A Test of Highly Optimized Tolerance Reveals Fragile Cell-Cycle Mechanisms Are Molecular Targets in Clinical Cancer Trials

Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The “robust yet fragile” duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; ∼32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation

Role of CD45 Signaling Pathway in Galactoxylomannan-Induced T Cell Damage

Previously, we reported that Galactoxylomannan (GalXM) activates the extrinsic and intrinsic apoptotic pathways through an interaction with the glycoreceptors on T cells. In this study we establish the role of the glycoreceptor CD45 in GalXM-induced T cell apoptosis, using CD45+/+ and CD45−/− cell lines, derived from BW5147 murine T cell lymphoma. Our results show that whereas CD45 expression is not required for GalXM association by the cells, it is essential for apoptosis induction. In CD45+/+ cells, CD45 triggering by GalXM reduces the activation of Lck, ZAP70 and Erk1/2. Conversely, in CD45−/− cells, Lck was hyperphosphorylated and did not show any modulation after GalXM stimulation. On the whole, our findings provide evidence that the negative regulation of Lck activation occurs via CD45 engagement. This appears to be related to the capacity of GalXM to antagonize T cell activation and induce T cell death. Overall this mechanism may be responsible for the immune paralysis that follows GalXM administration and could explain the powerful immunosuppression that accompanies cryptococcosis

Long-term controlled antihypertensive therapy in Chernobyl liquidators, its effectiveness and benefits

Aim. To compare effectiveness of controlled antihypertenive therapy (AHT) and standard outpatient care among Chernobyl male liquidators (ML) with mild to moderate arterial hypertension (AH). Material and methods. This 12-month, open, comparative randomized study included 81 ML aged 37-70, with mild to moderate AH. The main group consisted of 42 patients, the control group – of 39; mean age 52.2±1.3 and 51.5±1.1 years, mean AH duration 10±1 and 9.6±1 years, respectively. In main group, patients received an ACE inhibitor spirapril, combined with hypothiazide (12.5-25 mg/d), and atenolol (12.5-100 mg/d), if necessary. In control group, AHT and its correction were performed by outpatient physicians. Medical history collection, physical examination, anthropometry, blood pressure (BP) measurement (three times), and electrocardiograpy were performed. Results. During one-year controlled AHT, comparing to standard outpatient care, more effective decrease in systolic and diastolic BP was achieved. Antihypertensive effect was registered in 78.6% and 38.0% of the main and control group patients, respectively. At the end of the study, most participants from the main group ((78.6%) received combined therapy (2 or more drugs); in control group, this number was only 17.2%. Conclusion. The results of the study demonstrated high effectiveness and benefits of long-term controlled AHT, comparing to standard outpatient care

Apoptosis and TRAF-1 cleavage in Epstein-Barr virus-positive nasopharyngeal carcinoma cells treated with doxorubicin combined with a farnesyl-transferase inhibitor.

Epstein-Barr virus (EBV)-associated nasopharyngeal carcinomas (NPC) are much more sensitive to chemotherapy than other head and neck carcinomas. Spectacular regressions are frequently observed after induction chemotherapy. However, these favorable responses are difficult to predict and often of short duration. So far there have been only few experiments to investigate the mechanisms which underline the cytotoxic effects of anti-neoplastic drugs against NPC cells. In addition, these studies were performed almost entirely on EBV-negative cell lines therefore not truly representative of NPC cells. For the first time, we have used two EBV-positive NPC tumor lines derived from a North African (C15) and a Chinese (C666-1) patient as in vitro targets for a panel of anti-neoplastic agents. Doxorubicin, taxol and in a lesser extent cis-platinum efficiently inhibited NPC cell proliferation at clinically relevant concentrations, but all three agents failed to induce apoptosis. However, massive apoptosis of C15 cells was achieved when doxorubicin (1 microM) was combined with a farnesyl-transferase inhibitor, BIM 2001 (5 microM). Moreover, this apoptotic process was associated with a caspase-dependent early cleavage of the TNF-receptor associated factor 1 (TRAF-1) molecule, a signaling adaptor which is specifically expressed in latently EBV-infected cells. TRAF-1 cleavage might become a useful indicator of chemo-induced apoptosis in EBV-associated NPCs

Field-based Evaluation of Malaria Outbreak Detection & Response, Mudzi and Goromonzi

