Precision Medicine in Therapy of Non-solid Cancer.

The development and approval of the tyrosine kinase inhibitor imatinib in 2001 has heralded the advance of directed therapy options. Today, an armamentarium of targeted therapeutics is available and enables the use of precision medicine in non-solid cancer. Precision medicine is guided by the detection of tumor-specific and targetable characteristics. These include pathogenic fusions and/or mutations, dependency on specific signaling pathways, and the expression of certain cell surface markers. Within the first part, we review approved targeted therapies for the compound classes of small molecule inhibitors, antibody-based therapies and cellular therapies. Particular consideration is given to the underlying pathobiology and the respective mechanism of action. The second part emphasizes on how biomarkers, whether they are of diagnostic, prognostic, or predictive relevance, are indispensable tools to guide therapy choice and management in precision medicine. Finally, the examples of acute myeloid leukemia, chronic lymphocytic leukemia, and chronic myeloid leukemia illustrate how integration of these biomarkers helps to tailor therapy.

RNA polymerase II is recruited to DNA double-strand breaks for dilncRNA transcription in Drosophila.

DNA double-strand breaks are among the most toxic lesions that can occur in a genome and their faithful repair is thus of great importance. Recent findings have uncovered local transcription that initiates at the break and forms a non-coding transcript, called damage-induced long non-coding RNA (dilncRNA), which helps to coordinate the DNA transactions necessary for repair. We provide nascent RNA sequencing-based evidence that RNA polymerase II transcribes the dilncRNA in Drosophila and that this is more efficient for DNA breaks in an intron-containing gene, consistent with the higher damage-induced siRNA levels downstream of an intron. The spliceosome thus stimulates recruitment of RNA polymerase II to the break, rather than merely promoting the annealing of sense and antisense RNA to form the siRNA precursor. In contrast, RNA polymerase III nascent RNA libraries did not contain reads corresponding to the cleaved loci and selective inhibition of RNA polymerase III did not reduce the yield of damage-induced siRNAs. Finally, the damage-induced siRNA density was unchanged downstream of a T8 sequence, which terminates RNA polymerase III transcription. We thus found no evidence for a participation of RNA polymerase III in dilncRNA transcription in cultured Drosophila cells.

How artificial intelligence might disrupt diagnostics in hematology in the near future.

Artificial intelligence (AI) is about to make itself indispensable in the health care sector. Examples of successful applications or promising approaches range from the application of pattern recognition software to pre-process and analyze digital medical images, to deep learning algorithms for subtype or disease classification, and digital twin technology and in silico clinical trials. Moreover, machine-learning techniques are used to identify patterns and anomalies in electronic health records and to perform ad-hoc evaluations of gathered data from wearable health tracking devices for deep longitudinal phenotyping. In the last years, substantial progress has been made in automated image classification, reaching even superhuman level in some instances. Despite the increasing awareness of the importance of the genetic context, the diagnosis in hematology is still mainly based on the evaluation of the phenotype. Either by the analysis of microscopic images of cells in cytomorphology or by the analysis of cell populations in bidimensional plots obtained by flow cytometry. Here, AI algorithms not only spot details that might escape the human eye, but might also identify entirely new ways of interpreting these images. With the introduction of high-throughput next-generation sequencing in molecular genetics, the amount of available information is increasing exponentially, priming the field for the application of machine learning approaches. The goal of all the approaches is to allow personalized and informed interventions, to enhance treatment success, to improve the timeliness and accuracy of diagnoses, and to minimize technically induced misclassifications. The potential of AI-based applications is virtually endless but where do we stand in hematology and how far can we go?

The power and potential of integrated diagnostics in acute myeloid leukaemia.

The field of acute myeloid leukaemia (AML) diagnostics, initially based solely on morphological assessment, has integrated more and more disciplines. Today, state-of-the-art AML diagnostics relies on cytomorphology, cytochemistry, immunophenotyping, cytogenetics and molecular genetics. Only the integration of all of these methods allows for a comprehensive and complementary characterisation of each case, which is prerequisite for optimal AML diagnosis and management. Here, we will review why multidisciplinary diagnostics is mandatory today and will gain even more importance in the future, especially in the context of precision medicine. We will discuss ideas and strategies that are likely to shape and improve multidisciplinary diagnostics in AML and may even overcome some of today's gold standards. This includes recent technical advances that provide genome-wide molecular insights. The enormous amount of data obtained by these latter techniques represents a great challenge, but also a unique chance. We will reflect on how this increase in knowledge can be incorporated into the routine to pave the way for personalised medicine in AML.

Homology directed repair is unaffected by the absence of siRNAs in Drosophila melanogaster.

Small interfering RNAs (siRNAs) defend the organism against harmful transcripts from exogenous (e.g. viral) or endogenous (e.g. transposons) sources. Recent publications describe the production of siRNAs induced by DNA double-strand breaks (DSB) in Neurospora crassa, Arabidopsis thaliana, Drosophila melanogaster and human cells, which suggests a conserved function. A current hypothesis is that break-induced small RNAs ensure efficient homologous recombination (HR). However, biogenesis of siRNAs is often intertwined with other small RNA species, such as microRNAs (miRNAs), which complicates interpretation of experimental results. In Drosophila, siRNAs are produced by Dcr-2 while miRNAs are processed by Dcr-1. Thus, it is possible to probe siRNA function without miRNA deregulation. We therefore examined DNA double-strand break repair after perturbation of siRNA biogenesis in cultured Drosophila cells as well as mutant flies. Our assays comprised reporters for the single-strand annealing pathway, homologous recombination and sensitivity to the DSB-inducing drug camptothecin. We could not detect any repair defects caused by the lack of siRNAs derived from the broken DNA locus. Since production of these siRNAs depends on local transcription, they may thus participate in RNA metabolism-an established function of siRNAs-rather than DNA repair.

A Comprehensive Toolbox for Genome Editing in Cultured Drosophila melanogaster Cells.

Custom genome editing has become an essential element of molecular biology. In particular, the generation of fusion constructs with epitope tags or fluorescent proteins at the genomic locus facilitates the analysis of protein expression, localization, and interaction partners at physiologic levels. Following up on our initial publication, we now describe a considerably simplified, more efficient, and readily scalable experimental workflow for PCR-based genome editing in cultured Drosophila melanogaster cells. Our analysis at the act5C locus suggests that PCR-based homology arms of 60 bp are sufficient to reach targeting efficiencies of up to 80% after selection; extension to 80 bp (PCR) or 500 bp (targeting vector) did not further improve the yield. We have expanded our targeting system to N-terminal epitope tags; this also allows the generation of cell populations with heterologous expression control of the tagged locus via the copper-inducible mtnDE promoter. We present detailed, quantitative data on editing efficiencies for several genomic loci that may serve as positive controls or benchmarks in other laboratories. While our first PCR-based editing approach offered only blasticidin-resistance for selection, we now introduce puromycin-resistance as a second, independent selection marker; it is thus possible to edit two loci (e.g., for coimmunoprecipitation) without marker removal. Finally, we describe a modified FLP recombinase expression plasmid that improves the efficiency of marker cassette FLP-out. In summary, our technique and reagents enable a flexible, robust, and cloning-free genome editing approach that can be parallelized for scale-up.

Quantitation of Gingerols in Human Plasma by Newly Developed Stable Isotope Dilution Assays and Assessment of Their Immunomodulatory Potential.

In a pilot study with two volunteers, the main pungent and bioactive ginger (Zingiber officinale Roscoe) compounds, the gingerols, were quantitated in human plasma after ginger tea consumption using a newly established HPLC-MS/MS(ESI) method on the basis of stable isotope dilution assays. Limits of quantitation for [6]-, [8]-, and [10]-gingerols were determined as 7.6, 3.1, and 4.0 nmol/L, respectively. The highest plasma concentrations of [6]-, [8]-, and [10]-gingerols (42.0, 5.3, and 4.8 nmol/L, respectively) were reached 30-60 min after ginger tea intake. Incubation of activated human T lymphocytes with gingerols increased the intracellular Ca(2+) concentration as well as the IFN-γ secretion by about 20-30%. This gingerol-induced increase of IFN-γ secretion could be blocked by the specific TRPV1 antagonist SB-366791. The results of the present study point to an interaction of gingerols with TRPV1 in activated T lymphocytes leading to an augmentation of IFN-γ secretion.