Characterization of Mechanisms That Mediate Cancer Metastatic Colonization

Metastatic disease is the major cause of death in all solid tumor cancers. Current therapeutic strategies fail to target metastasis as the genes and mechanisms that regulate this process remain poorly understood. Metastatic colonization is the final step of the metastatic cascade whereby cancer cells form a tumor at a distant site. This final step is the culmination of clonal evolution of cancer populations that results in a highly aggressive population with enhanced metastatic capacity and often presents clinically as numerous inoperable tumor nodules that lead to mortality. Characterization of the mechanisms that govern metastatic colonization at cellular and molecular levels is necessary for the prevention and treatment of metastatic disease in patients. The first half of this thesis presents work towards understanding mechanisms that mediate colorectal cancer colonization of the liver in order to guide novel therapeutic strategies. An in vivo large-scale RNAinterference screen was performed to identify genes required for liver colonization. Liver and red blood cell pyruvate kinase (PKLR) was identified as a driver of liver metastasis in experimental models. In patients, PKLR was found to be expressed at higher levels in liver metastases relative to primary colorectal cancer tumors and also overexpressed in the primary tumors of patients with metastatic disease. PKLR was found to promote cell survival in the tumor core and enhance survival during conditions of concurrent high cell density and low oxygen availability. Molecular studies revealed that PKL negatively regulates pyruvate kinase M2 (PKM2) enzymatic activity. By inhibiting cellular pyruvate kinase activity, PKLR allows for the diversion of metabolites towards glutathione generation—allowing for the maintenance of glutathione levels. Adequate glutathione levels appears critical for metastatic colonization as GCLC, the catalytic subunit of glutamatecysteine ligase and the rate-limiting enzyme for glutathione synthesis, was found to be similarly required for effective metastasis, associated in its expression with human liver metastatic progression, and could be therapeutically targeted to reduce metastatic colonization. These findings highlight the impact of metabolic regulation on cancer cell adaptation within the metastatic niche. The robust effects on liver metastatic colonization observed upon modulating this metabolic pathway suggest clinical potential for therapeutic targeting of PKLR or cellular glutathione synthesis in colorectal cancer. The second half of this thesis presents work towards an understanding of diversity generation in clonal populations as it benefits cancer evolution and metastatic colonization. Clonal human breast cancer subpopulations were isolated to allow for the identification of subpopulations that exhibit population-level phenotypic diversity. These high variability clonal subpopulations were found to be more proficient at metastatic colonization—consistent with a positive role for diversification capacity in cancer progression. Through single-cell RNA-sequencing, cell-to-cell transcript expression variability was identified as a defining feature of these subpopulations, extending to protein-level variability. Furthermore, spliceosomal machinery was identified as a gene set with high expression variability, suggesting a means by which variation could be transmitted to a global level. Engineered variable expression of the spliceosomal gene SNRNP40 promoted metastatic fitness, and this metastatic capacity was attributable to cells with low SNRNP40 expression. Clinically, low SNRNP40 expression is associated with metastatic relapse. These findings reveal that transcriptomic variability generation may serve as a mechanism by which cancer subpopulations achieve diversification of gene expression states, which allows for enhanced fitness under changing environmental pressures encountered during metastatic progression

Door‐to‐Puncture: A Practical Metric for Capturing and Enhancing System Processes Associated With Endovascular Stroke Care, Preliminary Results From the Rapid Reperfusion Registry

Background: In 2011, the Brain Attack Coalition proposed door‐to‐treatment times of 2 hours as a benchmark for patients undergoing intra‐arterial therapy (IAT). We designed the Rapid Reperfusion Registry to capture the percentage of stroke patients who meet the target and its impact on outcomes. Methods and Results: This is a retrospective analysis of anterior circulation patients treated with IAT within 9 hours of symptom onset. Data was collected from December 31, 2011 to December 31, 2012 at 2 centers and from July 1, 2012 to December 31, 2012 at 7 centers. Short “Door‐to‐Puncture” (D2P) time was hypothesized to be associated with good patient outcomes. A total of 478 patients with a mean age of 68±14 years and median National Institutes of Health Stroke Scale (NIHSS) of 18 (IQR 14 to 21) were analyzed. The median times for IAT delivery were 234 minutes (IQR 163 to 304) for “last known normal‐to‐groin puncture” time (LKN‐to‐GP) and 112 minutes (IQR 68 to 176) for D2P time. The overall good outcome rate was 39.7% for the entire cohort. In a multivariable model adjusting for age, NIHSS, hypertension, diabetes, reperfusion status, and symptomatic hemorrhage, both short LKN‐to‐GP (OR 0.996; 95% CI [0.993 to 0.998]; P<0.001) and short D2P times (OR 0.993, 95% CI [0.990 to 0.996]; P<0.001) were associated with good outcomes. Only 52% of all patients in the registry achieved the targeted D2P time of 2 hours. Conclusions: The time interval of D2P presents a clinically relevant time frame by which system processes can be targeted to streamline the delivery of IAT care nationally. At present, there is much opportunity to enhance outcomes through reducing D2P

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension

Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p&lt;0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties