Modeling the Measurement: Δ₄₇, Corrections, and Absolute Ratios for Reference Materials

Clumped isotope studies on CO2, Δ47, that is the excess in the isotopologue containing both 13C and 18O at mass 47, can be very useful since they can give temperature estimates independent of the bulk isotopic composition. The measurement itself can be affected by a number of items. Here we develop a data processing model to examine the effects different interferences might have on the final calculated value. It incorporates known issues, for example, pressure baseline, 17O excess, and shifts in absolute ratios for primary reference materials and parameters used for 17O correction. We also included linearity effects as well as differences in isotopologue absolute abundances at a given m/z. What normally would be considered acceptable mass spectrometer 45R and 46R linearity can skew Δ47 results. That is 0.04‰/V and −0.04‰/V linearity on 45R and 46R respectively would also cause an apparent shift in the parameters used for 17O corrections. Measurements were made on CO2(g) equilibrated with water, and we were able to match up the effects seen with model results. Linearity and small differences in amplitude between sample and working reference gas affected Δ47 determination, as did apparent shifts in isotopologue abundances under different conditions. This may (partially) account for discrepancies seen in Δ47-temperature calibrations curves between laboratories. We also developed an easy way to precisely calculate the δ13C and δ18O that works well in spreadsheets without the need for multiple iterations

Evidence for Horizontal Gene Transfer of Anaerobic Carbon Monoxide Dehydrogenases

Carbon monoxide (CO) is commonly known as a toxic gas, yet both cultivation studies and emerging genome sequences of bacteria and archaea establish that CO is a widely utilized microbial growth substrate. In this study, we determined the prevalence of anaerobic carbon monoxide dehydrogenases ([Ni,Fe]-CODHs) in currently available genomic sequence databases. Currently, 185 out of 2887, or 6% of sequenced bacterial and archaeal genomes possess at least one gene encoding [Ni,Fe]-CODH, the key enzyme for anaerobic CO utilization. Many genomes encode multiple copies of [Ni,Fe]-CODH genes whose functions and regulation are correlated with their associated gene clusters. The phylogenetic analysis of this extended protein family revealed six distinct clades; many clades consisted of [Ni,Fe]-CODHs that were encoded by microbes from disparate phylogenetic lineages, based on 16S rRNA sequences, and widely ranging physiology. To more clearly define if the branching patterns observed in the [Ni,Fe]-CODH trees are due to functional conservation vs. evolutionary lineage, the genomic context of the [Ni,Fe]-CODH gene clusters was examined, and superimposed on the phylogenetic trees. On the whole, there was a correlation between genomic contexts and the tree topology, but several functionally similar [Ni,Fe]-CODHs were found in different clades. In addition, some distantly related organisms have similar [Ni,Fe]-CODH genes. Thermosinus carboxydivorans was used to observe horizontal gene transfer (HGT) of [Ni,Fe]-CODH gene clusters by applying Kullback–Leibler divergence analysis methods. Divergent tetranucleotide frequency and codon usage showed that the gene cluster of T. carboxydivorans that encodes a [Ni,Fe]-CODH and an energy-converting hydrogenase is dissimilar to its whole genome but is similar to the genome of the phylogenetically distant Firmicute, Carboxydothermus hydrogenoformans. These results imply that T carboxydivorans acquired this gene cluster via HGT from a relative of C. hydrogenoformans

A monoclonal antibody against kininogen reduces inflammation in the HLA-B27 transgenic rat

The human leukocyte antigen B27 (HLA-B27) transgenic rat is a model of human inflammatory bowel disease, rheumatoid arthritis and psoriasis. Studies of chronic inflammation in other rat models have demonstrated activation of the kallikrein–kinin system as well as modulation by a plasma kallikrein inhibitor initiated before the onset of clinicopathologic changes or a deficiency in high-molecular-mass kininogen. Here we study the effects of monoclonal antibody C11C1, an antibody against high-molecular-mass kininogen that inhibits the binding of high-molecular-mass kininogen to leukocytes and endothelial cells in the HLA-B27 rat, which was administered after the onset of the inflammatory changes. Thrice-weekly intraperitoneal injections of monoclonal antibody C11C1 or isotype IgG(1 )were given to male 23-week-old rats for 16 days. Stool character as a measure of intestinal inflammation, and the rear limbs for clinical signs of arthritis (tarsal joint swelling and erythema) were scored daily. The animals were killed and the histology sections were assigned a numerical score for colonic inflammation, synovitis, and cartilage damage. Administration of monoclonal C11C1 rapidly decreased the clinical scores of pre-existing inflammatory bowel disease (P < 0.005) and arthritis (P < 0.001). Histological analyses confirmed significant reductions in colonic lesions (P = 0.004) and synovitis (P = 0.009). Decreased concentrations of plasma prekallikrein and high-molecular-mass kininogen were found, providing evidence of activation of the kallikrein–kinin system. The levels of these biomarkers were reversed by monoclonal antibody C11C1, which may have therapeutic potential in human inflammatory bowel disease and arthritis

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

Rapid Environmental Change over the Past Decade Revealed by Isotopic Analysis of the California Mussel in the Northeast Pacific

The anthropogenic input of fossil fuel carbon into the atmosphere results in increased carbon dioxide (CO2) into the oceans, a process that lowers seawater pH, decreases alkalinity and can inhibit the production of shell material. Corrosive water has recently been documented in the northeast Pacific, along with a rapid decline in seawater pH over the past decade. A lack of instrumentation prior to the 1990s means that we have no indication whether these carbon cycle changes have precedence or are a response to recent anthropogenic CO2 inputs. We analyzed stable carbon and oxygen isotopes (δ13C, δ18O) of decade-old California mussel shells (Mytilus californianus) in the context of an instrumental seawater record of the same length. We further compared modern shells to shells from 1000 to 1340 years BP and from the 1960s to the present and show declines in the δ13C of modern shells that have no historical precedent. Our finding of decline in another shelled mollusk (limpet) and our extensive environmental data show that these δ13C declines are unexplained by changes to the coastal food web, upwelling regime, or local circulation. Our observed decline in shell δ13C parallels other signs of rapid changes to the nearshore carbon cycle in the Pacific, including a decline in pH that is an order of magnitude greater than predicted by an equilibrium response to rising atmospheric CO2, the presence of low pH water throughout the region, and a record of a similarly steep decline in δ13C in algae in the Gulf of Alaska. These unprecedented changes and the lack of a clear causal variable underscores the need for better quantifying carbon dynamics in nearshore environments

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment