Artificial intelligence, machine learning, and drug repurposing in cancer

Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means. Areas covered: The authors focus on supervised ML and AI methods that make use of publicly available databases and information resources. While most of the example applications are in the field of anticancer drug therapies, the methods and resources reviewed are widely applicable also to other indications including COVID-19 treatment. A particular emphasis is placed on the use of comprehensive target activity profiles that enable a systematic repurposing process by extending the target profile of drugs to include potent off-targets with therapeutic potential for a new indication. Expert opinion: The scarcity of clinical patient data and the current focus on genetic aberrations as primary drug targets may limit the performance of anticancer drug repurposing approaches that rely solely on genomics-based information. Functional testing of cancer patient cells exposed to a large number of targeted therapies and their combinations provides an additional source of repurposing information for tissue-aware AI approaches.Peer reviewe

Using BERT to identify drug-target interactions from whole PubMed

Drug-target interactions (DTIs) are critical for drug repurposing and elucidation of drug mechanisms, and are manually curated by large databases, such as ChEMBL, BindingDB, DrugBank and DrugTargetCommons. However, the number of curated articles likely constitutes only a fraction of all the articles that contain experimentally determined DTIs. Finding such articles and extracting the experimental information is a challenging task, and there is a pressing need for systematic approaches to assist the curation of DTIs. To this end, we applied Bidirectional Encoder Representations from Transformers (BERT) to identify such articles. Because DTI data intimately depends on the type of assays used to generate it, we also aimed to incorporate functions to predict the assay format.Peer reviewe

Cancer-Targeted Oncolytic Adenoviruses for Modulation of the Immune System

Adenovirus is one of the most commonly used vectors for gene therapy and it is the first approved virus-derived drug for treatment of cancer. As an oncolytic agent, it can induce lysis of infected cells, but it can also engage the immune system, promoting activation and maturation of antigen-presenting cells (APCs). In essence, oncolysis combined with the associated immunostimulatory actions result in a "personalized in situ vaccine" for each patient. In order to take full advantage of these features, we should try to understand how adenovirus interacts with the immune system, what are the receptors involved in triggering subsequent signals and which kind of responses they elicit. Tackling these questions will give us further insight in how to manipulate adenovirus-mediated immune responses for enhancement of anti-tumor efficacy. In this review, we first highlight how oncolytic adenovirus interacts with the innate immune system and its receptors such as Toll-like receptors, nucleotide-binding and oligomerization domain (NOD)-like receptors and other immune sensors. Then we describe the effect of these interactions on the adaptive immune system and its cells, especially B and T lymphocytes. Finally, we summarize the most significant preclinical and clinical results in the field of gene therapy where researchers have engineered adenovirus to manipulate the host immune system by expressing cytokines and signal-ingmediators.Peer reviewe

DrugRepo: a novel approach to repurposing drugs based on chemical and genomic features

The drug development process consumes 9–12 years and approximately one billion US dollars in costs. Due to the high finances and time costs required by the traditional drug discovery paradigm, repurposing old drugs to treat cancer and rare diseases is becoming popular. Computational approaches are mainly data-driven and involve a systematic analysis of different data types leading to the formulation of repurposing hypotheses. This study presents a novel scoring algorithm based on chemical and genomic data to repurpose drugs for 669 diseases from 22 groups, including various cancers, musculoskeletal, infections, cardiovascular, and skin diseases. The data types used to design the scoring algorithm are chemical structures, drug-target interactions (DTI), pathways, and disease-gene associations. The repurposed scoring algorithm is strengthened by integrating the most comprehensive manually curated datasets for each data type. At DrugRepo score ≥ 0.4, we repurposed 516 approved drugs across 545 diseases. Moreover, hundreds of novel predicted compounds can be matched with ongoing studies at clinical trials. Our analysis is supported by a web tool available at: http://drugrepo.org/.Peer reviewe

Pancreatic cancer is associated with aberrant monocyte function and successive differentiation into macrophages with inferior anti-tumour characteristics

Background/objectives: Inflammation is related to the development and progression of pancreatic cancer (PC). Locally, anti-inflammatory macrophages (M2), and systemically, high levels of certain inflammation-modulating cytokines associate with poor prognosis in PC. The detailed effects of systemic inflammation on circulating monocytes and macrophage polarisation remain unknown. We aimed to find out how intracellular signalling of peripheral blood monocytes is affected by the systemic inflammatory state in PC patients and how it affects their differentiation into macrophages. Methods: Monocytes were isolated from 50 consenting PC patients and 20 healthy controls (HC). The phosphorylation status of the signalling molecules was assessed by flow cytometry both from unstimulated and appropriately stimulated monocytes. Monocytes derived from HC and PC patients were cocultured with cancer cells (MIA PaCa-2 and HPAF-II) in media supplemented with autologous serum, and the CD marker expression of the obtained macrophages was assessed by flow cytometry. Results: Phosphorylation levels of unstimulated STAT2, STAT3 and STAT6 were higher (p <0.05) and those of stimulated NF-kB (p = 0.004) and STAT5 (p = 0.006) were lower in patients than in controls. The expression of CD86, a proinflammatory (Ml) marker, was higher in control- than patient-derived cocultured macrophages (p = 0.029). Conclusions: Circulating monocytes from PC patients showed constitutive phosphorylation and weaker response to stimuli, indicating aberrant activation and immune suppression. When co-culturing the patient-derived monocytes with cancer cells, they differentiated into macrophages with reduced levels of M1 macrophage marker CD86, suggesting compromised anti-tumour features. The results highlight the need for global management of tumour-associated immune aberrations in PC treatment. (C) 2021 Published by Elsevier B.V. on behalf of IAP and EPC.Peer reviewe

