Targeting RNA editing of antizyme inhibitor 1: A potential oligonucleotide-based antisense therapy for cancer.

Dysregulated adenosine-to-inosine (A-to-I) RNA editing is implicated in various cancers. However, no available RNA editing inhibitors have so far been developed to inhibit cancer-associated RNA editing events. Here, we decipher the RNA secondary structure of antizyme inhibitor 1 (AZIN1), one of the best-studied A-to-I editing targets in cancer, by locating its editing site complementary sequence (ECS) at the 3' end of exon 12. Chemically modified antisense oligonucleotides (ASOs) that target the editing region of AZIN1 caused a substantial exon 11 skipping, whereas ECS-targeting ASOs effectively abolished AZIN1 editing without affecting splicing and translation. We demonstrate that complete 2'-O-methyl (2'-O-Me) sugar ring modification in combination with partial phosphorothioate (PS) backbone modification may be an optimal chemistry for editing inhibition. ASO3.2, which targets the ECS, specifically inhibits cancer cell viability in vitro and tumor incidence and growth in xenograft models. Our results demonstrate that this AZIN1-targeting, ASO-based therapeutics may be applicable to a wide range of tumor types.

Targeting Jak/Stat pathway as a therapeutic strategy against SP/CD44+ tumorigenic cells in Akt/ß-catenin-driven hepatocellular carcinoma.

BACKGROUND & AIMS: Hepatic resection and liver transplantation with adjuvant chemo- and radiotherapy are the mainstay of hepatocellular carcinoma (HCC) treatment, but the 5-year survival rate remains poor because of frequent recurrence and intrahepatic metastasis. Only sorafenib and lenvatinib are currently approved for the first-line treatment of advanced, unresected HCC, but they yield modest survival benefits. Thus, there is a need to identify new therapeutic targets to improve current HCC treatment modalities. METHODS: The HCC tumor model was generated by hydrodynamic transfection of AKT1 and ß-catenin (CTNNB1) oncogenes. Cancer cells with stemness properties were characterized following isolation using side population (SP) and CD44 surface markers by flow cytometry. The effect of Jak/Stat inhibitors was analyzed in vitro by using tumorsphere culture and in vivo using an allograft mouse model. RESULTS: Co-activation of both Wnt/ß-catenin and Akt/mTOR pathways was found in 14.4% of our HCC patient cohort. More importantly, these patients showed poorer survival than those with either Wnt/ß-catenin or Akt/mTOR pathway activation alone, demonstrating the clinical relevance of our study. In addition, we observed that Akt/ß-catenin tumors contained a subpopulation of cells with stem/progenitor-like characteristics identified through SP analysis and expression of the cancer stem cell-like marker CD44, which may contribute to tumor self-renewal and drug resistance. Consequently, we identified small molecule inhibitors of the Jak/Stat pathway that demonstrated efficacy in mitigating tumor proliferation and formation in Akt/ß-catenin-driven HCC. CONCLUSIONS: In conclusion, we have shown that Akt/ß-catenin tumors contain a subpopulation of tumor-initiating cells with stem/progenitor-like characteristics which can be effectively targeted with inhibitors of the Jak/Stat pathway, demonstrating that inhibition of the Jak/Stat pathway could be an alternative method to overcome drug resistance and effectively treat Akt/ß-catenin-driven HCC tumors. LAY SUMMARY: The prognosis for patients with hepatocellular carcinoma is poor, partly because of the lack of effective treatment options for those with more advanced disease. In this study, we identified a subpopulation of cancer cells with stem cell-like properties that were critical for tumor maintenance and growth in a mouse model of hepatocellular carcinoma. Through further experiments, we demonstrated that the Jak/Stat pathway is a promising therapeutic target in hepatocellular carcinoma.

New High-Throughput Screening Identifies Compounds That Reduce Viability Specifically in Liver Cancer Cells That Express High Levels of SALL4 by Inhibiting Oxidative Phosphorylation.

BACKGROUND & AIMS: Some oncogenes encode transcription factors, but few drugs have been successfully developed to block their activity specifically in cancer cells. The transcription factor SALL4 is aberrantly expressed in solid tumor and leukemia cells. We developed a screen to identify compounds that reduce the viability of liver cancer cells that express high levels of SALL4, and we investigated their mechanisms. METHODS: We developed a stringent high-throughput screening platform comprising unmodified SNU-387 and SNU-398 liver cancer cell lines and SNU-387 cell lines engineered to express low and high levels of SALL4. We screened 1597 pharmacologically active small molecules and 21,575 natural product extracts from plant, bacteria, and fungal sources for those that selectively reduce the viability of cells with high levels of SALL4 (SALL4hi cells). We compared gene expression patterns of SALL4hi cells vs SALL4-knockdown cells using RNA sequencing and real-time polymerase chain reaction analyses. Xenograft tumors were grown in NOD/SCID gamma mice from SALL4hi SNU-398 or HCC26.1 cells or from SALL4lo patient-derived xenograft (PDX) cells; mice were given injections of identified compounds or sorafenib, and the effects on tumor growth were measured. RESULTS: Our screening identified 1 small molecule (PI-103) and 4 natural compound analogues (oligomycin, efrapeptin, antimycin, and leucinostatin) that selectively reduced viability of SALL4hi cells. We performed validation studies, and 4 of these compounds were found to inhibit oxidative phosphorylation. The adenosine triphosphate (ATP) synthase inhibitor oligomycin reduced the viability of SALL4hi hepatocellular carcinoma and non-small-cell lung cancer cell lines with minimal effects on SALL4lo cells. Oligomycin also reduced the growth of xenograft tumors grown from SALL4hi SNU-398 or HCC26.1 cells to a greater extent than sorafenib, but oligomycin had little effect on tumors grown from SALL4lo PDX cells. Oligomycin was not toxic to mice. Analyses of chromatin immunoprecipitation sequencing data showed that SALL4 binds approximately 50% of mitochondrial genes, including many oxidative phosphorylation genes, to activate their transcription. In comparing SALL4hi and SALL4-knockdown cells, we found SALL4 to increase oxidative phosphorylation, oxygen consumption rate, mitochondrial membrane potential, and use of oxidative phosphorylation-related metabolites to generate ATP. CONCLUSIONS: In a screening for compounds that reduce the viability of cells that express high levels of the transcription factor SALL4, we identified inhibitors of oxidative phosphorylation, which slowed the growth of xenograft tumors from SALL4hi cells in mice. SALL4 activates the transcription of genes that regulate oxidative phosphorylation to increase oxygen consumption, mitochondrial membrane potential, and ATP generation in cancer cells. Inhibitors of oxidative phosphorylation might be used for the treatment of liver tumors with high levels of SALL4.

Dual-Targeting Dual-Action Platinum(IV) Platform for Enhanced Anticancer Activity and Reduced Nephrotoxicity.

A novel and highly efficient dual-targeting platform was designed to ensure targeted in vivo delivery of dual-action PtIV prodrugs. The dual targeting was established by liposomal encapsulation of PtIV complexes, thereby utilizing the enhanced permeability and retention (EPR) effect as the first stage of targeting to attain a high accumulation of the drug-loaded liposomes in the tumor. After the release of the PtIV prodrug inside cancer cells, a second stage of targeting directed a portion of the PtIV prodrugs to the mitochondria. Upon intracellular reduction, these PtIV prodrugs released two bioactive molecules, acting both on the mitochondrial and on the nuclear DNA. Our PtIV system showed excellent activity in vitro and in vivo, characterized by a cytotoxicity in a low micromolar range and complete tumor remission, respectively. Notably, marked in vivo activity was accompanied by reduced kidney toxicity, highlighting the unique therapeutic potential of our novel dual-targeting dual-action platform.

A functional personalised oncology approach against metastatic colorectal cancer in matched patient derived organoids.

Globally, colorectal cancer (CRC) is the third most frequently occurring cancer. Progression on to an advanced metastatic malignancy (metCRC) is often indicative of poor prognosis, as the 5-year survival rates of patients decline rapidly. Despite the availability of many systemic therapies for the management of metCRC, the long-term efficacies of these regimens are often hindered by the emergence of treatment resistance due to intratumoral and intertumoral heterogeneity. Furthermore, not all systemic therapies have associated biomarkers that can accurately predict patient responses. Hence, a functional personalised oncology (FPO) approach can enable the identification of patient-specific combinatorial vulnerabilities and synergistic combinations as effective treatment strategies. To this end, we established a panel of CRC patient-derived organoids (PDOs) as clinically relevant biological systems, of which three pairs of matched metCRC PDOs were derived from the primary sites (ptCRC) and metastatic lesions (mCRC). Histological and genomic characterisation of these PDOs demonstrated the preservation of histopathological and genetic features found in the parental tumours. Subsequent application of the phenotypic-analytical drug combination interrogation platform, Quadratic Phenotypic Optimisation Platform, in these pairs of PDOs identified patient-specific drug sensitivity profiles to epigenetic-based combination therapies. Most notably, matched PDOs from one patient exhibited differential sensitivity patterns to the rationally designed drug combinations despite being genetically similar. These findings collectively highlight the limitations of current genomic-driven precision medicine in guiding treatment strategies for metCRC patients. Instead, it suggests that epigenomic profiling and application of FPO could complement the identification of novel combinatorial vulnerabilities to target synchronous ptCRC and mCRC.

Splice-switch oligonucleotide-based combinatorial platform prioritizes synthetic lethal targets CHK1 and BRD4 against MYC-driven hepatocellular carcinoma.

Deregulation of MYC is among the most frequent oncogenic drivers in hepatocellular carcinoma (HCC). Unfortunately, the clinical success of MYC-targeted therapies is limited. Synthetic lethality offers an alternative therapeutic strategy by leveraging on vulnerabilities in tumors with MYC deregulation. While several synthetic lethal targets of MYC have been identified in HCC, the need to prioritize targets with the greatest therapeutic potential has been unmet. Here, we demonstrate that by pairing splice-switch oligonucleotide (SSO) technologies with our phenotypic-analytical hybrid multidrug interrogation platform, quadratic phenotypic optimization platform (QPOP), we can disrupt the functional expression of these targets in specific combinatorial tests to rapidly determine target-target interactions and rank synthetic lethality targets. Our SSO-QPOP analyses revealed that simultaneous attenuation of CHK1 and BRD4 function is an effective combination specific in MYC-deregulated HCC, successfully suppressing HCC progression in vitro. Pharmacological inhibitors of CHK1 and BRD4 further demonstrated its translational value by exhibiting synergistic interactions in patient-derived xenograft organoid models of HCC harboring high levels of MYC deregulation. Collectively, our work demonstrates the capacity of SSO-QPOP as a target prioritization tool in the drug development pipeline, as well as the therapeutic potential of CHK1 and BRD4 in MYC-driven HCC.

Histone-lysine N-methyltransferase EHMT2 (G9a) inhibition mitigates tumorigenicity in Myc-driven liver cancer.

Hepatocellular carcinoma (HCC) is the third deadliest and sixth most common cancer in the world. Histone-lysine N-methyltransferase EHMT2 (also known as G9a) is a histone methyltransferase frequently overexpressed in many cancer types, including HCC. We showed that Myc-driven liver tumours have a unique H3K9 methylation pattern with corresponding G9a overexpression. This phenomenon of increased G9a was further observed in our c-Myc-positive HCC patient-derived xenografts. More importantly, we showed that HCC patients with higher c-Myc and G9a expression levels portend a poorer survival with lower median survival months. We demonstrated that c-Myc interacts with G9a in HCC and cooperates to regulate c-Myc-dependent gene repression. In addition, G9a stabilises c-Myc to promote cancer development, contributing to the growth and invasive capacity in HCC. Furthermore, combination therapy between G9a and synthetic-lethal target of c-Myc, CDK9, demonstrates strong efficacy in patient-derived avatars of Myc-driven HCC. Our work suggests that targeting G9a could prove to be a potential therapeutic avenue for Myc-driven liver cancer. This will increase our understanding of the underlying epigenetic mechanisms of aggressive tumour initiation and lead to improved therapeutic and diagnostic options for Myc-driven hepatic tumours.

