Lentiviral vectors for inducible, transactivator-free advanced therapy medicinal products: Application to CAR-T cells.

Controlling transgene expression through an externally administered inductor is envisioned as a potent strategy to improve safety and efficacy of gene therapy approaches. Generally, inducible ON systems require a chimeric transcription factor (transactivator) that becomes activated by an inductor, which is not optimal for clinical translation due to their toxicity. We generated previously the first all-in-one, transactivator-free, doxycycline (Dox)-responsive (Lent-On-Plus or LOP) lentiviral vectors (LVs) able to control transgene expression in human stem cells. Here, we have generated new versions of the LOP LVs and have analyzed their applicability for the generation of inducible advanced therapy medicinal products (ATMPs) with special focus on primary human T cells. We have shown that, contrary to all other cell types analyzed, an Is2 insulator must be inserted into the 3' long terminal repeat of the LOP LVs in order to control transgene expression in human primary T cells. Importantly, inducible primary T cells generated by the LOPIs2 LVs are responsive to ultralow doses of Dox and have no changes in phenotype or function compared with untransduced T cells. We validated the LOPIs2 system by generating inducible CAR-T cells that selectively kill CD19+ cells in the presence of Dox. In summary, we describe here the first transactivator-free, all-one-one system capable of generating Dox-inducible ATMPs.

Efficacy and safety of universal (TCRKO) ARI-0001 CAR-T cells for the treatment of B-cell lymphoma.

Autologous T cells expressing the Chimeric Antigen Receptor (CAR) have been approved as advanced therapy medicinal products (ATMPs) against several hematological malignancies. However, the generation of patient-specific CAR-T products delays treatment and precludes standardization. Allogeneic off-the-shelf CAR-T cells are an alternative to simplify this complex and time-consuming process. Here we investigated safety and efficacy of knocking out the TCR molecule in ARI-0001 CAR-T cells, a second generation αCD19 CAR approved by the Spanish Agency of Medicines and Medical Devices (AEMPS) under the Hospital Exemption for treatment of patients older than 25 years with Relapsed/Refractory acute B cell lymphoblastic leukemia (B-ALL). We first analyzed the efficacy and safety issues that arise during disruption of the TCR gene using CRISPR/Cas9. We have shown that edition of TRAC locus in T cells using CRISPR as ribonuleorproteins allows a highly efficient TCR disruption (over 80%) without significant alterations on T cells phenotype and with an increased percentage of energetic mitochondria. However, we also found that efficient TCRKO can lead to on-target large and medium size deletions, indicating a potential safety risk of this procedure that needs monitoring. Importantly, TCR edition of ARI-0001 efficiently prevented allogeneic responses and did not detectably alter their phenotype, while maintaining a similar anti-tumor activity ex vivo and in vivo compared to unedited ARI-0001 CAR-T cells. In summary, we showed here that, although there are still some risks of genotoxicity due to genome editing, disruption of the TCR is a feasible strategy for the generation of functional allogeneic ARI-0001 CAR-T cells. We propose to further validate this protocol for the treatment of patients that do not fit the requirements for standard autologous CAR-T cells administration.

Erratum: Physiological lentiviral vectors for the generation of improved CAR-T cells.

[This corrects the article DOI: 10.1016/j.omto.2022.05.003.].

Physiological lentiviral vectors for the generation of improved CAR-T cells.

