Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting

Cancer immunoediting, the process by which the immune system controls tumour outgrowth and shapes tumour immunogenicity, is comprised of three phases: elimination, equilibrium and escape. Although many immune components that participate in this process are known, its underlying mechanisms remain poorly defined. A central tenet of cancer immunoediting is that T-cell recognition of tumour antigens drives the immunological destruction or sculpting of a developing cancer. However, our current understanding of tumour antigens comes largely from analyses of cancers that develop in immunocompetent hosts and thus may have already been edited. Little is known about the antigens expressed in nascent tumour cells, whether they are sufficient to induce protective antitumour immune responses or whether their expression is modulated by the immune system. Here, using massively parallel sequencing, we characterize expressed mutations in highly immunogenic methylcholanthrene-induced sarcomas derived from immunodeficient Rag2(-/-) mice that phenotypically resemble nascent primary tumour cells. Using class I prediction algorithms, we identify mutant spectrin-β2 as a potential rejection antigen of the d42m1 sarcoma and validate this prediction by conventional antigen expression cloning and detection. We also demonstrate that cancer immunoediting of d42m1 occurs via a T-cell-dependent immunoselection process that promotes outgrowth of pre-existing tumour cell clones lacking highly antigenic mutant spectrin-β2 and other potential strong antigens. These results demonstrate that the strong immunogenicity of an unedited tumour can be ascribed to expression of highly antigenic mutant proteins and show that outgrowth of tumour cells that lack these strong antigens via a T-cell-dependent immunoselection process represents one mechanism of cancer immunoediting.     

Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci

We carried out a meta-analysis of data from three genome-wide association (GWA) studies of type 1 diabetes (T1D), testing 305,090 SNPs in 3,561 T1D cases and 4,646 controls of European ancestry. We obtained further support for 4q27 (IL2-IL21, P = 1.9 x 10(-8)) and, after genotyping an additional 6,225 cases, 6,946 controls and 2,828 families, convincing evidence for four previously unknown and distinct risk loci in chromosome regions 6q15 (BACH2, P = 4.7 x 10(-12)), 10p15 (PRKCQ, P = 3.7 x 10(-9)), 15q24 (CTSH, P = 3.2 x 10(-15)) and 22q13 (C1QTNF6, P = 2.0 x 10(-8)).     

Large-scale genetic fine mapping and genotype-phenotype associations implicate polymorphism in the IL2RA region in type 1 diabetes

Genome-wide association studies are now identifying disease-associated chromosome regions. However, even after convincing replication, the localization of the causal variant(s) requires comprehensive resequencing, extensive genotyping and statistical analyses in large sample sets leading to targeted functional studies. Here, we have localized the type 1 diabetes (T1D) association in the interleukin 2 receptor alpha (IL2RA) gene region to two independent groups of SNPs, spanning overlapping regions of 14 and 40 kb, encompassing IL2RA intron 1 and the 5' regions of IL2RA and RBM17 (odds ratio = 2.04, 95% confidence interval = 1.70-2.45; P = 1.92 x 10(-28); control frequency = 0.635). Furthermore, we have associated IL2RA T1D susceptibility genotypes with lower circulating levels of the biomarker, soluble IL-2RA (P = 6.28 x 10(-28)), suggesting that an inherited lower immune responsiveness predisposes to T1D.     

Short-run macroeconomic forecasting: The OECD performance

Forecasts for the seven major industrial countries, Canada, France, Germany, Italy, Japan, the United Kingdom and the United States, are published on a regular basis in the OECD's Economic Outlook. This paper analyses the accuracy of the OECD annual forecasts of output and price changes and of the current balance in the balance of payments. As a reference basis, the forecasts are compared with those generated by a naive model, a random walk process. The measures of forecasting accuracy used are the mean-absolute error, the root-mean-square error, the median-absolute error, and Theil's inequality coefficient. The OECD forecasts of real GNP changes are significantly superior to those generated by the random walk process; however, the OECD price and current balance forecasts are not significantly more accurate than those obtained from the naive model. The OECD's forecasting performance has neither improved nor deteriorated over time.     

Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease

Genes and mechanisms involved in common complex diseases, such as the autoimmune disorders that affect approximately 5% of the population, remain obscure. Here we identify polymorphisms of the cytotoxic T lymphocyte antigen 4 gene (CTLA4)--which encodes a vital negative regulatory molecule of the immune system--as candidates for primary determinants of risk of the common autoimmune disorders Graves' disease, autoimmune hypothyroidism and type 1 diabetes. In humans, disease susceptibility was mapped to a non-coding 6.1 kb 3' region of CTLA4, the common allelic variation of which was correlated with lower messenger RNA levels of the soluble alternative splice form of CTLA4. In the mouse model of type 1 diabetes, susceptibility was also associated with variation in CTLA-4 gene splicing with reduced production of a splice form encoding a molecule lacking the CD80/CD86 ligand-binding domain. Genetic mapping of variants conferring a small disease risk can identify pathways in complex disorders, as exemplified by our discovery of inherited, quantitative alterations of CTLA4 contributing to autoimmune tissue destruction.