The Impact of Deprescribing Interventions on the Drug Burden Index and Other Outcomes: A Systematic Review.

OBJECTIVES: The Drug Burden Index (DBI) calculates a person's exposure to anticholinergic and sedative medications. We aimed to review randomized controlled trials (RCTs) of deprescribing interventions that reported the DBI as an outcome, their characteristics, effectiveness in reducing the DBI, and impact on other outcomes. DESIGN: Systematic review with meta-analysis. SETTING AND PARTICIPANTS: RCTs of deprescribing interventions where the DBI was measured as a primary or secondary outcome in humans within any setting were included. METHODS: Electronic databases, citation indexes, and gray literature were searched from April 1, 2007, to September 1, 2023. Quality was assessed using the Cochrane risk-of-bias tool. RESULTS: Of 1721 records identified, 9 met the inclusion criteria. Six interventions were delivered by pharmacists and 3 were delivered by pharmacists/nurses or pharmacists/geriatricians. All interventions required at least intermediate-level skills and involved multiple components and target groups. Studies were conducted in the community (n = 5), nursing homes (n = 2), and hospitals (n = 2). The mean or median age was ≥75 years and most participants were women in all studies. Most (n = 6) studies were underpowered. The follow-up period ranged from 3 to 12 months. Three studies reported a lower DBI in the intervention group compared with control: 1 pharmacist independent prescriber-delivered in nursing homes (adjusted rate ratio, 0.83; 95% CI, 0.74 to 0.92), 1 pharmacist/nurse practitioner-delivered in hospital (adjusted mean difference (MD), -0.28; 95% CI, -0.51 to -0.04), and 1 geriatrician/pharmacist-delivered in hospital (MD, -0.28; 95% CI, -0.52 to -0.04). Meta-analysis showed no difference in the change in DBI between control and intervention groups in the community including nursing homes (MD, -0.03; 95% CI, -0.08 to 0.01) or hospital setting (MD, -0.19; 95% CI, -0.45 to 0.06). Interventions had inconsistent effects on cognition and no effect on other reported outcomes. CONCLUSIONS AND IMPLICATIONS: RCTs of deprescribing interventions had no significant impact on reducing DBI or improving outcomes. Further suitably powered studies are required.

Treatment of critical bleeding events in patients with immune thrombocytopenia: a protocol for a systematic review and meta-analysis.

BACKGROUND: Critical bleeding events in adults and children with ITP are medical emergencies; however, evidence-based treatment protocols are lacking. Due to the severe thrombocytopenia, (typically platelet count less than 20 × 109/L), a critical bleed portends a high risk of death or disability. We plan to perform a systematic review and meta-analysis of treatments for critical bleeding in patients with ITP that will inform evidence-based recommendations. METHODS: Literature searches will be conducted in four electronic databases: Ovid MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and PubMed. Eligible studies will be randomized controlled trials or observational studies that enrolled patients with ITP describing one or more interventions for the management of critical bleeding. Title and abstract screening, full-text screening, data extraction, and risk of bias evaluation will be conducted independently and in duplicate using Covidence and Excel. Outcomes will be pooled for meta-analysis where appropriate or summarized descriptively. Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology will be used to evaluate the certainty of the evidence. Primary outcomes of interest will include frequency of critical bleeds, mortality and bleeding-related mortality, bleeding resolution, platelet count, and disability. DISCUSSION: Evidence-based treatments for critical bleeding in patients with ITP are needed to improve patient outcomes and standardize care in the emergency setting. SYSTEMATIC REVIEW REGISTRATION: CRD42020161206.

Association of the Drug Burden Index (DBI) exposure with outcomes: A systematic review.

