Investigating Childhood Leukemia in Churchill County, Nevada

BACKGROUND: Sixteen children diagnosed with acute leukemia between 1997 and 2002 lived in Churchill County, Nevada, at the time of or before their illness. Considering the county population and statewide cancer rate, fewer than two cases would be expected. OBJECTIVES: In March 2001, the Centers for Disease Control and Prevention led federal, state, and local agencies in a cross-sectional, case-comparison study to determine if ongoing environmental exposures posed a health risk to residents and to compare levels of contaminants in environmental and biologic samples collected from participating families. METHODS: Surveys with more than 500 variables were administered to 205 people in 69 families. Blood, urine, and cheek cell samples were collected and analyzed for 139 chemicals, eight viral markers, and several genetic polymorphisms. Air, water, soil, and dust samples were collected from almost 80 homes to measure more than 200 chemicals. RESULTS: The scope of this cancer cluster investigation exceeded any previous study of pediatric leukemia. Nonetheless, no exposure consistent with leukemia risk was identified. Overall, tungsten and arsenic levels in urine and water samples were significantly higher than national comparison values; however, levels were similar among case and comparison groups. CONCLUSIONS: Although the cases in this cancer cluster may in fact have a common etiology, their small number and the length of time between diagnosis and our exposure assessment lessen the ability to find an association between leukemia and environmental exposures. Given the limitations of individual cancer cluster investigations, it may prove more efficient to pool laboratory and questionnaire data from similar leukemia clusters

HSPVdb—the Human Short Peptide Variation Database for improved mass spectrometry-based detection of polymorphic HLA-ligands

T cell epitopes derived from polymorphic proteins or from proteins encoded by alternative reading frames (ARFs) play an important role in (tumor) immunology. Identification of these peptides is successfully performed with mass spectrometry. In a mass spectrometry-based approach, the recorded tandem mass spectra are matched against hypothetical spectra generated from known protein sequence databases. Commonly used protein databases contain a minimal level of redundancy, and thus, are not suitable data sources for searching polymorphic T cell epitopes, either in normal or ARFs. At the same time, however, these databases contain much non-polymorphic sequence information, thereby complicating the matching of recorded and theoretical spectra, and increasing the potential for finding false positives. Therefore, we created a database with peptides from ARFs and peptide variation arising from single nucleotide polymorphisms (SNPs). It is based on the human mRNA sequences from the well-annotated reference sequence (RefSeq) database and associated variation information derived from the Single Nucleotide Polymorphism Database (dbSNP). In this process, we removed all non-polymorphic information. Investigation of the frequency of SNPs in the dbSNP revealed that many SNPs are non-polymorphic “SNPs”. Therefore, we removed those from our dedicated database, and this resulted in a comprehensive high quality database, which we coined the Human Short Peptide Variation Database (HSPVdb). The value of our HSPVdb is shown by identification of the majority of published polymorphic SNP- and/or ARF-derived epitopes from a mass spectrometry-based proteomics workflow, and by a large variety of polymorphic peptides identified as potential T cell epitopes in the HLA-ligandome presented by the Epstein–Barr virus cells

Transcriptome sequencing of three Pseudo-nitzschia species reveals comparable gene sets and the presence of Nitric Oxide Synthase genes in diatoms

Diatoms are among the most diverse eukaryotic microorganisms on Earth, they are responsible for a large fraction of primary production in the oceans and can be found in different habitats. Pseudo-nitzschia are marine planktonic diatoms responsible for blooms in coastal and oceanic waters. We analyzed the transcriptome of three species, Pseudo-nitzschia arenysensis, Pseudo-nitzschia delicatissima and Pseudo-nitzschia multistriata, with different levels of genetic relatedness. These species have a worldwide distribution and the last one produces the neurotoxin domoic acid. We were able to annotate about 80% of the sequences in each transcriptome and the analysis of the relative functional annotations allowed comparison of the main metabolic pathways, pathways involved in the biosynthesis of isoprenoids (MAV and MEP pathways), and pathways putatively involved in domoic acid synthesis. The search for homologous transcripts among the target species and other congeneric species resulted in the discovery of a sequence annotated as Nitric Oxide Synthase (NOS), found uniquely in Pseudo-nitzschia multistriata. The predicted protein product contained all the domains of the canonical metazoan sequence. Putative NOS sequences were found in other available diatom datasets, supporting a role for nitric oxide as signaling molecule in this group of microalgae