Anti-CD19 chimeric antigen receptor (CAR)-T cells have achieved impressive outcomes for the treatment of relapsed and refractory B-lineage neoplasms. However, important limitations still remain due to severe adverse events (i.e., cytokine release syndrome and neuroinflammation) and relapse of 40%-50% of the treated patients. Most CAR-T cells are generated using retroviral vectors with strong promoters that lead to high CAR expression levels, tonic signaling, premature exhaustion, and overstimulation, reducing efficacy and increasing side effects. Here, we show that lentiviral vectors (LVs) expressing the transgene through a WAS gene promoter (AW-LVs) closely mimic the T cell receptor (TCR)/CD3 expression kinetic upon stimulation. These AW-LVs can generate improved CAR-T cells as a consequence of their moderate and TCR-like expression profile. Compared with CAR-T cells generated with human elongation factor α (EF1α)-driven-LVs, AW-CAR-T cells exhibited lower tonic signaling, higher proportion of naive and stem cell memory T cells, less exhausted phenotype, and milder secretion of tumor necrosis factor alpha (TNF-α) and interferon (IFN)-É£ after efficient destruction of CD19+ lymphoma cells, both in vitro and in vivo. Moreover, we also showed their improved efficiency using an in vitro CD19+ pancreatic tumor model. We finally demonstrated the feasibility of large-scale manufacturing of AW-CAR-T cells in guanosine monophosphate (GMP)-like conditions. Based on these data, we propose the use of AW-LVs for the generation of improved CAR-T products.

Predicting Treatment Outcomes Using Explainable Machine Learning in Children with Asthma.

Asthma in children is a heterogeneous disease manifested by various phenotypes and endotypes. The level of disease control, as well as the effectiveness of anti-inflammatory treatment, is variable and inadequate in a significant portion of patients. By applying machine learning algorithms, we aimed to predict the treatment success in a pediatric asthma cohort and to identify the key variables for understanding the underlying mechanisms. We predicted the treatment outcomes in children with mild to severe asthma (N = 365), according to changes in asthma control, lung function (FEV1 and MEF50) and FENO values after 6 months of controller medication use, using Random Forest and AdaBoost classifiers. The highest prediction power is achieved for control- and, to a lower extent, for FENO-related treatment outcomes, especially in younger children. The most predictive variables for asthma control are related to asthma severity and the total IgE, which were also predictive for FENO-based outcomes. MEF50-related treatment outcomes were better predicted than the FEV1-based response, and one of the best predictive variables for this response was hsCRP, emphasizing the involvement of the distal airways in childhood asthma. Our results suggest that asthma control- and FENO-based outcomes can be more accurately predicted using machine learning than the outcomes according to FEV1 and MEF50. This supports the symptom control-based asthma management approach and its complementary FENO-guided tool in children. T2-high asthma seemed to respond best to the anti-inflammatory treatment. The results of this study in predicting the treatment success will help to enable treatment optimization and to implement the concept of precision medicine in pediatric asthma treatment.

Understanding the true effects of the COVID-19 lockdown on air pollution by means of machine learning.

During March 2020, most European countries implemented lockdowns to restrict the transmission of SARS-CoV-2, the virus which causes COVID-19 through their populations. These restrictions had positive impacts for air quality due to a dramatic reduction of economic activity and atmospheric emissions. In this work, a machine learning approach was designed and implemented to analyze local air quality improvements during the COVID-19 lockdown in Graz, Austria. The machine learning approach was used as a robust alternative to simple, historical measurement comparisons for various individual pollutants. Concentrations of NO2 (nitrogen dioxide), PM10 (particulate matter), O3 (ozone) and Ox (total oxidant) were selected from five measurement sites in Graz and were set as target variables for random forest regression models to predict their expected values during the city's lockdown period. The true vs. expected difference is presented here as an indicator of true pollution during the lockdown. The machine learning models showed a high level of generalization for predicting the concentrations. Therefore, the approach was suitable for analyzing reductions in pollution concentrations. The analysis indicated that the city's average concentration reductions for the lockdown period were: -36.9 to -41.6%, and -6.6 to -14.2% for NO2 and PM10, respectively. However, an increase of 11.6-33.8% for O3 was estimated. The reduction in pollutant concentration, especially NO2 can be explained by significant drops in traffic-flows during the lockdown period (-51.6 to -43.9%). The results presented give a real-world example of what pollutant concentration reductions can be achieved by reducing traffic-flows and other economic activities.

Using Gene Editing Approaches to Fine-Tune the Immune System.

