Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Evaluation of Remote Sensing Reflectance Derived From the Sentinel-2 Multispectral Instrument Observations Using POLYMER Atmospheric Correction

With a five-day revisit frequency over coastal regions and a spatial resolution of 10-60 m, the Sentinel-2 multispectral instrument (MSI) has shown its capacity to provide a reasonably accurate remote sensing reflectance (R rs ) data product over water when the standard “black pixel” (BP) atmospheric correction algorithm was applied to the top-ofatmospheric (TOA) reflectance data. Alternative atmospheric correction approaches, such as the POLYnomial-based algorithm applied to Medium Resolution Imaging Spectrometer (MERIS) (POLYMER), may show advantages under nonoptimal observation conditions (e.g., in the presence of strong sun glint). Here, POLYMER is implemented to process the data collected by both MSI and the Moderate Resolution Imaging Spectroradiometer (MODIS) with the resulting R rs evaluated with concurrent and colocated in situ R rs data collected from the AERONET-OC platforms. The results indicate less uncertainties in the MSI Rrs than those in the MODIS R rs , and also less uncertainties in the MSI Rrs than those reported earlier. This is possibly attributed to the spatial heterogeneity of coastal waters where MODIS coarseresolution data may suffer, and to the high-quality AERONETOC data. In addition, for the evaluation data set, MSI R rs does not appear to suffer from adjacency effects from the AERONETOC platform and clouds, leading to more coverage than MODIS in nearshore waters. However, MSI R rs is noisy in relatively clear waters, possibly due to the noisy TOA reflectance in the atmospheric correction bands over clear waters

Challenges in Methane Column Retrievals from AVIRIS-NG Imagery Over Spectrally Cluttered Surfaces: A Sensitivity Analysis

A comparison between efforts to detect methane anomalies by a simple band ratio approach from the Airborne Visual Infrared Imaging Spectrometer-Classic (AVIRIS-C) data for the Kern Front oil field, Central California, and the Coal Oil Point marine hydrocarbon seep field, offshore southern California, was conducted. The detection succeeded for the marine source and failed for the terrestrial source, despite these sources being of comparable strength. Scene differences were investigated in higher spectral and spatial resolution collected by the AVIRIS-C successor instrument, AVIRIS Next Generation (AVIRIS-NG), by a sensitivity study. Sensitivity to factors including water vapor, aerosol, planetary boundary layer (PBL) structure, illumination and viewing angle, and surface albedo clutter were explored. The study used the residual radiance method, with sensitivity derived from MODTRAN (MODerate resolution atmospheric correction TRANsmission) simulations of column methane (XCH4). Simulations used the spectral specifications and geometries of AVIRIS-NG and were based on a uniform or an in situ vertical CH4 profile, which was measured concurrent with the AVIRIS-NG data. Small but significant sensitivity was found for PBL structure and water vapor; however, highly non-linear, extremely strong sensitivity was found for surface albedo error. For example, a 10% decrease in the surface albedo corresponded to a 300% XCH4 increase over background XCH4 to compensate for the total signal, less so for stronger plumes. This strong non-linear sensitivity resulted from the high percentage of surface-reflected radiance in the airborne at-sensor total radiance. Coarse spectral resolution and feedback from interferents like water vapor underlay this sensitivity. Imaging spectrometry like AVIRIS and the Hyperspectral InfraRed Imager (HyspIRI) candidate satellite mission, have the advantages of contextual spatial information and greater at-sensor total radiance. However, they also face challenges due to their relatively broad spectral resolution compared to trace gas specific orbital sensors, e.g., the Greenhouse gases Observing SATellite (GOSAT), which is especially applicable to trace gas retrievals over scenes with high spectral albedo variability. Results of the sensitivity analysis are applicable for the residual radiance method and CH4 profiles used in the analysis, but they illustrate potential significant challenges in CH4 retrievals using other approaches. View Full-Tex

Challenges in Methane Column Retrievals from AVIRIS-NG Imagery Over Spectrally Cluttered Surfaces: A Sensitivity Analysis

