Diagnosing mucopolysaccharidosis IVA

Mucopolysaccharidosis IVA (MPS IVA; Morquio A syndrome) is an autosomal recessive lysosomal storage disorder resulting from a deficiency of N-acetylgalactosamine-6-sulfate sulfatase (GALNS) activity. Diagnosis can be challenging and requires agreement of clinical, radiographic, and laboratory findings. A group of biochemical genetics laboratory directors and clinicians involved in the diagnosis of MPS IVA, convened by BioMarin Pharmaceutical Inc., met to develop recommendations for diagnosis. The following conclusions were reached. Due to the wide variation and subtleties of radiographic findings, imaging of multiple body regions is recommended. Urinary glycosaminoglycan analysis is particularly problematic for MPS IVA and it is strongly recommended to proceed to enzyme activity testing even if urine appears normal when there is clinical suspicion of MPS IVA. Enzyme activity testing of GALNS is essential in diagnosing MPS IVA. Additional analyses to confirm sample integrity and rule out MPS IVB, multiple sulfatase deficiency, and mucolipidoses types II/III are critical as part of enzyme activity testing. Leukocytes or cultured dermal fibroblasts are strongly recommended for enzyme activity testing to confirm screening results. Molecular testing may also be used to confirm the diagnosis in many patients. However, two known or probable causative mutations may not be identified in all cases of MPS IVA. A diagnostic testing algorithm is presented which attempts to streamline this complex testing process

Determination of sin2 θeff w using jet charge measurements in hadronic Z decays

The electroweak mixing angle is determined with high precision from measurements of the mean difference between forward and backward hemisphere charges in hadronic decays of the Z. A data sample of 2.5 million hadronic Z decays recorded over the period 1990 to 1994 in the ALEPH detector at LEP is used. The mean charge separation between event hemispheres containing the original quark and antiquark is measured for bb̄ and cc̄ events in subsamples selected by their long lifetimes or using fast D*'s. The corresponding average charge separation for light quarks is measured in an inclusive sample from the anticorrelation between charges of opposite hemispheres and agrees with predictions of hadronisation models with a precision of 2%. It is shown that differences between light quark charge separations and the measured average can be determined using hadronisation models, with systematic uncertainties constrained by measurements of inclusive production of kaons, protons and A's. The separations are used to measure the electroweak mixing angle precisely as sin2 θeff w = 0.2322 ± 0.0008(exp. stat.) ±0.0007(exp. syst.) ± 0.0008(sep.). The first two errors are due to purely experimental sources whereas the third stems from uncertainties in the quark charge separations

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Bottom-up, integrated -omics analysis identifies broadly dosage-sensitive genes in breast cancer samples from TCGA.

The massive genomic data from The Cancer Genome Atlas (TCGA), including proteomics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC), provides a unique opportunity to study cancer systematically. While most observations are made from a single type of genomics data, we apply big data analytics and systems biology approaches by simultaneously analyzing DNA amplification, mRNA and protein abundance. Using multiple genomic profiles, we have discovered widespread dosage compensation for the extensive aneuploidy observed in TCGA breast cancer samples. We do identify 11 genes that show strong correlation across all features (DNA/mRNA/protein) analogous to that of the well-known oncogene HER2 (ERBB2). These genes are generally less well-characterized regarding their role in cancer and we advocate their further study. We also discover that shRNA knockdown of these genes has an impact on cancer cell growth, suggesting a vulnerability that could be used for cancer therapy. Our study shows the advantages of systematic big data methodologies and also provides future research directions

Identification and prediction of promiscuous aggregating inhibitors among known drugs

Some small molecules, often hits from screening, form aggregates in solution that inhibit many enzymes. In contrast, drugs are thought to act specifically. To investigate this assumption, 50 unrelated drugs were tested for promiscuous inhibition via aggregation. Each drug was tested against three unrelated model enzymes: �-lactamase, chymotrypsin, and malate dehydrogenase, none of which are considered targets of these drugs. To be judged promiscuous, the drugs had to inhibit all three enzymes, do so in a time-dependent manner, be sensitive to detergent and to enzyme concentration, and form particles detectable by light scattering. Of the 50 drugs tested, 43 were nonpromiscuous by these criteria. Surprisingly, four of the drugs showed promiscuous, aggregation-based inhibition at concentrations below 100 µM: clotrimazole, benzyl benzoate, nicardipine, and delavirdine. Three other drugs also behaved as aggregation-based inhibitors, but only at high concentrations (about 400 µM). To investigate possible structureactivity relationships among promiscuous drugs, five analogues of the antifungal clotrimazole were studied. Three of these, miconazole, econazole, and sulconazole, were promiscuous but the other two, fluconazole and ketoconazole, were not. Using recursive partitioning, these experimental results were used to develop a model for predicting aggregate-based promiscuity

Treatment with a VEGFR-2 antibody results in intra-tumor immune modulation and enhances anti-tumor efficacy of PD-L1 blockade in syngeneic murine tumor models

Prolonged activation of vascular endothelial growth factor receptor-2 (VEGFR-2) due to mis-regulation of the VEGF pathway induces aberrant blood vessel expansion, which supports growth and survival of solid tumors. Therapeutic interventions that inhibit the VEGFR-2 pathway have therefore become a mainstay of cancer treatment. Non-clinical studies have recently revealed that blockade of angiogenesis can modulate the tumor microenvironment and enhance the efficacy of concurrent immune therapies. Ramucirumab is an FDA-approved anti-angiogenic antibody that inhibits VEGFR-2 and is currently being evaluated in clinical studies in combination with anti-programmed cell death (PD-1) axis checkpoint inhibitors (pembrolizumab, durvalumab, or sintilimab) across several cancer types. The purpose of this study is to establish a mechanistic basis for the enhanced activity observed in the combined blockade of VEGFR-2 and PD-1-axis pathways. Pre-clinical studies were conducted in murine tumor models known to be responsive to anti-PD-1 axis therapy, using monoclonal antibodies that block mouse VEGFR-2 and programmed death-ligand 1 (PD-L1). Combination therapy resulted in enhanced anti-tumor activity compared to anti-PD-L1 monotherapy. VEGFR-2 blockade at early timepoints post-anti-PD-L1 therapy resulted in a dose-dependent and transient enhanced infiltration of T cells, and establishment of immunological memory. VEGFR-2 blockade at later timepoints resulted in enhancement of anti-PD-L1-driven immune cell infiltration. VEGFR-2 and PD-L1 monotherapies induced both unique and overlapping patterns of immune gene expression, and combination therapy resulted in an enhanced immune activation signature. Collectively, these results provide new and actionable insights into the mechanisms by which concurrent VEGFR-2 and PD-L1 antibody therapy leads to enhanced anti-tumor efficacy

Identification of druggable cancer driver genes amplified across TCGA datasets.

The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 16 cancer subtypes and identified 486 genes that were amplified in two or more datasets. The list was narrowed to 75 cancer-associated genes with potential "druggable" properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 42 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 42 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapters GRB2 and GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer drug targets and we further discuss potential novel opportunities for drug discovery efforts