Pancreatic Cancer Organoids in the Field of Precision Medicine: A Review of Literature and Experience on Drug Sensitivity Testing with Multiple Readouts and Synergy Scoring

Pancreatic ductal adenocarcinoma (PDAC) is a silent killer, often diagnosed late. However, it is also dishearteningly resistant to nearly all forms of treatment. New therapies are urgently needed, and with the advent of organoid culture for pancreatic cancer, an increasing number of innovative approaches are being tested. Organoids can be derived within a short enough time window to allow testing of several anticancer agents, which opens up the possibility for functional precision medicine for pancreatic cancer. At the same time, organoid model systems are being refined to better mimic the cancer, for example, by incorporation of components of the tumor microenvironment. We review some of the latest developments in pancreatic cancer organoid research and in novel treatment design. We also summarize our own current experiences with pancreatic cancer organoid drug sensitivity and resistance testing (DSRT) in 14 organoids from 11 PDAC patients. Our data show that it may be necessary to include a cell death read-out in ex vivo DSRT assays, as metabolic viability quantitation does not capture actual organoid killing. We also successfully adapted the organoid platform for drug combination synergy discovery. Lastly, live organoid culture 3D confocal microscopy can help identify individual surviving tumor cells escaping cell death even during harsh combination treatments. Taken together, the organoid technology allows the development of novel precision medicine approaches for PDAC, which paves the way for clinical trials and much needed new treatment options for pancreatic cancer patients

Pancreatic Cancer Organoids in the Field of Precision Medicine : A Review of Literature and Experience on Drug Sensitivity Testing with Multiple Readouts and Synergy Scoring

Pancreatic ductal adenocarcinoma (PDAC) is a silent killer, often diagnosed late. However, it is also dishearteningly resistant to nearly all forms of treatment. New therapies are urgently needed, and with the advent of organoid culture for pancreatic cancer, an increasing number of innovative approaches are being tested. Organoids can be derived within a short enough time window to allow testing of several anticancer agents, which opens up the possibility for functional precision medicine for pancreatic cancer. At the same time, organoid model systems are being refined to better mimic the cancer, for example, by incorporation of components of the tumor microenvironment. We review some of the latest developments in pancreatic cancer organoid research and in novel treatment design. We also summarize our own current experiences with pancreatic cancer organoid drug sensitivity and resistance testing (DSRT) in 14 organoids from 11 PDAC patients. Our data show that it may be necessary to include a cell death read-out in ex vivo DSRT assays, as metabolic viability quantitation does not capture actual organoid killing. We also successfully adapted the organoid platform for drug combination synergy discovery. Lastly, live organoid culture 3D confocal microscopy can help identify individual surviving tumor cells escaping cell death even during harsh combination treatments. Taken together, the organoid technology allows the development of novel precision medicine approaches for PDAC, which paves the way for clinical trials and much needed new treatment options for pancreatic cancer patients

Interactive visual analysis of drug-target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing

Knowledge of the full target space of drugs (or drug-like compounds) provides important insights into the potential therapeutic use of the agents to modulate or avoid their various on- and off-targets in drug discovery and precision medicine. However, there is a lack of consolidated databases and associated data exploration tools that allow for systematic profiling of drug target-binding potencies of both approved and investigational agents using a network-centric approach. We recently initiated a community-driven platform, Drug Target Commons (DTC), which is an open-data crowdsourcing platform designed to improve the management, reproducibility and extended use of compound-target bioactivity data for drug discovery and repurposing, as well as target identification applications. In this work, we demonstrate an integrated use of the rich bioactivity data from DTC and related drug databases using Drug Target Profiler (DTP), an open-source software and web tool for interactive exploration of drug-target interaction networks. DTP was designed for network-centric modeling of mode-of-action of multi-targeting anticancer compounds, especially for precision oncology applications. DTP enables users to construct an interaction network based on integrated bioactivity data across selected chemical compounds and their protein targets, further customizable using various visualization and filtering options, as well as cross-links to several drug and protein databases to provide comprehensive information of the network nodes and interactions. We demonstrate here the operation of the DTP tool and its unique features by several use cases related to both drug discovery and drug repurposing applications, using examples of anticancer drugs with shared target profiles. DTP is freely accessible at http://drugtargetprofiler.fimm.fi/

Attenuated Semliki Forest virus for cancer treatment in dogs : safety assessment in two laboratory Beagles

Background: Dogs suffer from spontaneous tumors which may be amenable to therapies developed for human cancer patients, and dogs may serve as large-animal cancer models. A non-pathogenic Semliki Forest virus vector VA7-EGFP previously showed promise in targeting human tumor xenografts in mice, but the oncolytic capacity of the virus in canine cancer cells and the safety of the virus in higher mammals such as dogs, are not known. We therefore assessed the oncolytic potency of VA7-EGFP against canine cancer cells by infectivity and viability assays in two dog solid tumor cell lines. Furthermore we performed a 3-week safety study in two adult Beagles which received a single intravenous injection of similar to 2 x 10(5) plaque forming units of parental A7(74) strain. Results: VA7-EGFP was able to replicate in and kill both canine cancer cell lines tested. No adverse events were observed in either of the two virus-injected adult Beagles and no infective virus could be recovered from any of the biological samples collected over the course of the study. Neutralizing antibodies to Semliki Forest virus became detectable in the dogs at 5 days post infection and remained elevated until study termination. Conclusions: Based on these results, testing of the oncolytic potential of attenuated Semliki Forest virus in canine cancer patients appears feasible.Peer reviewe

Safety and biodistribution of a double-deleted oncolytic vaccinia virus encoding CD40 ligand in laboratory Beagles

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