BACKGROUND: The Drug Burden Index (DBI) measures an individual's total exposure to anticholinergic and sedative medications. This systematic review aimed to investigate the association of the DBI with clinical and prescribing outcomes in observational pharmaco-epidemiological studies, and the effect of DBI exposure on functional outcomes in pre-clinical models. METHODS: A systematic search of nine electronic databases, citation indexes and gray literature was performed (April 1, 2007-December 31, 2022). Studies that reported primary data on the association of the DBI with clinical or prescribing outcomes conducted in any setting in humans aged ≥18 years or animals were included. Quality assessment was performed using the Joanna Briggs Institute critical appraisal tools and the Systematic Review Centre for Laboratory animal Experimentation risk of bias tool. RESULTS: Of 2382 studies screened, 70 met the inclusion criteria (65 in humans, five in animals). In humans, outcomes reported included function (n = 56), cognition (n = 20), falls (n = 14), frailty (n = 7), mortality (n = 9), quality of life (n = 8), hospitalization (n = 7), length of stay (n = 5), readmission (n = 1), other clinical outcomes (n = 15) and prescribing outcomes (n = 2). A higher DBI was significantly associated with increased falls (11/14, 71%), poorer function (31/56, 55%), and cognition (11/20, 55%) related outcomes. Narrative synthesis was used due to significant heterogeneity in the study population, setting, study type, definition of DBI, and outcome measures. Results could not be pooled due to heterogeneity. In animals, outcomes reported included function (n = 18), frailty (n = 2), and mortality (n = 1). In pre-clinical studies, a higher DBI caused poorer function and frailty. CONCLUSIONS: A higher DBI may be associated with an increased risk of falls and decreased function and cognition. Higher DBI was inconsistently associated with increased mortality, length of stay, frailty, hospitalization or reduced quality of life. Human observational findings with respect to functional outcomes are supported by preclinical interventional studies. The DBI may be used as a tool to identify older adults at higher risk of harm.

A comprehensive AI-driven analysis of large-scale omic datasets reveals novel dual-purpose targets for the treatment of cancer and aging.

As aging and tumorigenesis are tightly interconnected biological processes, targeting their common underlying driving pathways may induce dual-purpose anti-aging and anti-cancer effects. Our transcriptomic analyses of 16,740 healthy samples demonstrated tissue-specific age-associated gene expression, with most tumor suppressor genes downregulated during aging. Furthermore, a large-scale pan-cancer analysis of 11 solid tumor types (11,303 cases and 4431 control samples) revealed that many cellular processes, such as protein localization, DNA replication, DNA repair, cell cycle, and RNA metabolism, were upregulated in cancer but downregulated in healthy aging tissues, whereas pathways regulating cellular senescence were upregulated in both aging and cancer. Common cancer targets were identified by the AI-driven target discovery platform-PandaOmics. Age-associated cancer targets were selected and further classified into four groups based on their reported roles in lifespan. Among the 51 identified age-associated cancer targets with anti-aging experimental evidence, 22 were proposed as dual-purpose targets for anti-aging and anti-cancer treatment with the same therapeutic direction. Among age-associated cancer targets without known lifespan-regulating activity, 23 genes were selected based on predicted dual-purpose properties. Knockdown of histone demethylase KDM1A, one of these unexplored candidates, significantly extended lifespan in Caenorhabditis elegans. Given KDM1A's anti-cancer activities reported in both preclinical and clinical studies, our findings propose KDM1A as a promising dual-purpose target. This is the first study utilizing an innovative AI-driven approach to identify dual-purpose target candidates for anti-aging and anti-cancer treatment, supporting the value of AI-assisted target identification for drug discovery.

Prospective evaluation of postoperative pain and opioid use after minor urologic surgery.

