Gene expression-based chemical genomics identifies rapamycin as a modulator of MCL1 and glucocorticoid resistance

Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery

Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles offer a comprehensive view of drug mechanisms, inherent noise often obscures the true signal, hindering their potential for meaningful insights. Here, we highlight the development of TranSiGen, a deep generative model employing self-supervised representation learning. TranSiGen analyzes basal cell gene expression and molecular structures to reconstruct chemical-induced transcriptional profiles with high accuracy. By capturing both cellular and compound information, TranSiGen-derived representations demonstrate efficacy in diverse downstream tasks like ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. Notably, in vitro validation of TranSiGen's application in pancreatic cancer drug discovery highlights its potential for identifying effective compounds. We envisage that integrating TranSiGen into the drug discovery and mechanism research holds significant promise for advancing biomedicine.

Glucocorticoids paradoxically promote steroid resistance in B cell acute lymphoblastic leukemia through CXCR4/PLC signaling

Glucocorticoid (GC) resistance in childhood relapsed B-cell acute lymphoblastic leukemia (B-ALL) represents an important challenge. Despite decades of clinical use, the mechanisms underlying resistance remain poorly understood. Here, we report that in B-ALL, GC paradoxically induce their own resistance by activating a phospholipase C (PLC)-mediated cell survival pathway through the chemokine receptor, CXCR4. We identify PLC as aberrantly activated in GC-resistant B-ALL and its inhibition is able to induce cell death by compromising several transcriptional programs. Mechanistically, dexamethasone (Dex) provokes CXCR4 signaling, resulting in the activation of PLC-dependent Ca2+ and protein kinase C signaling pathways, which curtail anticancer activity. Treatment with a CXCR4 antagonist or a PLC inhibitor improves survival of Dex-treated NSG mice in vivo. CXCR4/PLC axis inhibition significantly reverses Dex resistance in B-ALL cell lines (in vitro and in vivo) and cells from Dex resistant ALL patients. Our study identifies how activation of the PLC signalosome in B-ALL by Dex limits the upfront efficacy of this chemotherapeutic agent.

Effectively α-Terpineol Suppresses Glioblastoma Aggressive Behavior and Downregulates KDELC2 Expression

BACKGROUND

Glioblastoma (GBM) is notorious for the aggressive behaviors and easily results in chemo-resistance. Studies have shown that the use of herbal medicines as treatments for GBM as limited by the blood-brain barrier (BBB) and glioma stem cells.

PURPOSE

The aim of this study was to investigate the relationship between GBM suppression and α-terpineol, the monoterpenoid alcohol derived from Eucalyptus glubulus and Pinus merkusii.

STUDY DESIGN

Using serial in-vitro and in-vivo studies to confirm the mechanism of α-terpineol on down-regulating GBM development.

METHODS

The 3-[4,5-dimethylthiazol-2-yl)]-2,5-diphenyltetrazolium bromide (MTT) assay was performed to evaluate IC50 of α-terpineol to inhibit GBM cell survival. In order to evaluate the impact of GBM aggressive behaviors by α-terpineol, the analysis of cell migration, invasion and colony formation were implemented. In addition, the ability of tumor spheres and WB of CD44 and OCT3/4 were evaluated under the impression of α-terpineol decreased GBM stemness. The regulation of neoangiogenesis by α-terpineol via the WB of angiogenic factors and human umbilical vein endothelial cells (HUVEC) tube assay. To survey the decided factors of α-terpineol downregulating GBM chemoresistance depended on the impact of O6-methylguanine-DNA methyltransferase (MGMT) expression and autophagy-related factors activation. Additionally, WB and quantitative real-time polymerase chain reaction (qRT/PCR) of KDEL (Lys-Asp-Glu-Leu) containing 2 (KDELC2), endoplasmic reticulum (ER) stress, phosphoinositide 3-kinase (PI3k), mammalian target of rapamycin (mTOR) and mitogen-activated protein kinase (MAPK) cascade signaling factors were examined to explore the mechanism of α-terpineol inhibiting GBM viability. Finally, the orthotopic GBM mouse model was applied to prove the efficacy and toxicity of α-terpineol on regulating GBM survival.

RESULTS

α-terpineol significantly suppressed GBM growth, migration, invasion, angiogenesis and temozolomide (TMZ) resistance. Furthermore, α-terpineol specifically targeted KDELC2 to downregulate Notch and PI3k/mTOR/MAPK signaling pathway. Finally, we also demonstrated that α-terpineol could penetrate the BBB to inhibit GBM proliferation, which resulted in reduced cytotoxicity to vital organs.

CONCLUSION

Compared to published literatures, we firstly proved α-terpineol possessed the capability to inhibit GBM through various mechanisms and potentially decreased the occurrence of chemoresistance, making it a promising alternative therapeutic option for GBM in the future.

G-protein signaling of oxytocin receptor as a potential target for cabazitaxel-resistant prostate cancer

Although the treatment armamentarium for patients with metastatic prostate cancer has improved recently, treatment options after progression on cabazitaxel (CBZ) are limited. To identify the mechanisms underlying CBZ resistance and therapeutic targets, we performed single-cell RNA sequencing of circulating tumor cells (CTCs) from patients with CBZ-resistant prostate cancer. Cells were clustered based on gene expression profiles. In silico screening was used to nominate candidate drugs for overcoming CBZ resistance in castration-resistant prostate cancer. CTCs were divided into three to four clusters, reflecting intrapatient tumor heterogeneity in refractory prostate cancer. Pathway analysis revealed that clusters in two cases showed up-regulation of the oxytocin (OXT) receptor-signaling pathway. Spatial gene expression analysis of CBZ-resistant prostate cancer tissues confirmed the heterogeneous expression of OXT-signaling molecules. Cloperastine (CLO) had significant antitumor activity against CBZ-resistant prostate cancer cells. Mass spectrometric phosphoproteome analysis revealed the suppression of OXT signaling specific to CBZ-resistant models. These results support the potential of CLO as a candidate drug for overcoming CBZ-resistant prostate cancer via the inhibition of OXT signaling.

JUN mediates glucocorticoid resistance by stabilizing HIF1a in T cell acute lymphoblastic leukemia

Dexamethasone (Dex) plays a critical role in T-ALL treatment, but the mechanisms of Dex resistance are poorly understood. Here, we demonstrated that the expression of JUN was regulated in Dex-resistant T-ALL cell lines and patient samples. JUN knockdown increased the sensitivity to Dex. Moreover, the survival data showed that high expression of JUN related to poor prognosis of T-ALL patients. Then, we generated dexamethasone-resistant clones and conducted RNA-seq and ATAC-seq. We demonstrated that the upregulation of JUN was most significant and regulated by JNK pathway in Dex-resistant cells. High-throughput screening showed that HIF1α inhibitors synergized with Dex could enhance Dex resistance cells death in vitro and in vivo. Additionally, JUN combined and stabilized HIF1α in Dex resistance cells. These results reveal a new mechanism of Dex resistance in T-ALL and provide experimental evidence for the potential therapeutic benefit of targeting the JNK-JUN-HIF1α axis for T-ALL treatment.

An integrated computational strategy to predict personalized cancer drug combinations by reversing drug resistance signatures

Drug resistance currently poses the greatest barrier to cancer treatments. To overcome drug resistance, drug combination therapy has been proposed as a promising treatment strategy. Herein, we present Re-Sensitizing Drug Prediction (RSDP), a novel computational strategy, for predicting the personalized cancer drug combination A + B by reversing the resistance signature of drug A. The process integrates multiple biological features using a robust rank aggregation algorithm, including Connectivity Map, synthetic lethality, synthetic rescue, pathway, and drug target. Bioinformatics assessments revealed that RSDP achieved a relatively accurate prediction performance for identifying personalized combinational re-sensitizing drug B against cell line-specific intrinsic resistance, cell line-specific acquired resistance, and patient-specific intrinsic resistance to drug A. In addition, we developed the largest resource of cell line-specific cancer drug resistance signatures, including intrinsic and acquired resistance, as a byproduct of the proposed strategy. The findings indicate that personalized drug resistance signature reversal is a promising strategy for identifying personalized drug combinations, which may guide future clinical decisions regarding personalized medicine.

PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer

Introduction

Endeavors in the molecular characterization of breast cancer opened the doors to endocrine therapies in ER+/HER2- breast cancer, increasing response rates substantially. Despite that, taxane-based neoadjuvant chemotherapy is still a cornerstone for achieving breast-conserving surgery and complete tumor resection in locally advanced cancers with high recurrence risk. Nonetheless, the rate of chemoresistance is high, and deselecting patients who will not benefit from chemotherapy is a significant task to prevent futile toxicities. Several multigene assays are being used to guide decisions on chemotherapy. However, their development as prognostic assays but not predictive assays limits predictive strength, leading to discordant results. Moreover, high costs impediment their use in developing countries. For global health equity, robust predictors that can be cost-effectively incorporated into routine clinical management are essential.

Methods

In this study, we comprehensively analyzed 5 GEO datasets, 2 validation sets, and The Cancer Genome Atlas breast cancer data to identify predictors of resistance to taxane-based neoadjuvant therapy in ER+/HER2- breast cancer using efficient bioinformatics algorithms.

Results

Gene expression and gene set enrichment analysis of 5 GEO datasets revealed the upregulation of 63 genes and the enrichment of CTNNB1-related oncogenic signatures in non-responsive patients. We validated the upregulation and predictive strength of 18 genes associated with resistance in the validation cohort, all exhibiting higher predictive powers for residual disease and higher specificities for ER+/HER2- breast cancers compared to one of the benchmark multi-gene assays. Cox Proportional Hazards Regression in three different treatment arms (neoadjuvant chemotherapy, endocrine therapy, and no systemic treatment) in a second comprehensive validation cohort strengthened the significance of PTCH1 and CTNNB1 as key predictors, with hazard ratios over 1.5, and 1.6 respectively in the univariate and multivariate models.

Discussion

Our results strongly suggest that PTCH1 and CTNNB1 can be used as robust and cost-effective predictors in developing countries to guide decisions on chemotherapy in ER +/HER2- breast cancer patients with a high risk of recurrence. The dual function of PTCH1 as a multidrug efflux pump and a hedgehog receptor, and the active involvement of CTNNB1 in breast cancer strongly indicate that PTCH1 and CTNNB1 can be potential drug targets to overcome chemoresistance in ER +/HER2- breast cancer patients.

Regulators mount up: the metabolic roles of apoptotic proteins

The induction of apoptosis, a programmed cell death pathway governed by activation of caspases, can result in fundamental changes in metabolism that either facilitate or restrict the execution of cell death. In addition, metabolic adaptations can significantly impact whether cells in fact initiate the apoptotic cascade. In this mini-review, we will highlight and discuss the interconnectedness of apoptotic regulation and metabolic alterations, two biological outcomes whose regulators are intertwined.

mTOR in programmed cell death and its therapeutic implications

Mechanistic target of rapamycin (mTOR), a highly conserved serine/threonine kinase, is involved in cellular metabolism, protein synthesis, and cell death. Programmed cell death (PCD) assists in eliminating aging, damaged, or neoplastic cells, and is indispensable for sustaining normal growth, fighting pathogenic microorganisms, and maintaining body homeostasis. mTOR has crucial functions in the intricate signaling pathway network of multiple forms of PCD. mTOR can inhibit autophagy, which is part of PCD regulation. Cell survival is affected by mTOR through autophagy to control reactive oxygen species production and the degradation of pertinent proteins. Additionally, mTOR can regulate PCD in an autophagy-independent manner by affecting the expression levels of related genes and phosphorylating proteins. Therefore, mTOR acts through both autophagy-dependent and -independent pathways to regulate PCD. It is conceivable that mTOR exerts bidirectional regulation of PCD, such as ferroptosis, according to the complexity of signaling pathway networks, but the underlying mechanisms have not been fully explained. This review summarizes the recent advances in understanding mTOR-mediated regulatory mechanisms in PCD. Rigorous investigations into PCD-related signaling pathways have provided prospective therapeutic targets that may be clinically beneficial for treating various diseases.

Beyond Corticoresistance, A Paradoxical Corticosensitivity Induced by Corticosteroid Therapy in Pediatric Acute Lymphoblastic Leukemias

Known as a key effector in relapse of acute lymphoblastic leukemia (ALL), resistance to drug-induced apoptosis, is tightly considered one of the main prognostic factors for the disease. ALL cells are constantly developing cellular strategies to survive and resist therapeutic drugs. Glucocorticoids (GCs) are one of the most important agents used in the treatment of ALL due to their ability to induce cell death. The mechanisms of GC resistance of ALL cells are largely unknown and intense research is currently focused on this topic. Such resistance can involve different cellular and molecular mechanisms, including the modulation of signaling pathways involved in the regulation of proliferation, apoptosis, autophagy, metabolism, epigenetic modifications and tumor suppressors. Recently, several studies point to the paradoxical role of GCs in many survival processes that may lead to therapy-induced resistance in ALL cells, which we called "paradoxical corticosensitivity". In this review, we aim to summarize all findings on cell survival pathways paradoxically activated by GCs with an emphasis on previous and current knowledge on gene expression and signaling pathways.

Anti-Leukemic Effects of Idesia polycarpa Maxim Branch on Human B-Cell Acute Lymphoblastic Leukemia Cells

Patients with pediatric B-cell acute lymphoblastic leukemia (B-ALL) have a high survival rate, yet the prognosis of adults and patients with relapsed/refractory disease is relatively poor. Therefore, it is imperative to develop new therapeutic strategies. Here, we screened 100 plant extracts from South Korean Flora and investigated their anti-leukemic effect using CCRF-SB cells as a B-ALL model. The top cytotoxic extract identified in this screening was the Idesia polycarpa Maxim. branch (IMB), which efficiently inhibited the survival and proliferation of CCRF-SB cells, while having minimal to no impact on normal murine bone marrow cells. Mechanistically, the IMB-induced proapoptotic effect involves the increase of caspase 3/7 activity, which was shown to be associated with the disruption of the mitochondrial membrane potential (MMP) through the reduction in antiapoptotic Bcl-2 family expression. IMB also promoted the differentiation of CCRF-SB cells via the upregulation of the expression of differentiation-related genes, PAX5 and IKZF1. Given that resistance to glucocorticoid (GC) is often found in patients with relapsed/refractory ALL, we investigated whether IMB could restore GC sensitivity. IMB synergized GC to enhance apoptotic rate by increasing GC receptor expression and downmodulating mTOR and MAPK signals in CCRF-SB B-ALL cells. These results suggest that IMB has the potential to be a novel candidate for the treatment of B-ALL.

Discovery of a new candidate drug to overcome cabazitaxel-resistant gene signature in castration-resistant prostate cancer by in silico screening

BACKGROUND

The taxane cabazitaxel (CBZ) is a promising treatment for docetaxel-resistant castration-resistant prostate cancer (CRPC). However, the survival benefit with CBZ for patients with CRPC is limited. This study used screening tests for candidate drugs targeting CBZ-resistant-related gene expression and identified pimozide as a potential candidate for overcoming CBZ resistance in CRPC.

