Erythroid/megakaryocytic differentiation confers BCL-XL dependency and venetoclax resistance in acute myeloid leukemia.

Myeloid neoplasms with erythroid or megakaryocytic differentiation include pure erythroid leukemia, myelodysplastic syndrome with erythroid features, and acute megakaryoblastic leukemia (FAB M7) and are characterized by poor prognosis and limited treatment options. Here, we investigate the drug sensitivity landscape of these rare malignancies. We show that acute myeloid leukemia (AML) cells with erythroid or megakaryocytic differentiation depend on the antiapoptotic protein B-cell lymphoma (BCL)-XL, rather than BCL-2, using combined ex vivo drug sensitivity testing, genetic perturbation, and transcriptomic profiling. High-throughput screening of >500 compounds identified the BCL-XL-selective inhibitor A-1331852 and navitoclax as highly effective against erythroid/megakaryoblastic leukemia cell lines. In contrast, these AML subtypes were resistant to the BCL-2 inhibitor venetoclax, which is used clinically in the treatment of AML. Consistently, genome-scale CRISPR-Cas9 and RNAi screening data demonstrated the striking essentiality of BCL-XL-encoding BCL2L1 but not BCL2 or MCL1, for the survival of erythroid/megakaryoblastic leukemia cell lines. Single-cell and bulk transcriptomics of patient samples with erythroid and megakaryoblastic leukemias identified high BCL2L1 expression compared with other subtypes of AML and other hematological malignancies, where BCL2 and MCL1 were more prominent. BCL-XL inhibition effectively killed blasts in samples from patients with AML with erythroid or megakaryocytic differentiation ex vivo and reduced tumor burden in a mouse erythroleukemia xenograft model. Combining the BCL-XL inhibitor with the JAK inhibitor ruxolitinib showed synergistic and durable responses in cell lines. Our results suggest targeting BCL-XL as a potential therapy option in erythroid/megakaryoblastic leukemias and highlight an AML subgroup with potentially reduced sensitivity to venetoclax-based treatments.

Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments.

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of Minimal Information for Chemosensitivity Assays (MICHA), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies as well as six recently conducted COVID-19 studies. With the MICHA web server and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

Exploration of databases and methods supporting drug repurposing: a comprehensive survey.

Drug development involves a deep understanding of the mechanisms of action and possible side effects of each drug, and sometimes results in the identification of new and unexpected uses for drugs, termed as drug repurposing. Both in case of serendipitous observations and systematic mechanistic explorations, confirmation of new indications for a drug requires hypothesis building around relevant drug-related data, such as molecular targets involved, and patient and cellular responses. These datasets are available in public repositories, but apart from sifting through the sheer amount of data imposing computational bottleneck, a major challenge is the difficulty in selecting which databases to use from an increasingly large number of available databases. The database selection is made harder by the lack of an overview of the types of data offered in each database. In order to alleviate these problems and to guide the end user through the drug repurposing efforts, we provide here a survey of 102 of the most promising and drug-relevant databases reported to date. We summarize the target coverage and types of data available in each database and provide several examples of how multi-database exploration can facilitate drug repurposing.

Using BERT to identify drug-target interactions from whole PubMed.

BACKGROUND: 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. RESULTS: Our novel method identified 0.6 million articles (along with drug and protein information) which are not previously included in public DTI databases. Using 10-fold cross-validation, we obtained ~ 99% accuracy for identifying articles containing quantitative drug-target profiles. The F1 micro for the prediction of assay format is 88%, which leaves room for improvement in future studies. CONCLUSION: The BERT model in this study is robust and the proposed pipeline can be used to identify previously overlooked articles containing quantitative DTIs. Overall, our method provides a significant advancement in machine-assisted DTI extraction and curation. We expect it to be a useful addition to drug mechanism discovery and repurposing.

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/.

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 co-cultured 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 (M1) marker, was higher in control- than patient-derived co-cultured 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.

Adenoviral Delivery of Tumor Necrosis Factor-α and Interleukin-2 Enables Successful Adoptive Cell Therapy of Immunosuppressive Melanoma.

Adoptive T-cell transfer is a promising treatment approach for metastatic cancer, but efficacy in solid tumors has only been achieved with toxic pre- and postconditioning regimens. Thus, adoptive T-cell therapies would benefit from complementary modalities that enable their full potential without excessive toxicity. We aimed to improve the efficacy and safety of adoptive T-cell transfer by using adenoviral vectors for direct delivery of immunomodulatory murine cytokines into B16.OVA melanoma tumors with concomitant T-cell receptor transgenic OT-I T-cell transfer. Armed adenoviruses expressed high local and low systemic levels of cytokine when injected into B16.OVA tumors, suggesting safety of virus-mediated cytokine delivery. Antitumor efficacy was significantly enhanced with adenoviruses coding for murine interleukin-2 (mIL-2) and tumor necrosis factor-α (mTNFα) when compared with T-cell transfer alone or viruses alone. Further improvement in efficacy was achieved with a triple combination of mIL-2, mTNFα, and OT-I T-cells. Mechanistic studies suggest that mIL-2 has an important role in activating T-cells at the tumor, while mTNFα induces chemokine expression. Furthermore, adenovirus treatments enhanced tumor-infiltration of OT-I T-cells as demonstrated by SPECT/CT imaging of (111)In-labeled cells. Our results suggest the utility of cytokine-coding adenoviruses for improving the efficacy of adoptive T-cell therapies.