Red Blood Cell-Derived Extracellular Vesicles Display Endogenous Antiviral Effects and Enhance the Efficacy of Antiviral Oligonucleotide Therapy.

The COVID-19 pandemic has resulted in a large number of fatalities and, at present, lacks a readily available curative treatment for patients. Here, we demonstrate that unmodified red blood cell-derived extracellular vesicles (RBCEVs) can inhibit SARS-CoV-2 infection in a phosphatidylserine (PS) dependent manner. Using T cell immunoglobulin mucin domain-1 (TIM-1) as an example, we demonstrate that PS receptors on cells can significantly increase the adsorption and infection of authentic and pseudotyped SARS-CoV-2 viruses. RBCEVs competitively inhibit this interaction and block TIM-1-mediated viral entry into cells. We further extend the therapeutic efficacy of this antiviral treatment by loading antisense oligonucleotides (ASOs) designed to target conserved regions of key SARS-CoV-2 genes into RBCEVs. We establish that ASO-loaded RBCEVs are efficiently taken up by cells in vitro and in vivo to suppress SARS-CoV-2 replication. Our findings indicate that this RBCEV-based SARS-CoV-2 therapeutic displays promise as a potential treatment capable of inhibiting SARS-CoV-2 entry and replication.

Addressing antimicrobial resistance with the IDentif.AI platform: Rapidly optimizing clinically actionable combination therapy regimens against nontuberculous mycobacteria.

Background: Current standard of care (SOC) regimens against nontuberculous mycobacteria (NTM) usually result in unsatisfactory therapeutic responses, primarily due to multi-drug resistance and antibiotic susceptibility-guided therapies. In the midst of rising incidences in NTM infections, strategies to develop NTM-specific treatments have been explored and validated. Methods: To provide an alternative approach to address NTM-specific treatment, IDentif.AI was harnessed to rapidly optimize and design effective combination therapy regimens against Mycobacterium abscessus (M. abscessus), the highly resistant and rapid growth species of NTM. IDentif.AI interrogated the drug interaction space from a pool of 6 antibiotics, and pinpointed multiple clinically actionable drug combinations. IDentif.AI-pinpointed actionable combinations were experimentally validated and their interactions were assessed using Bliss independence model and diagonal measurement of n-way drug interactions. Results: Notably, IDentfi.AI-designed 3- and 4-drug combinations demonstrated greater %Inhibition efficacy than the SOC regimens. The platform also pinpointed two unique drug interactions (Levofloxacin (LVX)/Rifabutin (RFB) and LVX/Meropenem (MEM)) that may serve as the backbone of potential 3- and 4-drug combinations like LVX/MEM/RFB, which exhibited 58.33±4.99 %Inhibition efficacy against M. abscessus. Further analysis of LVX/RFB via Bliss independence model pointed to dose-dependent synergistic interactions in clinically actionable concentrations. Conclusions: IDentif.AI-designed combinations may provide alternative regimen options to current SOC combinations that are often administered with Amikacin, which has been known to induce ototoxicity in patients. Furthermore, IDentif.AI pinpointed 2-drug interactions may also serve as the backbone for the development of other effective 3- and 4-drug combination therapies. The findings in this study suggest that this platform may contribute to NTM-specific drug development.

Rational drug combination design in patient-derived avatars reveals effective inhibition of hepatocellular carcinoma with proteasome and CDK inhibitors.

