Dynamic distribution and expression in vivo of the human interferon gamma gene delivered by adenoviral vector

<p>Abstract</p> <p>Background</p> <p>We previously found that r-hu-IFNγ exerts a potent anti-tumor effect on human nasopharyngeal carcinoma xenografts <it>in vivo</it>. Considering the fact that the clinical use of recombinant IFNγ is limited by its short half-life and systemic side effects, we developed a recombinant adenovirus, Ad-IFNγ.</p> <p>Methods</p> <p>Dynamic distribution of the adenovirus vector and expression of IFNγ were evaluated by Q-PCR and ELISA after intratumoral administration of Ad-IFNγ into CNE-2 xenografts.</p> <p>Results</p> <p>Ad-IFNγ DNA was mainly enriched in tumors where the Ad-IFNγ DNA was injected (<it>P </it>< 0.05, compared to blood or parenchymal organs), as well as in livers (<it>P </it>< 0.05). Concentrations of Ad-IFNγ DNA in other organs and blood were very low. Intratumoral Ad-IFNγ DNA decreased sharply at high concentrations (9 × 10⁵copies/μg tissue DNA), and slowly at lower concentrations (1.7–2.9 × 10⁵copies/μg tissue DNA). IFNγ was detected in the tumors and parenchymal organs. The concentration of IFNγ was highest in the tumor (<it>P </it>< 0.05), followed by the liver and kidney (<it>P </it>< 0.05). High-level intratumoral expression of IFNγ was maintained for at least 7 days, rapidly peaking on day 3 after injection of Ad-IFNγ DNA.</p> <p>Conclusion</p> <p>An IFNγ gene delivered by an adenoviral vector achieved high and consistent intratumoral expression. Disseminated Ad-IFNγ DNA and the transgene product were mainly enriched in the liver.</p

A Computational Method for Prediction of Excretory Proteins and Application to Identification of Gastric Cancer Markers in Urine

A novel computational method for prediction of proteins excreted into urine is presented. The method is based on the identification of a list of distinguishing features between proteins found in the urine of healthy people and proteins deemed not to be urine excretory. These features are used to train a classifier to distinguish the two classes of proteins. When used in conjunction with information of which proteins are differentially expressed in diseased tissues of a specific type versus control tissues, this method can be used to predict potential urine markers for the disease. Here we report the detailed algorithm of this method and an application to identification of urine markers for gastric cancer. The performance of the trained classifier on 163 proteins was experimentally validated using antibody arrays, achieving >80% true positive rate. By applying the classifier on differentially expressed genes in gastric cancer vs normal gastric tissues, it was found that endothelial lipase (EL) was substantially suppressed in the urine samples of 21 gastric cancer patients versus 21 healthy individuals. Overall, we have demonstrated that our predictor for urine excretory proteins is highly effective and could potentially serve as a powerful tool in searches for disease biomarkers in urine in general

PatternLab for proteomics: a tool for differential shotgun proteomics

<p>Abstract</p> <p>Background</p> <p>A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu <it>et al</it>. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen <it>et al</it>. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.</p> <p>Results</p> <p>To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen <it>et al</it>. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine) because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies.</p> <p>Conclusion</p> <p>PatternLab offers an easy and unified access to a variety of feature selection and normalization strategies, each having its own niche. Additionally, graphing tools are available to aid in the analysis of high throughput experimental data. PatternLab is available at <url>http://pcarvalho.com/patternlab</url>.</p

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.</p> <p>Results</p> <p>Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few.</p> <p>Conclusion</p> <p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at <url>http://pcarvalho.com/patternlab</url>.</p

Health-related quality of life in glioma patients in China

<p>Abstract</p> <p>Background</p> <p>Health-related quality of life (HRQOL) has been increasingly emphasized in cancer patients. There are no reports comparing baseline HRQOL of different subgroups of glioma patients prior to surgery.</p> <p>Methods</p> <p>HRQOL assessments by the standard Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire 30 (EORTC QLQ-C30, version 3.0), the Mini-Mental State Examination and Karnofsky Performance Status were obtained from glioma patients prior to surgery.</p> <p>Results</p> <p>Ninety-two pathologically confirmed glioma patients were recruited. There were 84.8% patients with emotional impairment, 75% with social and cognitive impairment, 70.7% with physical impairment, and 50% with role impairment. Eighty-two percent of patients reported fatigue symptoms, 72.8% reported pain, 50% reported appetite loss, 39.1% reported insomnia, and 36.9% reported nausea/vomiting, whereas other symptoms (dyspnea, diarrhea, constipation) in the QLQ-C30 were reported by fewer than 30% of patients. Fatigue and pain symptoms and all "functioning" scales were strongly correlated with global health status/quality of life (QoL). Fatigue was strongly related to all functioning scales, pain, appetite loss, and global health status/QoL. No difference in baseline HRQOL prior to surgery was reported between females and males, among different lesion locations, or between normal- and abnormal-cognition subgroups of glioma patients. Age, KPS, WHO grade, and tumor recurrence significantly affected HRQOL in glioma patients.</p> <p>Conclusions</p> <p>These data provided the baseline HRQOL in glioma patients prior to surgery in China. Most pre-surgery glioma patients indicated emotional, social, cognitive, physical, and role impairment. Fatigue, pain, appetite loss, insomnia, and nausea/vomiting were common in these patients. The fatigue and pain symptoms and all types of functioning strongly affected global health status/QoL. Old age, worse performance status, WHO grade IV and tumor recurrence had deleterious effects on HRQOL.</p