Chronic Activation of Innate Immunity Correlates With Poor Prognosis in Cancer Patients Treated With Oncolytic Adenovirus.

Despite many clinical trials conducted with oncolytic viruses, the exact tumor-level mechanisms affecting therapeutic efficacy have not been established. Currently there are no biomarkers available that would predict the clinical outcome to any oncolytic virus. To assess the baseline immunological phenotype and find potential prognostic biomarkers, we monitored mRNA expression levels in 31 tumor biopsy or fluid samples from 27 patients treated with oncolytic adenovirus. Additionally, protein expression was studied from 19 biopsies using immunohistochemical staining. We found highly significant changes in several signaling pathways and genes associated with immune responses, such as B-cell receptor signaling (P < 0.001), granulocyte macrophage colony-stimulating factor (GM-CSF) signaling (P < 0.001), and leukocyte extravasation signaling (P < 0.001), in patients surviving a shorter time than their controls. In immunohistochemical analysis, markers CD4 and CD163 were significantly elevated (P = 0.020 and P = 0.016 respectively), in patients with shorter than expected survival. Interestingly, T-cell exhaustion marker TIM-3 was also found to be significantly upregulated (P = 0.006) in patients with poor prognosis. Collectively, these data suggest that activation of several functions of the innate immunity before treatment is associated with inferior survival in patients treated with oncolytic adenovirus. Conversely, lack of chronic innate inflammation at baseline may predict improved treatment outcome, as suggested by good overall prognosis.

MicroRNA-Attenuated Clone of Virulent Semliki Forest Virus Overcomes Antiviral Type I Interferon in Resistant Mouse CT-2A Glioma.

UNLABELLED: Glioblastoma is a terminal disease with no effective treatment currently available. Among the new therapy candidates are oncolytic viruses capable of selectively replicating in cancer cells, causing tumor lysis and inducing adaptive immune responses against the tumor. However, tumor antiviral responses, primarily mediated by type I interferon (IFN-I), remain a key problem that severely restricts viral replication and oncolysis. We show here that the Semliki Forest virus (SFV) strain SFV4, which causes lethal encephalitis in mice, is able to infect and replicate independent of the IFN-I defense in mouse glioblastoma cells and cell lines originating from primary human glioblastoma patient samples. The ability to tolerate IFN-I was retained in SFV4-miRT124 cells, a derivative cell line of strain SFV4 with a restricted capacity to replicate in neurons due to insertion of target sites for neuronal microRNA 124. The IFN-I tolerance was associated with the viral nsp3-nsp4 gene region and distinct from the genetic loci responsible for SFV neurovirulence. In contrast to the naturally attenuated strain SFV A7(74) and its derivatives, SFV4-miRT124 displayed increased oncolytic potency in CT-2A murine astrocytoma cells and in the human glioblastoma cell lines pretreated with IFN-I. Following a single intraperitoneal injection of SFV4-miRT124 into C57BL/6 mice bearing CT-2A orthotopic gliomas, the virus homed to the brain and was amplified in the tumor, resulting in significant tumor growth inhibition and improved survival. IMPORTANCE: Although progress has been made in development of replicative oncolytic viruses, information regarding their overall therapeutic potency in a clinical setting is still lacking. This could be at least partially dependent on the IFN-I sensitivity of the viruses used. Here, we show that the conditionally replicating SFV4-miRT124 virus shares the IFN-I tolerance of the pathogenic wild-type SFV, thereby allowing efficient targeting of a glioma that is refractory to naturally attenuated therapy vector strains sensitive to IFN-I. This is the first evidence of orthotopic syngeneic mouse glioma eradication following peripheral alphavirus administration. Our findings indicate a clear benefit in harnessing the wild-type virus replicative potency in development of next-generation oncolytic alphaviruses.

T-cell subsets in peripheral blood and tumors of patients treated with oncolytic adenoviruses.

The quality of the antitumor immune response is decisive when developing new immunotherapies for cancer. Oncolytic adenoviruses cause a potent immunogenic stimulus and arming them with costimulatory molecules reshapes the immune response further. We evaluated peripheral blood T-cell subsets of 50 patients with refractory solid tumors undergoing treatment with oncolytic adenovirus. These data were compared to changes in antiviral and antitumor T cells, treatment efficacy, overall survival, and T-cell subsets in pre- and post-treatment tumor biopsies. Treatment caused a significant (P < 0.0001) shift in T-cell subsets in blood, characterized by a proportional increase of CD8(+) cells, and decrease of CD4(+) cells. Concomitant treatment with cyclophosphamide and temozolomide resulted in less CD4(+) decrease (P = 0.041) than cyclophosphamide only. Interestingly, we saw a correlation between T-cell changes in peripheral blood and the tumor site. This correlation was positive for CD8(+) and inverse for CD4(+) cells. These findings give insight to the interconnections between peripheral blood and tumor-infiltrating lymphocyte (TIL) populations regarding oncolytic virotherapy. In particular, our data suggest that induction of T-cell response is not sufficient for clinical response in the context of immunosuppressive tumors, and that peripheral blood T cells have a complicated and potentially misleading relationship with TILs.