Targeting survivin and p53 in pediatric acute lymphoblastic leukemia

Despite advances in treatment and outcomes for patients with pediatric acute lymphoblastic leukemia (ALL), there continue to be subsets of patients who are refractory to standard chemotherapy and hematopoietic stem cell transplant. Therefore, novel gene targets for therapy are needed to further advance treatment for this disease. RNA interference technology has identified survivin as a potential therapeutic target. Survivin, a member of the inhibitor of apoptosis (IAP) proteins and chromosome passenger complex, is expressed in hematologic malignancies and overexpressed in relapsed pediatric ALL. Our studies show that survivin is uniformly expressed at high levels in multiple pediatric ALL cell lines. Furthermore, silencing of survivin expression in pediatric ALL cell lines as well as primary leukemic blasts reduces viability of these cells. This includes cell lines derived from patients with relapsed disease featuring cytogenetic anomalies such as t(12;21), Philadelphia chromosome t(9;22), t(1;19) as well as a cell line carrying t(17;19) from a patient with de novo ALL. Furthermore, inhibition of survivin increases p53-dependent apoptosis that can be rescued by inhibition of p53. Finally, a screen of randomly selected primary patient samples confirms that survivin-specific small interfering RNA and survivin-targeted drug, YM155, effectively reduce viability of leukemic blasts

ALL-1/MLL1, a homologue of Drosophila TRITHORAX, modifies chromatin and is directly involved in infant acute leukaemia

Rearrangements of the ALL-1/MLL1 gene underlie the majority of infant acute leukaemias, as well as of therapy-related leukaemias developing in cancer patients treated with inhibitors of topoisomerase II, such as VP16 and doxorubicin. The rearrangements fuse ALL-1 to any of \u3e50 partner genes or to itself. Here, we describe the unique features of ALL-1-associated leukaemias, and recent progress in understanding molecular mechanisms involved in the activity of the ALL-1 protein and of its Drosophila homologue TRITHORAX

Cell proliferation is related to in vitro drug resistance in childhood acute leukaemia

0.05) with sensitivity to antimetabolites (cytarabine, mercaptopurine, thioguanine), L-asparaginase, teniposide, and vincristine. Similar results were found within subgroups of initial ALL (nonhyperdiploid and common/precursor-B-lineage ALL). In relapsed ALL and AML such correlations were not found. In conclusion, cell proliferation differs between leukaemia subgroups and increased proliferation is associated with increased in vitro sensitivity to several anticancer agents in initial ALL

Translating microarray data for diagnostic testing in childhood leukaemia

BACKGROUND: Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). METHODS: We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. RESULTS: We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. CONCLUSION: Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team

Selective IgA Deficiency

Immunoglobulin A (IgA) deficiency is the most common primary immunodeficiency defined as decreased serum level of IgA in the presence of normal levels of other immunoglobulin isotypes. Most individuals with IgA deficiency are asymptomatic and identified coincidentally. However, some patients may present with recurrent infections of the respiratory and gastrointestinal tracts, allergic disorders, and autoimmune manifestations. Although IgA is the most abundant antibody isotype produced in the body, its functions are not clearly understood. Subclass IgA1 in monomeric form is mainly found in the blood circulation, whereas subclass IgA2 in dimeric form is the dominant immunoglobulin in mucosal secretions. Secretory IgA appears to have prime importance in immune exclusion of pathogenic microorganisms and maintenance of intestinal homeostasis. Despite this critical role, there may be some compensatory mechanisms that would prevent disease manifestations in some IgA-deficient individuals. In IgA deficiency, a maturation defect in B cells to produce IgA is commonly observed. Alterations in transmembrane activator and calcium modulator and cyclophilin ligand interactor gene appear to act as disease-modifying mutations in both IgA deficiency and common variable immunodeficiency, two diseases which probably lie in the same spectrum. Certain major histocompatibility complex haplotypes have been associated with susceptibility to IgA deficiency. The genetic basis of IgA deficiency remains to be clarified. Better understanding of the production and function of IgA is essential in elucidating the disease mechanism in IgA deficiency

Network-Guided Analysis of Genes with Altered Somatic Copy Number and Gene Expression Reveals Pathways Commonly Perturbed in Metastatic Melanoma

Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression (‘SCNA-genes’) in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer