Ralf Küppers

Bio: Ralf Küppers is an academic researcher from University of Duisburg-Essen. The author has contributed to research in topics: Germinal center & Lymphoma. The author has an hindex of 77, co-authored 283 publications receiving 24677 citations. Previous affiliations of Ralf Küppers include University of Cologne & Columbia University.

Human Immunoglobulin (Ig)M+IgD+ Peripheral Blood B Cells Expressing the CD27 Cell Surface Antigen Carry Somatically Mutated Variable Region Genes: CD27 as a General Marker for Somatically Mutated (Memory) B Cells

Abstract: Immunoglobulin (Ig)M+IgD+ B cells are generally assumed to represent antigen-inexperienced, naive B cells expressing variable (V) region genes without somatic mutations. We report here that human IgM+IgD+ peripheral blood (PB) B cells expressing the CD27 cell surface antigen carry mutated V genes, in contrast to CD27-negative IgM+IgD+ B cells. IgM+IgD+CD27+ B cells resemble class-switched and IgM-only memory cells in terms of cell phenotype, and comprise ∼15% of PB B lymphocytes in healthy adults. Moreover, a very small population (<1% of PB B cells) of highly mutated IgD-only B cells was detected, which likely represent the PB counterpart of IgD-only tonsillar germinal center and plasma cells. Overall, the B cell pool in the PB of adults consists of ∼40% mutated memory B cells and 60% unmutated, naive IgD+CD27− B cells (including CD5+ B cells). In the somatically mutated B cells, VH region genes carry a two- to threefold higher load of somatic mutation than rearranged Vκ genes. This might be due to an intrinsically lower mutation rate in κ light chain genes compared with heavy chain genes and/or result from κ light chain gene rearrangements in GC B cells. A common feature of the somatically mutated B cell subsets is the expression of the CD27 cell surface antigen which therefore may represent a general marker for memory B cells in humans.

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.

The landscape of genomic alterations across childhood cancers

Abstract: Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.

Mechanisms of B-cell lymphoma pathogenesis

Abstract: Chromosomal translocations involving the immunoglobulin loci are a hallmark of many types of B-cell lymphoma. Other factors, however, also have important roles in the pathogenesis of B-cell malignancies. Most B-cell lymphomas depend on the expression of a B-cell receptor (BCR) for survival, and in several B-cell malignancies antigen activation of lymphoma cells through BCR signalling seems to be an important factor for lymphoma pathogenesis. Recent insights into the lymphomagenic role of factors supplied by the microenvironment also offer new therapeutic strategies.

Hodgkin and Reed-Sternberg cells in Hodgkin's disease represent the outgrowth of a dominant tumor clone derived from (crippled) germinal center B cells.

Abstract: In Hodgkin's disease (HD), the Hodgkin and Reed-Sternberg (HRS) cells represent only a minute population in the diseased tissue. The investigation of lineage derivation and clonal origin of these cells has yielded conflicting results. We have analyzed HRS cells micromanipulated from infiltrated tissue sections of 10 primary HD patients for rearranged V genes, extending a previous study. Clonally related rearrangements were found in nine cases, indicating that HRS cells represent a dominant clone of B lineage-derived cells in at least a large fraction of cases of HD. Rearranged VH genes from HRS cells carried a high load of somatic mutation, indicating that HRS cells are derived from germinal center (GC) cells or their progeny. Stop codons in some in-frame V gene rearrangements suggest that the HRS cell precursors reside inside GCs, have acquired crippling mutations that prevent antigenic selection, but escape apoptosis through some transforming event.

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。

WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues

Abstract: WHO CLASSIFICATION OF TUMOURS OF HAEMATOPOIETIC AND LYMPHOID TISSUES , WHO CLASSIFICATION OF TUMOURS OF HAEMATOPOIETIC AND LYMPHOID TISSUES , کتابخانه مرکزی دانشگاه علوم پزشکی تهران

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

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.