INTRODUCTION: Filling an opioid prescription after a minor urologic procedure increases patient risk of overdose and misuse. Strategies to reduce the number of opioids reaching the community are critical. This study evaluates opioid use after minor urologic procedures at a Canadian academic center and guides future prescribing recommendations. METHODS: We prospectively evaluated patients over 18 years old undergoing minor urologic procedures (penile, scrotal, urethral, etc.) from September 2020 to May 2022. Consenting participants were given a pain diary and postoperative pain questionnaire. Patients on chronic pain medications or those who had major surgery within six months were excluded. Response rate, pain on visual analog scale, pain control satisfaction, quantity of opioids prescribed, and consumption of opioid and non-opioid medication were collected and analyzed. RESULTS: Ninety-five patients met the inclusion criteria. The mean age was 61.7 years (range 20- 87) and 96% of patients identified as male. The response rate for the opioid diary and pain questionnaire was 57%. Forty-two patients (78%) were offered an opioid prescription following their surgery, but only 12 of those patients (22%) filled and consumed any opioids analgesics. Forty-two patients (78%) used no postoperative opioids, and the mean oral morphine equivalents (OME) consumed was 5.87 (standard deviation 16.7). There was a total of 259 OME unused from post-procedure prescriptions. The mean overall pain score for patients who did and did not fill opioid prescriptions were 3.18/10 and 1.79/10 (p<0.01), respectively, with mean overall pain management satisfaction score of 8.63/10 and 8.58/10 (p=0.94), respectively. CONCLUSIONS: Most patients undergoing minor urologic procedures do not require opioids to manage postoperative pain. Based on our data, we suggest that a prescription for 39 OME would adequately treat postoperative pain in 95% of patients undergoing minor urologic procedures. Education around pain management with non-narcotic modalities is imperative, and practice changes are warranted to address the opioid crisis within our specialty.

Biomedical generative pre-trained based transformer language model for age-related disease target discovery.

Target discovery is crucial for the development of innovative therapeutics and diagnostics. However, current approaches often face limitations in efficiency, specificity, and scalability, necessitating the exploration of novel strategies for identifying and validating disease-relevant targets. Advances in natural language processing have provided new avenues for predicting potential therapeutic targets for various diseases. Here, we present a novel approach for predicting therapeutic targets using a large language model (LLM). We trained a domain-specific BioGPT model on a large corpus of biomedical literature consisting of grant text and developed a pipeline for generating target prediction. Our study demonstrates that pre-training of the LLM model with task-specific texts improves its performance. Applying the developed pipeline, we retrieved prospective aging and age-related disease targets and showed that these proteins are in correspondence with the database data. Moreover, we propose CCR5 and PTH as potential novel dual-purpose anti-aging and disease targets which were not previously identified as age-related but were highly ranked in our approach. Overall, our work highlights the high potential of transformer models in novel target prediction and provides a roadmap for future integration of AI approaches for addressing the intricate challenges presented in the biomedical field.

AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor.

The application of artificial intelligence (AI) has been considered a revolutionary change in drug discovery and development. In 2020, the AlphaFold computer program predicted protein structures for the whole human genome, which has been considered a remarkable breakthrough in both AI applications and structural biology. Despite the varying confidence levels, these predicted structures could still significantly contribute to structure-based drug design of novel targets, especially the ones with no or limited structural information. In this work, we successfully applied AlphaFold to our end-to-end AI-powered drug discovery engines, including a biocomputational platform PandaOmics and a generative chemistry platform Chemistry42. A novel hit molecule against a novel target without an experimental structure was identified, starting from target selection towards hit identification, in a cost- and time-efficient manner. PandaOmics provided the protein of interest for the treatment of hepatocellular carcinoma (HCC) and Chemistry42 generated the molecules based on the structure predicted by AlphaFold, and the selected molecules were synthesized and tested in biological assays. Through this approach, we identified a small molecule hit compound for cyclin-dependent kinase 20 (CDK20) with a binding constant Kd value of 9.2 ± 0.5 µM (n = 3) within 30 days from target selection and after only synthesizing 7 compounds. Based on the available data, a second round of AI-powered compound generation was conducted and through this, a more potent hit molecule, ISM042-2-048, was discovered with an average Kd value of 566.7 ± 256.2 nM (n = 3). Compound ISM042-2-048 also showed good CDK20 inhibitory activity with an IC50 value of 33.4 ± 22.6 nM (n = 3). In addition, ISM042-2-048 demonstrated selective anti-proliferation activity in an HCC cell line with CDK20 overexpression, Huh7, with an IC50 of 208.7 ± 3.3 nM, compared to a counter screen cell line HEK293 (IC50 = 1706.7 ± 670.0 nM). This work is the first demonstration of applying AlphaFold to the hit identification process in drug discovery.

