Integrated Calendar

Breast cancer (BC) divides into three major subtypes. 1) Estrogen/Progesterone Receptor positive (ER+ve), 2) ErbB2/Her2 genome amplified (Her2+), and for cancers exhibiting none of these markers, triple negative breast cancer (TNBC). These classifications defined by histo-pathologists have important ramifications as they indicate alternative therapy options best suited to treat a given patient.
We have used high throughput transcriptomic data from > 1000 breast cancer biopsies derived from The Cancer Genome Atlas (TCGA) and demonstrate that RNASEQ can with high fidelity subcategorize BC into one of these three major subgroups. Surprisingly, we found that three levels of ErbB2 expression ErbBLOW, ErbB2MED and ErbB2HIGH closely correlate with TNBC, ER+ and HER+ tumor subtypes respectively, a finding not paralleled by genome copy-number alone. Pathway analyses of differentially expressed genes demonstrated that TNBCs are particularly enriched for “Lymphocyte Activation” correlating with “chemotaxis”, “NK-cell activation” and “IFN-gamma signaling”. These immune-related gene signatures may provide an additional layer of clinically-relevant patient information as others have reported that T-cell infiltration into tumors indicate potential good response to cancer immunotherapy (e.g. Anti-PD1, Anti-CTLA4 drugs). We can use these transcriptomic immune signatures to determine their level of expression in individual patients, thus providing context for predicting response to immunotherapy in personalized medicinal manner.

Recently developed DIANA platform (DNA-linked Inhibitor ANtibody Assay) is suitable for both ultrasensitive protein detection in in vitro diagnostics and for enzyme inhibitor or protein ligand screening in drug discovery. As its name suggests, we originally designed DIANA to detect enzymes and its inhibitors, but we later showed that it is well suited also for detection of receptors and its ligands, to screen for protein-protein interaction inhibitors and for detection of small molecules. DIANA overcomes the limitations of current state of the art methods, as it can detect zeptomole amounts of targets, has a linear range of up to six logs and is applicable to biological matrices.

Screening of chemical libraries is an important step in drug discovery, but it remains challenging for targets, which are difficult to express and purify, and current methods tend to produce false results. The sensitivity and selectivity of DIANA enables quantitative high-throughput screening of enzyme inhibitors, receptor ligands or inhibitors of protein-protein interactions with unpurified proteins. DIANA addresses also the remaining limitations of the current screening methods, as it allows high-throughput screening with high signal-to-noise ratio (Z’ factor > 0.9), sensitive hit discovery and ultralow rate of false positives (< 0.02%); while quantitatively determining the inhibition potency from a single well and requiring only picogram to nanogram quantities of potentially unpurified protein target (e.g. in human serum).

At DIANA Biotechnologies, a recently established spin-off from the Institute of Organic Chemistry and Biochemistry in Prague, we aim to fully exploit the potential of the platform and to become center for development of new diagnostics and drug discovery. We are building up infrastructure for screening and hit to lead conversion, including our own ~150,000 compound library, which we will screen for medicinally relevant targets, taking just one week per target. The most promising compounds will be optimized for potency, selectivity, physical properties, pharmacology profile and in vitro and in vivo efficacy, where DIANA-based high-throughput ADME pharmacology tests can also be applied.

In our talk, we will briefly summarize the assay protocol and its performance on model targets, as well as recent developments at DIANA Biotechnologies. We will discuss in more detail examples of current internal projects, mainly of the development of selectivity panels (example of inhibitors of human carbonic anhydrases) and of the first drug discovery project directed on influenza RNA polymerase and its different subunits.

The hunt for Dark Matter is reaching at a crossroads - after two decades of incredible pace, where five orders of magnitude in parameter space were covered, no unambiguous signal has emerged for interaction between the alleged particles and our normal, baryonic matter. The next generation detectors, aiming at another order of magnitude sensitivity increase, are on the runway, and the question of what will be next takes interesting turns.
I will cover the evidence for the existence of Dark Matter, present the state of the art results from the XENON1T experiment, and play with some novel ideas for the next step, trying to move the lamppost to where Dark Matter may still stay hidden.

In order to make modelling of aqueous electrolytes more accurate, we explore the recently suggested approach for effectively accounting for electronic polarization effects using ionic charge rescaling. Based on this approach we develop a new and accurate parametrization of ions. Comparison to neutron scattering and ab initio molecular dynamics simulations demonstrates that the charge scaling approach allows for an accurate description of concentrated aqueous salt solutions including divalent ions. The present approach should thus find broad use in efficient and accurate modelling of polyvalent ions in aqueous environments, such as those encountered in biological and technological applications.