BACKGROUND: Hepatocellular carcinoma (HCC) remains difficult to treat due to limited effective treatment options. While the proteasome inhibitor bortezomib has shown promising preclinical activity in HCC, clinical trials of bortezomib showed no advantage over the standard-of-care treatment sorafenib, highlighting the need for more clinically relevant therapeutic strategies. Here, we propose that rational drug combination design and validation in patient-derived HCC avatar models such as patient-derived xenografts (PDXs) and organoids can improve proteasome inhibitor-based therapeutic efficacy and clinical potential. METHODS: HCC PDXs and the corresponding PDX-derived organoids (PDXOs) were generated from primary patient samples for drug screening and efficacy studies. To identify effective proteasome inhibitor-based drug combinations, we applied a hybrid experimental-computational approach, Quadratic Phenotypic Optimization Platform (QPOP) on a pool of nine drugs comprising proteasome inhibitors, kinase inhibitors and chemotherapy agents. QPOP utilizes small experimental drug response datasets to accurately identify globally optimal drug combinations. RESULTS: Preliminary drug screening highlighted the increased susceptibility of HCC PDXOs towards proteasome inhibitors. Through QPOP, the combination of second-generation proteasome inhibitor ixazomib (Ixa) and CDK inhibitor dinaciclib (Dina) was identified to be effective against HCC. In vitro and in vivo studies demonstrated the synergistic pro-apoptotic and anti-proliferative activity of Ixa + Dina against HCC PDXs and PDXOs. Furthermore, Ixa + Dina outperformed sorafenib in mitigating tumor formation in mice. Mechanistically, increased activation of JNK signaling mediates the combined anti-tumor effects of Ixa + Dina in HCC tumor cells. CONCLUSIONS: Rational drug combination design in patient-derived avatars highlights the therapeutic potential of proteasome and CDK inhibitors and represents a feasible approach towards developing more clinically relevant treatment strategies for HCC.

Hepatocellular carcinoma organoid co-cultures mimic angiocrine crosstalk to generate inflammatory tumor microenvironment.

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the second leading cause of cancer worldwide. Despite approvals of several therapeutics to treat advanced HCC in the past few years, the impact of anti-angiogenic treatment on HCC patient overall survival remains limited. This suggests there may be alternative, perfusion-independent roles of endothelial cells that support tumor progression. Thus, we leveraged a well-defined hydrogel system to establish co-culture models to mimic and characterize the angiocrine crosstalk between HCC and endothelial cells in vitro. Co-cultures of HCC cell lines or patient-derived xenograft organoids with endothelial cells exhibited the upregulation of MCP-1, IL-8 and CXCL16, suggesting that the HCC-endothelial interactions established in our models recapitulate known angiocrine signaling. Additionally, by subjecting co-cultures and mono-cultures to RNA sequencing, transcriptomic analysis revealed an upregulation in the expression of genes associated with tumor necrosis factor (TNF) signaling, such as that of chemokines, suggesting that endothelial cells induce HCC cells to generate an inflammatory microenvironment by recruiting immune cells. Finally, HCC-endothelial angiocrine crosstalk in the co-culture models polarized macrophages towards a pro-inflammatory and pro-angiogenic phenotype, paralleling a tumor-associated macrophage subset previously reported in HCC. Together, these findings suggest that these HCC-endothelial co-culture models may serve as important models to understand and target the interplay between angiogenesis and the immune milieu.

IDentif.AI-Omicron: Harnessing an AI-Derived and Disease-Agnostic Platform to Pinpoint Combinatorial Therapies for Clinically Actionable Anti-SARS-CoV-2 Intervention.

Nanomedicine-based and unmodified drug interventions to address COVID-19 have evolved over the course of the pandemic as more information is gleaned and virus variants continue to emerge. For example, some early therapies (e.g., antibodies) have experienced markedly decreased efficacy. Due to a growing concern of future drug resistant variants, current drug development strategies are seeking to find effective drug combinations. In this study, we used IDentif.AI, an artificial intelligence-derived platform, to investigate the drug-drug and drug-dose interaction space of six promising experimental or currently deployed therapies at various concentrations: EIDD-1931, YH-53, nirmatrelvir, AT-511, favipiravir, and auranofin. The drugs were tested in vitro against a live B.1.1.529 (Omicron) virus first in monotherapy and then in 50 strategic combinations designed to interrogate the interaction space of 729 possible combinations. Key findings and interactions were then further explored and validated in an additional experimental round using an expanded concentration range. Overall, we found that few of the tested drugs showed moderate efficacy as monotherapies in the actionable concentration range, but combinatorial drug testing revealed significant dose-dependent drug-drug interactions, specifically between EIDD-1931 and YH-53, as well as nirmatrelvir and YH-53. Checkerboard validation analysis confirmed these synergistic interactions and also identified an interaction between EIDD-1931 and favipiravir in an expanded range. Based on the platform nature of IDentif.AI, these findings may support further explorations of the dose-dependent drug interactions between different drug classes in further pre-clinical and clinical trials as possible combinatorial therapies consisting of unmodified and nanomedicine-enabled drugs, to combat current and future COVID-19 strains and other emerging pathogens.

The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens.

IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies against COVID-19 by pairing a prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus and Vero E6 assay with a quadratic optimization workflow. A starting pool of 12 candidate drugs developed in collaboration with a community of infectious disease clinicians was first narrowed down to a six-drug pool and then interrogated in 50 combination regimens at three dosing levels per drug, representing 729 possible combinations. IDentif.AI-x revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived, and pinpointed a number of clinically actionable drug interactions, which were further reconfirmed in SARS-CoV-2 variants B.1.351 (Beta) and B.1.617.2 (Delta). IDentif.AI-x prioritized promising drug combinations for clinical translation and can be immediately adjusted and re-executed with a new pool of promising therapies in an actionable path towards rapidly optimizing combination therapy following pandemic emergence.

Enhanced penetrative siRNA delivery by a nanodiamond drug delivery platform against hepatocellular carcinoma 3D models.

Small interfering RNA (siRNA) can cause specific gene silencing and is considered promising for treating a variety of cancers, including hepatocellular carcinoma (HCC). However, siRNA has many undesirable physicochemical properties that limit its application. Additionally, conventional methods for delivering siRNA are limited in their ability to penetrate solid tumors. In this study, nanodiamonds (NDs) were evaluated as a nanoparticle drug delivery platform for improved siRNA delivery into tumor cells. Our results demonstrated that ND-siRNA complexes could effectively be formed through electrostatic interactions. The ND-siRNA complexes allowed for efficient cellular uptake and endosomal escape that protects siRNA from degradation. Moreover, ND delivery of siRNA was more effective at penetrating tumor spheroids compared to liposomal formulations. This enhanced penetration capacity makes NDs ideal vehicles to deliver siRNA against solid tumor masses as efficient gene knockdown and decreased tumor cell proliferation were observed in tumor spheroids. Evaluation of ND-siRNA complexes within the context of a 3D cancer disease model demonstrates the potential of NDs as a promising gene delivery platform against solid tumors, such as HCC.

IDentif.AI: Rapidly optimizing combination therapy design against severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) with digital drug development.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to multiple drug repurposing clinical trials that have yielded largely uncertain outcomes. To overcome this challenge, we used IDentif.AI, a platform that pairs experimental validation with artificial intelligence (AI) and digital drug development to rapidly pinpoint unpredictable drug interactions and optimize infectious disease combination therapy design with clinically relevant dosages. IDentif.AI was paired with a 12-drug candidate therapy set representing over 530,000 drug combinations against the SARS-CoV-2 live virus collected from a patient sample. IDentif.AI pinpointed the optimal combination as remdesivir, ritonavir, and lopinavir, which was experimentally validated to mediate a 6.5-fold enhanced efficacy over remdesivir alone. Additionally, it showed hydroxychloroquine and azithromycin to be relatively ineffective. The study was completed within 2 weeks, with a three-order of magnitude reduction in the number of tests needed. IDentif.AI independently mirrored clinical trial outcomes to date without any data from these trials. The robustness of this digital drug development approach paired with in vitro experimentation and AI-driven optimization suggests that IDentif.AI may be clinically actionable toward current and future outbreaks.

Project IDentif.AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention.

