Microvascular Ultrasonic Imaging of Angiogenesis Identifies Tumors in a Murine Spontaneous Breast Cancer Model

The purpose of this study is to determine if microvascular tortuosity can be used as an imaging biomarker for the presence of tumor-associated angiogenesis and if imaging this biomarker can be used as a specific and sensitive method of locating solid tumors. Acoustic angiography, an ultrasound-based microvascular imaging technology, was used to visualize angiogenesis development of a spontaneous mouse model of breast cancer (n=48). A reader study was used to assess visual discrimination between image types, and quantitative methods utilized metrics of tortuosity and spatial clustering for tumor detection. The reader study resulted in an area under the curve of 0.8, while the clustering approach resulted in the best classification with an area under the curve of 0.95. Both the qualitative and quantitative methods produced a correlation between sensitivity and tumor diameter. Imaging of vascular geometry with acoustic angiography provides a robust method for discriminating between tumor and healthy tissue in a mouse model of breast cancer. Multiple methods of analysis have been presented for a wide range of tumor sizes. Application of these techniques to clinical imaging could improve breast cancer diagnosis, as well as improve specificity in assessing cancer in other tissues. The clustering approach may be beneficial for other types of morphological analysis beyond vascular ultrasound images

Guiding the Way to Gamma-Ray Sources: X-ray Studies of Supernova Remnants

Supernova remnants have long been suggested as a class of potential counterparts to unidentified gamma-ray sources. The mechanisms by which such gamma-rays can arise may include emission from a pulsar associated with a remnant, or a variety of processes associated with energetic particles accelerated by the SNR shock. Imaging and spectral observations in the X-ray band can be used to identify properties of the remnants that lead to gamma-ray emission, including the presence of pulsar-driven nebulae, nonthermal X-ray emission from the SNR shells, and the interaction of SNRs with dense surrounding material.Comment: 16 pages, 11 figures, To appear in the proceedings of the workshop: "The Nature of the Unidentified Galactic Gamma-Ray Sources" held at INAOE, Mexico, October 2000, (A.Carraminana, O. Reiner and D. Thompson, eds.

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

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe

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

Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types

Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis