Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

Supported by the Office of International Affairs, National Cancer Institute (NCI), the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc) and the United States Food and Drug Administration (FDA) to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a) to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b) to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations

Simultaneous Detection, Genotyping, and Quantification of Human Papillomaviruses by Multicolor Real-Time PCR and Melting Curve Analysis

Key Project of Science and Technology Program of Fujian [2009D024]Long-term infection with high-risk human papillomavirus (HPV) is the leading cause of cervical cancer, while infection with low-risk HPV is the major reason for condylomata acuminata. An accurate, rapid, and convenient assay that is able to simultaneously detect, genotype, and quantify HPV would be of great clinical value yet remains to be achieved. We developed a three-color real-time PCR assay that is able to analyze 30 predominant HPV types in three reactions. The amplification curves indicated the presence of HPV, melting curve analysis identified the HPV genotype, and the quantification cycle value determined the quantity. We applied this assay to 647 cervical swab samples, and the results were compared with those obtained with a commercial genotyping system. The proposed assay had a limit of detection of 5 to 50 copies per reaction and a dynamic range of 5 x 10(1) to 5 x 10(6) copies per reaction. A comparison study showed that the overall sample concordance with the comparison method was 91.6% and the type agreement was greater than 98.7%. The quantification study demonstrated that the loads of HPV type 16 in 30 samples with cervical intraepithelial neoplasia grade III (CIN III) lesions were significantly higher than those in samples with CIN I lesions or CIN II lesions, and the results were concordant with those of the comparison method. The increased information content, high throughput, and low cost would facilitate the use of this real-time PCR-based assay in a variety of clinical settings

Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm

High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI

Systemic translocation of Staphylococcus drives autoantibody production in HIV disease

Abstract Background Increased autoreactive antibodies have been reported in HIV disease; however, the mechanism accounting for autoantibody induction in HIV remains unknown. Results Herein, we show that seasonal influenza vaccination induces autoantibody production (e.g., IgG anti-nuclear antibody (ANA) and anti-double-stranded DNA antibody (anti-dsDNA)) in some viral-suppressed antiretroviral therapy (ART)-treated HIV+ subjects, but not in healthy controls. These autoantibodies were not derived from antigen-specific B cells but from activated “bystander” B cells analyzed by single-cell assay and by study of purified polyclonal ANAs from plasma. To explore the mechanism of autoantibody generation in HIV+ subjects, plasma level of microbial products, gene expression profile of B cells, and B cell receptor (BCR) repertoires were analyzed. We found that autoantibody production was associated with increased plasma level of microbial translocation; the patients with high autoantibodies had skewed B cell repertoires and upregulation of genes related to innate immune activation in response to microbial translocation. By analyzing circulating microbial 16S rDNA in plasma, the relative abundance of Staphylococcus was found to be associated with autoantibody production in HIV+ subjects. Finally, we found that injection of heat-killed Staphylococcus aureus promoted germinal center B cell responses and autoantibody production in mice, consistent with the notion that autoantibody production in HIV+ patients is triggered by microbial products. Conclusions Our results showed that translocation of Staphylococcus can promote B cell activation through enhancing germinal center response and induces autoantibody production. It uncovers a potential mechanism linking microbial translocation and autoimmunity in HIV+ disease and provides a strong rationale for targeting Staphylococcus to prevent autoantibody production