In 2019/2020, the emergence of coronavirus disease 2019 (COVID-19) resulted in rapid increases in infection rates as well as patient mortality. Treatment options addressing COVID-19 included drug repurposing, investigational therapies such as remdesivir, and vaccine development. Combination therapy based on drug repurposing is among the most widely pursued of these efforts. Multi-drug regimens are traditionally designed by selecting drugs based on their mechanism of action. This is followed by dose-finding to achieve drug synergy. This approach is widely-used for drug development and repurposing. Realizing synergistic combinations, however, is a substantially different outcome compared to globally optimizing combination therapy, which realizes the best possible treatment outcome by a set of candidate therapies and doses toward a disease indication. To address this challenge, the results of Project IDentif.AI (Identifying Infectious Disease Combination Therapy with Artificial Intelligence) are reported. An AI-based platform is used to interrogate a massive 12 drug/dose parameter space, rapidly identifying actionable combination therapies that optimally inhibit A549 lung cell infection by vesicular stomatitis virus within three days of project start. Importantly, a sevenfold difference in efficacy is observed between the top-ranked combination being optimally and sub-optimally dosed, demonstrating the critical importance of ideal drug and dose identification. This platform is disease indication and disease mechanism-agnostic, and potentially applicable to the systematic N-of-1 and population-wide design of highly efficacious and tolerable clinical regimens. This work also discusses key factors ranging from healthcare economics to global health policy that may serve to drive the broader deployment of this platform to address COVID-19 and future pandemics.

Frequent upregulation of G9a promotes RelB-dependent proliferation and survival in multiple myeloma.

BACKGROUND: Multiple myeloma is an incurable hematological malignancy characterized by a heterogeneous genetic and epigenetic landscape. Although a number of genetic aberrations associated with myeloma pathogenesis, progression and prognosis have been well characterized, the role of many epigenetic aberrations in multiple myeloma remain elusive. G9a, a histone methyltransferase, has been found to promote disease progression, proliferation and metastasis via diverse mechanisms in several cancers. A role for G9a in multiple myeloma, however, has not been previously explored. METHODS: Expression levels of G9a/EHMT2 of multiple myeloma cell lines and control cells Peripheral Blood Mononuclear Cells (PBMCs) were analyzed. Correlation of G9a expression and overall survival of multiple myeloma patients were analyzed using patient sample database. To further study the function of G9a in multiple myeloma, G9a depleted multiple myeloma cells were built by lentiviral transduction, of which proliferation, colony formation assays as well as tumorigenesis were measured. RNA-seq of G9a depleted multiple myeloma with controls were performed to explore the downstream mechanism of G9a regulation in multiple myeloma. RESULTS: G9a is upregulated in a range of multiple myeloma cell lines. G9a expression portends poorer survival outcomes in a cohort of multiple myeloma patients. Depletion of G9a inhibited proliferation and tumorigenesis in multiple myeloma. RelB was significantly downregulated by G9a depletion or small molecule inhibition of G9a/GLP inhibitor UNC0642, inducing transcription of proapoptotic genes Bim and BMF. Rescuing RelB eliminated the inhibition in proliferation and tumorigenesis by G9a depletion. CONCLUSIONS: In this study, we demonstrated that G9a is upregulated in most multiple myeloma cell lines. Furthermore, G9a loss-of-function analysis provided evidence that G9a contributes to multiple myeloma cell survival and proliferation. This study found that G9a interacts with NF-κB pathway as a key regulator of RelB in multiple myeloma and regulates RelB-dependent multiple myeloma survival. G9a therefore is a promising therapeutic target for multiple myeloma.

Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression.

