OncoNEM: inferring tumor evolution from single-cell sequencing data.

Single-cell sequencing promises a high-resolution view of genetic heterogeneity and clonal evolution in cancer. However, methods to infer tumor evolution from single-cell sequencing data lag behind methods developed for bulk-sequencing data. Here, we present OncoNEM, a probabilistic method for inferring intra-tumor evolutionary lineage trees from somatic single nucleotide variants of single cells. OncoNEM identifies homogeneous cellular subpopulations and infers their genotypes as well as a tree describing their evolutionary relationships. In simulation studies, we assess OncoNEM's robustness and benchmark its performance against competing methods. Finally, we show its applicability in case studies of muscle-invasive bladder cancer and essential thrombocythemia.The authors would like to acknowledge the support of the University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited. This work was funded by CRUK core grant C14303/A17197.This is the final version of the article. It first appeared from BioMed Central via https://doi.org/10.1186/s13059-016-0929-

The Genomic and Immune Landscapes of Lethal Metastatic Breast Cancer

TCR repertoire; Breast cancer; Clade mutationsRepertori TCR; Càncer de mama; Mutacions cladeRepertorio TCR; Cáncer de mama; Mutaciones cladoThe detailed molecular characterization of lethal cancers is a prerequisite to understanding resistance to therapy and escape from cancer immunoediting. We performed extensive multi-platform profiling of multi-regional metastases in autopsies from 10 patients with therapy-resistant breast cancer. The integrated genomic and immune landscapes show that metastases propagate and evolve as communities of clones, reveal their predicted neo-antigen landscapes, and show that they can accumulate HLA loss of heterozygosity (LOH). The data further identify variable tumor microenvironments and reveal, through analyses of T cell receptor repertoires, that adaptive immune responses appear to co-evolve with the metastatic genomes. These findings reveal in fine detail the landscapes of lethal metastatic breast cancer

Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west african populations.

Background Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC. Methods Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis. Results Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages. Conclusions The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance

Interaction of STAT6 with its co-activator SRC-1/NCoA-1 is regulated by dephosphorylation of the latter via PP2A

Regulation of gene expression represents a central issue in signal-regulated cellular responses. STAT6 is a critical mediator of IL-4 stimulated gene activation. To mediate this function, STAT6 recruits co-activator complexes. We have previously shown that STAT6 binds the PAS-B domain of the co-activator NCoA-1 via an LXXLL motif in its transactivation domain. Our recent finding that the PAS-B domain of NCoA-1 is also essential for co-activator complex formation points to an additional level of regulation of the co-activator assembly. In this study, we discovered that dephosphorylation of NCoA-1 is essential for the interaction with STAT6 and for IL-4-dependent transcriptional activation. PP2A dephosphorylates NCoA-1 and facilitates the activation of STAT6 target genes. Interestingly, simultaneous inhibition of phosphatase and cyclin-dependent kinases rescues the NCoA-1/STAT6 interaction. Moreover, arrest of cells at G1/S results in enhanced NCoA-1 phosphorylation. In summary, our results indicate that the interaction of NCoA-1 and STAT6 is dynamically regulated by the phosphatase PP2A and by cyclin-dependent kinases. This provides a mechanism for integrating transcriptional regulation by STAT6 with cell cycle progression

Mice Deficient in T-bet Form Inducible NO Synthase-Positive Granulomas That Fail to Constrain Salmonella.

Clearance of intracellular infections caused by Salmonella Typhimurium (STm) requires IFN-γ and the Th1-associated transcription factor T-bet. Nevertheless, whereas IFN-γ-/- mice succumb rapidly to STm infections, T-bet-/- mice do not. In this study, we assess the anatomy of immune responses and the relationship with bacterial localization in the spleens and livers of STm-infected IFN-γ-/- and T-bet-/- mice. In IFN-γ-/- mice, there is deficient granuloma formation and inducible NO synthase (iNOS) induction, increased dissemination of bacteria throughout the organs, and rapid death. The provision of a source of IFN-γ reverses this, coincident with subsequent granuloma formation and substantially extends survival when compared with mice deficient in all sources of IFN-γ. T-bet-/- mice induce significant levels of IFN-γ- after challenge. Moreover, T-bet-/- mice have augmented IL-17 and neutrophil numbers, and neutralizing IL-17 reduces the neutrophilia but does not affect numbers of bacteria detected. Surprisingly, T-bet-/- mice exhibit surprisingly wild-type-like immune cell organization postinfection, including extensive iNOS+ granuloma formation. In wild-type mice, most bacteria are within iNOS+ granulomas, but in T-bet-/- mice, most bacteria are outside these sites. Therefore, Th1 cells act to restrict bacteria within IFN-γ-dependent iNOS+ granulomas and prevent dissemination

FrenchFISH: Poisson Models for Quantifying DNA Copy Number From Fluorescence In Situ Hybridization of Tissue Sections

Purpose: Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. The gold standard for detecting copy number changes in tumor cells is fluorescence in situ hybridization (FISH) using locus-specific probes that are imaged as fluorescent spots. However, spot counting often does not perform well on solid tumor tissue sections due to partially represented or overlapping nuclei. Materials and Methods: To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes or a homogeneous Poisson point process model for automated spot counting. Results: We benchmarked the performance of FrenchFISH against previous approaches using a controlled simulation scenario and tested it experimentally in 12 ovarian carcinoma FFPE-tissue sections for copy number alterations at three loci (c-Myc, hTERC, and SE7). FrenchFISH outperformed standard spot counting with 74% of the automated counts having < 1 copy number difference from the manual counts and 17% having < 2 copy number differences, while taking less than one third of the time of manual counting. Conclusion: FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue by both speeding up and improving the accuracy of spot count estimates

Regulators of genetic risk of breast cancer identified by integrative network analysis.

Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.This work was funded by Cancer Research UK and the Breast Cancer Research Foundation. MAAC is funded by the National Research Council (CNPq) of Brazil. TEH held a fellowship from the US DOD Breast Cancer Research Program (W81XWH-11-1-0592) and is currently supported by an RAH Career Development Fellowship (Australia). TEH and WDT are funded by the NHMRC of Australia (NHMRC) (ID: 1008349 WDT; 1084416 WDT, TEH) and Cancer Australia/National Breast Cancer Foundation (ID 627229; WDT, TEH). BAJP is a Gibb Fellow of Cancer Research UK. We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.345

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Discovery of common and rare genetic risk variants for colorectal cancer.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.Goncalo R Abecasis has received compensation from 23andMe and Helix. He is currently an employee of Regeneron Pharmaceuticals. Heather Hampel performs collaborative research with Ambry Genetics, InVitae Genetics, and Myriad Genetic Laboratories, Inc., is on the scientific advisory board for InVitae Genetics and Genome Medical, and has stock in Genome Medical. Rachel Pearlman has participated in collaborative funded research with Myriad Genetics Laboratories and Invitae Genetics but has no financial competitive interest