Mechanism and rational combinations with GP-2250, a novel oxathiazine derivative, in ovarian cancer.

BACKGROUND: GP-2250, a novel analog of taurultam (TRLT), has emerged as a potent anti-neoplastic drug; however, the mechanisms underlying its effects are not well understood. Here, we investigated the mechanism of action and the biological effects of GP-2250 using in vitro and in vivo models. METHODS: We carried out a series of in vitro (MTT assay, Annexin V/PI assay, colony formation assay, reverse-phase protein array [RPPA], and HRLC/IC analysis) to determine the biological activity of GP-2250 and investigate the mechanism of action. In vivo experiments were carried out to determine the therapeutic efficacy of GP-2250 alone and in combination with standard-of-care drugs (e.g., paclitaxel, cisplatin, topotecan, and poly ADP-ribose polymerase [PARP] inhibitors). RESULTS: We investigated the cytotoxic effect of GP-2250 in 10 ovarian cancer cell lines and found GP-2250 combined with a PARP inhibitor had the greatest synergy. RPPA revealed that GP-2250 inhibited hypoxia-inducible factor-1α, AKT, and mammalian target of rapamycin (mTOR) activation and expression. High-resolution mass spectrometry revealed that hexokinase2 activity and protein expression were significantly reduced by GP-2250 exposure. Furthermore, GP-2250 reduced glycolysis and ATP synthesis in cancer cells. An in vivo pharmacodynamic experiment using the OVCAR8 mouse model demonstrated that 500 mg/kg GP-2250 was effective in downregulating AKT and mTOR activation and expression. In the in vivo therapy experiment using an orthotopic mouse model, a combination of GP-2250 with either PARP inhibitors or bevacizumab showed a significant reduction of tumor weights and nodules compared to those treated with a vehicle, control IgG groups, or monotherapy groups. CONCLUSIONS: Taken together, our data indicate that GP-2250 exerts profound effects on tumor metabolism and, in combination with PARP inhibitors or bevacizumab, showed promising anti-tumor efficacy. These findings could have implications for the clinical development of GP-2250.

Primary Care Provider Medicaid Participation Across the United States, 2016.

PURPOSE: To understand primary care provider participation in Medicaid programs across states and provider specialties and professions. METHODS: We examined the 2016 Medicaid claims data across 45 states and territories from the Transformed Medicaid Statistical Information System (T-MSIS). RESULTS: Of the 616,182 primary care providers we identified, 111,152 (18.0%) saw no Medicaid patients, 88,723 (14.4%) providers saw one to 10 Medicaid patients, 163,806 (26.6%) saw 11 to 100 Medicaid patients, and 252,501 (41.0%) saw more than 100 Medicaid patients in 2016. The proportion of providers who saw more than 100 Medicaid patients ranged from 22.9% in Virginia to 56.1% in New Mexico. Medicaid participation also differed by specialty, from 78.4% among pediatricians to 61.2% among nurse practitioners. This study lays the foundations for using T-MSIS data to identify communities at the highest risk for access barriers and support targeted policy responses.

Overcoming adaptive resistance to anti-VEGF therapy by targeting CD5L.

Antiangiogenic treatment targeting the vascular endothelial growth factor (VEGF) pathway is a powerful tool to combat tumor growth and progression; however, drug resistance frequently emerges. We identify CD5L (CD5 antigen-like precursor) as an important gene upregulated in response to antiangiogenic therapy leading to the emergence of adaptive resistance. By using both an RNA-aptamer and a monoclonal antibody targeting CD5L, we are able to abate the pro-angiogenic effects of CD5L overexpression in both in vitro and in vivo settings. In addition, we find that increased expression of vascular CD5L in cancer patients is associated with bevacizumab resistance and worse overall survival. These findings implicate CD5L as an important factor in adaptive resistance to antiangiogenic therapy and suggest that modalities to target CD5L have potentially important clinical utility.

Enhancing oral delivery of plant-derived vesicles for colitis.

Plant-derived vesicles (PDVs) are attractive for therapeutic applications, including as potential nanocarriers. However, a concern with oral delivery of PDVs is whether they would remain intact in the gastrointestinal tract. We found that 82% of cabbage PDVs were destroyed under conditions mimicking the upper digestive tract. To overcome this limitation, we developed a delivery method whereby lyophilized Eudragit S100-coated cabbage PDVs were packaged into a capsule (Cap-cPDVs). Lyophilization and suspension of PDVs did not have an appreciable impact on PDV structure, number, or therapeutic effect. Additionally, packaging the lyophilized Eudragit S100-coated PDVs into capsules allowed them to pass through the upper gastrointestinal tract for delivery into the colon better than did suspension of PDVs in phosphate-buffered saline. Cap-cPDVs showed robust therapeutic effect in a dextran sulfate sodium-induced colitis mouse model. These findings could have broad implications for the use of PDVs as orally delivered nanocarriers of natural therapeutic plant compounds or other therapeutics.