Tumor-specific metabolic rewiring, acquired to confer a proliferative and survival advantage over nontransformed cells, represents a renewed focus in cancer therapy development. Hepatocellular carcinoma (HCC), a malignancy that has hitherto been resistant to compounds targeting oncogenic signaling pathways, represents a candidate cancer to investigate the efficacy of selectively antagonizing such adaptive metabolic reprogramming. To this end, we sought to characterize metabolic changes in HCC necessary for tumorigenesis. We analyzed gene expression profiles in three independent large-scale patient cohorts who had HCC. We identified a commonly deregulated purine metabolic signature in tumors with the extent of purine biosynthetic enzyme up-regulation correlated with tumor grade and a predictor of clinical outcome. The functional significance of enhanced purine metabolism as a hallmark in human HCC was then validated using a combination of HCC cell lines, patient-derived xenograft (PDX) organoids, and mouse models. Targeted ablation of purine biosynthesis by knockdown of the rate-limiting enzyme inosine-5'-monophosphate dehydrogenase (IMPDH) or using the drug mycophenolate mofetil (MMF) reduced HCC proliferation in vitro and decreased the tumor burden in vivo. In comparing the sensitivities of PDX tumor organoids to MMF therapy, we found that HCC tumors defined by high levels of IMPDH and guanosine nucleosides were most susceptible to treatment. Mechanistically, a phosphoinositide 3-kinase (PI3K)-E2F transcription factor 1 (E2F1) axis coordinated purine biosynthetic enzyme expression, deregulation of which altered the activity of mitogen-activated protein kinase/RAS signaling. Simultaneously abolishing PI3K signaling and IMPDH activity with clinically approved inhibitors resulted in greatest efficacy in reducing tumor growth in a PDX mouse model. Conclusion: Enhanced purine metabolic activity regulated by PI3K pathway-dependent activation of E2F1 promotes HCC carcinogenesis, suggesting the potential for targeting purine metabolic reprogramming as a precision therapeutic strategy for patients with HCC.

A Flexi-PEGDA Upconversion Implant for Wireless Brain Photodynamic Therapy.

Near-infrared (NIR) activatable upconversion nanoparticles (UCNPs) enable wireless-based phototherapies by converting deep-tissue-penetrating NIR to visible light. UCNPs are therefore ideal as wireless transducers for photodynamic therapy (PDT) of deep-sited tumors. However, the retention of unsequestered UCNPs in tissue with minimal options for removal limits their clinical translation. To address this shortcoming, biocompatible UCNPs implants are developed to deliver upconversion photonic properties in a flexible, optical guide design. To enhance its translatability, the UCNPs implant is constructed with an FDA-approved poly(ethylene glycol) diacrylate (PEGDA) core clad with fluorinated ethylene propylene (FEP). The emission spectrum of the UCNPs implant can be tuned to overlap with the absorption spectra of the clinically relevant photosensitizer, 5-aminolevulinic acid (5-ALA). The UCNPs implant can wirelessly transmit upconverted visible light till 8 cm in length and in a bendable manner even when implanted underneath the skin or scalp. With this system, it is demonstrated that NIR-based chronic PDT is achievable in an untethered and noninvasive manner in a mouse xenograft glioblastoma multiforme (GBM) model. It is postulated that such encapsulated UCNPs implants represent a translational shift for wireless deep-tissue phototherapy by enabling sequestration of UCNPs without compromising wireless deep-tissue light delivery.

Nanodiamond-Mediated Delivery of a G9a Inhibitor for Hepatocellular Carcinoma Therapy.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with high mortality but limited therapeutic options. Epigenetic regulations including DNA methylation and histone modification control gene expressions and play a crucial role during tumorigenesis. G9a, also known as EHMT2 (euchromatic histone-lysine N-methyltransferase 2), is a histone methyltransferase predominantly responsible for dimethylation of histone H3 lysine 9 (H3K9). G9a has been shown to play a key role in promoting tumor progression. Recent studies have identified that G9a is a critical mediator of HCC pathogenesis. UNC0646 is a G9a inhibitor that has shown potent in vitro efficacy. However, due to its water insolubility, the in vivo efficacy of UNC0646 is not satisfactory. In this study, nanodiamonds (NDs) were utilized as a drug delivery platform to improve in vivo delivery of this small-molecule inhibitor. Our results showed that ND-UNC0646 complexes could be rapidly synthesized by physical adsorption, meanwhile possessing favorable drug delivery properties and was able to improve the dispersibility of UNC0646 in water, therefore making it amenable for intravenous administration. The release profile of UNC0646 from ND-UNC0646 was demonstrated to be pH-responsive. Moreover, ND-UNC0646 maintained the biological functionality of UNC0646, with higher efficacy in reducing H3K9 methylation as well as enhanced invasion suppressive effects. Most importantly, increased in vivo efficacy was demonstrated using an orthotopic HCC mouse model, which paves the way of translating this small-molecule inhibitor toward HCC treatment. Our work demonstrates the potential of NDs in the clinical application for HCC treatment.