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Rosalie Chu

Pacific Northwest National Laboratory

ORCID: 0000-0001-7428-7647

Publishes on Ionosphere and magnetosphere dynamics, Geophysics and Gravity Measurements, Earthquake Detection and Analysis. 10.1k papers and 7.5k citations.

10.1kPublications
7.5kTotal Citations

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Top publicationsby citations

Proteogenomic Characterization of Endometrial Carcinoma
Cited by 530Open Access

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover
James Stegen, James K. Fredrickson, Michael J. Wilkins et al.|Nature Communications|2016
Cited by 400Open Access

Environmental transitions often result in resource mixtures that overcome limitations to microbial metabolism, resulting in biogeochemical hotspots and moments. Riverine systems, where groundwater mixes with surface water (the hyporheic zone), are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. Here, to investigate the coupling among groundwater–surface water mixing, microbial communities and biogeochemistry, we apply ecological theory, aqueous biogeochemistry, DNA sequencing and ultra-high-resolution organic carbon profiling to field samples collected across times and locations representing a broad range of mixing conditions. Our results indicate that groundwater–surface water mixing in the hyporheic zone stimulates heterotrophic respiration, alters organic carbon composition, causes ecological processes to shift from stochastic to deterministic and is associated with elevated abundances of microbial taxa that may degrade a broad suite of organic compounds. Groundwater-surface water mixing zones link critical ecosystem domains, but attendant microbe-biogeochemistry-hydrology interactions are poorly known. Here, the authors show that groundwater-surface water mixing stimulates respiration, alters carbon composition, and shifts the ecology from stochastic to deterministic.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses
Ernesto Nakayasu, Carrie Nicora, Amy Sims et al.|mSystems|2016
Cited by 244Open Access

In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.