, and etoposide) (RICER) as a salvage regimen for first-relapse or primary refractory DLBCL. Dose-escalated lenalidomide was combined with RICE every 14 d. After three cycles of RICER, patients with chemosensitive disease underwent stem cell collection and consolidation with BEAM [BCNU (carmustine), etoposide, cytarabine, melphalan] followed by autologous stem cell transplantation (autoSCT). Patients who recovered from autoSCT toxicities within 90 d initiated maintenance treatment with lenalidomide 25 mg daily for 21 d every 28 d for 12 months. No dose-limiting or unexpected toxicities occurred with lenalidomide 25 mg plus RICE. Grade 3/4 haematological toxicities resolved appropriately, and planned dose density and dose intensity of RICER were preserved. No lenalidomide or RICE dose reductions were required in any of the three cycles. After two cycles of RICER, nine of 15 patients (60%) achieved a complete response, and two achieved a partial response (13%). Combining lenalidomide with RICE is feasible, and results in promising response rates (particularly complete response rates) in high-risk DLBCL patients.
PMCID: PMC4283736  PMID: 24661044
lenalidomide; diffuse large B-cell lymphoma; rituximab; salvage; bone marrow transplantation

Results 1-7 (7)