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Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient's tumour possesses a unique set of mutations ('the mutanome') that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient's individual tumour-specific mutations. Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4+ T cells. Vaccination with such CD4+ immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4+ T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient's tumour with vaccines produced 'just in time'. [ABSTRACT FROM AUTHOR]

The transcription of tumor mutations from DNA into RNA has implications for biology, epigenetics and clinical practice. It is not clear if mutations are in general transcribed and, if so, at what proportion to the wild-type allele. Here, we examined the correlation between DNA mutation allele frequency and RNA mutation allele frequency. We sequenced the exome and transcriptome of tumor cell lines with large copy number variations, identified heterozygous single nucleotide mutations and absolute DNA copy number, and determined the corresponding DNA and RNA mutation allele fraction. We found that 99% of the DNA mutations in expressed genes are expressed as RNA. Moreover, we found a high correlation between the DNA and RNA mutation allele frequency. Exceptions are mutations that cause premature termination codons and therefore activate nonsense-mediated decay. Beyond this, we did not find evidence of any wide-scale mechanism, such as allele-specific epigenetic silencing, preferentially promoting mutated or wild-type alleles. In conclusion, our data strongly suggest that genes are equally transcribed from all alleles, mutated and wild-type, and thus transcribed in proportion to their DNA allele frequency. [ABSTRACT FROM AUTHOR]

Alternative pre–messenger RNA splicing influences development, physiology and disease, but its regulation in humans is not well understood, partially because of the limited scale at which the expression of specific splicing events has been measured. We generated the first genome-scale expression compendium of human alternative splicing events using custom whole-transcript microarrays monitoring expression of 24,426 alternative splicing events in 48 diverse human samples. Over 11,700 genes and 9,500 splicing events were differentially expressed, providing a rich resource for studying splicing regulation. An unbiased, systematic screen of 21,760 4-mer to 7-mer words for cis-regulatory motifs identified 143 RNA 'words' enriched near regulated cassette exons, including six clusters of motifs represented by UCUCU, UGCAUG, UGCU, UGUGU, UUUU and AGGG, which map to trans-acting regulators PTB, Fox, Muscleblind, CELF/CUG-BP, TIA-1 and hnRNP F/H, respectively. Each cluster showed a distinct pattern of genomic location and tissue specificity. For example, UCUCU occurs 110 to 35 nucleotides preceding cassette exons upregulated in brain and striated muscle but depleted in other tissues. UCUCU and UGCAUG seem to have similar function but independent action, occurring 5′ and 3′, respectively, of 33% of the cassette exons upregulated in skeletal muscle but co-occurring for only 2%. [ABSTRACT FROM AUTHOR]

A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations. Ordering gene expression traits relative to one another and relative to other complex traits is achieved by systematically testing whether variations in DNA that lead to variations in relative transcript abundances statistically support an independent, causative or reactive function relative to the complex traits under consideration. We show that this approach can predict transcriptional responses to single gene–perturbation experiments using gene-expression data in the context of a segregating mouse population. We also demonstrate the utility of this approach by identifying and experimentally validating the involvement of three new genes in susceptibility to obesity. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression in plants and animals. To investigate the influence of miRNAs on transcript levels, we transfected miRNAs into human cells and used microarrays to examine changes in the messenger RNA profile. Here we show that delivering miR-124 causes the expression profile to shift towards that of brain, the organ in which miR-124 is preferentially expressed, whereas delivering miR-1 shifts the profile towards that of muscle, where miR-1 is preferentially expressed. In each case, about 100 messages were downregulated after 12?h. The 3'untranslated regions of these messages had a significant propensity to pair to the 5'region of the miRNA, as expected if many of these messages are the direct targets of the miRNAs. Our results suggest that metazoan miRNAs can reduce the levels of many of their target transcripts, not just the amount of protein deriving from these transcripts. Moreover, miR-1 and miR-124, and presumably other tissue-specific miRNAs, seem to downregulate a far greater number of targets than previously appreciated, thereby helping to define tissue-specific gene expression in humans. [ABSTRACT FROM AUTHOR]

We analyzed the spatial heterogeneity in vegetation indices among 13 North American landscapes by using full Landsat Thematic Mapper images. Landscapes varied broadly in the statistical distribution of vegetation indices, but were successfully ordinated by using a measure of central tendency (the mean) and a measure of dispersion (the standard deviation or the coefficient of variation). Differences in heterogeneity among landscapes were explained by their topographic relief and their land cover. Landscape heterogeneity (standard deviation of the Normalized Difference Vegetation Index, NDVI) tended to increase linearly with topographic relief (standard deviation of elevation), but landscapes with low relief were much more heterogeneous than expected from this relationship. The latter were characterized by a large proportion of agricultural land. Percent agriculture, in turn, was inversely related to topographic relief. The strength of these relationships was evaluated against changes in image spatial resolution (grain size). Aggregation of NDVI images to coarser grain size resulted in steady decline of their standard deviation. Although the relationship between landscape heterogeneity and explanatory variables was generally preserved, rates of decrease in heterogeneity with grain size differed among landscapes. A spatial autocorrelation analysis showed that rates of decrease were related to the scale at which pattern is manifested. On one end of the spectrum are agricultural, low-relief landscapes with low spatial autocorrelation and small-scale heterogeneity associated with fields; their heterogeneity decreased sharply as grain size increased. At the other end, desert landscapes were characterized by low small-scale heterogeneity, high spatial autocorrelation, and almost no change in heterogeneity as grain sized was increased—their heterogeneity, associated with land forms, was present at a large scale. [ABSTRACT FROM AUTHOR]

We developed a procedure for the preparation of whole transcriptome cDNA libraries depleted of ribosomal RNA from only 1 μg of total RNA. The method relies on a collection of short, computationally selected oligonucleotides, called 'not-so-random' (NSR) primers, to obtain full-length, strand-specific representation of nonribosomal RNA transcripts. In this study we validated the technique by profiling human whole brain and universal human reference RNA using ultra-high-throughput sequencing. [ABSTRACT FROM AUTHOR]

A correction to the article "Mutant MHC class II epitopes drive therapeutic immune responses to cancer" which was published in issue #520 is presented.