SimTune: bridging the simulator reality gap for resource management in edge-cloud computing.

Industries and services are undergoing an Internet of Things centric transformation globally, giving rise to an explosion of multi-modal data generated each second. This, with the requirement of low-latency result delivery, has led to the ubiquitous adoption of edge and cloud computing paradigms. Edge computing follows the data gravity principle, wherein the computational devices move closer to the end-users to minimize data transfer and communication times. However, large-scale computation has exacerbated the problem of efficient resource management in hybrid edge-cloud platforms. In this regard, data-driven models such as deep neural networks (DNNs) have gained popularity to give rise to the notion of edge intelligence. However, DNNs face significant problems of data saturation when fed volatile data. Data saturation is when providing more data does not translate to improvements in performance. To address this issue, prior work has leveraged coupled simulators that, akin to digital twins, generate out-of-distribution training data alleviating the data-saturation problem. However, simulators face the reality-gap problem, which is the inaccuracy in the emulation of real computational infrastructure due to the abstractions in such simulators. To combat this, we develop a framework, SimTune, that tackles this challenge by leveraging a low-fidelity surrogate model of the high-fidelity simulator to update the parameters of the latter, so to increase the simulation accuracy. This further helps co-simulated methods to generalize to edge-cloud configurations for which human encoded parameters are not known apriori. Experiments comparing SimTune against state-of-the-art data-driven resource management solutions on a real edge-cloud platform demonstrate that simulator tuning can improve quality of service metrics such as energy consumption and response time by up to 14.7% and 7.6% respectively.

Association of the COVID-19 Pandemic With Medical School Diversity Pathway Programs.

Importance: Medical school pathway programs are a strategy to increase the diversity of the physician workforce. The COVID-19 pandemic may have negatively affected pathway programs, further challenging efforts to increase diversity. Objectives: To describe the changes in medical school pathway programs during the COVID-19 pandemic and identify methods for sustaining and supporting these programs during and after the pandemic. Design, Setting, and Participants: A survey study using an exploratory sequential mixed-method design was conducted from January 4 to August 3, 2021. Semistructured interviews with a sample of medical school pathway program administrators and academic leaders of US allopathic and osteopathic medical school diversity pathway programs identified themes and patterns of change to pathway programs since the onset of the pandemic compared with previous years. These themes were used to develop a survey that was sent to medical schools to assess the association between COVID-19 and their programs. Main Outcomes and Measures: The association between the COVID-19 pandemic and medical school diversity pathway programs was explored using interview and survey data assessing respondent characteristics; changes in the scope, size, and funding of programs in 2020 compared with previous years; and respondents' perceptions of future needs for pathway programs. Results: Twelve program administrators and academic leaders were interviewed. Interviews revealed challenges and benefits of virtual programming in engaging and reaching students and speakers, the value of community partnerships to sustaining programming, and the importance of psychosocial support to mediating students' mental health challenges due to COVID-19 and remote learning. Of 198 schools surveyed in the quantitative phase, 112 responded (56.6%), 106 (94.6%) of which had been sponsoring or assisting with pathway programs during the COVID-19 pandemic. Forty-two respondents (39.6%) had reduced pathway programs since the onset of the COVID-19 pandemic compared with the previous year. Program cancellations were more likely to be noted in elementary school-aged (50.0% decrease in programming; P = .01) and middle school-aged (32.6%; P = .02) students compared with older groups. Conclusions and Relevance: In this survey study, schools indicated that pathway programs were disrupted by COVID-19. Ongoing and flexible supports may be needed to sustain these programs. These findings are timely given recent investments in equity-focused programs to diversify the health workforce.

Molecular Profiles of Serum-Derived Extracellular Vesicles in High-Grade Serous Ovarian Cancer.

Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have a response enabling interval cytoreductive surgery. Clinically useful biomarkers for predicting these outcomes are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated the findings with therapeutic outcomes in patients with HGSC. Using EV-DNA whole-genome sequencing and EV-RNA sequencing, we identified distinct somatic EV-DNA alterations in cancer-hallmark genes and in ovarian cancer genes, as well as significantly altered oncogenic pathways between the R0 group and NACT groups. We also found significantly altered EV-RNA transcriptomic variations and enriched pathways between the groups. Taken together, our data suggest that the molecular characteristics of EVs could enable prediction of patients with HGSC who could undergo R0 surgery or respond to chemotherapy.