Genome editing technologies not only provide unprecedented opportunities to study basic cellular system functionality but also improve the outcomes of several clinical applications. In this review, we analyze various gene editing techniques used to fine-tune immune systems from a basic research and clinical perspective. We discuss recent advances in the development of programmable nucleases, such as zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeat (CRISPR)-Cas-associated nucleases. We also discuss the use of programmable nucleases and their derivative reagents such as base editing tools to engineer immune cells via gene disruption, insertion, and rewriting of T cells and other immune components, such natural killers (NKs) and hematopoietic stem and progenitor cells (HSPCs). In addition, with regard to chimeric antigen receptors (CARs), we describe how different gene editing tools enable healthy donor cells to be used in CAR T therapy instead of autologous cells without risking graft-versus-host disease or rejection, leading to reduced adoptive cell therapy costs and instant treatment availability for patients. We pay particular attention to the delivery of therapeutic transgenes, such as CARs, to endogenous loci which prevents collateral damage and increases therapeutic effectiveness. Finally, we review creative innovations, including immune system repurposing, that facilitate safe and efficient genome surgery within the framework of clinical cancer immunotherapies.

DIRECTION: a machine learning framework for predicting and characterizing DNA methylation and hydroxymethylation in mammalian genomes.

MOTIVATION: 5-Methylcytosine and 5-Hydroxymethylcytosine in DNA are major epigenetic modifications known to significantly alter mammalian gene expression. High-throughput assays to detect these modifications are expensive, labor-intensive, unfeasible in some contexts and leave a portion of the genome unqueried. Hence, we devised a novel, supervised, integrative learning framework to perform whole-genome methylation and hydroxymethylation predictions in CpG dinucleotides. Our framework can also perform imputation of missing or low quality data in existing sequencing datasets. Additionally, we developed infrastructure to perform in silico, high-throughput hypotheses testing on such predicted methylation or hydroxymethylation maps. RESULTS: We test our approach on H1 human embryonic stem cells and H1-derived neural progenitor cells. Our predictive model is comparable in accuracy to other state-of-the-art DNA methylation prediction algorithms. We are the first to predict hydroxymethylation in silico with high whole-genome accuracy, paving the way for large-scale reconstruction of hydroxymethylation maps in mammalian model systems. We designed a novel, beam-search driven feature selection algorithm to identify the most discriminative predictor variables, and developed a platform for performing integrative analysis and reconstruction of the epigenome. Our toolkit DIRECTION provides predictions at single nucleotide resolution and identifies relevant features based on resource availability. This offers enhanced biological interpretability of results potentially leading to a better understanding of epigenetic gene regulation. AVAILABILITY AND IMPLEMENTATION: http://www.pradiptaray.com/direction, under CC-by-SA license. CONTACTS: pradiptaray@gmail.com or mchen@utdallas.edu or michael.zhang@utdallas.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Stents for malignant ureteral obstruction.

Malignant ureteral obstruction can result in renal dysfunction or urosepsis and can limit the physician's ability to treat the underlying cancer. There are multiple methods to deal with ureteral obstruction including regular polymeric double J stents (DJS), tandem DJS, nephrostomy tubes, and then more specialized products such as solid metal stents (e.g., Resonance Stent, Cook Medical) and polyurethane stents reinforced with nickel-titanium (e.g., UVENTA stents, TaeWoong Medical). In patients who require long-term stenting, a nephrostomy tube could be transformed subcutaneously into an extra-anatomic stent that is then inserted into the bladder subcutaneously. We outline the most recent developments published since 2012 and report on identifiable risk factors that predict for failure of urinary drainage. These failures are typically a sign of cancer progression and the natural history of the disease rather than the individual type of drainage device. Factors that were identified to predict drainage failure included low serum albumin, bilateral hydronephrosis, elevated C-reactive protein, and the presence of pleural effusion. Head-to-head studies show that metal stents are superior to polymeric DJS in terms of maintaining patency. Discussions with the patient should take into consideration the frequency that exchanges will be needed, the need for externalized hardware (with nephrostomy tubes), or severe urinary symptoms in the case of internal DJS. This review will highlight the current state of diversions in the setting of malignant ureteral obstruction.