Detection of pollution transport events southeast of Mexico City using ground-based visible spectroscopy measurements of nitrogen dioxide

This work presents ground based differential optical absorption spectroscopy (DOAS) measurements of nitrogen dioxide (NO<sub>2</sub>) during the MILAGRO field campaign in March 2006 at the Tenango del Aire research site located to the southeast of Mexico City. The DOAS NO<sub>2</sub> column density measurements are used in conjunction with ceilometer, meteorological and surface nitric oxide (NO), nitrogen oxides (NO<sub>x</sub>) and total reactive nitrogen (NO<sub>y</sub>) measurements to analyze pollution transport events to the southeast of Mexico City during the MILARGO field campaign. The study divides the data set into three case study pollution transport events that occurred at the Tenango del Aire research site. The unique data set is then used to provide an in depth analysis of example days of each of the pollution transport events. An in depth analysis of 13 March 2006, a Case One day, shows the transport of several air pollution plumes during the morning through the Tenango del Aire research site when southerly winds are present and demonstrates how DOAS tropospheric NO<sub>2</sub> vertical column densities (VCD), surface NO<sub>2</sub> mixing ratios and ceilometer data are used to determine the vertical homogeneity of the pollution layer. The analysis of 18 March 2006, a Case Two day, shows that when northerly winds are present for the entire day, the air at the Tenango del Aire research site is relatively clean and no major pollution plumes are detected. Case 3 days are characterized by relatively clean air throughout the morning with large DOAS NO<sub>2</sub> enhancements detected in the afternoon. The analysis of 28 March 2006 show the DOAS NO<sub>2</sub> enhancements are likely due to lightning activity and demonstrate how suitable ground-based DOAS measruements are for monitoring anthropogenic and natural pollution sources that reside above the mixing layer

Changes in serum calcium, phosphate, and PTH and the risk of death in incident dialysis patients: A longitudinal study

Elevated bone mineral parameters have been associated with mortality in dialysis patients. There are conflicting data about calcium, parathyroid hormone (PTH), and mortality and few data about changes in bone mineral parameters over time. We conducted a prospective cohort study of 1007 incident hemodialysis and peritoneal dialysis patients. We examined longitudinal changes in bone mineral parameters and whether their associations with mortality were independent of time on dialysis, inflammation, and comorbidity. Serum calcium, phosphate, and calcium–phosphate product (CaP) increased in these patients between baseline and 6 months (P<0.001) and then remained stable. Serum PTH decreased over the first year (P<0.001). In Cox proportional hazards models adjusting for inflammation, comorbidity, and other confounders, the highest quartile of phosphate was associated with a hazard ratio (HR) of 1.57 (1.07–2.30) using both baseline and time-dependent values. The highest quartiles of calcium, CaP, and PTH were associated with mortality in time-dependent models but not in those using baseline values. The lowest quartile of PTH was associated with an HR of 0.65 (0.44–0.98) in the time-dependent model with 6-month lag analysis. We conclude that high levels of phosphate both at baseline and over follow-up are associated with mortality in incident dialysis patients. High levels of calcium, CaP, and PTH are associated with mortality immediately preceding an event. Promising new interventions need to be rigorously tested in clinical trials for their ability to achieve normalization of bone mineral parameters and reduce deaths of dialysis patients

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

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

SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids

Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this is a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells and is associated with increased tubule-interstitial kidney fibrosis in patient autopsy samples. To study direct effects of the virus on the kidney independent of systemic effects of COVID-19, we infected human-induced pluripotent stem-cell-derived kidney organoids with SARS-CoV-2. Single-cell RNA sequencing indicated injury and dedifferentiation of infected cells with activation of profibrotic signaling pathways. Importantly, SARS-CoV-2 infection also led to increased collagen 1 protein expression in organoids. A SARS-CoV-2 protease inhibitor was able to ameliorate the infection of kidney cells by SARS-CoV-2. Our results suggest that SARS-CoV-2 can directly infect kidney cells and induce cell injury with subsequent fibrosis. These data could explain both acute kidney injury in COVID-19 patients and the development of chronic kidney disease in long COVID

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

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

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

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN. We present a computational study determining the frequency and extent of alterations of the MYC network across the 33 human cancers of TCGA. These data, together with MYC, positively correlated pathways as well as mutually exclusive cancer genes, will be a resource for understanding MYC-driven cancers and designing of therapeutics