Accuracy of International Classification of Diseases, 10th Revision Codes for Identifying Sepsis: A Systematic Review and Meta-Analysis.

Administrative databases are increasingly used in research studies to capture clinical outcomes such as sepsis. This systematic review and meta-analysis examines the accuracy of International Classification of Diseases, 10th revision (ICD-10), codes for identifying sepsis in adult and pediatric patients. DATA SOURCES: We searched MEDLINE, EMBASE, Web of Science, CENTRAL, Epistemonikos, and McMaster Superfilters from inception to September 7, 2021. STUDY SELECTION: We included studies that validated the accuracy of sepsis ICD-10 codes against any reference standard. DATA EXTRACTION: Three authors, working in duplicate, independently extracted data. We conducted meta-analysis using a random effects model to pool sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We evaluated individual study risk of bias using the Quality Assessment of Diagnostic Accuracy Studies tool and assessed certainty in pooled diagnostic effect measures using the Grading of Recommendations Assessment, Development, and Evaluation framework. DATA SYNTHESIS: Thirteen eligible studies were included in the qualitative synthesis and the meta-analysis. Eleven studies used manual chart review as the reference standard, and four studies used registry databases. Only one study evaluated pediatric patients exclusively. Compared with the reference standard of detailed chart review and/or registry databases, the pooled sensitivity for sepsis ICD-10 codes was 35% (95% CI, 22-48, low certainty), whereas the pooled specificity was 98% (95% CI: 98-99, low certainty). The PPV for ICD-10 codes ranged from 9.8% to 100% (median, 72.0%; interquartile range [IQR], 50.0-84.7%). NPV ranged from 54.7% to 99.1% (median, 95.9%; interquartile range, 85.5-98.3%). CONCLUSIONS: Sepsis is undercoded in administrative databases. Future research is needed to explore if greater consistency in ICD-10 code definitions and enhanced quality measures for ICD-10 coders can improve the coding accuracy of sepsis in large databases.

Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics - An AI-Enabled Biological Target Discovery Platform.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease with ill-defined pathogenesis, calling for urgent developments of new therapeutic regimens. Herein, we applied PandaOmics, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and direct iPSC-derived motor neurons (diMNs) (135 cases; 31 controls) from Answer ALS. Seventeen high-confidence and eleven novel therapeutic targets were identified and will be released onto ALS.AI (http://als.ai/). Among the proposed targets screened in the c9ALS Drosophila model, we verified 8 unreported genes (KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA) whose suppression strongly rescues eye neurodegeneration. Dysregulated pathways identified from CNS and diMN data characterize different stages of disease development. Altogether, our study provides new insights into ALS pathophysiology and demonstrates how AI speeds up the target discovery process, and opens up new opportunities for therapeutic interventions.

Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to classify a multiplicity of mechanisms driving the aging process is the hallmarks of aging. In addition to the classic nine hallmarks of aging, processes such as extracellular matrix stiffness, chronic inflammation and activation of retrotransposons are also often considered, given their strong association with aging. In this study, we used a variety of target identification and prioritization techniques offered by the AI-powered PandaOmics platform, to propose a list of promising novel aging-associated targets that may be used for drug discovery. We also propose a list of more classical targets that may be used for drug repurposing within each hallmark of aging. Most of the top targets generated by this comprehensive analysis play a role in inflammation and extracellular matrix stiffness, highlighting the relevance of these processes as therapeutic targets in aging and age-related diseases. Overall, our study reveals both high confidence and novel targets associated with multiple hallmarks of aging and demonstrates application of the PandaOmics platform to target discovery across multiple disease areas.

