Riccardo Dalla-Favera

Bio: Riccardo Dalla-Favera is an academic researcher from Columbia University. The author has contributed to research in topics: Germinal center & B cell. The author has an hindex of 118, co-authored 276 publications receiving 48415 citations. Previous affiliations of Riccardo Dalla-Favera include Memorial Sloan Kettering Cancer Center & University of Padua.

Human c-myc onc gene is located on the region of chromosome 8 that is translocated in Burkitt lymphoma cells

Abstract: Human sequences related to the transforming gene (v-myc) of avian myelocytomatosis virus (MC29) are represented by at least one gene and several related sequences that may represent pseudogenes. By using a DNA probe that is specific for the complete gene (c-myc), different somatic cell hybrids possessing varying numbers of human chromosomes were analyzed by the Southern blotting technique. The results indicate that the human c-myc gene is located on chromosome 8. The analysis of hybrids between rodent cells and human Burkitt lymphoma cells, which carry a reciprocal translocation between chromosomes 8 and 14, allowed the mapping of the human c-myc gene on region (q24 leads to qter) of chromosome 8. This chromosomal region is translocated to either human chromosome 2, 14, or 22 in Burkitt lymphoma cells.

Reverse engineering of regulatory networks in human B cells.

Abstract: Cellular phenotypes are determined by the differential activity of networks linking coregulated genes. Available methods for the reverse engineering of such networks from genome-wide expression profiles have been successful only in the analysis of lower eukaryotes with simple genomes. Using a new method called ARACNe (algorithm for the reconstruction of accurate cellular networks), we report the reconstruction of regulatory networks from expression profiles of human B cells. The results are suggestive a hierarchical, scale-free network, where a few highly interconnected genes (hubs) account for most of the interactions. Validation of the network against available data led to the identification of MYC as a major hub, which controls a network comprising known target genes as well as new ones, which were biochemically validated. The newly identified MYC targets include some major hubs. This approach can be generally useful for the analysis of normal and pathologic networks in mammalian cells.

Mutations of multiple genes cause deregulation of NF-κB in diffuse large B-cell lymphoma

Abstract: Diffuse large B-cell lymphoma (DLBCL), the most common form of lymphoma in adulthood, comprises multiple biologically and clinically distinct subtypes including germinal centre B-cell-like (GCB) and activated B-cell-like (ABC) DLBCL Gene expression profile studies have shown that its most aggressive subtype, ABC-DLBCL, is associated with constitutive activation of the NF-kappaB transcription complex However, except for a small fraction of cases, it remains unclear whether NF-kappaB activation in these tumours represents an intrinsic program of the tumour cell of origin or a pathogenetic event Here we show that >50% of ABC-DLBCL and a smaller fraction of GCB-DLBCL carry somatic mutations in multiple genes, including negative (TNFAIP3, also called A20) and positive (CARD11, TRAF2, TRAF5, MAP3K7 (TAK1) and TNFRSF11A (RANK)) regulators of NF-kappaB Of these, the A20 gene, which encodes a ubiquitin-modifying enzyme involved in termination of NF-kappaB responses, is most commonly affected, with approximately 30% of patients displaying biallelic inactivation by mutations and/or deletions When reintroduced in cell lines carrying biallelic inactivation of the gene, A20 induced apoptosis and cell growth arrest, indicating a tumour suppressor role Less frequently, missense mutations of TRAF2 and CARD11 produce molecules with significantly enhanced ability to activate NF-kappaB Thus, our results demonstrate that NF-kappaB activation in DLBCL is caused by genetic lesions affecting multiple genes, the loss or activation of which may promote lymphomagenesis by leading to abnormally prolonged NF-kappaB responses

Hypermutation of multiple proto-oncogenes in B-cell diffuse large-cell lymphomas

Abstract: Genomic instability promotes tumorigenesis and can occur through various mechanisms, including defective segregation of chromosomes or inactivation of DNA mismatch repair. Although B-cell lymphomas are associated with chromosomal translocations that deregulate oncogene expression, a mechanism for genome-wide instability during lymphomagenesis has not been described. During B-cell development, the immunoglobulin variable (V) region genes are subject to somatic hypermutation in germinal-centre B cells. Here we report that an aberrant hypermutation activity targets multiple loci, including the proto-oncogenes PIM1, MYC, RhoH/TTF (ARHH) and PAX5, in more than 50% of diffuse large-cell lymphomas (DLCLs), which are tumours derived from germinal centres. Mutations are distributed in the 5' untranslated or coding sequences, are independent of chromosomal translocations, and share features typical of V-region-associated somatic hypermutation. In contrast to mutations in V regions, however, these mutations are not detectable in normal germinal-centre B cells or in other germinal-centre-derived lymphomas, suggesting a DLCL-associated malfunction of somatic hypermutation. Intriguingly, the four hypermutable genes are susceptible to chromosomal translocations in the same region, consistent with a role for hypermutation in generating translocations by DNA double-strand breaks. By mutating multiple genes, and possibly by favouring chromosomal translocations, aberrant hypermutation may represent the major contributor to lymphomagenesis.

Gene Expression Profiling of B Cell Chronic Lymphocytic Leukemia Reveals a Homogeneous Phenotype Related to Memory B Cells

Abstract: B cell–derived chronic lymphocytic leukemia (B-CLL) represents a common malignancy whose cell derivation and pathogenesis are unknown. Recent studies have shown that >50% of CLLs display hypermutated immunoglobulin variable region (IgV) sequences and a more favorable prognosis, suggesting that they may represent a distinct subset of CLLs which have transited through germinal centers (GCs), the physiologic site of IgV hypermutation. To further investigate the phenotype of CLLs, their cellular derivation and their relationship to normal B cells, we have analyzed their gene expression profiles using oligonucleotide-based DNA chip microarrays representative of ∼12,000 genes. The results show that CLLs display a common and characteristic gene expression profile that is largely independent of their IgV genotype. Nevertheless, a restricted number of genes (<30) have been identified whose differential expression can distinguish IgV mutated versus unmutated cases and identify them in independent panels of cases. Comparison of CLL profiles with those of purified normal B cell subpopulations indicates that the common CLL profile is more related to memory B cells than to those derived from naive B cells, CD5+ B cells, and GC centroblasts and centrocytes. Finally, this analysis has identified a subset of genes specifically expressed by CLL cells of potential pathogenetic and clinical relevance.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

Abstract: Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case. A class discovery procedure automatically discovered the distinction between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) without previous knowledge of these classes. An automatically derived class predictor was able to determine the class of new leukemia cases. The results demonstrate the feasibility of cancer classification based solely on gene expression monitoring and suggest a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.

Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling

Abstract: 12 Pathology and Microbiology, and 13 Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin's lymphoma, is clinically heterogeneous: 40% of patients respond well to current therapy and have prolonged survival, whereas the remainder succumb to the disease. We proposed that this variability in natural history reflects unrecognized molecular heterogeneity in the tumours. Using DNA microarrays, we have conducted a systematic characterization of gene expression in B-cell malignancies. Here we show that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour. We identified two molecularly distinct forms of DLBCL which had gene expression patterns indicative of different stages of B-cell differentiation. One type expressed genes characteristic of germinal centre B cells ('germinal centre B-like DLBCL'); the second type expressed genes normally induced during in vitro activation of peripheral blood B cells ('activated B-like DLBCL'). Patients with germinal centre B-like DLBCL had a significantly better overall survival than those with activated B-like DLBCL. The molecular classification of tumours on the basis of gene expression can thus identify previously undetected and clinically significant subtypes of cancer.