Single cell proteomics characterization of bone marrow hematopoiesis with distinct Ras pathway lesions.

Normal hematopoiesis requires constant prolific production of different blood cell lineages by multipotent hematopoietic stem cells (HSC). Stem- and progenitor- cells need to balance dormancy with proliferation. How genetic alterations impact frequency, lineage potential, and metabolism of HSC is largely unknown. Here, we compared induced expression of KRAS G12D or RasGRP1 to normal hematopoiesis. At low-resolution, both Ras pathway lesions result in skewing towards myeloid lineages. Single-cell resolution CyTOF proteomics unmasked an expansion of HSC- and progenitor- compartments for RasGRP1, contrasted by a depletion for KRAS G12D . SCENITH™ quantitates protein synthesis with single-cell precision and corroborated that immature cells display low metabolic SCENITH™ rates. Both RasGRP1 and KRAS G12D elevated mean SCENITH™ signals in immature cells. However, RasGRP1-overexpressing stem cells retain a metabolically quiescent cell-fraction, whereas this fraction diminishes for KRAS G12D . Our temporal single cell proteomics and metabolomics datasets provide a resource of mechanistic insights into altered hematopoiesis at single cell resolution.

Methods for high-throughput MethylCap-Seq data analysis.

BACKGROUND: Advances in whole genome profiling have revolutionized the cancer research field, but at the same time have raised new bioinformatics challenges. For next generation sequencing (NGS), these include data storage, computational costs, sequence processing and alignment, delineating appropriate statistical measures, and data visualization. Currently there is a lack of workflows for efficient analysis of large, MethylCap-seq datasets containing multiple sample groups. METHODS: The NGS application MethylCap-seq involves the in vitro capture of methylated DNA and subsequent analysis of enriched fragments by massively parallel sequencing. The workflow we describe performs MethylCap-seq experimental Quality Control (QC), sequence file processing and alignment, differential methylation analysis of multiple biological groups, hierarchical clustering, assessment of genome-wide methylation patterns, and preparation of files for data visualization. RESULTS: Here, we present a scalable, flexible workflow for MethylCap-seq QC, secondary data analysis, tertiary analysis of multiple experimental groups, and data visualization. We demonstrate the experimental QC procedure with results from a large ovarian cancer study dataset and propose parameters which can identify problematic experiments. Promoter methylation profiling and hierarchical clustering analyses are demonstrated for four groups of acute myeloid leukemia (AML) patients. We propose a Global Methylation Indicator (GMI) function to assess genome-wide changes in methylation patterns between experimental groups. We also show how the workflow facilitates data visualization in a web browser with the application Anno-J. CONCLUSIONS: This workflow and its suite of features will assist biologists in conducting methylation profiling projects and facilitate meaningful biological interpretation.

Patient Preferences for Attributes of Health Canada Approved Weight Loss Medications Among Adults Living with Obesity in Canada: A Qualitative Study.

Purpose: Obesity is a complex disease with negative impacts on physical and mental health. The treatment of obesity is an area where shared decision making and patient preferences play an important role. Recommendations surrounding weight loss medications are evolving and only recently, with the publication of the 2020 Canadian Obesity Management Clinical Guidelines, pharmacotherapy has become a recommended alternative for obesity management. Guidelines recommend three medications: orlistat, liraglutide, and naltrexone/bupropion. This study sought to identify medication attributes relevant to patients starting pharmacotherapy for weight management. Patients and Methods: Semi-structured focus groups and interviews were conducted with Canadian residents who were ≥18 years of age and were living with obesity (body mass index [BMI] ≥30kg/m2 or ≥27kg/m2 with adiposity-related complications). Sessions were conducted virtually, audio recorded, and transcribed. Two team members used a combination of inductive and deductive coding to independently code the data. A final coding template was agreed upon through discussion. Results: A total of 21 individuals participated (85.7% female, 76.2% ≥40 years of age) with the average BMI being 44.3 kg/m2. Participants touched upon many attributes which were categorized into five categories: 1) cost, 2) regimen, 3) side effects, 4) benefits, and 5) non-medication attributes. Cost of medications, lack of coverage by insurance companies, and stigma were identified as major barriers to accessing medications. There was consensus in the desire for a simple regimen, however there was heterogeneity among opinions on tolerability of side effects, desired benefits, and route of administration. Conclusion: This study identified attributes that influenced patient's decisions when considering a new anti-obesity medication. Understanding these attributes can assist clinicians in shared decision-making. This study highlighted the stigma that is prevalent among providers and the need for education. Further research should be conducted to understand the tradeoffs patients in our study make between the identified attributes.