Uptake of osteoporosis treatment recommended by an orthogeriatrics service after hip fracture: Retrospective cohort study of prevalence and potential barriers and enablers at a tertiary referral hospital in Sydney.

OBJECTIVE: The primary aim was to determine the 12-month period prevalence of and time to osteoporosis treatment following minimal trauma hip fractures in patients who were recommended treatment by an orthogeriatrics service. The secondary aim was to determine the factors associated with receiving treatment including the impact of osteoporosis clinic follow-up. METHODS: A retrospective cohort study of patients with minimal trauma hip fractures admitted at a tertiary hospital in Sydney between 1 April 2017 and 31 March 2019 was performed. Baseline characteristics were collected from medical records. Osteoporosis treatment data were collected from patients and general practitioners. Univariate and multivariate logistic regression analyses were used to determine the factors associated with receiving osteoporosis treatment. RESULTS: There were 189 participants who consented to participate with a mean age of 84.6 years. Most (76.7%) were females, 18.5% were nursing home residents, 70.9% had normal cognition, 20.6% were taking osteoporosis treatment prior to admission, 61.9% had osteoporosis treatment recommendations documented on the discharge summary, and 10.1% were followed up in the osteoporosis clinic. Ninety-eight patients (51.9%) received treatment within the first 12 months after fracture with a median time to treatment of 90 days. Factors associated with receiving osteoporosis treatment within 12 months on multivariate analysis included normal cognition (p = 0.03), taking osteoporosis treatment prior to admission (p < 0.001), including treatment recommendations in the discharge summary (p = 0.006) and osteoporosis clinic follow-up (p < 0.001). CONCLUSIONS: Osteoporosis treatment after hip fracture remains suboptimal at this hospital. Patient and health service factors associated with treatment uptake could inform future quality improvement work.

TPI1-reduced extracellular vesicles mediated by Rab20 downregulation promotes aerobic glycolysis to drive hepatocarcinogenesis.

Rab GTPases are major mediators that ensure the proper spatiotemporal regulation of intracellular trafficking. Functional impairment and altered expression of Rab proteins have been revealed in various human cancers. There is an emerging evidence about the role of Rab proteins in the biogenesis of extracellular vesicles (EVs). In hepatocellular carcinoma (HCC), using RNA sequencing comparing expression profiles of adjacent non-tumorous tissues and HCC, Rab20 is identified to be the most frequently downregulated Rab member in HCC. Functionally, restoration of Rab20 in metastatic HCC cells results in the release of EVs with a diminished activity to promote cell growth, motility and metastasis. Conversely, EVs released from normal liver cells with Rab20 knockdown loses suppressive effect on HCC cell growth and motility. Proteomic profiling revealed the level of triosephosphate isomerase 1 (TPI1), a glycolytic enzyme, in EVs to be positively associated with Rab20 expression of the releasing cells. TPI1 targeted to be expressed in EVs released by Rab20 knockdown cells compromises the oncogenic activity of EVs. Besides, EVs released by TPI1 knockdown cells recapitulates the promoting effect of EVs derived from HCC cells with Rab20 underexpression. Aerobic glycolysis is beneficial to the survival and proliferation of tumour cells. Here, we observed that the enhanced cell growth and motility are driven by the enhanced aerobic glycolysis induced by EVs with reduced TPI1. The addition of glycolytic inhibitor blocks the promoting effect of EVs with reduced TPI1. Taken together, our study provides a mechanistic link among tumour cell-derived EVs and glucose metabolism in HCC with Rab20 deregulation.

High risk of Clostridium difficile infection among spinal cord injured patients after the use of antibiotics commonly used to treat urinary tract infections.

