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List of PIK3CA oncogenic mutations

Supplementary text that describes parameters used for driver prediction methods and analysis of machine learning approaches for consensus generation.

Existing cancer driver prediction methods are based on very different assumptions and each of them can detect only a particular subset of driver genes. Here we perform a comprehensive assessment of 18 driver prediction methods on more than 3,400 tumor samples from 15 cancer types, all to determine their suitability in guiding precision medicine efforts. We categorized these methods into five groups: functional impact on proteins in general (FI) or specific to cancer (FIC), cohort-based analysis for recurrent mutations (CBA), mutations with expression correlation (MEC), and methods that use gene interaction network-based analysis (INA). The performance of driver prediction methods varied considerably, with concordance with a gold standard varying from 9% to 68%. FI methods showed relatively poor performance (concordance Significance: These findings assess state-of-the-art cancer driver prediction methods and develop a new and improved consensus-based approach for use in precision oncology. Cancer Res; 78(1); 290–301. ©2017 AACR.

List of actionable genes

List of cancer diver genes and passenger genes

The transcription factor SOX9 is activated at the onset of endothelial-to-mesenchymal transition (EndMT) during embryonic development and in pathological conditions. Its roles in regulating these processes, however, are not clear. Using human umbilical vein endothelial cells (HUVECs) as an EndMT model, we show that SOX9 expression alone is sufficient to activate mesenchymal genes and steer endothelial cells towards a mesenchymal fate. By genome-wide mapping of the chromatin landscape, we show that SOX9 displays features of a pioneer transcription factor, such as opening of chromatin and leading to deposition of active histone modifications at silent chromatin regions, guided by SOX dimer motifs and H2A.Z enrichment. We further observe highly transient and dynamic SOX9 binding, possibly promoted through its eviction by histone phosphorylation. However, while SOX9 binding is dynamic, changes in the chromatin landscape and cell fate induced by SOX9 are persistent. Finally, our analysis of single-cell chromatin accessibility indicates that SOX9 opens chromatin to drive EndMT in atherosclerotic lesions in vivo. This study provides new insight into key molecular functions of SOX9 and mechanisms of EndMT and highlights the crucial developmental role of SOX9 and relevance to human disease.

The epithelial-to-mesenchymal transition (EMT) is a process critical for wound healing, fibrosis, and cancer metastasis, but is also essential for atrioventricular valve formation, where distinct EMTs of endocardium (EndMT) and epicardium (EpiMT) generate mesenchyme. To track these processes, we have analyzed over 50,000 murine single-cell transcriptomes from embryonic day (E)7.75 cardiac crescent to E12.5 atrioventricular canals. We detail mesenchymal and endocardial bifurcation during EndMT, identify a unique, Hic1-expressing epicardial population during EpiMT, and reveal epithelial-mesenchymal plasticity (EMP) during both processes. Single-cell and histological analysis of Sox9-deficient valves show the accumulation of cells exhibiting EMP. Lastly, we deconvolve the signaling pathways active during the initiation and progression of EndMT and EpiMT. Overall, these data are the first to reveal mechanisms of emergence of mesenchyme from endocardium or epicardium at single-cell resolution and will serve as an atlas of EMT initiation and progression with broad implications in regenerative medicine and cancer biology.

Liver development is controlled by key signals and transcription factors that drive cell proliferation, migration, differentiation and functional maturation. In the adult liver, cell maturity can be perturbed by genetic and environmental factors that disrupt hepatic identity and function. Developmental signals and fetal genetic programmes are often dysregulated or reactivated, leading to dedifferentiation and disease. Here, we highlight signalling pathways and transcriptional regulators that drive liver cell development and primary liver cancers. We also discuss emerging models derived from pluripotent stem cells, 3D organoids and bioengineering for improved studies of signalling pathways in liver cancer and regenerative medicine.