Targeting CCR2+ macrophages with BET inhibitor overcomes adaptive resistance to anti-VEGF therapy in ovarian cancer.

PURPOSE: Tumor-associated macrophages (TAMs) are known to contribute to adaptive resistance to anti-vascular endothelial growth factor (VEGF) antibody (AVA) therapy in ovarian cancer. BET (bromodomain and extra-terminal domain) inhibitors (BETi) may have unique roles in targeting TAMs. Our objective was to examine the effects of BETi on TAMs, especially in the context of enhancing the efficacy of AVA therapy. METHODS: We conducted a series of in vitro (MTT assay, apoptosis, flow cytometry, and RNA sequencing) and in vivo (xenograft ovarian cancer model) experiments to determine the biological effects of BETi combined with AVA in ovarian cancer. For statistical analysis, a two-tailed Student's t test (equal variance) or ANOVA was used for multiple groups' comparison, and p < 0.05 was considered significant. RESULTS: BETi resulted in a dose-dependent decrease in cell viability and induced apoptosis (p < 0.01) in ovarian cancer cells (SKOV3ip1, OVCAR5, and OVCAR8). Treatment with BETi significantly increased apoptosis in THP-1 monocytes and macrophages (PMA-differentiated THP-1; p < 0.01). Furthermore, BETi selectively induced greater apoptosis in M2-like macrophages (PMA and IL-4, IL-13-differentiated THP-1) (31.3%-36.1%) than in M1-like macrophages (PMA and LPS-differentiated THP-1) (12.4%-18.5%) (p < 0.01). Flow cytometry revealed that the percentage of M1-like macrophages (CD68+/CD80+) was significantly increased after treatment with low-dose BETi (ABBV-075 0.1 µM; p < 0.05), whereas the percentage of CD68+/CCR2+ macrophages was significantly decreased (p < 0.001); these findings suggest that BETi may selectively inhibit the survival of CCR2+ macrophages and re-polarize the macrophages into an M1-like phenotype. RNA-seq analysis revealed that BETi selectively targeted macrophage infiltration-related cytokines/chemokines in ovarian cancer (adjusted p < 0.05 and Log2 fold change ≥ 1.5). Finally, using in vivo ovarian cancer models, compared with control or monotherapy, the combination of BETi (ABBV-075) and bevacizumab resulted in greater inhibition of tumor growth and macrophage infiltration (p < 0.05) and longer survival of tumor-bearing mice (p < 0.001). CONCLUSIONS: Our findings indicate a previously unrecognized role for BETi in selectively targeting CCR2+ TAMs and enhancing the efficacy of AVA therapy in ovarian cancer.

Endothelial p130cas confers resistance to anti-angiogenesis therapy.

Anti-angiogenic therapies, such as anti-VEGF antibodies (AVAs), have shown promise in clinical settings. However, adaptive resistance to such therapies occurs frequently. We use orthotopic ovarian cancer models with AVA-adaptive resistance to investigate the underlying mechanisms. Genomic profiling of AVA-resistant tumors guides us to endothelial p130cas. We find that bevacizumab induces cleavage of VEGFR2 in endothelial cells by caspase-10 and that VEGFR2 fragments internalize into the nucleus and autophagosomes. Nuclear VEGFR2 and p130cas fragments, together with TNKS1BP1 (tankyrase-1-binding protein), initiate endothelial cell death. Blockade of autophagy in AVA-resistant endothelial cells retains VEGFR2 at the membrane with bevacizumab treatment. Targeting host p130cas with RGD (Arg-Gly-Asp)-tagged nanoparticles or genomic ablation of vascular p130cas in p130casflox/floxTie2Cre mice significantly extends the survival of mice with AVA-resistant ovarian tumors. Higher vascular p130cas is associated with shorter survival of individuals with ovarian cancer. Our findings identify opportunities for new strategies to overcome adaptive resistance to AVA therapy.

Medical end-of-life decision-making in a small resource-poor Caribbean country: a mortality follow-back study of home deaths.

BACKGROUND: In resource-poor countries, including in Latin American and the Caribbean, empirical information about the characteristics and incidence of medical end-of-life decisions (MELDs)-withholding or withdrawing potentially life-prolonging medical treatments-is largely absent. METHODS: The aim was to describe the incidence and decision-making characteristics of MELDs taken prior to the death of people who died at home in Trinidad and Tobago (T&T). A mortality follow-back study was used where a representative sample of deaths occurring at home in 2018 was drawn from death certificates at the national death registry. The general practitioners who certified the deaths were sent a questionnaire. RESULTS: The sample consisted of 309 adult deaths and the response rate was 31% (N=96). Physicians were: mostly male (79.2%), practiced medicine for more than twenty-years (63.5%), had no formal palliative care training (69.8%). Non-sudden deaths represented 76% (N=73), of these, medications to alleviate pain and symptoms in the last 7 days of life were administered in 65.8%, including opioids 21%. Potentially life-prolonging treatments were withheld in 9.6% but none withdrawn. No physician/patient discussions about various end-of-life treatment options occurred in 61.6%. Compared to physicians with no formal training in palliative care, those with training more often: prescribed or administered opioids in the last 7 days of life (35.7% vs. 11.1%, P=0.01), had discussions with patients about end-of-life treatment options (60.7% vs. 24.4%, P=0.002), and discussed medication use to alleviate pain and other symptoms with patients (50% vs. 17.8%, P=0.004). CONCLUSIONS: Differences in the care and treatment general practitioners provided to their patients could be associated with them having been formally trained in palliative care. The necessary support to further develop palliative care in T&T is needed.

Immune microenvironment composition in high-grade serous ovarian cancers based on BRCA mutational status.

PURPOSE: An in-depth analysis of the tumor microenvironment of ovarian cancer is needed. The purpose of this study was to elucidate the architecture of the immune microenvironment of high-grade serous ovarian cancers (HGSCs) with or without BRCA1 and BRCA2 mutations. METHODS: A cohort of highly annotated HGSC patients with known germline BRCA1 and BRCA2 status was selected, and pretreatment tumor tissue specimens were analyzed with a multiplexed staining technique aimed at detecting lymphocytes, macrophages, and fibroblasts in the whole tumor area and in specific regions including epithelium, stroma, and perivascular areas. RESULTS: BRCA1- or BRCA2-mutated tumors showed a more immunogenic microenvironment, characterized by a higher abundance of CD8+ and PD-L1+ cells, than did tumors with wild-type BRCA1 and BRCA2. High numbers of PD-L1+ and PD-L1+CD8+ cells were prognostic for event-free survival (hazard ratio [HR]: 0.41, 95% CI 0.21-0.79, p = 0.008 and HR 0.49, 95% CI 0.26-0.91, p = 0.025, respectively), as were high numbers of epithelial PD-L1+ and FAP+PD-L1+ cells (HR 0.52, 95% CI 0.28-0.96, p = 0.037 and HR 0.27, 95% CI 0.08-0.87, p = 0.029) and CD8+ cells (HR 0.51, 95% CI 0.28-0.93, p = 0.027). CONCLUSIONS: This study reveals substantial differences between the immune microenvironment composition of germline BRCA-mutated and BRCA wild-type HGSC.

CD63-mediated cloaking of VEGF in small extracellular vesicles contributes to anti-VEGF therapy resistance.

Despite wide use of anti-vascular endothelial growth factor (VEGF) therapy for many solid cancers, most individuals become resistant to this therapy, leading to disease progression. Therefore, new biomarkers and strategies for blocking adaptive resistance of cancer to anti-VEGF therapy are needed. As described here, we demonstrate that cancer-derived small extracellular vesicles package increasing quantities of VEGF and other factors in response to anti-VEGF therapy. The packaging process of VEGF into small extracellular vesicles (EVs) is mediated by the tetraspanin CD63. Furthermore, small EV-VEGF (eVEGF) is not accessible to anti-VEGF antibodies and can trigger intracrine VEGF signaling in endothelial cells. eVEGF promotes angiogenesis and enhances tumor growth despite bevacizumab treatment. These data demonstrate a mechanism where VEGF is partitioned into small EVs and promotes tumor angiogenesis and progression. These findings have clinical implications for biomarkers and therapeutic strategies for ovarian cancer.

Assessment of In Vivo siRNA Delivery in Cancer Mouse Models.

RNA interference (RNAi) has rapidly become a powerful tool for target discovery and therapeutics. Small interfering RNAs (siRNAs) are highly effective in mediating sequence-specific gene silencing. However, the major obstacle for using siRNAs for cancer therapeutics is their systemic delivery from the administration site to target cells in vivo. This chapter describes approaches to deliver siRNA effectively for cancer treatment and discusses in detail the current methods to assess pharmacokinetics and biodistribution of siRNAs in vivo.

Trustworthy human-AI partnerships.

In this paper, we foreground some of the key research challenges that arise in the design of trustworthy human-AI partnerships. In particular, we focus on the challenges in designing human-AI partnerships that need to be addressed to help humans and organizations trust their machine counterparts individually or as a collective (e.g., as robot teams or groups of software agents). We also aim to identify the risks associated with human-AI partnerships and therefore determine the associated measures to mitigate these risks. By so doing, we will trigger new avenues of research that will address the key barriers to the adoption of AI-based systems more widely in our daily lives and in industry.