Fred Hutchinson Cancer Research Center

About: Fred Hutchinson Cancer Research Center is a nonprofit organization based out in Cape Town, South Africa. It is known for research contribution in the topics: Population & Transplantation. The organization has 12322 authors who have published 30954 publications receiving 2288772 citations. The organization is also known as: Fred Hutch & The Hutch.

Prevalence of Prostate Cancer among Men with a Prostate-Specific Antigen Level ≤4.0 ng per Milliliter

Abstract: Background The optimal upper limit of the normal range for prostate-specific antigen (PSA) is unknown. We investigated the prevalence of prostate cancer among men in the Prostate Cancer Prevention Trial who had a PSA level of 4.0 ng per milliliter or less. Methods Of 18,882 men enrolled in the prevention trial, 9459 were randomly assigned to receive placebo and had an annual measurement of PSA and a digital rectal examination. Among these 9459 men, 2950 men never had a PSA level of more than 4.0 ng per milliliter or an abnormal digital rectal examination, had a final PSA determination, and underwent a prostate biopsy after being in the study for seven years. Results Among the 2950 men (age range, 62 to 91 years), prostate cancer was diagnosed in 449 (15.2 percent); 67 of these 449 cancers (14.9 percent) had a Gleason score of 7 or higher. The prevalence of prostate cancer was 6.6 percent among men with a PSA level of up to 0.5 ng per milliliter, 10.1 percent among those with values of 0.6 to 1.0 ng per mi...

Nomenclature for factors of the HLA system, 2010.

Abstract: The WHO Nomenclature Committee for Factors of the HLA System met following the 14th International HLA and Immunogenetics Workshop in Melbourne, Australia in December 2005 and Buzios, Brazil during the 15th International HLA and Immunogenetics Workshop in September 2008. This report documents the additions and revisions to the nomenclature of HLA specificities following the principles established in previous reports (1–18).

Predicting Deleterious Amino Acid Substitutions

Abstract: Many missense substitutions are identified in single nucleotide polymorphism (SNP) data and large-scale random mutagenesis projects. Each amino acid substitution potentially affects protein function. We have constructed a tool that uses sequence homology to predict whether a substitution affects protein function. SIFT, which sorts intolerant from tolerant substitutions, classifies substitutions as tolerated or deleterious. A higher proportion of substitutions predicted to be deleterious by SIFT gives an affected phenotype than substitutions predicted to be deleterious by substitution scoring matrices in three test cases. Using SIFT before mutagenesis studies could reduce the number of functional assays required and yield a higher proportion of affected phenotypes. may be used to identify plausible disease candidates among the SNPs that cause missense substitutions.

Prediction of central nervous system embryonal tumour outcome based on gene expression

Abstract: Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis.