EXTH-20. SINGLE-CELL DRUG ACTIVITY MAPPING IN GLIOBLASTOMA IDENTIFIES EXTENDED DRUG RESPONSE HETEROGENEITY AND THERAPY-INDUCED CELLULAR PLASTICITY

Glioblastoma (GBM) remains a highly malignant and incurable brain tumour. The inability to achieve clinical improvements in GBM treatment can be attributed to the excessive heterogeneity and plasticity of GBM cells, which is reflected by the presence of various cellular states within each tumour. How each of these tumour cell subtypes respond to therapy remains largely unknown. In this work, we developed a functional diagnostic analysis pipeline to measure therapeutic activity in GBM tumour cells at single-cell resolution using mass cytometry by time-of-flight (CyTOF). By applying an optimised GBM-specific and therapy-tailored antibody panel, we measured therapeutic activity upon exposure to ionising radiation (RT) or a small molecule MDM2 inhibitor (AMG232) in a cohort of patient-derived GBM cell lines (n=14). As such, extended heterogeneity in drug responsiveness was reflected by diverse degrees of alterations in cell cycle progression and apoptotic signalling, in addition to shifts in tumoral phenotypic states implying therapy-induced plasticity. A similar approach was used to measure drug activity in freshly resected tumour samples (n=18) harvested from different tumour regions (core or invasive front) within hours following surgery. Accordingly, we identified highly variable fractions of responsive tumour and microenvironmental cell populations in a patient-specific way. The ability to measure drug activity at single-cell resolution in a patient-tailored manner by applying a genotype-agnostic method, paves the way for advanced precision cancer medicine in GBM by offering a novel approach to more precisely select eligible patients for prospective clinical trials.

Sentencing Drug Offenders Justly While Reducing Mass Incarceration

In my paper, I discuss what I believe is the most effective approach to sentencing drug defendants. I start with the proposition that in many, if not most cases, incarcerating drug offenders does more harm than good. Imprisonment contributes to mass incarceration, does not deter unlawful drug activity and has an adverse racial impact. Thus, if a judge can reasonably avoid imposing a prison sentence, he or she should do so. Fortunately, this is the judge’s duty under the law. 18 U.S.C. §3553(a) requires a judge to impose a sentence that is “sufficient but not greater than necessary…” or, in other words, the least restrictive reasonable sentence. Thus, in every case, the judge must first consider whether a non-incarcerative sentence is sufficient. It often will be. In determining the appropriate sentence, a judge should focus on what the offender did and why and what he or she will likely do in the future and pay less attention to such factors as drug type and drug weight. Sometimes, a mandatory minimum sentence will apply and prevent a judge from imposing a fair sentence, but that is outside the judge’s control. Fortunately, because of Booker and its progeny, the Federal Sentencing Guidelines do not pose a similar problem. The judge, of course, must calculate and consider the applicable guideline but in many cases the guideline will be irrelevant to a just sentence. This is so because the guidelines are excessively oriented toward prison sentences and thus frequently conflict with the sufficient but not greater than necessary command of §3553(a). In my paper, I provide numerous examples of sentences that I have imposed and explanations of those sentences to illustrate this approach.

Abstract P433: A Pharmacological Model Predicts Drug Activity In Cardiomyocyte Hypertrophy

Introduction: Cardiomyocyte (CM) hypertrophy is predictive of heart failure, however there are no clinical therapies that target its intracellular pathways. Hypertrophy is a complex process involving numerous neurohormonal and cytokine inputs, resulting in context-dependent responses that determine CM growth. In the face of this complexity, it is critical that computational models are developed. Accurate predictions of drug activity in CM hypertrophy will require a pharmacological model that is developed with and validated against experimental data. Hypothesis: We test the hypothesis that our in silico pharmacological model accurately predicts drugs that inhibit cardiac hypertrophy as well as the context-dependent mechanisms by which they work. Methods: Here we employ a previously published computational model of cardiac hypertrophy signaling. This model utilizes logic-based ordinary differential equations to simulate a network of 106 nodes. Using the DrugBank database, we constructed a pipeline for simulating FDA-approved drugs within this hypertrophy network under multiple environmental contexts. The predicted outcomes of the model were then compared to measured phenotypes from experimental findings in literature. Results: Predicted outcomes of our model were successfully validated against 29 out of 36 distinct experiments described in literature. These simulations identify the optimal drug types that inhibit hypertrophy for each of 17 different stimuli. Sensitivity analyses performed by simulating knockdowns in our model reveals context-dependent mechanisms predicted for 51 drug types. These predictions confirmed, for example, the role of celecoxib in inhibiting CM hypertrophy induced by isoproterenol. Mechanistic analysis suggests celecoxib prevents protein kinase B (Akt) inhibition of glycogen synthase kinase 3 beta (GSK3β), consistent with literature. Conclusions: Our pharmacological model accurately predicts FDA-approved drugs that show in vitro inhibition of CM hypertrophy.