Review of risk factors for human echinococcosis prevalence on the Qinghai-Tibet Plateau, China: a prospective for control options

Objective: Echinococcosis is a major parasitic zoonosis of public health importance in western China. In 2004, the Chinese Ministry of Health estimated that 380,000 people had the disease in the region. The Qinghai-Tibet Plateau is highly co-endemic with both alveolar echinococcosis (AE) and cystic echinococcosis (CE). In the past years, the Chinese government has been increasing the financial support to control the diseases in this region. Therefore, it is very important to identify the significant risk factors of the diseases by reviewing studies done in the region in the past decade to help policymakers design appropriate control strategies. Review: Selection criteria for which literature to review were firstly defined. Medline, CNKI (China National Knowledge Infrastructure), and Google Scholar were systematically searched for literature published between January 2000 and July 2011. Significant risk factors found by single factor and/or multiple factors analysis were listed, counted, and summarized. Literature was examined to check the comparability of the data; age and sex specific prevalence with same data structures were merged and used for further analysis. A variety of assumed social, economical, behavioral, and ecological risk factors were studied on the Plateau. Those most at risk were Tibetan herdsmen, the old and female in particular. By analyzing merged comparable data, it was found that females had a significant higher prevalence, and a positive linearity relationship existed between echinococcosis prevalence and increasing age. In terms of behavioral risk factors, playing with dogs was mostly correlated with CE and/or AE prevalence. In terms of hygiene, employing ground water as the drinking water source was significantly correlated with CE and AE prevalence. For definitive hosts, dog related factors were most frequently identified with prevalence of CE or/and AE; fox was a potential risk factor for AE prevalence only. Overgrazing and deforestation were significant for AE prevalence only. Conclusion: Tibetan herdsmen communities were at the highest risk of echinococcosis prevalence and should be the focus of echinococcosis control. Deworming both owned and stray dogs should be a major measure for controlling echinococcosis; treatment of wild definitive hosts should also be considered for AE endemic areas. Health education activities should be in concert with the local people's education backgrounds and languages in order to be able to improve behaviors. Further researches are needed to clarify the importance of wild hosts for AE/CE prevalence, the extent and range of the impacts of ecologic changes (overgrazing and deforestation) on the AE prevalence, and risk factors in Tibet

COVID-19: Third dose booster vaccine effectiveness against breakthrough coronavirus infection, hospitalisations and death in patients with cancer: A population-based study

Purpose: People living with cancer and haematological malignancies are at increased risk of hospitalisation and death following infection with acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus third dose vaccine boosters are proposed to boost waning immune responses in immunocompromised individuals and increase coronavirus protection; however, their effectiveness has not yet been systematically evaluated. Methods: This study is a population-scale real-world evaluation of the United Kingdom’s third dose vaccine booster programme for cancer patients from 8th December 2020 to 7th December 2021. The cancer cohort comprises individuals from Public Health England’s national cancer dataset, excluding individuals less than 18 years. A test-negative case-control design was used to assess third dose booster vaccine effectiveness. Multivariable logistic regression models were fitted to compare risk in the cancer cohort relative to the general population. Results: The cancer cohort comprised of 2,258,553 tests from 361,098 individuals. Third dose boosters were evaluated by reference to 87,039,743 polymerase chain reaction (PCR) coronavirus tests. Vaccine effectiveness against breakthrough infections, symptomatic infections, coronavirus hospitalisation and death in cancer patients were 59.1%, 62.8%, 80.5% and 94.5% respectively. Lower vaccine effectiveness was associated with a cancer diagnosis within 12 months, lymphoma, recent systemic anti-cancer therapy (SACT) or radiotherapy. Lymphoma patients had low levels of protection from symptomatic disease. In spite of third dose boosters, following multivariable adjustment, individuals with cancer remain at increased risk of coronavirus hospitalisation and death compared to the population control (OR 3.38, 3.01 respectively. p<0.001 for both). Conclusions: Third dose boosters are effective for most individuals with cancer, increasing protection from coronavirus. However, their effectiveness is heterogenous, and lower than the general population. Many patients with cancer will remain at increased risk of coronavirus infections, even after 3 doses. In the case of patients with lymphoma, there is a particularly strong disparity of vaccine effectiveness against breakthrough infection and severe disease. Breakthrough infections will disrupt cancer care and treatment with potentially adverse consequences on survival outcomes. The data support the role of vaccine boosters in preventing severe disease, and further pharmacological intervention to prevent transmission and aid viral clearance to limit disruption of cancer care as the delivery of care continues to evolve during the coronavirus pandemic