Investigations on some innate immunity proteins can yield misleading information, as investigators often rely on static measurements and assume a direct correlation to function. As protein function is often not directly proportional to protein abundance, and mechanistic pathways are interconnected and under constant feedback regulatory control, functional analysis is required. In this study, we used functional mass spectrometry to measure anti-protease and complement activity in plasma obtained from coronavirus disease 2019 (COVID-19) patients. Our data suggests that within 48 h of hospital admission, COVID-19 patients undergo a protease storm with significantly elevated neutrophil elastase (p < 0.001) and lymphocyte granzyme B (p < 0.01), while, anti-protease activity is significantly increased, including alpha-1 antitrypsin (AAT; p < 0.001) and alpha-1-antichymotrypsin (ACT; p < 0.001). Concurrently, the ratio of C3a to C3beta activity significantly decreased with increasing COVID-19 severity, suggesting more complement activation (Mild COVID-19 p < 0.05; Severe COVID-19 p < 0.001). Activity levels of AAT, ACT and C3a/C3beta remained unchanged over 10 hospital days. Our data suggests that COVID-19 is associated with both a protease storm and complement activation, with the former somewhat balanced with increased anti-protease activity. Evaluation of the AAT/ACT ratio and C3a/C3beta ratio indicated that COVID-19 severity is associated with both neutrophil elastase neutralization and complement activation.

Liquid biopsy has emerged as a novel approach to tumor characterization, offering advantages in sample accessibility and tissue heterogeneity. However, as mutational analysis predominates, the tumor microenvironment has largely remained unacknowledged in liquid biopsy research. The current work provides an explorative transcriptomic characterization of the Stroma Liquid BiopsyTM (SLB) proteomics panel in colon carcinoma by integrating single-cell and bulk transcriptomics data from publicly available repositories. Expression of SLB genes was significantly enriched in tumors with high histologic stromal content in comparison to tumors with low stromal content (median enrichment score 0.308 vs. 0.222, p = 0.036). In addition, we identified stromal-specific and epithelial-specific expression of the SLB genes, that was subsequently integrated into a gene signature ratio. The stromal-epithelial signature ratio was found to have prognostic significance in a discovery cohort of 359 colon adenocarcinoma patients (OS HR 2.581, 95%CI 1.567-4.251, p < 0.001) and a validation cohort of 229 patients (OS HR 2.590, 95%CI 1.659-4.043, p < 0.001). The framework described here provides transcriptomic evidence for the prognostic significance of the SLB panel constituents in colon carcinoma. Plasma protein levels of the SLB panel may reflect histologic intratumoral stromal content, a poor prognostic tumor characteristic, and hence provide valuable prognostic information in liquid biopsy.

The COVID-19 pandemic has dealt a devastating blow to healthcare systems globally. Approximately 3.2% of patients infected with COVID-19 require invasive ventilation during the course of the illness. Within this population, 25% of patients are affected with neurological manifestations. Among those who are affected by severe neurological manifestations, some may have acute cerebrovascular complications (5%), impaired consciousness (15%) or exhibit skeletal muscle hypokinesis (20%). The cause of the severe cognitive impairment and hypokinesis is unknown at this time. Potential causes include COVID-19 viral encephalopathy, toxic metabolic encephalopathy, post-intensive care unit syndrome and cerebrovascular pathology. We present a case of a 60 year old patient who sustained a prolonged hospitalization with COVID-19, had a cerebrovascular event and developed a persistent unexplained encephalopathy along with a hypokinetic state. He was treated successfully with modafinil and carbidopa/levodopa showing clinical improvement within 3–7 days and ultimately was able to successfully discharge home.

For years the protein depletion toolkit was limited primarily to immuno-affinity chromatography and other biologically-derived tools. While effective for many applications, such tools were not efficient for “omics” sample preparation, when throughput, economy and simplicity were required. Furthermore, these same separation tools often denatured proteins which limited there use in applications which required the measurement of function, structure or bio-activity. BSG is dedicated to create new methods and applications to drive efficient workflows and better data quality for all proteomic and biomarker analyses.

For many diseases, pancreatic cancer for example, long term survival is critically dependent upon early detection. So various strategies for early detectable markers are being investigated. One such strategy is hypothesis driven, first by identifying a singular biomarker, usually derived from genomic analysis of the tumor type, and then determine its derivative protein concentration in blood. This has been challenging as many differentially regulated genes do not generate a differentially regulated protein, or one of sufficient concentration for current means of detection. An alternative biomarker strategy is purely data driven, as panels of proteins may be up and/or down regulated, or altered by post-translational modifications. These can be monitored and quantified to differences in diseased and normal/healthy individuals. In this study we adopt such a data driven strategy using a new product which combines Albumin depletion and on-bead digestion of the enriched serum proteome in a seamless process, called AlbuVoid™ LC-MS On-Bead. From these methods, we were able to compare labeled quantification of proteins from normal and disease state sera - for this case, breast, lung and pancreatic cancer at different clinically defined stages. The methods spectrally quantify over 250 total proteins, in a cost effective and reproducible manner. No offline peptide level fractionation prior to LC-MS was employed, lowering the LC-MS acquisition time 5-10x compared to common serum proteomic workflows. We describe these workflow advantages applied towards a “wellness” proteome algorithm combining knowledge and data surrounding individual normal and healthy proteomes, compared and contrasted to those with a clinically definable disease. From our initial tests, a candidate panel of 20 proteins are determined to be differentially expressed and such data suggests the feasibility for their use in the early detection of cancer. The critical parameters for success to our strategy are considered as well as some of the remaining challenges to clinical utility. Citation Format: Haiyan Zheng, Caifeng Zhao, Swapan Roy, Amenah Soherwardy, Ravish Amin, Devjit Roy, Matthew Kuruc. Comparison of the serum proteome in individuals with cancers versus those without cancer, and its application to wellness. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-065.

Abstract ProFACT‟s SeraFILE™ surface,library affords high-resolution partitioning of complex protein extracts into differential sub-proteomes that can be characterized further. The benefit of applying SeraFILE™ is that the resulting protein profiles offer,a,much,more,comprehensive signature of the starting complex,sample,leading to comparative,disease-specific differences. The SeraFILE™ protocol generates,approximately 80 biologically active,sub-proteome,pools,and decreases,the complexity,of a parent,protein sample. Th ese sub-proteomes,offer researchers a way,to maintain the enzymatic,function(s) of interest in a relatively simplified protein sample, and,perhaps,provide,insight,into,protein interactions required for function.