Functional Stratification of Cancer Drugs through Integrated Network Similarity

Heterogeneity across tumors is the main obstacle in developing treatment strategies. Drug molecules not only perturb their immediate protein targets but also modulate multiple signaling pathways. In this study, we explored the networks modulated by several drug molecules across multiple cancer cell lines by integrating the drug targets with transcriptomic and phosphoproteomic data. As a result, we obtained 236 reconstructed networks covering five cell lines and 70 drugs. A rigorous topological and pathway analysis showed that chemically and functionally different drugs may modulate overlapping networks. Additionally, we revealed a set of tumor-specific hidden pathways with the help of drug network models that are not detectable from the initial data. The difference in the target selectivity of the drugs leads to disjoint networks despite sharing the exact mechanism of action, e.g., HDAC inhibitors. We also used the reconstructed network models to study potential drug combinations based on the topological separation, found literature evidence for a set of drug pairs. Overall, the network-level exploration of the drug perturbations may potentially help optimize treatment strategies and suggest new drug combinations.

MICROBIOLOGICAL AND TREATMENT STUDIES OF OVINE FOOTROT INFECTION IN MOSUL AREA

It emerges from bacteriological study that it is possible to isolate many bacterial types and yeasts from the lesions of footrot infection in sheep. Anaerobic cultivation came out with the isolation of Spherophorus spp. (24%), Bacteroides spp. (60%), Corynebacterium spp. (64%), Enterobacteracae (76%), Streptococcus spp. (76%), Staphylococcus spp. (36%), Clostridum sordellii (46%) and Irichosporon cutaneum (4%). On the other hand aerobic cultivation rendered the isolation of Corynebacterium spp. (100%), Entrobacteracae (100%), Staphylococcus spp. (15%), Penicillium spp., Aspergillus fumigatus and Trichosporon cutaneum. Five different drug combinations were studied for their efficacy in the treatment of ovine footrot. Their healing rates were as follows : oxytetracycline (59%), oxytetracyclin with formaline (70.9%), Procaine penicillin and streptomycin (72.5%), Procaine penicillin and streptomycin with formaline dipping (80.76%), Formaline alone (63.8%). All kinds of treatment indicated statistically significant differences to exit between the treated (experimental) and untreated (control) groups

Molnupiravir combined with different repurposed drugs further inhibits SARS-CoV-2 infection in human nasal epithelium in vitro

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in late 2019, has caused a worldwide pandemic with unprecedented economic and societal impact. Currently, several vaccines are available, and multitudes of antiviral treatments have been proposed and tested. Although many of the vaccines show high clinical efficacy, they are not equally accessible worldwide. Additionally, due to the continuous emergence of new virus variants, and generally short duration of immunity, the development of safe and effective antiviral treatments remains of the utmost importance. Since the emergence of SARS-CoV-2, substantial efforts have been undertaken to repurpose existing and approved drugs for accelerated clinical testing and potential emergency use authorizations. However, drug-repurposing using high throughput screenings in cellular assays, often identify hits that later prove ineffective in clinical studies. Our approach was to evaluate the activity of compounds that have either been tested clinically or already undergone extensive preclinical profiling, using a standardized in vitro model of human nasal epithelium. Secondly, we evaluated drug combinations using sub-maximal doses of each active single compound. Here, we report the antiviral effects of 95 single compounds and 30 combinations. The data show that selected drug combinations including 10 μM of molnupiravir, a viral RNA-dependent RNA polymerase (RdRp) inhibitor, effectively inhibit SARS-CoV-2 replication. This indicates that such combinations are worthy of further evaluation as potential treatment strategies against coronavirus disease 2019 (COVID-19).

High-Throughput 3D Tumor Spheroid Array Platform for Evaluating Sensitivity of Proton-Drug Combinations

Proton beam therapy (PBT) is a critical treatment modality for head and neck squamous cell carcinoma (HNSCC). However, not much is known about drug combinations that may improve the efficacy of PBT. This study aimed to test the feasibility of a three-dimensional (3D) tumor-spheroid-based high-throughput screening platform that could assess cellular sensitivity against PBT. Spheroids of two HNSCC cell lines—Fadu and Cal27—cultured with a mixture of Matrigel were arrayed on a 384-pillar/well plate, followed by exposure to graded doses of protons or targeted drugs including olaparib at various concentrations. Calcein staining of HNSCC spheroids revealed a dose-dependent decrease in cell viability for proton irradiation or multiple targeted drugs, and provided quantitative data that discriminated the sensitivity between the two HNSCC cell lines. The combined effect of protons and olaparib was assessed by calculating the combination index from the survival rates of 4 × 4 matrices, showing that Cal27 spheroids had greater synergy with olaparib than Fadu spheroids. In contrast, adavosertib did not synergize with protons in both spheroids. Taken together, we demonstrated that the 3D pillar/well array platform was a useful tool that provided rapid, quantitative data for evaluating sensitivity to PBT and drug combinations. Our results further supported that administration of the combination of PBT and olaparib may be an effective treatment strategy for HNSCC patients.

Combination treatment optimization using a pan-cancer pathway model

The design of efficient combination therapies is a difficult key challenge in the treatment of complex diseases such as cancers. The large heterogeneity of cancers and the large number of available drugs renders exhaustive in vivo or even in vitro investigation of possible treatments impractical. In recent years, sophisticated mechanistic, ordinary differential equation-based pathways models that can predict treatment responses at a molecular level have been developed. However, surprisingly little effort has been put into leveraging these models to find novel therapies. In this paper we use for the first time, to our knowledge, a large-scale state-of-the-art pan-cancer signaling pathway model to identify candidates for novel combination therapies to treat individual cancer cell lines from various tissues (e.g., minimizing proliferation while keeping dosage low to avoid adverse side effects) and populations of heterogeneous cancer cell lines (e.g., minimizing the maximum or average proliferation across the cell lines while keeping dosage low). We also show how our method can be used to optimize the drug combinations used in sequential treatment plans—that is, optimized sequences of potentially different drug combinations—providing additional benefits. In order to solve the treatment optimization problems, we combine the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm with a significantly more scalable sampling scheme for truncated Gaussian distributions, based on a Hamiltonian Monte-Carlo method. These optimization techniques are independent of the signaling pathway model, and can thus be adapted to find treatment candidates for other complex diseases than cancers as well, as long as a suitable predictive model is available.

DERIVITISATION OF PREGABALIN FOR SIMULTANEOUS ESTIMATION WITH METHYLCOBALAMINE USING ULTRAVIOLET SPECTROSCOPY

Accurate, sensitive, and economical procedures for simultaneous estimation of pregabalin and methylcobalamine in tablet dosage form have been developed. The method employed is simultaneous equation method. This method employs the formation and solving of simultaneous equation using 528 nm and 568 nm as the two wavelengths for forming equation. Drugs obey Beer’s law in the concentration range 10-50 µg mL-1 for pregabalin and 10-50 µg mL-1 for methylcobalamine. The proposed spectrophotometric method was validated and successfully applied for the assay of both drug combinations in several laboratory prepared mixtures and commercial tablets