Deciphering the Immune Evolution Landscape of Multiple Myeloma Long-Term Survivors Using Single Cell Genomics

Multiple myeloma (MM) is a malignant bone marrow (BM) disease characterized by somatic hypermutation and DNA damage in plasma cells; leading to the overproduction of dysfunctional malignant myeloma cells. Accumulation of myeloma cells has direct and indirect effects on the BM and other organs. Despite the development of new therapeutic options; MM remains incurable and only a small fraction of patients experiences long-term survival (LTS). The past has shown that ultimately all patients still relapse; leading to the hypothesis that a state of active immune-surveillance is required to control the residual disease. To understand the long-term survival phenomenon and its link to the immune-phenotypes in MM disease; we collected paired bone marrow samples from 24 patients who survived for about 7 to 17 years after Autologous Stem Cell Transplant (ASCT), with a high plasma cell infiltration in the BM (median 49.5%) at diagnosis time. Response assessment according to the International Myeloma Working Group (IMWG) revealed that 15 patients were in complete remission (CR), whereas 9 patients were in non-complete remission (non-CR) that had tumor cells which remained stable over recent years. We performed single-cell RNA-seq sequencing on more than 290,000 bone marrow cells from 11 patients before treatment (BT) and in LTS, as well as three healthy controls using 10x Genomics technology. I developed a computational approach using the state-of-the-art single cell methods, statistical inference and machine learning models to decipher the bone marrow immune cell types and states across all clinical groups. I performed in-depth analyses of the bone marrow immune microenvironment across all captured cell types, and provided the global landscape of cellular states across all clinical groups. In this work, I defined new cellular states, marker genes, and gene signatures associated with the patients’ clinical and survival states. Additionally, I defined a new myeloid population termed Myeloma-associated Neutrophils (MAN) cells and a T cell exhaustion population termed Aberrant Memory Cytotoxic (AMC) CD8+ T cells in newly diagnosed Multiple Myeloma patients. Moreover, I propose new therapeutic targets CXCR3 and NR4A2 in AMC CD8+ T cells, which could be further investigated to reverse the T cell exhaustion state in newly diagnosed MM patients. Furthermore, I defined new prognostic markers in the CD8+ T cell compartment which could be predictive for the global disease state. Finally, I propose that MM long-term survivors go through a complex and evolving immune landscape and acquire cellular states in a stepwise manner. Furthermore, I propose the Continuum Immune Landscape (CIL) Model which explains the immune landscape of MM patients before and after long-term survival. Additionally, I introduced the Disease-State Trajectories (DST) hypothesis regarding the disease-associated dysregulated cellular states in MM context, which could be generalized into other tumor entities and diseases

Analytical and numerical investigation of the ultra-relativistic Euler equations

von Mahmoud Abdelaziz Elbiomy Abdelrahma

Novel inhibitors of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) and steroid sulfatase (STS) with unique dual mode of action : potential drugs for the treatment of non-small cell lung cancer (NSCLC) and endometriosis