LMD-01. Quantifying intrathecal drug delivery utilizing programmable ventriculoperitoneal shunts

Background Programmable ventriculoperitoneal shunts (pVP shunts) are increasingly utilized for intraventricular chemotherapy, radioimmunotherapy, and/or cellular therapy. Shunt adjustments allow optimization of thecal space drug concentrations with minimization in the peritoneum. Drug delivery quantification using several types of pVP shunts has not been reported. Methods We performed a retrospective analysis on patients with CNS tumors and pVP shunts at Memorial Sloan Kettering Cancer Center from 2003–2020, noting shunt model. CSF flow through the pVP shunt was evaluated using In-111-DTPA scintigraphy at approximately 4 and 24 hours after injection. pVP shunts were calibrated pre-injection to minimize peritoneal flow and re-calibrated to baseline setting 4–5 hours following injection. Scintigraphy studies quantified ventricular-thecal and peritoneal drug activity at these 2 time points. Results Twenty-one CSF flow studies were administered to 15 patients, ages 1–27 years. Diagnoses included medulloblastoma (N=10), metastatic neuroblastoma (N=3), pineoblastoma (N=1), and choroid plexus carcinoma (N=1). Models of pVP shunts included Aesculap Miethke proGAV (N=3), Aesculap Miethke proGAV2.0 (N=3), Codman HAKIM (N=2), Codman Certas Plus (N=1), Medtronic STRATA (N= 5), and Sophysa Polaris (N= 1). All 21 studies (100%) demonstrated ventriculo-thecal drug activity. 29% (6 of 21) of the studies had no peritoneal uptake visible by imaging. 73% (16 of 21) of the studies had minimal peritoneal uptake (<12%), and 24% (5 of 21) demonstrated moderate peritoneal uptake (12–37%). Models of pVP shunts measuring minimal to no peritoneal uptake included: Aesculap Miethke proGAV (N=2), Aesculap Miethke proGAV2.0 (N=3), Codman HAKIM (N=2), Codman Certas Plus (N=1), Medtronic STRATA (N= 3), and Sophysa Polaris (N= 1). Conclusions pVP shunts successfully deliver drugs to the ventriculo-thecal space with 80% of studies having minimal (<12%) peritoneal drug activity. Though efficacy varies by shunt model, low numbers preclude conclusions regarding model superiority. CSF flow scintigraphy studies reliably assess drug distribution.

Antimicrobial activity of copper and silver metal nanoparticles synthesized from Riccia fluitans

Riccia bryophyte, a genus of liverworts that comes under the family of Ricciaceae, order Marchantiales. The plants are primitive plant structure, that's not differentiated into root, stem, and leaf. The material utilized in this study was a Spp of a Riccia fluitans, that grows on damp soil or, less unremarkably, floating in ponds, and is usually utilized in aquariums. The nanoparticles utilized in this study exhibit potential medicinal drug activity. Advantages of its therapeutic potential can be utilized in a sizable number of fields like health care, cosmetics, biomedical, food and feed, drug-gene delivery, surroundings, health mechanics, optics, chemical industries, physical science, area industries, energy science, catalysis, lightweight emitters, single lepton transistors, nonlinear optical devices, and photo-electrochemical applications. This study aimed to gauge the medicinal drug activity of Riccian nanoparticles, copper-loaded nanoparticles, and silver-loaded nanoparticles against varied microorganisms. The result of the study showed that the Nanoparticle, Ag-NP and Cu-Np synthesized from Riccia is having good antimicrobial activity against tested organisms.