ObjectiveTo conduct a field-based assessment of the malaria outbreak surveillance system in Mashonaland East, Zimbabwe.IntroductionInfectious disease outbreaks, such as the Ebola outbreak in West Africa, highlight the need for surveillance systems to quickly detect outbreaks and provide data to prevent future pandemics.1–3 The World Health Organization (WHO) developed the Joint External Evaluation (JEE) tool to conduct country-level assessments of surveillance capacity.4 However, considering that outbreaks begin and are first detected at the local level, national-level evaluations may fail to identify capacity improvements for outbreak detection. The gaps in local surveillance system processes illuminate a need for investment in on-the-ground surveillance improvements that may be lower cost than traditional surveillance improvement initiatives, such as enhanced training or strengthening data transfer mechanisms before building new laboratory facilities.5 To explore this premise, we developed a methodology for assessing surveillance systems with special attention to the local level and applied this methodology to the malaria outbreak surveillance system in Mashonaland East, Zimbabwe.MethodsIn a collaboration between the Zimbabwe Field Epidemiology Training Program and the University of Washington, an interview guide was developed based on the Centers for Disease Control and Prevention’s (CDC) Updated Guidelines for Surveillance Evaluations and WHO’s JEE tool.4,6 The guide was tailored in country with input from key stakeholders from the Ministry of Health and Child Care and National Malaria Control Program. Interview guides included questions focused on outbreak detection, response, and control procedures, and surveillance system attributes (preparedness, data quality, timeliness, stability) and functionality (usefulness). The team utilized the tool to evaluate surveillance capacity in eleven clinics across two malaria-burdened districts of Mashonaland East, Mudzi and Goromonzi. Twenty-one interviews were conducted with key informants from the provincial (n=2), district (n=7), and clinic (n=12) levels. Main themes present in interviews were captured using standard qualitative data analysis methods.ResultsThe majority of key informants interviewed were nurses, nurse aids, or nurse officers (57%, 12/21). This evaluation identified clinic-level surveillance system barriers that may be driving malaria outbreak detection and response challenges. Clinics reported little opportunity for cross-training of staff, with 81% (17/21) mentioning that additional staff training support was needed. Only one clinic (10%, 1/11) had malaria emergency preparedness and response guidelines present, a resource recommended by the National Malaria Control Program for all clinics encountering malaria cases. A third of interviewees (33%, 7/21) reported having a standard protocol for validating malaria case data and 29% (6/21) reported challenges with data quality and validation, such as a duplication of case counts. While the surveillance system at all levels detects malaria outbreaks, clinics experience barriers to timely and reliable reporting of cases and outbreaks to the district level. Stability of resources, including transportation and staff capacity, presented barriers, with half (48%, 10/21) of interviewees reporting that their clinics were under-staffed. Additionally, the assessment revealed that the electronic case reporting system (a WHO-developed SMS application, Frontline) that is used to report malaria cases to the district was not functioning in either district, which was unknown at the provincial and national levels. To detect malaria outbreaks, clinics and districts use graphs showing weekly malaria case counts against threshold limit values (TLVs) based on historic five-year malaria case count averages; however, because TLVs are based on 5-year historic data, they are only relevant for clinics that have been in existence for at least five years. Only 30% (3/10) of interviewees asked about outbreak detection graphs reported that TLV graphs were up-to-date.ConclusionsThis surveillance assessment revealed several barriers to system performance at the clinic-level, including challenges with staff cross-training, data quality of malaria case counts, timeliness of updating outbreak detection graphs, stability of transportation, prevention, treatment, and human resources, and usefulness of TLVs for outbreak detection among new clinics. Strengthening these system barriers may improve staff readiness to detect and respond to malaria outbreaks, resulting in timelier outbreak response and decreased malaria mortality. This evaluation has some limitations. We interviewed key informants from a non-random sample covering 30% of all clinics in Mudzi and Goromonzi districts; thus, barriers identified may not be representative of all clinics in these districts. Secondly, evaluators did not interview individuals who may have been involved in outbreak detection and response but were not present at the clinic when interviews were conducted. Lastly, many of the evaluation indicators were based on self-reported information from key informants. Despite these limitations, convenience sampling is common to public health practice, and we reached a saturation of key informant themes with the 21 key informants included in this evaluation.7 By designing evaluation tools that focus on local-level knowledge and priorities, our assessment approach provides a framework for identifying and addressing gaps that may be overlooked when utilizing multi-national tools that evaluate surveillance capacity and improvement priorities at the national level.References1. World Health Organzation. International Health Regulations - Third Edition. Vol Third. Geneva, Switzerland; 2005. doi:10.1017/CBO9781107415324.004.2. Global Health Security Agenda. Implementing the Global Health Security Agenda: Progress and Impact from U.S. Government Investments.; 2018. https://www.ghsagenda.org/docs/default-source/default-document-library/global-health-security-agenda-2017-progress-and-impact-from-u-s-investments.pdf?sfvrsn=4.3. McNamara LA, Schafer IJ, Nolen LD, et al. Ebola Surveillance — Guinea, Liberia, and Sierra Leone. MMWR Suppl. 2016;65(3):35-43. doi:10.15585/mmwr.su6503a6.4. World Health Organization (WHO). Joint External Evaluation Tool: International Health Regulations (2005). Geneva; 2016. http://apps.who.int/iris/bitstream/10665/204368/1/9789241510172_eng.pdf.5. Groseclose SL, Buckeridge DL. Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation. Annu Rev Public Health. 2017;38(1):57-79. doi:10.1146/annurev-publhealth-031816-044348.6. Centers for Disease Control and Prevention. Updated guidelines for evaluating public health surveillance systems: recommendations from the guidelines working group. MWWR. 2001;50(No. RR-13).7. Dworkin SL. Sample size policy for qualitative studies using in-depth interviews. Arch Sex Behav. 2012;41(6):1319-1320. doi:10.1007/s10508-012-0016-6.