A comparison between efforts to detect methane anomalies by a simple band ratio approach from the Airborne Visual Infrared Imaging Spectrometer-Classic (AVIRIS-C) data for the Kern Front oil field, Central California, and the Coal Oil Point marine hydrocarbon seep field, offshore southern California, was conducted. The detection succeeded for the marine source and failed for the terrestrial source, despite these sources being of comparable strength. Scene differences were investigated in higher spectral and spatial resolution collected by the AVIRIS-C successor instrument, AVIRIS Next Generation (AVIRIS-NG), by a sensitivity study. Sensitivity to factors including water vapor, aerosol, planetary boundary layer (PBL) structure, illumination and viewing angle, and surface albedo clutter were explored. The study used the residual radiance method, with sensitivity derived from MODTRAN (MODerate resolution atmospheric correction TRANsmission) simulations of column methane (XCH4). Simulations used the spectral specifications and geometries of AVIRIS-NG and were based on a uniform or an in situ vertical CH4 profile, which was measured concurrent with the AVIRIS-NG data. Small but significant sensitivity was found for PBL structure and water vapor; however, highly non-linear, extremely strong sensitivity was found for surface albedo error. For example, a 10% decrease in the surface albedo corresponded to a 300% XCH4 increase over background XCH4 to compensate for the total signal, less so for stronger plumes. This strong non-linear sensitivity resulted from the high percentage of surface-reflected radiance in the airborne at-sensor total radiance. Coarse spectral resolution and feedback from interferents like water vapor underlay this sensitivity. Imaging spectrometry like AVIRIS and the Hyperspectral InfraRed Imager (HyspIRI) candidate satellite mission, have the advantages of contextual spatial information and greater at-sensor total radiance. However, they also face challenges due to their relatively broad spectral resolution compared to trace gas specific orbital sensors, e.g., the Greenhouse gases Observing SATellite (GOSAT), which is especially applicable to trace gas retrievals over scenes with high spectral albedo variability. Results of the sensitivity analysis are applicable for the residual radiance method and CH4 profiles used in the analysis, but they illustrate potential significant challenges in CH4 retrievals using other approaches. View Full-Tex

Performance of POLYMER Atmospheric Correction of Ocean Color Imagery in the Presence of Absorbing Aerosols

The atmospheric correction approach currently being used operationally by NASA [termed as NASA standard atmospheric correction (NSAC) approach] to process ocean color data relies on traditional “black pixel” approach, with additional modifications to account for nonnegligible water-leaving radiance in the near-infrared (NIR) bands. The NSAC approach underestimates remote-sensing reflectance (R rs , sr -1 ) in blue wavelengths in the presence of absorbing aerosols. Addressing this issue requires realistic absorbing-aerosol model and knowledge of the vertical distribution of aerosols, which are currently difficult to achieve. An alternative atmospheric correction approach has been evaluated in this paper for Moderate Resolution Imaging Spectroradiometer (MODIS) data. The approach is based on a previously developed spectra-matching optimization [POLYnomial-based approach established for the atmospheric correction of MERIS data (POLYMER)], where polynomial functions are used to express atmospheric contribution to the measured radiance and where a bio-optical model is used to estimate the water contribution. Evaluation against in situ data measured over the regions frequently affected by absorbing aerosols indicates that, compared with the NSAC approach, the POLYMER approach improves the R rs retrievals in blue wavelengths while having a slightly worse performance in other wavelengths. Evaluation using NSAC-retrieved Rrs in adjacent days free of absorbing aerosols suggests that the POLYMER approach could improve the spectral shape and increase valid spatial coverage. When applied to time-series MODIS data, the POLYMER approach could generate more temporary coherent daily and monthly R rs patterns than the NSAC approach. These results suggest that the POLYMER approach could be an alternative approach to partly correct for absorbing aerosols in the absence of explicit information on the aerosol type and the vertical distribution

Salmonella typhimurium may support cancer treatment: a review

Antitumour treatments are evolving, including bacteria-mediated cancer therapy which is concurrently an ancient and cutting-edge approach. Salmonella typhimurium is a widely studied bacterial species that colonizes tumor tissues, showing oncolytic and immune system-regulating properties. It can be used as a delivery vector for genes and drugs, supporting conventional treatments that lack tumor-targeting abilities. This article summarizes recent evidence on the anticancer mechanisms of S. typhimurium alone and in combination with other anticancer treatments, suggesting that it may be a suitable approach to disease management