AIM: To characterize the use of common urinary tract infections (UTI)-relevant antibiotics after an SCI and determine the risk of Clostridium difficile infection (CDI) from these antibiotics. METHODS: We used routinely collected data from Ontario (Canada) to conduct a retrospective, cohort study. We identified people >18 years of age with a traumatic SCI between April 2003 and March 2017. The primary exposure was an outpatient UTI-relevant antibiotic prescription during our observation period, and the primary outcome was evidence of a CDI. An adjusted cox proportional hazards model was used, and antibiotic exposure was modeled as a categorical, time-varying variable based on whether the patient likely had a UTI or not. RESULTS: We identified 2528 people with SCI; 1642 (65%) were exposed at least once to an antibiotic of interest. The most commonly prescribed UTI-relevant antibiotic was fluoroquinolone (34%). Most patients did not have investigations for a UTI before the use of any of the different antibiotic classes. A small number of patients (5%) used chronic (>3 months) UTI-relevant antibiotics. The overall proportion of patients diagnosed with CDI was 7.4% (9.3/10 000 patient-days). The adjusted hazard ratio for CDI within 30 days was 3.5 (95% confidence interval, 1.9-6.7, p < .01) if they were exposed to a UTI-relevant antibiotic likely associated with a UTI, which was similar to the risk from UTI-relevant antibiotics which may not have been for a UTI. CONCLUSIONS: The rate of CDI is high in this population and outpatient antibiotics that are commonly used for UTIs are a significant risk factor for CDI.

Urological malignancies in neurogenic patients.

PURPOSE OF REVIEW: To review recent literature related to urologic malignancies in patients with neurogenic lower urinary tract dysfunction (NLUTD). We performed a literature search of electronic databases (PubMed, ScienceDirect, Scopus, and CIANHL), with a focus on articles published between January 2015 and December 2019. RECENT FINDINGS: Recent reports demonstrate a lower incidence of bladder cancer in the NLUTD population than previously found, although still significantly higher than the general population. Bladder cancer in patients with NLUTD is usually diagnosed at a younger age, and is associated with higher rates of squamous cell cancer, a higher stage at presentation, and increased mortality. Evidence for screening for bladder cancer in NLUTD is conflicting, with no formal protocols proven for general use. NLUTD has been shown to have a lower rate of prostate cancer, and may be associated with an earlier diagnosis of renal cancer. SUMMARY: Genitourinary malignancies, although still rare, are an important source of morbidity and mortality in patients with NLUTD. Physicians should recognize that bladder cancer in NLUTD is often a lethal disease. Further research is needed to assist physicians with early recognition of these malignancies to improve patient outcomes.

Predictors of mortality in Maori, Pacific Island, and European patients diagnosed with dementia at a New Zealand Memory Service.

BACKGROUND: As the economic impact of dementia on health and social care increases, governments require disease-specific epidemiological data that will help inform spending and policy decisions. The aim of this study is to examine predictors of mortality in dementia in consecutive referrals to a New Zealand (NZ) memory service that includes Maori, Pacific Islander, and NZ European patients. METHODS: Date of birth, sex, ethnicity, living situation, cognitive function, dementia subtype, dementia severity, physical comorbidity, and medication data were collected from electronic health records. The resulting data set was linked to administrative data on mortality and last hospital contact dates to allow time-dependent survival analyses. RESULTS: The risk of death in people with dementia was increased by age (adjusted HR per year 1.08, 95%CI:1.05-1.12) and lower cognitive score at baseline (adjusted HR for severe impairment:2.54, 95% CI:1.25-5.16), and was reduced by cholinesterase inhibitors (adjusted HR:0.54, 95% CI:0.34-0.88). Compared to NZ Europeans (HR:1.19, 95% CI:0.63-2.25), antipsychotics increased the risk of death three-fold in Maori (adjusted HR:3.62, 95% CI:0.79-16.7) and Pacific Islanders (adjusted HR:2.54, 95%CI:1.10-5.85). CONCLUSIONS: Further research is required to elucidate the mechanisms underlying the survival rates in Maori and Pacific Islanders living with dementia in NZ,and their increased risk of death if antipsychotics are used.

