Fludarabine modulates composition and function of the T cell pool in patients with chronic lymphocytic leukaemia

The combination of cytotoxic treatment with strategies for immune activation represents an attractive strategy for tumour therapy. Following reduction of high tumour burden by effective cytotoxic agents, two major immune-stimulating approaches are being pursued. First, innate immunity can be activated by monoclonal antibodies triggering antibody-dependent cellular cytotoxicity. Second, tumour-specific T cell responses can be generated by immunization of patients with peptides derived from tumour antigens and infused in soluble form or loaded onto dendritic cells. The choice of cytotoxic agents for such combinatory regimens is crucial since most substances such as fludarabine are considered immunosuppressive while others such as cyclophosphamide can have immunostimulatory activity. We tested in this study whether fludarabine and/or cyclophosphamide, which represent a very effective treatment regimen for chronic lymphocytic leukaemia, would interfere with a therapeutic strategy of T cell activation. Analysis of peripheral blood samples from patients prior and during fludarabine/cyclophosphamide therapy revealed rapid and sustained reduction of tumour cells but also of CD4+ and CD8+ T cells. This correlated with a significant cytotoxic activity of fludarabine/cyclophosphamide on T cells in vitro. Unexpectedly, T cells surviving fludarabine/cyclophosphamide treatment in vitro had a more mature phenotype, while fludarabine-treated T cells were significantly more responsive to mitogenic stimulation than their untreated counterparts and showed a shift towards TH1 cytokine secretion. In conclusion, fludarabine/cyclophosphamide therapy though inducing significant and relevant T cell depletion seems to generate a micromilieu suitable for subsequent T cell activation

Detecting Bacterial–Human Lateral Gene Transfer in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a very common and mostly incurable B-cell malignancy. Recent studies revealed high interpatient mutational heterogeneity and worsened therapy response and survival of patients with complex genomic aberrations. In line with this, a better understanding of the underlying mechanisms of specific genetic aberrations would reveal new prognostic factors and possible therapeutic targets. It is known that chromosomal rearrangements including DNA insertions often play a role during carcinogenesis. Recently it was reported that bacteria (microbiome)–human lateral gene transfer occurs in somatic cells and is enriched in cancer samples. To further investigate this mechanism in CLL, we analyzed paired-end RNA sequencing data of 45 CLL patients and 9 healthy donors, in which we particularly searched for bacterial DNA integrations into the human somatic genome. Applying the Burrows–Wheeler aligner (BWA) first on a human genome and then on bacterial genome references, we differentiated between sequencing reads mapping to the human genome, to the microbiome or to bacterial integrations into the human genome. Our results indicate that CLL samples featured bacterial DNA integrations more frequently (approx. two-fold) compared to normal samples, which corroborates the latest findings in other cancer entities. Moreover, we determined common integration sites and recurrent integrated bacterial transcripts. Finally, we investigated the contribution of bacterial integrations to oncogenesis and disease progression

Investigating epigenetic effects of activation-induced deaminase in chronic lymphocytic leukemia.

Activation induced deaminase (AID) has two distinct and well defined roles, both relying on its deoxycytidine (dC) deaminating function: one as a DNA mutator and another in DNA demethylation. In chronic lymphocytic leukemia (CLL), AID was previously shown to be an independent negative prognostic factor. While there is substantial impact on DNA mutations, effects of AID on gene expression by promoter demethylation of disease related target genes in leukemia has not been addressed. To shed light on this question, we aimed at determining genome wide methylation changes as well as gene expression changes in response to AID expression in CLL. Although we found minor differences in individual methylation variable positions following AID expression, we could not find recurrent methylation changes of specific target sites or changes in global methylation

Validation of genetic variants from NGS data using deep convolutional neural networks

Abstract Accurate somatic variant calling from next-generation sequencing data is one most important tasks in personalised cancer therapy. The sophistication of the available technologies is ever-increasing, yet, manual candidate refinement is still a necessary step in state-of-the-art processing pipelines. This limits reproducibility and introduces a bottleneck with respect to scalability. We demonstrate that the validation of genetic variants can be improved using a machine learning approach resting on a Convolutional Neural Network, trained using existing human annotation. In contrast to existing approaches, we introduce a way in which contextual data from sequencing tracks can be included into the automated assessment. A rigorous evaluation shows that the resulting model is robust and performs on par with trained researchers following published standard operating procedure

Stratified prevention: opportunities and limitations

Sufficient exercise and sleep, a balanced diet, moderate alcohol consumption and a good approach to handle stress have been known as lifestyles that protect health and longevity since the Middle Age. This traditional prevention quintet, turned into a sextet by smoking cessation, has been the basis of the preventive personality that formed in the twentieth century. Recent analyses of big data sets including genomic and physiological measurements have unleashed novel opportunities to estimate individual health risks with unprecedented accuracy, allowing to target preventive interventions to persons at high risk and at the same time to spare those in whom preventive measures may not be needed or even be harmful. To fully grasp these opportunities for modern preventive medicine, the established healthy life styles require supplementation by stratified prevention. The opportunities of these developments for life and health contrast with justified concerns: A surveillance society, able to predict individual behaviour based on big data, threatens individual freedom and jeopardises equality. Social insurance law and the new German Disease Prevention Act (Präventionsgesetz) rightly stress the need for research to underpin stratified prevention which is accessible to all, ethical, effective, and evidence based. An ethical and acceptable development of stratified prevention needs to start with autonomous individuals who control and understand all information pertaining to their health. This creates a mandate for lifelong health education, enabled in an individualised form by digit al technology. Stratified prevention furthermore requires the evidence-based development of a new taxonomy of cardiovascular diseases that reflects disease mechanisms. Such interdisciplinary research needs broad support from society and a better use of biosamples and data sets within an updated research governance framework