Gamma-delta (γδ) T cells are unconventional T cells that help control cytomegalovirus (CMV) infection in adults. γδ T cells develop early in gestation, and a fetal public γδ T cell receptor (TCR) clonotype is detected in congenital CMV infections. However, age-dependent γδ T cell responses to primary CMV infection are not well-understood. Flow cytometry and TCR sequencing was used to comprehensively characterize γδ T cell responses to CMV infection in a cohort of 32 infants followed prospectively from birth. Peripheral blood γδ T cell frequencies increased during infancy, and were higher among CMV-infected infants relative to uninfected. Clustering analyses revealed associations between CMV infection and activation marker expression on adaptive-like Vδ1 and Vδ3, but not innate-like Vγ9Vδ2 γδ T cell subsets. Frequencies of NKG2C+CD57+ γδ T cells were temporally associated with the quantity of CMV shed in saliva by infants with primary infection. The public γδ TCR clonotype was only detected in CMV-infected infants, SCOPUS: ar.j, info:eu-repo/semantics/published

The cellular complexity and scale of the early liver have constrained analyses examining its emergence during organogenesis. To circumvent these issues, we analyzed 45,334 single-cell transcriptomes from embryonic day (E)7.5, when endoderm progenitors are specified, to E10.5 liver, when liver parenchymal and non-parenchymal cell lineages emerge. Our data detail divergence of vascular and sinusoidal endothelia, including a distinct transcriptional profile for sinusoidal endothelial specification by E8.75. We characterize two distinct mesothelial cell types as well as early hepatic stellate cells, and reveal distinct spatiotemporal distributions for these populations. We capture transcriptional profiles for hepatoblast specification and migration, including the emergence of a hepatomesenchymal cell type and evidence for hepatoblast collective cell migration. Further, we identify cell-cell interactions during the organization of the primitive sinusoid. This study provides a comprehensive atlas of liver lineage establishment from the endoderm and mesoderm through to the organization of the primitive sinusoid at single-cell resolution.

The transcription factor SOX9 is expressed in multiple tissues during embryogenesis and directs developmental processes. SOX9 is activated upon endothelial-to-mesenchymal transition (EndMT) in the developing heart, but its role in regulating this process is less clear. Using human umbilical vein endothelial cells as an EndMT model, we show that SOX9 expression alone is sufficient to activate mesenchymal enhancers and steer endothelial cells towards a mesenchymal fate. By genome-wide mapping of the chromatin landscape, we show that SOX9 acts as a pioneer transcription factor, having the ability to open chromatin and lead to deposition of active histone marks at a specific subset of previously silent enhancers, guided by SOX motifs and H2A.Z enrichment. This leads to a switch in enhancer activity states resulting in activation of mesenchymal genes and concurrent suppression of endothelial genes to drive EndMT. Moreover, we show that SOX9 chromatin binding is dynamic, but induces stable changes in the chromatin landscape. Our data also show widespread SOX9 chromatin scanning in silent chromatin that is not associated with SOX motifs or H2A.Z enrichment. Our study highlights the crucial developmental role of SOX9 and provides new insight into key molecular functions of SOX9 in the chromatin landscape and mechanisms of EndMT.Graphical abstract

Existing cancer driver prediction methods are based on very different assumptions and each of them can detect only a particular subset of driver genes. Here we perform a comprehensive assessment of 18 driver prediction methods on more than 3,400 tumor samples from 15 cancer types, all to determine their suitability in guiding precision medicine efforts. We categorized these methods into five groups: functional impact on proteins in general (FI) or specific to cancer (FIC), cohort-based analysis for recurrent mutations (CBA), mutations with expression correlation (MEC), and methods that use gene interaction network-based analysis (INA). The performance of driver prediction methods varied considerably, with concordance with a gold standard varying from 9% to 68%. FI methods showed relatively poor performance (concordance Significance: These findings assess state-of-the-art cancer driver prediction methods and develop a new and improved consensus-based approach for use in precision oncology. Cancer Res; 78(1); 290–301. ©2017 AACR.

By developing a high-density murine immunophenotyping platform compatible with high-throughput genetic screening, we have established profound contributions of genetics and structure to immune variation. Specifically, high-throughput phenotyping of 530 knockout mouse lines identified 140 monogenic “hits” (>25%), most of which had never hitherto been implicated in immunology. Furthermore, they were conspicuously enriched in genes for which humans show poor tolerance to loss-of-function. The immunophenotyping platform also exposed dense correlation networks linking immune parameters with one another and with specific physiologic traits. By limiting the freedom of individual immune parameters, such linkages impose genetically regulated “immunological structures”, whose integrity was found to be associated with immunocompetence. Hence, our findings provide an expanded genetic resource and structural perspective for understanding and monitoring immune variation in health and disease.