METHODS

We established CBZ-resistant cell lines, DU145CR and PC3CR by incubating DU145 cells and PC3 cells with gradually increasing concentrations of CBZ. We performed in silico drug screening for candidate drugs that could reprogram the gene expression signature of a CBZ-resistant prostate cancer cells using a Connectivity Map. The in vivo effect of the drug combination was tested in xenograft mice models.

RESULTS

We identified pimozide as a promising candidate drug for CBZ-resistant CRPC. Pimozide had a significant antitumor effect on DU145CR cells. Moreover, combination treatment with pimozide and CBZ had a synergic effect for DU145CR cells in vitro and in vivo. Microarray analysis identified AURKB and KIF20A as potential targets of pimozide in CBZ-resistant CRPC. DU145CR had significantly higher AURKB and KIF20A expression compared with a non-CBZ-resistant cell line. Inhibition of AURKB and KIF20A had an antitumor effect in DU145CR xenograft tumors. Higher expression of AURKB and KIF20A was a poor prognostic factor of TGCA prostate cancer cohort. CBZ-resistant prostate cancer tissues in our institution had higher AURKB and KIF20A expression.

CONCLUSIONS

Pimozide appears to be a promising drug to overcome CBZ resistance in CRPC by targeting AURKB and KIF20A.

Cell-specific imputation of drug connectivity mapping with incomplete data

Drug repositioning allows expedited discovery of new applications for existing compounds, but re-screening vast compound libraries is often prohibitively expensive. "Connectivity mapping" is a process that links drugs to diseases by identifying compounds whose impact on expression in a collection of cells reverses the disease's impact on expression in disease-relevant tissues. The LINCS project has expanded the universe of compounds and cells for which data are available, but even with this effort, many clinically useful combinations are missing. To evaluate the possibility of repurposing drugs despite missing data, we compared collaborative filtering using either neighborhood-based or SVD imputation methods to two naive approaches via cross-validation. Methods were evaluated for their ability to predict drug connectivity despite missing data. Predictions improved when cell type was taken into account. Neighborhood collaborative filtering was the most successful method, with the best improvements in non-immortalized primary cells. We also explored which classes of compounds are most and least reliant on cell type for accurate imputation. We conclude that even for cells in which drug responses have not been fully characterized, it is possible to identify unassayed drugs that reverse in those cells the expression signatures observed in disease.

Targeted Treatment and Immunotherapy in High-risk and Relapsed/ Refractory Pediatric Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia is the most frequent pediatric malignancy in children, comprising 30% of all pediatric malignancies; adult ALL comprises 5% of all ALL cases, which have a 186.6 per 1 million incidence. In pediatric ALL (pALL), on which this review focuses, approximately 1 in 285 children are diagnosed with cancer before the age of 20, and approximately 1 in 530 young adults between the ages of 20 and 39 years old is a childhood cancer survivor. The survival probability in pALL is now very high, approximately 80-90%. Thus, the most important is to improve supportive care and treatment based on relapse risk, optimally being based on the genetic feature of malignant cells. Improvements made by now are mainly the classifying of subgroups based on genetic characteristics such as aneuploidy or translocation and aligning them with treatment response. Relevant genetic changes in ALL pathogenesis are transcription regulators of lymphoid development (PAX5, IKZF1, EBF1, and LEF1) and/or coactivators (TBL1XR1 and ERG), lymphoid signaling (BTLA, and CD200 TOX), and tumor suppressor genes (CDKN2A, CDKN2B, RB1, and TP53). This review aims to summarize treatment strategies inhibiting tyrosine kinases, influencing different signaling pathways, BCL inhibitors, and anti-CD therapy (anti-cluster differentiation therapy) in pALL. CAR T-cell therapy (chimeric antigen receptors T-cell therapy) is under research and requires further development.

Glutamine synthetase limits β-catenin-mutated liver cancer growth by maintaining nitrogen homeostasis and suppressing mTORC1

Glutamine synthetase (GS) catalyzes de novo synthesis of glutamine that facilitates cancer cell growth. In the liver, GS functions next to the urea cycle to remove ammonia waste. As a dysregulated urea cycle is implicated in cancer development, the impact of GS's ammonia clearance function has not been explored in cancer. Here, we show that oncogenic activation of β-catenin (encoded by CTNNB1) led to a decreased urea cycle and elevated ammonia waste burden. While β-catenin induced the expression of GS, which is thought to be cancer promoting, surprisingly, genetic ablation of hepatic GS accelerated the onset of liver tumors in several mouse models that involved β-catenin activation. Mechanistically, GS ablation exacerbated hyperammonemia and facilitated the production of glutamate-derived nonessential amino acids, which subsequently stimulated mechanistic target of rapamycin complex 1 (mTORC1). Pharmacological and genetic inhibition of mTORC1 and glutamic transaminases suppressed tumorigenesis facilitated by GS ablation. While patients with hepatocellular carcinoma, especially those with CTNNB1 mutations, have an overall defective urea cycle and increased expression of GS, there exists a subset of patients with low GS expression that is associated with mTORC1 hyperactivation. Therefore, GS-mediated ammonia clearance serves as a tumor-suppressing mechanism in livers that harbor β-catenin activation mutations and a compromised urea cycle.

Oncogenic deubiquitination controls tyrosine kinase signaling and therapy response in acute lymphoblastic leukemia

Dysregulation of kinase signaling pathways favors tumor cell survival and therapy resistance in cancer. Here, we reveal a posttranslational regulation of kinase signaling and nuclear receptor activity via deubiquitination in T cell acute lymphoblastic leukemia (T-ALL). We observed that the ubiquitin-specific protease 11 (USP11) is highly expressed and associates with poor prognosis in T-ALL. USP11 ablation inhibits leukemia progression in vivo, sparing normal hematopoiesis. USP11 forms a complex with USP7 to deubiquitinate the oncogenic lymphocyte cell-specific protein-tyrosine kinase (LCK) and enhance its activity. Impairment of LCK activity leads to increased glucocorticoid receptor (GR) expression and glucocorticoids sensitivity. Genetic knockout of USP7 improved the antileukemic efficacy of glucocorticoids in vivo. The transcriptional activation of GR target genes is orchestrated by the deubiquitinase activity and mediated via an increase in enhancer-promoter interaction intensity. Our data unveil how dysregulated deubiquitination controls leukemia survival and drug resistance, suggesting previously unidentified therapeutic combinations toward targeting leukemia.

Artificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors

BACKGROUND

Vast amounts of rapidly accumulating biological data related to cancer and a remarkable progress in the field of artificial intelligence (AI) have paved the way for precision oncology. Our recent contribution to this area of research is CancerOmicsNet, an AI-based system to predict the therapeutic effects of multitargeted kinase inhibitors across various cancers. This approach was previously demonstrated to outperform other deep learning methods, graph kernel models, molecular docking, and drug binding pocket matching.

METHODS

CancerOmicsNet integrates multiple heterogeneous data by utilizing a deep graph learning model with sophisticated attention propagation mechanisms to extract highly predictive features from cancer-specific networks. The AI-based system was devised to provide more accurate and robust predictions than data-driven therapeutic discovery using gene signature reversion.

RESULTS

Selected CancerOmicsNet predictions obtained for "unseen" data are positively validated against the biomedical literature and by live-cell time course inhibition assays performed against breast, pancreatic, and prostate cancer cell lines. Encouragingly, six molecules exhibited dose-dependent antiproliferative activities, with pan-CDK inhibitor JNJ-7706621 and Src inhibitor PP1 being the most potent against the pancreatic cancer cell line Panc 04.03.