Estrogens, in particular estradiol‎ (E2)‎ play an important role in estrogen-dependent diseases (EDDs), such as non-small-cell lung cancer ‎‎(NSCLC) and endometriosis. 17β-Hydroxysteroid dehydrogenase type 1 (17β-HSD1) is frequently expressed in NSCLC tissues, leading to cancer development and progression. Thus, the first objective of this study (chapter 3.1) is the development of a novel series of highly potent non-steroidal, selective ‎‎17β-HSD1 inhibitors in order to enhance the treatment of NSCLC. ‎ This section of the study showed that 17β-HSD1 is a promising therapeutic target for NSCLC, providing new avenues for the treatment of this lethal cancer. Steroid sulfatase (STS) and 17β-HSD1 are promising targets for the treatment of endometriosis because they ‎limit estrogen formation mainly in the target cells, leading to fewer ‎side effects. ‎Thus, the second part of the study ‎(chapter 3.2) ‎aims at developing dual inhibitors of STS and 17β-HSD1, which provide a novel treatment option. The synthesized sulfamates should be drugs for inhibition of STS, and prodrugs for 17β-HSD1 inhibition. The most active compounds of this part showed nanomolar IC50 values for STS in cellular assays ‎and their corresponding phenols displayed potent 17β-HSD1 inhibition in cell-free and cellular ‎assays as well as high selectivity over 17β-HSD2. These findings suggest that the “drug-prodrug concept” ‎has been applied successfully ‎(chapter 3.2).Estrogene, insbesondere Estradiol (E2), spielen eine zentrale Rolle bei Estrogen-abhängigen Erkrankungen (estrogen-dependent diseases, EDD) wie nicht-kleinzellige Bronchialkarzinome (non-small-cell lung cancer, NSCLC) und Endometriose. 17β-Hydroxysteroid Dehydrogenase Typ 1 (17β-HSD1) ist in NSCLC-Gewebe häufig überexprimiert und trägt zu Tumorentstehung und -wachstum bei. Das erste Ziel dieser Arbeit war daher die Entwicklung von neuartigen und hochpotenten, nicht-steroidalen 17β-HSD1 Inhibitoren als potenzielle NSCLC-Therapeutika (Kapitel 3.1). Die Daten zeigen, dass 17β-HSD1 ein vielversprechendes Target darstellt, das neue Möglichkeiten in der NSCLC-Therapie eröffnen kann. Steroid Sulfatase (STS) und 17β-HSD1 sind vielversprechende Wirkstofftargets zur Behandlung der Endometriose, da sie die E2-Produktion lokal im erkrankten Gewebe reduzieren, was im Vergleich zu systemischen Therapien zu weniger Nebenwirkungen führen sollte. Gegenstand des zweiten Teils der Arbeit (Kapitel 3.2) war die Entwicklung von dualen Inhibitoren von STS und 17β-HSD1. Die so synthetisierten Sulfamate sollten Drugs für die Hemmung von STS und gleichzeitig Prodrugs für die Hemmung von 17β-HSD1 darstellen. Die aktivsten Verbindungen dieses Teils zeigten nanomolare IC50-Werte für STS in zellulären Assays und ihre entsprechenden Phenole zeigten eine starke 17β-HSD1-Hemmung in zellfreien und zellulären Assays sowie eine hohe Selektivität gegenüber 17β-HSD2. Die Daten belegen, dass das verfolgte “Drug-Prodrug-Konzept” der dualen Hemmstoffwirkung erfolgreich umgesetzt wurde (Kapitel 3.2)

A Riccati-Bernoulli Sub-ODE Method for the Resonant Nonlinear Schrödinger Equation with Both Spatio-Temporal Dispersions and Inter-Modal

This work uses the Riccati-Bernoulli sub-ODE method in constructing various new optical soliton solutionsto the resonant nonlinear Schrodinger equation with both Spatio-temporal dispersion and inter-modal dispersion. Actually, the proposed method is effective tool to solve many other nonlinear partial differential equations in mathematical physics. Moreover this method can give a new infinite sequence of solutions. These solutions are expressed by hyperbolic functions, trigonometric functions and rational functions. Finally, with the aid of Matlab release 15, some graphical simulations were designed to see the behavior of these solutions

Deployment of Indoor LTE Small-Cells in TV White Spaces

In this thesis, we present a systematic computer-based approach to solve the problem of optimum transmitter placement for indoor LTE coverage systems operating in the TVWS. This approach is supported with rigorous simulations that reflect very promising results.This work focuses on the deployment of indoor LTE small cells acting as secondary transmitters in TVWS. Proposed methods make use of measurements stored in a Radio Environment Map (REM) that characterizes the DVB-T reception inside the building under consideration. Under this framework, this work analyses two different approaches for the deployment of small cells. First approach is based on maximizing total secondary transmit power inside the building, while the second approach is based on maximizing the percentage of positions having a Signal to Interference and Noise Ratio (SINR) above a desired threshold. Approaches are validated by means of rigorous simulations supported by real measurements of DVB-T signal reception. Results include optimum secondary transmitter placement, and transmit power values for providing indoor LTE coverage considering operating in a channel adjacent to the one used by DVB-T. These results are compared against exhaustive enumeration techniques and proven to provide very accurate results. Results reveal that when considering system capacity or network throughput, the second approach is more efficient and provides better results than the first approach. To the author's best knowledge, this model is the only model that provides an actual deployment strategy of indoor LTE secondary transmitters while considering interference constraints from adjacent channel DVB-T transmission. While our approaches are only tested in the considered building, the methods used are generic and can be applied in the same manner within any indoor environment provided that the REM for that environment is established