Thermal excitations of frustated XY spins in two dimensions

We present a new variational approach to the study of phase transitions in frustrated 2D XY models. In the spirit of Villain's approach for the ferromagnetic case we divide thermal excitations into a low temperature long wavelength part (LW) and a high temperature short wavelength part (SW). In the present work we mainly deal with LW excitations and we explicitly consider the cases of the fully frustrated triangular (FFTXY) and square ( FFSQXY) XY models. The novel aspect of our method is that it preserves the coupling between phase (spin angles) and chiral degrees of freedom. LW fluctuations consist of coupled phase and chiral excitations. As a result, we find that for frustrated systems the effective interactions between phase variables is long range and oscillatory in contrast to the unfrustrated problem. Using Monte Carlo (MC) simulations we show that our analytical calculations produce accurate results at all temperature $T$; this is seen at low $T$ in the spin wave stiffness constant and in the staggered chirality; this is also the case near $T_c$: transitions are driven by the SW part associated with domain walls and vortices, but the coupling between phase and chiral variables is still relevant in the critical region. In that regime our analytical results yield the correct $T$ dependence for bare couplings (given by the LW fluctuations) such as the Coulomb gas temperature $T_{CG}$ of the frustrated XY models . In particular we find that $T_{CG}$ tracks chiral rather than phase fluctuations. Our results provides support for a single phase transition scenario in the FFTXY and FFSQXY models.Comment: 32 pages, RevTex, 11 eps figures available upon request, article to appear in Phys. Rev.

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Glutaminolysis and fumarate accumulation integrate immunometabolic and epigenetic programs in trained immunity

Induction of trained immunity (innate immune memory) is mediated by activation of immune and metabolic pathways that result in epigenetic rewiring of cellular functional programs. Through network-level integration of transcriptomics and metabolomics data, we identify glycolysis, glutaminolysis, and the cholesterol synthesis pathway as indispensable for the induction of trained immunity by ß-glucan in monocytes. Accumulation of fumarate, due to glutamine replenishment of the TCA cycle, integrates immune and metabolic circuits to induce monocyte epigenetic reprogramming by inhibiting KDM5 histone demethylases. Furthermore, fumarate itself induced an epigenetic program similar to ß-glucan-induced trained immunity. In line with this, inhibition of glutaminolysis and cholesterol synthesis in mice reduced the induction of trained immunity by ß-glucan. Identification of the metabolic pathways leading to induction of trained immunity contributes to our understanding of innate immune memory and opens new therapeutic avenues.Netherlands Organization for Scientific Research (NWO). B.N. is supported by an NHMRC (Australia) CJ Martin Early Career Fellowship. N.P.R. Netherlands Heart Foundation (2012T051). N.P.R. and M.G.N. received a H2020 grant (H2020-PHC-2015-667873-2) from the European Union (grant agreement 667837). Fundação para a Ciência e Tecnologia, FCT (IF/00735/2014 to A.C., IF/00021/2014 to R.S., RECI/BBB-BQB/0230/2012 to L.G.G., and SFRH/BPD/96176/2013 to C. Cunha). The NMR spectrometers are part of the National NMR Facility supported by FCT (RECI/BBB-BQB/0230/2012). The research leading to these results received funding from the Fundação para a Ciência e Tecnologia (FCT), cofunded by Programa Operacional Regional do Norte (ON.2—O Novo Norte); from the Quadro de Referência Estratégico Nacional (QREN) through the Fundo Europeu de Desenvolvimento Regional (FEDER) and from the Projeto Estratégico – LA 26 – 2013–2014 (PEst-C/SAU/LA0026/2013). NIH (DK43351 and DK097485) and Helmsley Trust. D.L.W. is supported, in part, by the NIH (GM53522, GM083016, GM119197, and C06RR0306551

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Genomic and Functional Approaches to Understanding Cancer Aneuploidy

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Analyzing >10,000 human cancers, Taylor et al. show that aneuploidy is correlated with somatic mutation rate, expression of proliferation genes, and decreased leukocyte infiltration. Loss of chromosome arm 3p is common in squamous cancers, but deletion of chromosome 3p reduces cell proliferation in vitro

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these \u201chidden responders\u201d may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders. Way et al. develop a machine-learning approach using PanCanAtlas data to detect Ras activation in cancer. Integrating mutation, copy number, and expression data, the authors show that their method detects Ras-activating variants in tumors and sensitivity to MEK inhibitors in cell lines