CONCLUSIONS

CancerOmicsNet is a promising AI-based platform to help guide the development of new approaches in precision oncology involving a variety of tumor types and therapeutics.

mTORC1 beyond anabolic metabolism: Regulation of cell death

The mechanistic target of rapamycin complex 1 (mTORC1), a multi-subunit protein kinase complex, interrogates growth factor signaling with cellular nutrient and energy status to control metabolic homeostasis. Activation of mTORC1 promotes biosynthesis of macromolecules, including proteins, lipids, and nucleic acids, and simultaneously suppresses catabolic processes such as lysosomal degradation of self-constituents and extracellular components. Metabolic regulation has emerged as a critical determinant of various cellular death programs, including apoptosis, pyroptosis, and ferroptosis. In this article, we review the expanding knowledge on how mTORC1 coordinates metabolic pathways to impinge on cell death regulation. We focus on the current understanding on how nutrient status and cellular signaling pathways connect mTORC1 activity with ferroptosis, an iron-dependent cell death program that has been implicated in a plethora of human diseases. In-depth understanding of the principles governing the interaction between mTORC1 and cell death pathways can ultimately guide the development of novel therapies for the treatment of relevant pathological conditions.

MCL-1 is a master regulator of cancer dependency on fatty acid oxidation

MCL-1 is an anti-apoptotic BCL-2 family protein essential for survival of diverse cell types and is a major driver of cancer and chemoresistance. The mechanistic basis for the oncogenic supremacy of MCL-1 among its anti-apoptotic homologs is unclear and implicates physiologic roles of MCL-1 beyond apoptotic suppression. Here we find that MCL-1-dependent hematologic cancer cells specifically rely on fatty acid oxidation (FAO) as a fuel source because of metabolic wiring enforced by MCL-1 itself. We demonstrate that FAO regulation by MCL-1 is independent of its anti-apoptotic activity, based on metabolomic, proteomic, and genomic profiling of MCL-1-dependent leukemia cells lacking an intact apoptotic pathway. Genetic deletion of Mcl-1 results in transcriptional downregulation of FAO pathway proteins such that glucose withdrawal triggers cell death despite apoptotic blockade. Our data reveal that MCL-1 is a master regulator of FAO, rendering MCL-1-driven cancer cells uniquely susceptible to treatment with FAO inhibitors.

Reversal of IKZF1-induced glucocorticoid resistance by dual targeting of AKT and ERK signaling pathways

Although long-term survival in pediatric acute lymphoblastic leukemia (ALL) currently exceeds 90%, some subgroups, defined by specific genomic aberrations, respond poorly to treatment. We previously reported that leukemias harboring deletions or mutations affecting the B-cell transcription factor IKZF1 exhibit a tumor cell intrinsic resistance to glucocorticoids (GCs), one of the cornerstone drugs used in the treatment of ALL. Here, we identified increased activation of both AKT and ERK signaling pathways as drivers of GC resistance in IKZF1-deficient leukemic cells. Indeed, combined pharmacological inhibition of AKT and ERK signaling effectively reversed GC resistance in IKZF1-deficient leukemias. As inhibitors for both pathways are under clinical investigation, their combined use may enhance the efficacy of prednisolone-based therapy in this high-risk patient group.

Targeting the Unwindosome by Mebendazole Is a Vulnerability of Chemoresistant Hepatoblastoma

Resistance to conventional chemotherapy remains a huge challenge in the clinical management of hepatoblastoma, the most common liver tumor in childhood. By integrating the gene expression data of hepatoblastoma patients into the perturbation prediction tool Connectivity Map, we identified the clinical widely used anthelmintic mebendazole as a drug to circumvent chemoresistance in permanent and patient-derived xenograft cell lines that are resistant to cisplatin, the therapeutic backbone of hepatoblastoma treatment. Viability assays clearly indicated a potent reduction of tumor cell growth upon mebendazole treatment in a dose-dependent manner. The combination of mebendazole and cisplatin revealed a strong synergistic effect, which was comparable to the one seen with cisplatin and doxorubicin, the current treatment for high-risk hepatoblastoma patients. Moreover, mebendazole treatment resulted in reduced colony and tumor spheroid formation capabilities, cell cycle arrest, and induction of apoptosis of hepatoblastoma cells. Mechanistically, mebendazole causes blockage of microtubule formation and transcriptional downregulation of genes encoding the unwindosome, which are highly expressed in chemoresistant tumors. Most importantly, mebendazole significantly reduced tumor growth in a subcutaneous xenograft transplantation mouse model without side effects. In conclusion, our results strongly support the clinical use of mebendazole in the treatment of chemoresistant hepatoblastoma and highlight the potential theranostic value of unwindosome-associated genes.

Scope of repurposed drugs against the potential targets of the latest variants of SARS-CoV-2

The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing.

Circulating tumor and invasive cell expression profiling predicts effective therapy in pancreatic cancer

BACKGROUND

Pancreatic adenocarcinoma (PDAC) remains a refractory disease; however, modern cytotoxic chemotherapeutics can induce tumor regression and extend life. A blood-based, pharmacogenomic, chemosensitivity assay using gene expression profiling of circulating tumor and invasive cells (CTICs) to predict treatment response was previously developed. The combination regimen of 5-fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) and gemcitabine/nab-paclitaxel (G/nab-P) are established frontline approaches for treating advanced PDAC; however, there are no validated biomarkers for treatment selection. A similar unmet need exists for choosing second-line therapy.

METHODS

The chemosensitivity assay was evaluated in metastatic PDAC patients presenting for frontline treatment. A prospective study enrolled patients (n = 70) before receiving either FOLFIRINOX or G/nab-P at a 1:1 ratio. Six milliliters of peripheral blood was collected at baseline and at time of disease progression. CTICs were isolated, gene-expression profiling was performed, and the assay was used to predict effective and ineffective chemotherapeutic agents. Treating physicians were blinded to the assay prediction results.

RESULTS

Patients receiving an effective regimen as predicted by the chemosensitivity assay experienced significantly longer median progression-free survival (mPFS; 7.8 months vs. 4.2 months; hazard ratio [HR], 0.35; p = .0002) and median overall survival (mOS; 21.0 months vs. 9.7 months; HR, 0.40; p = .005), compared with an ineffective regimen. Assay prediction for effective second-line therapy was explored. The entire study cohort experienced favorable outcomes compared with historical controls, 7.1-month mPFS and 12.3-month mOS.

CONCLUSIONS

Chemosensitivity assay profiling is a promising tool for guiding therapy in advanced PDAC. Further prospective validation is under way (clinicaltrials.gov NCT03033927).

MCL-1 is a clinically targetable vulnerability in breast cancer

Pro-survival members of the BCL-2 family, including MCL-1, are emerging as important proteins during the development and therapeutic response of solid tumors. Notably, high levels of MCL-1 occur in breast cancer, where functional dependency has been demonstrated using cell lines and mouse models. The utility of restoring apoptosis in cancer cells through inhibition of pro-survival BCL-2 proteins has been realized in the clinic, where the first specific inhibitor of BCL-2 is approved for use in leukemia. A variety of MCL-1 inhibitors are now undergoing clinical trials for blood cancer treatment and application of this new class of drugs is also being tested in solid cancers. On-target compounds specific to MCL-1 have demonstrated promising efficacy in preclinical models of breast cancer and show potential to enhance the anti-tumor effect of conventional therapies. Taken together, this makes MCL-1 an extremely attractive target for clinical evaluation in the context of breast cancer.Abbreviations: ADC (antibody-drug conjugate); AML (Acute myeloid leukemia); APAF1 (apoptotic protease activating factor 1); bCAFs (breast cancer associated fibroblasts); BCL-2 (B-cell lymphoma 2); BH (BCL-2 homology); CLL (chronic lymphocytic leukemia); EGF (epidermal growth factor); EMT (epithelial to mesenchymal transition); ER (estrogen receptor); FDA (food and drug administration); GEMM (genetically engineered mouse model); HER2 (human epidermal growth factor 2); IL6 (interleukin 6); IMM (inner mitochondrial membrane); IMS (intermembrane space); MCL-1 (myeloid cell leukemia-1); MOMP (mitochondrial outer membrane permeabilisation); MM (multiple myeloma); PDX (patient-derived xenograft); OMM (outer mitochondrial membrane); PROTAC (proteolysis-targeting chimeras) TNBC (triple negative breast cancer); UPS (ubiquitin mediated proteolysis system).

Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing

Chemical-induced gene expression profiles provide critical information of chemicals in a biological system, thus offering new opportunities for drug discovery. Despite their success, large-scale analysis leveraging gene expressions is limited by time and cost. Although several methods for predicting gene expressions were proposed, they only focused on imputation and classification settings, which have limited applications to real-world scenarios of drug discovery. Therefore, a chemical-induced gene expression ranking (CIGER) framework is proposed to target a more realistic but more challenging setting in which overall rankings in gene expression profiles induced by de novo chemicals are predicted. The experimental results show that CIGER significantly outperforms existing methods in both ranking and classification metrics. Furthermore, a drug screening pipeline based on CIGER is proposed to identify potential treatments of drug-resistant pancreatic cancer. Our predictions have been validated by experiments, thereby showing the effectiveness of CIGER for phenotypic compound screening of precision medicine.

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A new deep-learning method (CIGER) for chemical-induced gene expression ranking

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CIGER can predict gene expression for de novo chemicals from chemical structures

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We discovered drugs for the treatment of drug-resistant pancreatic cancer

In recent years, a phenotype-based drug discovery approach using chemical-induced gene expressions has shown to be effective in drug discovery and precision medicine. However, it is not feasible to experimentally determine chemical-induced gene expressions for all available chemicals of interest, thereby hindering the application of gene expression-based compound screening on a large scale. Thus, it is crucial to design a computational approach that can generate gene expression information for any chemicals. We proposed a new, deep-learning framework named chemical-induced gene expression ranking (CIGER) to predict a landmark gene expression profile (i.e., gene ranking) induced by de novo chemicals based on their chemical structures. Leveraging CIGER, we predicted and experimentally validated that several existing drugs can increase the therapeutic response on drug-resistant pancreatic cancer. Our results demonstrated the effectiveness of CIGER for precision drug discovery in practice.

Rapamycin Promotes the Expansion of Myeloid Cells by Increasing G-CSF Expression in Mesenchymal Stem Cells

Rapamycin, also known as sirolimus, an inhibitor of mammalian target of rapamycin (mTOR), is a regulatory kinase responsible for multiple signal transduction pathways. Although rapamycin has been widely used in treating various hematologic diseases, the effects of rapamycin are still not fully understood. Here we found that both oral and intraperitoneal administration of rapamycin led to the expansion of myeloid lineage, while intraperitoneal administration of rapamycin impaired granulocyte differentiation in mice. Rapamycin induced bone marrow mesenchymal stem cells to produce more G-CSF in vitro and in vivo, and promoted the myeloid cells expansion. Our results thus demonstrated that intraperitoneal administration of rapamycin might promote the expansion of myeloid lineage while impair myeloid cell differentiation in vivo.

Impact of Glucocorticoid Use in Oncology in the Immunotherapy Era

Thanks to their anti-inflammatory, anti-oedema, and anti-allergy properties, glucocorticoids are among the most widely prescribed drugs in patients with cancer. The indications for glucocorticoid use are very wide and varied in the context of cancer and include the symptomatic management of cancer-related symptoms (compression, pain, oedema, altered general state) but also prevention or treatment of common side effects of anti-cancer therapies (nausea, allergies, etc.) or immune-related adverse events (irAE). In this review, we first give an overview of the different clinical situations where glucocorticoids are used in oncology. Next, we describe the current state of knowledge regarding the effects of these molecules on immune response, in particular anti-tumour response, and we summarize available data evaluating how these effects may interfere with the efficacy of immunotherapy using immune checkpoint inhibitors.

A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer

Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed expression data, providing enormous opportunities for computational therapeutic discovery. However, there is no consensus on which methodologies and parameters are the most optimal to conduct such analysis. Aiming to fill this gap, new benchmarking standards were developed to quantitatively evaluate drug retrieval performance. Investigations of potential factors influencing drug retrieval were conducted based on these standards. As a result, we determined an optimal approach for LINCS data-based therapeutic discovery. With this approach, homoharringtonine (HHT) was identified to be a candidate agent with potential therapeutic and preventive effects on liver cancer. The antitumor and antifibrotic activity of HHT was validated experimentally using subcutaneous xenograft tumor model and carbon tetrachloride (CCL₄)-induced liver fibrosis model, demonstrating the reliability of the prediction results. In summary, our findings will not only impact the future applications of LINCS data but also offer new opportunities for therapeutic intervention of liver cancer.

The long winding road to the safer glucocorticoid receptor (GR) targeting therapies

Glucocorticoids (Gcs) are widely used to treat inflammatory diseases and hematological malignancies, and despite the introduction of novel anti-inflammatory and anti-cancer biologics, the use of inexpensive and effective Gcs is expected to grow. Unfortunately, chronic treatment with Gcs results in multiple atrophic and metabolic side effects. Thus, the search for safer glucocorticoid receptor (GR)-targeted therapies that preserve therapeutic potential of Gcs but result in fewer adverse effects remains highly relevant. Development of selective GR agonists/modulators (SEGRAM) with reduced side effects, based on the concept of dissociation of GR transactivation and transrepression functions, resulted in limited success, and currently focus has shifted towards partial GR agonists. Additional approach is the identification and inhibition of genes associated with Gcs specific side effects. Others and we recently identified GR target genes REDD1 and FKBP51 as key mediators of Gcs-induced atrophy, and selected and validated candidate molecules for REDD1 blockage including PI3K/Akt/mTOR inhibitors. In this review, we summarized classic and contemporary approaches to safer GR-mediated therapies including unique concept of Gcs combination with REDD1 inhibitors. We discussed protective effects of REDD1 inhibitors against Gcs–induced atrophy in skin and bone and underlined the translational potential of this combination for further development of safer and effective Gcs-based therapies.

Overcoming Drug Resistance in Advanced Prostate Cancer by Drug Repurposing

Prostate cancer (PCa) is the second most common cancer in men. Common treatments include active surveillance, surgery, or radiation. Androgen deprivation therapy and chemotherapy are usually reserved for advanced disease or biochemical recurrence, such as castration-resistant prostate cancer (CRPC), but they are not considered curative because PCa cells eventually develop drug resistance. The latter is achieved through various cellular mechanisms that ultimately circumvent the pharmaceutical’s mode of action. The need for novel therapeutic approaches is necessary under these circumstances. An alternative way to treat PCa is by repurposing of existing drugs that were initially intended for other conditions. By extrapolating the effects of previously approved drugs to the intracellular processes of PCa, treatment options will expand. In addition, drug repurposing is cost-effective and efficient because it utilizes drugs that have already demonstrated safety and efficacy. This review catalogues the drugs that can be repurposed for PCa in preclinical studies as well as clinical trials.

PON2 blockade overcomes dexamethasone resistance in acute lymphoblastic leukemia

OBJECTIVES

The high frequency of chemotherapy resistance is ultimately responsible for clinical relapse in acute lymphoblastic leukemia (ALL). Nevertheless, the molecular mechanism relevant to glucocorticoid (GC) resistance remains ambiguous.