Tumour extracellular vesicle-derived Complement Factor H promotes tumorigenesis and metastasis by inhibiting complement-dependent cytotoxicity of tumour cells.

The complement system is involved in the immunosurveillance of pathogens and tumour cells. Proteomic profiling revealed that extracellular vesicles (EVs) released by metastatic hepatocellular carcinoma (HCC) cells contained a significant number of complement proteins. Complement Factor H (CFH), an abundant soluble serum protein that inhibits the alternative complement pathway, was found to be highly expressed in EVs of metastatic HCC cell lines. Here, we investigated the functional role of EV-CFH and explored the therapeutic efficacy of targeting EV-CFH with an anti-CFH antibody in HCC. The results showed that EVs that are enriched in CFH promoted HCC cell growth, migration, invasiveness and enhanced liver tumour formation in mice. EV-CFH also promoted metastasis, which was significantly abrogated when treated with an anti-CFH antibody. These findings demonstrate an unexplored function of EV-CFH in protecting HCC cells by evading complement attack, thereby facilitating tumorigenesis and metastasis. Lastly, we demonstrated the therapeutic efficacy of an anti-CFH antibody in suppressing tumour formation in a syngeneic mouse model. This study suggests a new therapeutic strategy for HCC, by inhibiting EV-CFH with a tumour specific anti-CFH antibody.

Galectin-1 promotes hepatocellular carcinoma and the combined therapeutic effect of OTX008 galectin-1 inhibitor and sorafenib in tumor cells.

BACKGROUND: Galectins are beta-galactose specific binding proteins. In human cancers, including hepatocellular carcinoma (HCC), galectin-1 (Gal-1) is often found to be overexpressed. In order to combat the dismal diagnosis and death rates of HCC, gene silencing and targeted inhibition of Gal-1 was investigated for its improved therapeutic potential. METHODS: Cellular and secretory Gal-1 levels were analyzed using HCC clinical samples. The study of Gal-1 was carried by both knockdown and overexpression approaches. The stable clones were tested by in vitro assays and in vivo experiments. Mass spectrometry was used to identify downstream targets of Gal-1. The upstream regulator of Gal-1, microRNA-22 (miR-22) was characterized by functional assays. The therapeutic effect of inhibiting Gal-1 was also analyzed. RESULTS: Gal-1 overexpression was observed in HCC and correlated with aggressive clinicopathological features and poorer survival. The loss of Gal-1 resulted in hindered cell migration, invasion and anchorage independent growth. This was also observed in the animal models, in that when Gal-1 was knocked down, there were fewer lung metastases. Proteomic profiling of control and Gal-1 knockdown cells identified that the level of retention in endoplasmic reticulum 1 (RER1) was suppressed when Gal-1 level was reduced. The cell motility of Gal-1 knockdown cells was enhanced upon the rescue of RER1 expression. In HCC tissues, Gal-1 and RER1 expressions displayed a significant positive correlation. The upstream regulator of Gal-1, miR-22 was observed to be underexpressed in HCC tissues and negatively correlated with Gal-1. Silencing of miR-22 resulted in the upregulation of Gal-1 and enhanced cell growth, migration and invasion. However, such enhancement was abolished in cells treated with OTX008, an inhibitor of Gal-1. Combinational treatment of OTX008 and sorafenib significantly reduced tumor growth and size. CONCLUSIONS: Gal-1 overexpression was detected in HCC and this played a role in promoting tumorigenic processes and metastasis. The function of Gal-1 was found to be mediated through RER1. The correlations between miR-22, Gal-1 and RER1 expressions demonstrated the importance of miR-22 regulation on Gal-1/RER1 oncogenic activity. Lastly, the combinational treatment of OTX008 and sorafenib proved to be an improved therapeutic option compared to when administering sorafenib alone.