Refinement of the Critical Angle Calculation for the Contrast Reversal of Oil Slicks under Sunglint

It has long been observed that oil slicks under sunglint can reverse their optical contrast against nearby oil‐free seawater. Such a phenomenon has been described through both empirical statistical analysis of the sunglint strength and modeled theoretically using a critical angle concept. The critical angle, in this model, is the angle at which the image pixels show no or negligible contrast between oiled and nonoiled seawater. Pixels away from this critical angle show either positive or negative contrast from the oil‐free pixels. Although this concept has been fully demonstrated in the published literature, its calculation needs to be further refined to take into account: (1) the different refractive indices of oil slicks (from natural seeps) and seawater and (2) atmospheric effects in the sensor‐measured radiance. Using measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) over oil films in the Gulf of Mexico, we show improvement in the modeled and MODIS‐derived reflectance over oil slicks originated from natural seeps after incorporating these two factors in the model. Specifically, agreement between modeled and measured sunglint reflectance is found for both negative and positive‐contrasting oil slicks. These results indicate that surface roughness and reflectance from oil films can be estimated given any solar/viewing geometry and surface wind. Further, this model might be used to correct the sunglint effect on thick oil under similar illumination conditions. Once proven possible, it may allow existing laboratory‐based models, which estimate oil thickness after such corrections, to be applied to remote sensing imagery

Refinement of the Critical Angle Calculation for the Contrast Reversal of Oil Slicks under Sunglint

It has long been observed that oil slicks under sunglint can reverse their optical contrast against nearby oil‐free seawater. Such a phenomenon has been described through both empirical statistical analysis of the sunglint strength and modeled theoretically using a critical angle concept. The critical angle, in this model, is the angle at which the image pixels show no or negligible contrast between oiled and nonoiled seawater. Pixels away from this critical angle show either positive or negative contrast from the oil‐free pixels. Although this concept has been fully demonstrated in the published literature, its calculation needs to be further refined to take into account: (1) the different refractive indices of oil slicks (from natural seeps) and seawater and (2) atmospheric effects in the sensor‐measured radiance. Using measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) over oil films in the Gulf of Mexico, we show improvement in the modeled and MODIS‐derived reflectance over oil slicks originated from natural seeps after incorporating these two factors in the model. Specifically, agreement between modeled and measured sunglint reflectance is found for both negative and positive‐contrasting oil slicks. These results indicate that surface roughness and reflectance from oil films can be estimated given any solar/viewing geometry and surface wind. Further, this model might be used to correct the sunglint effect on thick oil under similar illumination conditions. Once proven possible, it may allow existing laboratory‐based models, which estimate oil thickness after such corrections, to be applied to remote sensing imagery

Atmospheric Correction of Hyperspectral GCAS Airborne Measurements Over the North Atlantic Ocean and Louisiana Shelf

The Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instrument has been used as a precursor for a hyperspectral instrument on the future geostationary satellite, yet its ability to “measure” ocean reflectance needs to be evaluated. Here, we demonstrate its capacity through vicarious calibration and atmospheric correction of data collected during flight campaigns over the Louisiana shelf in September 2013 and over the North Atlantic Ocean in November 2015. GCAS-measured at-sensor radiance was first vicariously calibrated using concurrent measurements by the Moderate Resolution Imaging Spectrometer (MODIS) and radiative transfer simulations with the MODerate resolution atmospheric TRANsmission (MODTRAN). Then, atmospheric correction has been implemented using MODTRAN-developed lookup tables and the traditional Gordon and Wang “black pixel” approach but with nonzero water-leaving radiance in the near-infrared accounted for through iteration. The atmospheric correction algorithm was applied to the vicariously calibrated GCAS imagery, with resulting R rs compared with concurrent MODIS R rs and in situ R rs . The comparison shows a mean relative difference of about 25% (N = 11) between GCAS and in situ R rs in the blue-green bands for clear to moderately turbid waters