METHODS

Quantitative real-time polymerase chain reaction and Western blot were performed to detect the expressions of paraoxonase 2 (PON2), Bcl-2 and Bax. shRNA was used to knockdown PON2 expression in SUP-B15 and REH cell. CCK-8 and flow cytometry assay were conducted to monitor the changes of proliferation and apoptosis in ALL cells. The growth of ALL REH cells in vivo was determined using transplanted tumor model.

RESULTS

This study was designed to identify GC resistance-associated genes by means of the transcriptome chip from the public Gene Expression Omnibus database, and preliminarily investigation of dexamethasone (DEX)-resistance mechanism in ALL. We disclosed that PON2 expression was elevated in ALL patients and especially higher in DEX-resistance ALL patients. Then, cell apoptosis assay suggested that silencing of PON2 dramatically promoted in DEX-resistant ALL cells apoptosis and the activity of Caspase 3 induced by DEX administration. In xenograft tumor model, PON2 knockdown significantly reduced DEX-resistant ALL cells growth in immunodeficient mice.

CONCLUSIONS

Collectively, inhibition of PON2 may represent a novel method to restore the sensitivity of treatment-resistant ALL to GC-induced cell death.

Topoisomerase II alpha inhibition can overcome taxane-resistant prostate cancer through DNA repair pathways

Cabazitaxel (CBZ) is approved for the treatment of docetaxel-resistant castration-resistant prostate cancer (CRPC). However, its efficacy against CRPC is limited, and there are no effective treatments for CBZ-resistant CRPC. This study explored the optimal treatment for CRPC in the post-cabazitaxel setting. PC3 (CBZ-sensitive) and PC3CR cells (CBZ-resistant) were used in this study. We performed in silico drug screening for candidate drugs that could reprogram the gene expression signature of PC3CR cells. The in vivo effect of the drug combination was tested in xenograft mice models. We identified etoposide (VP16) as a promising treatment candidate for CBZ-resistant CRPC. The WST assay revealed that VP16 had a significant antitumor effect on PC3CR cells. PC3CR cells exhibited significantly higher topoisomerase II alpha (TOP2A) expression than PC3 cells. Higher TOP2A expression was a poor prognostic factor in The Cancer Genome Atlas prostate cancer cohort. In the Fred Hutchinson Cancer Research Center dataset, docetaxel-exposed tissues and metastatic tumors had higher TOP2A expression. In addition, VP16 significantly inhibited the growth of tumors generated from both cell lines. Based on these findings, VP16-based chemotherapy may be an optimal treatment for CPRC in the post-CBZ setting.

Verification of the role of spiperone in the treatment of COPD through bioinformatics analysis

BACKGROUND

Aim of this study is investigates the influence of spiperone on hydrolase activity pathway in chronic obstructive pulmonary disease (COPD).

PATIENTS AND METHODS

Differentially expressed genes (DEGs) were calculated by the limma package from microarray data GSE20257, and analysed via gene set enrichment analysis (GSEA) for identifying COPD related pathways. The regulation of hydrolase activity pathway related drugs was predicted by connectivity Map analysis (CMap). Western blotting and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were used to investigate the effect of spiperone on regulation of hydrolase activity pathway in vitro experiment.

RESULTS

A total of 378 DEGs were identified by the limma package. GSEA suggested that the regulation of hydrolase activity pathway was involved in the development of COPD. CMap of hub genes of regulation of hydrolase activity pathwayshown the most significant compound was spiperone. Results of vitro experiment verify that cigarette smoke extract (CSE) can increase the expression of fibronectin 1 (FN1) and epidermal growth factor (EGF), coinsided with decrease the expression of chemokine (C-X3-C motif) ligand 1 (CX3CL1), chemokoine (C-C motif) ligand 20 (CCL20), complement component 3 (C3) and slithomolog 2 (SLIT2) in BESA-2B cells and U937 cells. Spiperone can reverse the effect of CSE in BESA-2B cells and U937 cells.

CONCLUSION

Regulation of hydrolase activity pathway was involved in the occurrence of COPD, spiperone was a potential drug for the treatment of COPD by affecting the regulation of hydrolase activity pathway. This study had provided new insights into the potential pathogenesis and treatment of COPD.

TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning

One of the most challenging tasks in the drug-discovery process is the efficient identification of small molecules with desired phenotypes. In this study, we propose a novel computational method for omics-based de novo drug design, which we call TRIOMPHE (transcriptome-based inference and generation of molecules with desired phenotypes). We investigated the correlation between chemically induced transcriptome profiles (reflecting cellular responses to compound treatment) and genetically perturbed transcriptome profiles (reflecting cellular responses to gene knock-down or gene overexpression of target proteins) in terms of ligand-target interactions. Subsequently, we developed novel machine learning methods to generate the chemical structures of new molecules with desired transcriptome profiles in the framework of a variational autoencoder. The use of desired transcriptome profiles enables the automatic design of molecules that are likely to have bioactivities for target proteins of interest. We showed that our methods can generate chemically valid molecules that are likely to have biological activities on 10 target proteins; moreover, they can outperform previous methods that had the same objective. Our omics-based structure generator is expected to be useful for the de novo design of drugs for a variety of target proteins.

CTR-DB, an omnibus for patient-derived gene expression signatures correlated with cancer drug response

To date, only some cancer patients can benefit from chemotherapy and targeted therapy. Drug resistance continues to be a major and challenging problem facing current cancer research. Rapidly accumulated patient-derived clinical transcriptomic data with cancer drug response bring opportunities for exploring molecular determinants of drug response, but meanwhile pose challenges for data management, integration, and reuse. Here we present the Cancer Treatment Response gene signature DataBase (CTR-DB, http://ctrdb.ncpsb.org.cn/), a unique database for basic and clinical researchers to access, integrate, and reuse clinical transcriptomes with cancer drug response. CTR-DB has collected and uniformly reprocessed 83 patient-derived pre-treatment transcriptomic source datasets with manually curated cancer drug response information, involving 28 histological cancer types, 123 drugs, and 5139 patient samples. These data are browsable, searchable, and downloadable. Moreover, CTR-DB supports single-dataset exploration (including differential gene expression, receiver operating characteristic curve, functional enrichment, sensitizing drug search, and tumor microenvironment analyses), and multiple-dataset combination and comparison, as well as biomarker validation function, which provide insights into the drug resistance mechanism, predictive biomarker discovery and validation, drug combination, and resistance mechanism heterogeneity.

Prediction and identification of synergistic compound combinations against pancreatic cancer cells

Resistance to current therapies is common for pancreatic cancer and hence novel treatment options are urgently needed. In this work, we developed and validated a computational method to select synergistic compound combinations based on transcriptomic profiles from both the disease and compound side, combined with a pathway scoring system, which was then validated prospectively by testing 30 compounds (and their combinations) on PANC-1 cells. Some compounds selected as single agents showed lower GI50 values than the standard of care, gemcitabine. Compounds suggested as combination agents with standard therapy gemcitabine based on the best performing scoring system showed on average 2.82-5.18 times higher synergies compared to compounds that were predicted to be active as single agents. Examples of highly synergistic in vitro validated compound pairs include gemcitabine combined with Entinostat, thioridazine, loperamide, scriptaid and Saracatinib. Hence, the computational approach presented here was able to identify synergistic compound combinations against pancreatic cancer cells.

Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes

Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy. Cytogenetic and genomic features are used to classify AML patients into prognostic and treatment groups. However, these molecular characteristics harbor significant patient-to-patient variability and do not fully account for AML heterogeneity. RNA-based classifications have also been applied in AML as an alternative approach, but transcriptomic grouping is strongly associated with AML morphologic lineages. We used a training cohort of newly diagnosed AML patients and conducted unsupervised RNA-based classification after excluding lineage-associated genes. We identified three AML patient groups that have distinct biological pathways associated with outcomes. Enrichment of inflammatory pathways and downregulation of HOX pathways were associated with improved outcomes, and this was validated in 2 independent cohorts. We also identified a group of AML patients who harbored high metabolic and mTOR pathway activity, and this was associated with worse clinical outcomes. Using a comprehensive reverse phase protein array, we identified higher mTOR protein expression in the highly metabolic group. We also identified a positive correlation between degree of resistance to venetoclax and mTOR activation in myeloid and lymphoid cell lines. Our approach of integrating RNA, protein, and genomic data uncovered lineage-independent AML patient groups that share biologic mechanisms and can inform outcomes independent of commonly used clinical and demographic variables; these groups could be used to guide therapeutic strategies.

Drug repurposing strategies of relevance for Parkinson's disease

Parkinson's disease is a highly disabling, progressive neurodegenerative disease that manifests as a mix of motor and non-motor signs. Although we are equipped with some symptomatic treatments, especially for the motor signs of the disease, there are still no established disease-modifying drugs so the disease progresses unchecked. Standard drug discovery programs for disease-modifying therapies have provided key insights into the pathogenesis of Parkinson's disease but, of the many positive candidates identified in pre-clinical studies, none has yet translated into a successful clinically efficacious drug. Given the huge cost of drug discovery programs, it is not surprising that much attention has turned toward repurposing strategies. The trialing of an established therapeutic has the advantage of bypassing the need for preclinical safety testing and formulation optimization, thereby cutting both time and costs involved in getting a treatment to the clinic. Additional reduced failure rates for repurposed drugs are also a potential bonus. Many different strategies for drug repurposing are open to researchers in the Parkinson's disease field. Some of these have already proven effective in identifying suitable drugs for clinical trials, lending support to such approaches. In this review, we present a summary of the different strategies for drug repurposing, from large-scale epidemiological correlation analysis through to single-gene transcriptional approaches. We provide examples of past or ongoing studies adopting each strategy, where these exist. For strategies that have yet to be applied to Parkinson's disease, their utility is illustrated using examples taken from other disorders.

Identification and characterization of relapse-initiating cells in MLL-rearranged infant ALL by single-cell transcriptomics

Infants with MLL-rearranged infant acute lymphoblastic leukemia (MLL-r iALL) undergo intense therapy to counter a highly aggressive malignancy with survival rates of only 30–40%. The majority of patients initially show therapy response, but in two-thirds of cases the leukemia returns, typically during treatment. The glucocorticoid drug prednisone is established as a major player in the treatment of leukemia and the in vivo response to prednisone monotreatment is currently the best indicator of risk for MLL-r iALL. We used two different single-cell RNA sequencing technologies to analyze the expression of a prednisone-dependent signature, derived from an independent study, in diagnostic bone marrow and peripheral blood biopsies. This allowed us to classify individual leukemic cells as either resistant or sensitive to treatment and show that quantification of these two groups can be used to better predict the occurrence of future relapse in individual patients. This work also sheds light on the nature of the therapy-resistant subpopulation of relapse-initiating cells. Leukemic cells associated with high relapse risk are characterized by basal activation of glucocorticoid response, smaller size, and a quiescent gene expression program with cell stemness properties. These results improve current risk stratification and elucidate leukemic therapy-resistant subpopulations at diagnosis.

A Systems Approach to Brain Tumor Treatment

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood-brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.

Inhibition of Sp1-mediated survivin and MCL1 expression cooperates with SLC35F2 and myeloperoxidase to modulate YM155 cytotoxicity to human leukemia cells

Although YM155 is reported to suppress survivin (also known as BIRC5) expression in cancer cells, its cytotoxic mechanism in human acute myeloid leukemia (AML) cells has not been clearly resolved. In this study, we analyzed the mechanistic pathways that modulate the sensitivity of human AML U937 and HL-60 cells to YM155. YM155 induced apoptosis in AML cells, which was characterized by p38 MAPK phosphorylation and downregulation of survivin and MCL1 expression. Phosphorylated p38 MAPK causes autophagy-mediated Sp1 degradation, thereby inhibiting the transcription of survivin and MCL1. The reduction of survivin and MCL1 levels further facilitated Sp1 protein degradation through autophagy. The restoration of Sp1, survivin, or MCL1 expression protected U937 and HL-60 cells from YM155-mediated cytotoxicity. U937 and HL-60 cells were continuously exposed to hydroquinone (HQ) to generate U937/HQ and HL-60/HQ cells, which showed increased SLC35F2 expression. The increase in SLC35F2 expression led to an increase in the sensitivity of U937/HQ cells to YM155-mediated cytotoxicity, whereas no such effect was observed in HL-60/HQ cells. Of note, myeloperoxidase (MPO) activity in HL-60 and HL-60/HQ cells enhanced YM155 cytotoxicity in these cells, and the enforced expression of MPO also increased the sensitivity of U937 cells to YM155. Taken together, we conclude that p38 MAPK-modulated autophagy inhibits Sp1-mediated survivin and MCL1 expression, which, in turn, leads to the death of U937 and HL-60 cells following YM155 treatment. In addition, our data indicate that SLC35F2 increases the sensitivity of U937 cells to YM155-mediated cytotoxicity, whereas MPO enhances YM155 cytotoxicity in U937 and HL-60 cells.

Drug Repositioning for the Treatment of Hematologic Disease: Limits, Challenges and Future Perspectives

Drug repositioning is a strategy to identify new uses for approved or investigational drugs that are used off-label outside the scope of the original medical indication. In this review, we report the most relevant studies about drug repositioning in hematology, reporting the signalling pathways and molecular targets of these drugs, and describing the biological mechanisms which are responsible for their anticancer effects. Although the majority of studies on drug repositioning in hematology concern acute myeloid leukemia and multiple myeloma, numerous studies are present in the literature on the possibility of using these drugs also in other hematological diseases, such as acute lymphoblastic leukemia, chronic myeloid leukemia, and lymphomas. Numerous anti-infectious drugs and chemical entities used for the therapy of neurological or endocrine diseases, oral antidiabetics, statins and medications used to treat high blood pressure and heart failure, bisphosphonate and natural substance such as artemisin and curcumin, have found a place in the treatment of hematological diseases. Moreover, several molecules drastically reversed the resistance of the tumor cells to the chemotherapeutic drugs both in vitro and in vivo.

Advances in the Diagnosis and Treatment of Pediatric Acute Lymphoblastic Leukemia

The outcomes of pediatric acute lymphoblastic leukemia (ALL) have improved remarkably during the last five decades. Such improvements were made possible by the incorporation of new diagnostic technologies, the effective administration of conventional chemotherapeutic agents, and the provision of better supportive care. With the 5-year survival rates now exceeding 90% in high-income countries, the goal for the next decade is to improve survival further toward 100% and to minimize treatment-related adverse effects. Based on genome-wide analyses, especially RNA-sequencing analyses, ALL can be classified into more than 20 B-lineage subtypes and more than 10 T-lineage subtypes with prognostic and therapeutic implications. Response to treatment is another critical prognostic factor, and detailed analysis of minimal residual disease can detect levels as low as one ALL cell among 1 million total cells. Such detailed analysis can facilitate the rational use of molecular targeted therapy and immunotherapy, which have emerged as new treatment strategies that can replace or reduce the use of conventional chemotherapy.

Identifying Novel Drug Targets by iDTPnd: A Case Study of Kinase Inhibitors

Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. Here, we develop iDTPnd (integrated Drug Target Predictor with negative dataset), a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding sites. To facilitate assessment of unintended targets, iDTPnd also provides a docking-based interaction score and its statistical significance. We confirm the interactions of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity of 52% and a specificity of 55%. We also validate 10 predicted novel targets by using in vitro experiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450, and MHC class I molecules, can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein–small molecule interactions, when sufficient drug–target 3D data are available. The code for constructing the structural signatures is available at https://sfb.kaust.edu.sa/Documents/iDTP.zip.