Astrocytes display complex morphologies with an array of fine extensions extending from the soma and the primary thick processes. Until the use of genetically encoded calcium indicators (GECIs) selectively expressed in astrocytes, Ca2+ signaling was only examined in soma and thick primary processes of astrocytes where Ca2+ -sensitive fluorescent dyes could be imaged. GECI imaging in astrocytes revealed a previously unsuspected pattern of spontaneous Ca2+ transients in fine processes that has not been observed without chronic expression of GECIs, raising potential concerns about the effects of GECI expression. Here, we perform two-photon imaging of Ca2+ transients in adult CA1 hippocampal astrocytes using a new single-cell patch-loading strategy to image Ca2+ -sensitive fluorescent dyes in the cytoplasm of fine processes. We observed that astrocyte fine processes exhibited a high frequency of spontaneous Ca2+ transients whereas astrocyte soma rarely showed spontaneous Ca2+ oscillations similar to previous reports using GECIs. We exploited this new approach to show these signals were independent of neuronal spiking, metabotropic glutamate receptor (mGluR) activity, TRPA1 channels, and L- or T-type voltage-gated calcium channels. Removal of extracellular Ca2+ almost completely and reversibly abolished the spontaneous signals while IP3 R2 KO mice also exhibited spontaneous and compartmentalized signals, suggesting they rely on influx of extracellular Ca2+ . The Ca2+ influx dependency of the spontaneous signals in patch-loaded astrocytes was also observed in astrocytes expressing GCaMP3, further highlighting the presence of Ca2+ influx pathways in astrocytes. The mechanisms underlying these localized Ca2+ signals are critical for understanding how astrocytes regulate important functions in the adult brain. GLIA 2016;64:2093-2103.

The rapid expansion of flow cytometry applications has outpaced the functionality of traditional manual analysis tools used to interpret flow cytometry data. Scientists are faced with the daunting prospect of manually identifying interesting cell populations in 50-dimensional datasets, equalling the complexity previously only reached in mass cytometry. Data can no longer be analyzed or interpreted fully by manual approaches. While automated gating has been the focus of intense efforts, there are many significant additional steps to the analytical pipeline (e.g., cleaning the raw files, event outlier detection, extracting immunophenotypes). We review the components of a customized automated analysis pipeline that can be generally applied to large scale flow cytometry data. We demonstrate these methodologies on data collected by the International Mouse Phenotyping Consortium (IMPC).

BackgroundIn recent years, several large-scale cancer genomics studies have helped generate detailed molecular profiling datasets for many cancer types and thousands of patients. These datasets provide a unique resource for studying cancer driver prediction methods and their utility for precision oncology, both to predict driver genetic alterations in patient subgroups (e.g. defined by histology or clinical phenotype) or even individual patients.MethodsWe performed the most comprehensive assessment to date of 18 driver gene prediction methods, on more than 3,400 tumour samples, from 15 cancer types, to determine their suitability in guiding precision medicine efforts. These methods have diverse approaches, which can be classified into five categories:functionalimpact on proteins in general (FI) or specific tocancer (FIC),cohort-basedanalysis for recurrent mutations (CBA),mutations withexpressioncorrelation (MEC) and methods that use geneinteractionnetwork-basedanalysis (INA).ResultsThe performance of driver prediction methods varies considerably, with concordance with a gold-standard varying from 9% to 68%. FI methods show relatively poor performance (concordance ConclusionExisting cancer driver prediction methods are based on very different assumptions and each of them can only detect a particular subset of driver events. Consensus-based methods, like ConsensusDriver, are thus a promising approach to harness the strengths of different driver prediction paradigms.

Astrocytes display complex morphologies with an array of fine extensions extending from the soma and the primary thick processes. Until the use of genetically encoded calcium indicators (GECIs) selectively expressed in astrocytes, Ca

A self-referenced optical frequency comb, derived from a mode-locked fiber laser, and a cavity-enhanced diode-laser-based saturated absorption spectrometer were employed to measure the absolute frequency of 55 absorption lines of the P and R branches of the 2ν1 band of 12C2HD at 1.5 μm with a one standard deviation uncertainty of better than 2.5 kHz for all lines measured. The shift sensitivities of the P(16) line to changes in power, pressure, and modulation amplitude have been studied in detail. Improved values of the ground-state molecular constants are obtained.

The paper describes two approaches for minimization of phase noise of the comb generated from a mode-locked fiber laser. First is the implementation of higher speed actuators for control of the comb and second is direct generation of an octave of continuum.