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The work presented in this thesis applies integrative genomic and experimental approaches to investigate mechanisms involved in regulation of gene expression in the context of disease and normal cell biology.

In papers I and II, we have explored the role of epigenetic regulation of gene expression in multiple myeloma (MM). By using a bioinformatic approach we identified the Polycomb repressive complex 2 (PRC2) to be a common denominator for the underexpressed gene signature in MM. By using inhibitors of the PRC2 we showed an activation of the genes silenced by H3K27me3 and a reduction in the tumor load and increased overall survival in the in vivo 5TMM model. Using ChIP-sequencing we defined the distribution of H3K27me3 and H3K4me3 marks in MM patients cells. In an integrated bioinformatic approach, the H3K27me3-associated genes significantly correlated to under-expression in patients with less favorable survival. Thus, our data indicates the presence of a common under-expressed gene profile and provides a rationale for implementing new therapies focusing on epigenetic alterations in MM.

In paper III we address the existence of a small cell population in MM presenting with differential tumorigenic properties in the 5T33MM murine model. We report that the predominant population of CD138+ cells had higher engraftment potential, higher clonogenic growth, whereas the CD138- MM cells presented with less mature phenotype and higher drug resistance. Our findings suggest that while designing treatment regimes for MM, both the cellpopulations must be targeted.

In paper IV we have studied the general mechanism of differential gene expression regulation by CGGBP1 in response to growth signals in normal human fibroblasts. We found that CGGBP1 binding affects global gene expression by RNA Polymerase II. This is mediated by Alu RNAdependentinhibition of RNA Polymerase II. In presence of growth signals CGGBP1 is retained in the nuclei and exhibits enhanced Alu binding thus inhibiting RNA Polymerase III binding on Alus. Hence we suggest a mechanism by which CGGBP1 orchestrates Alu RNA-mediated regulation of RNA Polymerase II. This thesis provides new insights for using integrative bioinformatic approaches to decipher gene expression regulation mechanisms in MM and in normal cells.

CGGBP1 (CGG triplet repeat-binding protein 1) regulates cell proliferation, stress response,cytokinesis, telomeric integrity and transcription. It could affect these processes by modulatingtarget gene expression under different conditions. Identification of CGGBP1-target genes andtheir regulation could reveal how a transcription regulator affects such diverse cellular processes.Here we describe the mechanisms of differential gene expression regulation by CGGBP1 inquiescent or growing cells. By studying global gene expression patterns and genome-wide DNAbindingpatterns of CGGBP1, we show that a possible mechanism through which it affects theexpression of RNA Pol II-transcribed genes in trans depends on Alu RNA. We also show that itregulates Alu transcription in cis by binding to Alu promoter. Our results also indicate thatpotential phosphorylation of CGGBP1 upon growth stimulation facilitates its nuclear retention,Alu-binding and dislodging of RNA Pol III therefrom. These findings provide insights into howAlu transcription is regulated in response to growth signals.

Multiple myeloma (MM) is characterized by accumulation of post-germinal center, isotype switched, long-living plasma cells with retained proliferation capacity within the bone marrow. MM is highly heterogeneous and remains fatal. This heterogeneity has hampered identification of a common underlying mechanism for disease establishment and the development of targeted therapy. We recently provided proof-of-principle that gene silencing associated with H3K27me3 contributes to the malignancy of MM. Here we present the first epigenomic map of MM for H3K27me3 and H3K4me3 derived by ChIP- and RNA sequencing from freshly-isolated bone marrow plasma cells from four patients. We compile lists of targets common among the patients as well as unique to MM when compared with PBMCs. Indicating the clinical relevance of our findings, we find increased silencing of H3K27me3 targets with disease progression and in patients presenting with a poor prognosis. Bivalent genes further significantly correlated to under-expressed genes in MM and were unique to MM when compared to PBMCs. Furthermore, bivalent genes, unlike H3K27me3 targets, significantly associated with transcriptional activation upon Polycomb inhibition indicating a potential for drug targeting. Thus, we suggest that gene silencing by Polycomb plays an important role in the development of the malignant phenotype of the MM cell during tumor progression.

Mounting evidence indicates that grouping of chronic lymphocytic leukemia (CLL) into distinct subsets with stereotyped BCRs is functionally and prognostically relevant. However, several issues need revisiting, including the criteria for identification of BCR stereotypy and its actual frequency as well as the identification of "CLL-biased" features in BCR Ig stereotypes. To this end, we examined 7596 Ig VH (IGHV-IGHD-IGHJ) sequences from 7424 CLL patients, 3 times the size of the largest published series, with an updated version of our purpose-built clustering algorithm. We document that CLL may be subdivided into 2 distinct categories: one with stereotyped and the other with nonstereotyped BCRs, at an approximate ratio of 1: 2, and provide evidence suggesting a different ontogeny for these 2 categories. We also show that subset-defining sequence patterns in CLL differ from those underlying BCR stereotypy in other B-cell malignancies. Notably, 19 major subsets contained from 20 to 213 sequences each, collectively accounting for 943 sequences or one-eighth of the cohort. Hence, this compartmentalized examination of VH sequences may pave the way toward a molecular classification of CLL with implications for targeted therapeutic interventions, applicable to a significant number of patients assigned to the same subset.