LXR stimulates a metabolic switch and reveals cholesterol homeostasis as a statin target in Tasmanian devil facial tumor disease

Devil facial tumor disease (DFTD) and its lack of available therapies are propelling the Tasmanian devil population toward extinction. This study demonstrates that cholesterol homeostasis and carbohydrate energy metabolism sustain the proliferation of DFTD cells in a cell-type-dependent manner. In addition, we show that the liver-X nuclear receptor-β (LXRβ), a major cholesterol cellular sensor, and its natural ligand 24S-hydroxycholesterol promote the proliferation of DFTD cells via a metabolic switch toward aerobic glycolysis. As a proof of concept of the role of cholesterol homeostasis on DFTD proliferation, we show that atorvastatin, an FDA-approved statin-drug subtype used against human cardiovascular diseases that inhibits cholesterol synthesis, shuts down DFTD energy metabolism and prevents tumor growth in an in vivo DFTD-xenograft model. In conclusion, we show that intervention against cholesterol homeostasis and carbohydrate-dependent energy metabolism by atorvastatin constitutes a feasible biochemical treatment against DFTD, which may assist in the conservation of the Tasmanian devil.

Overcoming Glucocorticoid Resistance in Acute Lymphoblastic Leukemia: Repurposed Drugs Can Improve the Protocol

Glucocorticoids (GCs) are a central component of multi-drug treatment protocols against T and B acute lymphoblastic leukemia (ALL), which are used intensively during the remission induction to rapidly eliminate the leukemic blasts. The primary response to GCs predicts the overall response to treatment and clinical outcome. In this review, we have critically analyzed the available data on the effects of GCs on sensitive and resistant leukemic cells, in order to reveal the mechanisms of GC resistance and how these mechanisms may determine a poor outcome in ALL. Apart of the GC resistance, associated with a decreased expression of receptors to GCs, there are several additional mechanisms, triggered by alterations of different signaling pathways, which cause the metabolic reprogramming, with an enhanced level of glycolysis and oxidative phosphorylation, apoptosis resistance, and multidrug resistance. Due to all this, the GC-resistant ALL show a poor sensitivity to conventional chemotherapeutic protocols. We propose pharmacological strategies that can trigger alternative intracellular pathways to revert or overcome GC resistance. Specifically, we focused our search on drugs, which are already approved for treatment of other diseases and demonstrated anti-ALL effects in experimental pre-clinical models. Among them are some “truly” re-purposed drugs, which have different targets in ALL as compared to other diseases: cannabidiol, which targets mitochondria and causes the mitochondrial permeability transition-driven necrosis, tamoxifen, which induces autophagy and cell death, and reverts GC resistance through the mechanisms independent of nuclear estrogen receptors (“off-target effects”), antibiotic tigecycline, which inhibits mitochondrial respiration, causing energy crisis and cell death, and some anthelmintic drugs. Additionally, we have listed compounds that show a classical mechanism of action in ALL but are not used still in treatment protocols: the BH3 mimetic venetoclax, which inhibits the anti-apoptotic protein Bcl-2, the hypomethylating agent 5-azacytidine, which restores the expression of the pro-apoptotic BIM, and compounds targeting the PI3K-Akt-mTOR axis. Accordingly, these drugs may be considered for the inclusion into chemotherapeutic protocols for GC-resistant ALL treatments.

Prognostic Relevance of Expression of EMP1, CASP1, and NLRP3 Genes in Pediatric B-Lineage Acute Lymphoblastic Leukemia

Glucocorticoid (GC), such as prednisolone, is an essential component of multidrug chemotherapy regimen for pediatric acute lymphoblastic leukemia (ALL). Resistance to GC in leukemia cells is associated with disease progression and poor prognosis. Despite the extensive use of GC for many years, molecular mechanisms underlying its resistance in ALL have not been fully uncovered. Recent studies have shown a potential role of EMP1, CASP1, and NLRP3 genes in prednisolone response. In this study on 148 pediatric B-ALL patients, we studied these three genes to assess their association with prednisolone response measured by day 8 blast count after 7 days of induction therapy with prednisolone. Intriguingly, ALL samples exhibited higher expression of EMP1 along with a low expression of CASP1 and NLRP3 compared to disease free normal bone marrow collected from patients with solid tumors. Among the three analyzed genes, only EMP1 was found to be overexpressed in prednisolone poor responders (p=0.015). Further, a comparison of gene expression between cytogenetic subtypes revealed higher expression of EMP1 in BCR-ABL subtype. Expression of EMP1 in multiple gene expression datasets was used for gene set enrichment analysis, which revealed TNF-α, IL-2-STAT5 signaling, inflammatory responses and hypoxia as the major positively associated pathways and E2F targets as negatively associated pathways. Interestingly, the clinical remission rate was higher in CASP1 high patients (p=0.048). In univariate survival analysis, higher EMP1 expression was associated with poor prognostic measures while higher expression of NLRP3 and CASP1 was associated with better prognostic measures in our data. Further, multivariate analysis revealed an independent association of high CASP1 and NLRP3 with a better prognosis. This study strengthens the available evidence that mRNA expression of EMP1, CASP1, and NLRP3 may serve as potential biomarkers for risk stratification of pediatric B-ALL patients.

A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing

Phenotype-based compound screening has advantages over target-based drug discovery, but is unscalable and lacks understanding of mechanism. Chemical-induced gene expression profile provides a mechanistic signature of phenotypic response. However, the use of such data is limited by their sparseness, unreliability, and relatively low throughput. Few methods can perform phenotype-based de novo chemical compound screening. Here, we propose a mechanism-driven neural network-based method DeepCE, which utilizes graph neural network and multi-head attention mechanism to model chemical substructure-gene and gene-gene associations, for predicting the differential gene expression profile perturbed by de novo chemicals. Moreover, we propose a novel data augmentation method which extracts useful information from unreliable experiments in L1000 dataset. The experimental results show that DeepCE achieves superior performances to state-of-the-art methods. The effectiveness of gene expression profiles generated from DeepCE is further supported by comparing them with observed data for downstream classification tasks. To demonstrate the value of DeepCE, we apply it to drug repurposing of COVID-19, and generate novel lead compounds consistent with clinical evidence. Thus, DeepCE provides a potentially powerful framework for robust predictive modeling by utilizing noisy omics data and screening novel chemicals for the modulation of a systemic response to disease.

Prostaglandin E2 stimulates cAMP signaling and resensitizes human leukemia cells to glucocorticoid-induced cell death

Glucocorticoid (GC) resistance remains a clinical challenge in pediatric acute lymphoblastic leukemia where response to GC is a reliable prognostic indicator. To identify GC resistance pathways, we conducted a genome-wide, survival-based, short hairpin RNA screen in murine T-cell acute lymphoblastic leukemia (T-ALL) cells. Genes identified in the screen interfere with cyclic adenosine monophosphate (cAMP) signaling and are underexpressed in GC-resistant or relapsed ALL patients. Silencing of the cAMP-activating Gnas gene interfered with GC-induced gene expression, resulting in dexamethasone resistance in vitro and in vivo. We demonstrate that cAMP signaling synergizes with dexamethasone to enhance cell death in GC-resistant human T-ALL cells. We find the E prostanoid receptor 4 expressed in T-ALL samples and demonstrate that prostaglandin E2 (PGE2) increases intracellular cAMP, potentiates GC-induced gene expression, and sensitizes human T-ALL samples to dexamethasone in vitro and in vivo. These findings identify PGE2 as a target for GC resensitization in relapsed pediatric T-ALL.