CBP/p300 Drives the Differentiation of Regulatory T Cells through Transcriptional and Non-Transcriptional Mechanisms.

Regulatory T cells (Treg) are immunosuppressive and negatively impact response to cancer immunotherapies. CREB-binding protein (CBP) and p300 are closely related acetyltransferases and transcriptional coactivators. Here, we evaluate the mechanisms by which CBP/p300 regulate Treg differentiation and the consequences of CBP/p300 loss-of-function mutations in follicular lymphoma. Transcriptional and epigenetic profiling identified a cascade of transcription factors essential for Treg differentiation. Mass spectrometry analysis showed that CBP/p300 acetylates prostacyclin synthase, which regulates Treg differentiation by altering proinflammatory cytokine secretion by T and B cells. Reduced Treg presence in tissues harboring CBP/p300 loss-of-function mutations was observed in follicular lymphoma. Our findings provide novel insights into the regulation of Treg differentiation by CBP/p300, with potential clinical implications on alteration of the immune landscape. SIGNIFICANCE: This study provides insights into the dynamic role of CBP/p300 in the differentiation of Tregs, with potential clinical implications in the alteration of the immune landscape in follicular lymphoma.

Percutaneous irreversible electroporation for the treatment of small renal masses: The first Canadian case series.

INTRODUCTION: Irreversible electroporation (IRE) is a novel technology used in the minimally invasive treatment of small solid organ tumours. Currently, there is a paucity of literature studying treatment of small renal masses (SRMs) with IRE. Our pilot study is the first case series in Canada to use IRE in the treatment of SRMs. METHODS: This retrospective cohort pilot study includes five patients (three females and two males) who presented with a SRM that was deemed not amendable to any other treatment than a radical nephrectomy or IRE. The IRE procedures were carried out by an interventional radiologist in conjunction with a urologist using the Angiodynamics NanoKnife IRE device. RESULTS: Mean tumour size was 28 mm (range 18-39), with a mean R.E.N.A.L. nephrometry score of 8.4±0.55. Over a mean followup of 22.8 months (range 14-31), four out of the five patients did not have a radiological recurrence. No adverse events were reported after the five IRE procedures. Renal function was stable post-IRE, with no to negligible decreases in estimated glomerular filtration rate detected (range +2 to -13 mL/min/1.73 m2). CONCLUSIONS: Our pilot study demonstrates that renal percutaneous IRE is safe to use in the context of challenging-to-treat SRMs. Early radiological and renal function outcomes are encouraging, but further study is required to assess oncological success. The small sample size, retrospective nature of the study, relatively short followup, and the lack of routine renal biopsy to confirm malignancy are the major limitations noted.

Unified Fine-Grained Access Control for Personal Health Records in Cloud Computing.

Attribute-based encryption has been a promising encryption technology to secure personal health records (PHRs) sharing in cloud computing. PHRs consist of the patient data often collected from various sources including hospitals and general practice centres. Different patients' access policies have a common access sub-policy. In this paper, we propose a novel attribute-based encryption scheme for fine-grained and flexible access control to PHRs data in cloud computing. The scheme generates shared information by the common access sub-policy, which is based on different patients' access policies. Then, the scheme combines the encryption of PHRs from different patients. Therefore, both time consumption of encryption and decryption can be reduced. Medical staff require varying levels of access to PHRs. The proposed scheme can also support multi-privilege access control so that medical staff can access the required level of information while maximizing patient privacy. Through implementation and simulation, we demonstrate that the proposed scheme is efficient in terms of time. Moreover, we prove the security of the proposed scheme based on security of the ciphertext-policy attribute-based encryption scheme.