Immunogenetic analysis of mantle cell lymphoma (MCL) has offered important evidence helping to decipher the immune pathways leading to its development and also prompting a reappraisal of the views about its ontogeny. In particular, older and more recent studies have demonstrated that MCL is characterized by a highly distinctive immunoglobulin gene repertoire with remarkable predominance of the IGHV3-21 and IGHV4-34 genes; restricted associations of IGHV,IGHD and IGHJ genes, culminating in the creation of quasi-identical ("stereotyped") heavy complementarity-determining region 3 sequences in roughly 10% of cases; and, very precisely targeted and, probably, functionally driven somatic hypermutation, ranging from minimal (in most cases) to pronounced. Furthermore, comparison to other entities, in particular CLL, revealed that several of these immunogenetic features are "MCL-biased". On these grounds, an antigen-driven origin of MCL could be envisaged, at least for subsets of cases.

Over the last decade, immunogenetic analysis of B-cell receptor immunoglobulins (BcR IGs) has proved to be a particularly fruitful field in chronic lymphocytic leukemia (CLL), not only for understanding disease pathogenesis but also for discriminating clinical subgroups with markedly distinct course and outcome. Of utmost importance was the identification of quasi-identical BcR IGs among unrelated patients with CLL, fittingly coined as "stereotypy," that set the wheels in motion for unraveling the role of antigen(s) in the selection and expansion of the leukemic clones. The categorization of CLL clones into "subsets" according to shared BcR IG structural characteristics provided a compartmentalized view of this otherwise heterogeneous disease, which eventually led to defining strikingly homogeneous groups of patients in terms of: (i) functional properties of the clonal BcR IGs, e. g. BcR reactivity and signaling; (ii) clonal genetic landscape, e. g. genomic aberrations, gene expression/methylation profiles, microRNA signatures; and (iii) clinical course and outcome. The remarkable restriction of the CLL IG gene repertoire, resulting to a great degree from the high impact of BcR IG stereotypy, may also prompt speculations regarding CLL ontogenesis. Overall, the BcR IG molecule justifiably lies at the heart of CLL clinical research, holding the promise of subset-tailored therapies.

Introduction: Several common alleles have been shown to be associated with breast and/or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Recent genome-wide association studies of breast cancer have identified eight additional breast cancer susceptibility loci: rs1011970 (9p21, CDKN2A/B), rs10995190 (ZNF365), rs704010 (ZMIZ1), rs2380205 (10p15), rs614367 (11q13), rs1292011 (12q24), rs10771399 (12p11 near PTHLH) and rs865686 (9q31.2).

Methods: To evaluate whether these single nucleotide polymorphisms (SNPs) are associated with breast cancer risk for BRCA1 and BRCA2 carriers, we genotyped these SNPs in 12,599 BRCA1 and 7,132 BRCA2 mutation carriers and analysed the associations with breast cancer risk within a retrospective likelihood framework.

Results: Only SNP rs10771399 near PTHLH was associated with breast cancer risk for BRCA1 mutation carriers (per-allele hazard ratio (HR) = 0.87, 95% CI: 0.81 to 0.94, P-trend = 3 x 10(-4)). The association was restricted to mutations proven or predicted to lead to absence of protein expression (HR = 0.82, 95% CI: 0.74 to 0.90, P-trend = 3.1 x 10(-5), P-difference = 0.03). Four SNPs were associated with the risk of breast cancer for BRCA2 mutation carriers: rs10995190, P-trend = 0.015; rs1011970, P-trend = 0.048; rs865686, 2df P = 0.007; rs1292011 2df P = 0.03. rs10771399 (PTHLH) was predominantly associated with estrogen receptor (ER)-negative breast cancer for BRCA1 mutation carriers (HR = 0.81, 95% CI: 0.74 to 0.90, P-trend = 4 x 10(-5)) and there was marginal evidence of association with ER- negative breast cancer for BRCA2 mutation carriers (HR = 0.78, 95% CI: 0.62 to 1.00, P-trend = 0.049).

Conclusions: The present findings, in combination with previously identified modifiers of risk, will ultimately lead to more accurate risk prediction and an improved understanding of the disease etiology in BRCA1 and BRCA2 mutation carriers.