Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

<p>Abstract</p> <p>Background</p> <p>Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgV_H) mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgV_H status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgV_H mutational status which can accurately predict the survival outcome are yet to be discovered.</p> <p>Results</p> <p>In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO) and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgV_H mutation status from the ZAP70 co-expression network.</p> <p>Conclusions</p> <p>We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgV_H mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.</p

Advocating the need of a systems biology approach for personalised prognosis and treatment of B-CLL patients

The clinical course of B-CLL is heterogeneous. This heterogeneity leads to a clinical dilemma: can we identify those patients who will benefit from early treatment and predict the survival? In recent years, mathematical modelling has contributed significantly in understanding the complexity of diseases. In order to build a mathematical model for determining prognosis of B-CLL one has to identify, characterise and quantify key molecules involved in the disease. Here we discuss the need and role of mathematical modelling in predicting B-CLL disease pathogenesis and suggest a new systems biology approach for a personalised therapy of B-CLL patients

The expression and signalling patterns of CD180 toll like receptor in Chronic Lymphocytic Leukaemia (CLL)

Chronic lymphocytic leukaemia (CLL) is characterised by a progressive accumulation of mature CD5+CD20+CD23+ lymphocytes. Despite the remarkable progress in our understanding of the immunobiology of CLL, the aetiology of the disease remains unknown. The consensus is that CLL cells are driven by (auto)antigen(s) through the B cell receptor (BCR) and are regulated by a variety of signals received from the microenvironment, including toll-like receptors (TLR).Our group has previously shown that engagement of the CD180 orphan TLR expressed by approximately 60% of CLL cells, can re-wire the sIgM-mediated signalling from a pro-survival pathway, involving phosphatidylinositol-4,5-bisphosphate3-kinase (PI3K) and protein kinase B (AKT) to the potentially pro-apoptotic pathway through mitogen-activated protein kinase (p38MAPK). However, little is known about the function of the other BCR - sIgD in CLL and its possible interaction with CD180. Here we studied intracellular signalling and apoptosis of CLL cells following sole or sequential ligation of CD180 and sIgD. Our data indicated that following sequential ligation of CD180 and sIgD, CLL samples demonstrated enhanced p38MAPK phosphorylation leading to increased apoptosis of CLL cells indicating synergistic relationship between CD180 and sIgD. To better understand the prognostic importance of CD180 expression we sought to determine whether CD180 and other prognostic markers such as CD38 and ZAP70 displayed any correlation with the known cytogenetic aberrations:TP53 and DLEU1. Our results suggested that CLL cells with DLEU1 deletion are characterised by the negative expression of both, CD180 and CD38, and this might have a significance for CLL prognosis. To explain this correlation, we hypothesised that interaction of CLL cells with their microenvironment through TLRs leads to the expansion of leukaemic clones, in vivo, in lymph nodes. Our results indicated that CD180 is heterogeneously expressed in the paraffin tissue sections of the lymph nodes of CLL patients and its expression positively correlates with the expression of Ki-67. Our data demonstrated, that although CD180 expression and signaling might have negative prognostic importance in CLL due to the enhanced proliferation of leukaemic cells, its interaction with sIgD would re-direct leukaemic cells towards apoptosis thus opening new opportunities for the disease immunotherapy

Telomere protein complexes and their role in lymphoid malignancies

Telomeres are highly regulated and dynamic complexes that protect the genomic DNA and prevent the end of linear chromosomes from being misrecognized as a broken DNA. Due to the end replication problem, telomeres of somatic cells shorten with each cell division, inducing cell senescence. Telomerase is a reverse transcriptase capable of compensating telomere attrition by adding telomere repeats to the ends of chromosomes. Human telomeres are associated with the shelterin complex which consists of six telomere-associated proteins that specifically bind to telomeric DNA. Alterations or removal of individual shelterin components would lead to telomere uncapping and telomere dysfunction, resulting in cellular senescence and transformation to a malignant state. Another complex of multifunctional proteins, named non-shelterin complex, is thought to prevent telomere degradation and facilitate telomerase-based telomere elongation. As telomerase is highly expressed in most human tumor cells, it is considered an attractive target for new therapeutic strategies. In this review, we will summarize the characteristics of telomeres and telomerase in lymphoid malignancies and discuss the role of telomere-associated proteins in these entities.Fil: Panero, Julieta. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Dos Santos, Patricia Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentina. Laboratorio de Genética de Neoplasias Linfoides; ArgentinaFil: Slavutsky, Irma Rosa. Laboratorio de Genética de Neoplasias Linfoides; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentin

A gene expression assay based on chronic lymphocytic leukemia activation in the microenvironment to predict progression

Several gene expression profiles with a strong correlation with patient outcome have been previously described in chronic lymphocytic leukemia (CLL), although their applicability in clinical practice as biomarkers has been particularly limited. Here we describe the training and validation of a gene expression signature for predicting early progression of patients with CLL based on the analysis of 200 genes related to microenvironment signaling on the NanoString platform. In the training cohort (n=154), the CLL15 assay containing a 15-gene signature was associated with time to first treatment (TtFT) (HR: 2.83, 95%CI 2.17-3.68; p<0.001). The prognostic value of the CLL15 score (HR 1.71, [95%CI 1.15-2.52]; p=0.007) was further confirmed in an external independent validation cohort (n=112). Of note, the CLL15 score improved the prognostic capacity over the IGHV mutational status and the International Prognostic Score for asymptomatic early-stage (IPS-E) CLL. In multivariate analysis, the CLL15 score (HR: 1.83, 95%CI 1.32-2.56; p<0.001) and the IPS-E CLL (HR: 2.23, 95%CI 1.59-3.12; p<0.001) were independently associated with TtFT. The newly developed and validated CLL15 assay successfully translates previous gene signatures, such as the microenvironment signaling, into a new gene expression-based assay with prognostic implications in CLL

Chromatin accessibility maps of chronic lymphocytic leukemia identify subtypespecific epigenome signatures and associated transcription regulatory networks

Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay. These data were further complemented by ChIPmentation and RNA-seq profiling in ten samples. Based on this dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic regulatory differences between these two disease subtypes. In summary, we found widespread heterogeneity in the CLL chromatin landscape, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research