The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

SUMMARY Antibody blockade of the inhibitory CTLA-4 pathway has led to clinical benefit in a subset of patients with metastatic melanoma. Anti-CTLA-4 enhances T cell responses, including production of IFN-γ, which is a critical cytokine for host immune responses. However, the role of IFN-γ signaling in tumor cells in the setting of anti-CTLA-4 therapy remains unknown. Here we demonstrate that patients identified as non-responders to anti-CTLA-4 (ipilimumab) have tumors with genomic defects in IFN-γ pathway genes. Furthermore, mice bearing melanoma tumors with knockdown of IFN-γ receptor 1 (IFNGR1) have impaired tumor rejection upon anti-CTLA-4 therapy. These data highlight that loss of the IFN-γ signaling pathway is associated with primary resistance to anti-CTLA-4 therapy. Our findings demonstrate the importance of tumor genomic data, especially IFN-γ related genes, as prognostic information for patients selected to receive treatment with immune checkpoint therapy.

T cells become dysfunctional when they encounter self antigens or are exposed to chronic infection or to the tumour microenvironment1. The function of T cells is tightly regulated by a combinational co-stimulatory signal, and dominance of negative co-stimulation results in T cell dysfunction2. However, the molecular mechanisms that underlie this dysfunction remain unclear. Here, using an in vitro T cell tolerance induction system in mice, we characterize genome-wide epigenetic and gene expression features in tolerant T cells, and show that they are distinct from effector and regulatory T cells. Notably, the transcription factor NR4A1 is stably expressed at high levels in tolerant T cells. Overexpression of NR4A1 inhibits effector T cell differentiation, whereas deletion of NR4A1 overcomes T cell tolerance and exaggerates effector function, as well as enhancing immunity against tumour and chronic virus. Mechanistically, NR4A1 is preferentially recruited to binding sites of the transcription factor AP-1, where it represses effector-gene expression by inhibiting AP-1 function. NR4A1 binding also promotes acetylation of histone 3 at lysine 27 (H3K27ac), leading to activation of tolerance-related genes. This study thus identifies NR4A1 as a key general regulator in the induction of T cell dysfunction, and a potential target for tumour immunotherapy.

Large-scale sequencing efforts are uncovering the complexity of cancer genomes, which are comprised of causal “driver” mutations that promote tumor progression along with many more pathologically-neutral “passenger” events. The majority of mutations, both in known cancer drivers and uncharacterized genes, are generally of low occurrence, highlighting the need to functionally annotate the long tail of infrequent mutations present in heterogeneous cancers. Here we describe a mutation assessment pipeline enabled by high-throughput engineering of molecularly-barcoded gene variant expression clones identified by tumor sequencing. We first used this platform to functionally assess tail mutations observed in PIK3CA, which encodes the catalytic subunit alpha of the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) frequently mutated in cancer. Orthogonal screening for PIK3CA variant activity using in vitro and in vivo cell growth and transformation assays differentiated driver from passenger mutations, revealing that PIK3CA variant activity correlates imperfectly with its mutation frequency across breast cancer populations. While PIK3CA mutations with frequencies above 5% were significantly more oncogenic than wild-type in all assays, mutations occurring at 0.07 – 5.0% included those with and without oncogenic activities that ranged from weak to strong in at least one assay. Proteomic profiling coupled with therapeutic sensitivity assays on PIK3CA variant-expressing cell models revealed variant-specific activation of PI3K signaling as well as other pathways that include the MEK1/2 module of Mitogen-Activated Protein (MAP) Kinase pathway. Our data indicate that cancer treatments will need to increasingly consider the functional relevance of specific mutations in driver genes rather than considering all mutations in drivers as equivalent.

Lung cancer remains the leading cause of cancer death. Genome sequencing of lung tumors from patients with squamous cell carcinoma has identified SMAD4 to be frequently mutated. Here, we use a mouse model to determine the molecular mechanisms by which Smad4 loss leads to lung cancer progression. Mice with ablation of Pten and Smad4 in airway epithelium develop metastatic adenosquamous tumors. Comparative transcriptomic and in vivo cistromic analyses determine that loss of PTEN and SMAD4 results in ELF3 and ErbB2 pathway activation due to decreased expression of ERRFI1, a negative regulator of ERBB2 in mouse and human cells. The combinatorial inhibition of ErbB2 and Akt signaling attenuate tumor progression and cell invasion, respectively. Expression profile analysis of human lung tumors substantiated the importance of the ErbB2/Akt/ELF3 signaling pathway as both a prognostic biomarker and a therapeutic drug target for treating lung cancer.

Background Further advances of targeted cancer therapy require comprehensive in-depth profiling of somatic mutations that are present in subpopulations of tumor cells in a clinical tumor sample. However, it is unclear to what extent such intra-tumor heterogeneity is present and whether it may affect clinical decision making. To unravel this challenge, we established a deep targeted sequencing platform to identify potentially actionable DNA alterations in tumor samples. Methods We assayed 515 FFPE tumor samples and matched germline (475 patients) from 11 disease sites by capturing and sequencing all the exons in 201 cancer related genes. Mutations, indels and copy number data were reported. Results We obtained a 1000-fold average sequencing depth and identified 4794 non-synonymous mutations in the samples analyzed, which 15.2% were present at less than 10% allele frequency. Most of these low level mutations occurred at known oncogenic hotspots and are likely functional. Identifying low level mutations improved identification of mutations in actionable genes in 118 (24.84%) patients, among which 47 (9.8%) would otherwise be unactionable. In addition, acquiring ultra-high depth also ensured a low false discovery rate (less than 2.2%) from FFPE samples. Conclusion Our results were as accurate as a commercially available CLIA-compliant hotspot panel, but allowed the detection of a higher number of mutations in actionable genes. Our study revealed the critical importance of acquiring and utilizing high depth in profiling clinical tumor samples and presented a very useful platform for implementing routine sequencing in a cancer care institution.

We present novoBreak, a novel genome-wide local assembly algorithm that discovers somatic and germline structural variation breakpoints in whole genome sequencing data. In the ICGC-TCGA DREAM 8.5 Somatic Mutation Calling Challenge and real cancer genome data analysis, novoBreak consistently outperformed existing algorithms due largely to more effective utilization of reads spanning breakpoints. NovoBreak also demonstrated great sensitivity in identifying short INDELs. The source code is available at http://sourceforge.net/projects/novobreak/.

Here we report that mice deficient for the proteasome activator, REGg, exhibit a marked resistance to TPA (12-O-tetradecanoyl-phorbol-13-acetate)-induced keratinocyte proliferation, epidermal hyperplasia and onset of papillomas compared with wild-type counterparts. Interestingly, a massive increase of REGg in skin tissues or cells resulting from TPA induces activation of p38 mitogen-activated protein kinase (MAPK/p38). Blocking p38 MAPK activation prevents REGg elevation in HaCaT cells with TPA treatment. AP-1, the downstream effector of MAPK/p38, directly binds to the REGg promoter and activates its transcription in response to TPA stimulation. Furthermore, we find that REGg activates Wnt/b-catenin signalling by degrading GSK-3b in vitro and in cells, increasing levels of CyclinD1 and c-Myc, the downstream targets of b-catenin. Conversely, MAPK/p38 inactivation or REGg deletion prevents the increase of cyclinD1 and c-Myc by TPA. This study demonstrates that REGg acts in skin tumorigenesis mediating MAPK/p38 activation of the Wnt/b-catenin pathway.