Use of MS-GUIDE for identification of protein biomarkers for risk stratification of patients with prostate cancer.

BACKGROUND: Non-invasive liquid biopsies could complement current pathological nomograms for risk stratification of prostate cancer patients. Development and testing of potential liquid biopsy markers is time, resource, and cost-intensive. For most protein targets, no antibodies or ELISAs for efficient clinical cohort pre-evaluation are currently available. We reasoned that mass spectrometry-based prescreening would enable the cost-effective and rational preselection of candidates for subsequent clinical-grade ELISA development. METHODS: Using Mass Spectrometry-GUided Immunoassay DEvelopment (MS-GUIDE), we screened 48 literature-derived biomarker candidates for their potential utility in risk stratification scoring of prostate cancer patients. Parallel reaction monitoring was used to evaluate these 48 potential protein markers in a highly multiplexed fashion in a medium-sized patient cohort of 78 patients with ground-truth prostatectomy and clinical follow-up information. Clinical-grade ELISAs were then developed for two of these candidate proteins and used for significance testing in a larger, independent patient cohort of 263 patients. RESULTS: Machine learning-based analysis of the parallel reaction monitoring data of the liquid biopsies prequalified fibronectin and vitronectin as candidate biomarkers. We evaluated their predictive value for prostate cancer biochemical recurrence scoring in an independent validation cohort of 263 prostate cancer patients using clinical-grade ELISAs. The results of our prostate cancer risk stratification test were statistically significantly 10% better than results of the current gold standards PSA alone, PSA plus prostatectomy biopsy Gleason score, or the National Comprehensive Cancer Network score in prediction of recurrence. CONCLUSION: Using MS-GUIDE we identified fibronectin and vitronectin as candidate biomarkers for prostate cancer risk stratification.

In vitro quantification of botulinum neurotoxin type A1 using immobilized nerve cell-mimicking nanoreactors in a microfluidic platform.

The bacterial toxin botulinum neurotoxin A (BoNT/A) is not only an extremely toxic substance but also a potent pharmaceutical compound that is used in a wide spectrum of neurological disorders and cosmetic applications. The quantification of the toxin is extremely challenging due to its extraordinary high physiological potency and is further complicated by the toxin's three key functionalities that are necessary for its activity: receptor binding, internalization-translocation, and catalytic activity. So far, the industrial standard to measure the active toxin has been the mouse bioassay (MBA) that is considered today as outdated due to ethical issues. Therefore, recent introductions of cell-based assays were highly anticipated; their impact however remains limited due to their labor-intensive implementation. This report describes a new in vitro approach that combines a nanosensor based on the use of nerve cell-mimicking nanoreactors (NMN) with microfluidic technology. The nanosensor was able to measure all three key functionalities, and therefore suitable to quantify the amount of physiologically active BoNT/A. The integration of such a sensor in a microfluidic device allowed the detection and quantification of BoNT/A amounts in a much shorter time than the MBA (<10 h vs. 2-4 days). Lastly, the system was also able to reliably quantify physiologically active BoNT/A within a simple final pharmaceutical formulation. This complete in vitro testing system and its unique combination of a highly sensitive nanosensor and microfluidic technology represent a significant ethical advancement over in vivo measures and a possible alternative to cell-based in vitro detection methods.

Antibiotic Discovery with Synthetic Fermentation: Library Assembly, Phenotypic Screening, and Mechanism of Action of ß-Peptides Targeting Penicillin-Binding Proteins.

In analogy to biosynthetic pathways leading to bioactive natural products, synthetic fermentation generates mixtures of molecules from simple building blocks under aqueous, biocompatible conditions, allowing the resulting cultures to be directly screened for biological activity. In this work, a novel ß-peptide antibiotic was successfully identified using the synthetic fermentation platform. Phenotypic screening was carried out in an initially random fashion, allowing simple identification of active cultures. Subsequent deconvolution, focused screening, and structure-activity relationship studies led to the identification of a potent antimicrobial peptide, showing strong selectivity for our model system Bacillus subtilis over human HEK293 cells. To determine the antibacterial mechanism of action, a peptide probe bearing a photoaffinity tag was readily synthesized through the use of appropriate synthetic fermentation building blocks and utilized for target identification using a quantitative mass spectrometry-based strategy. The chemoproteomic approach led to the identification of a number of bacterial membrane proteins as prospective targets. These findings were validated through binding affinity studies with penicillin-binding protein 4 using microscale thermophoresis, with the bioactive peptide showing a dissociation constant ( Kd) in the nanomolar range. Through these efforts, we provide a proof of concept for the synthetic fermentation approach presented here as a new strategy for the phenotypic discovery of novel bioactive compounds.

Transcriptomic responses of cancerous and noncancerous human colon cells to sulforaphane and selenium.

Diets enriched with bioactive food components trigger molecular changes in cells that may contribute to either health-promoting or adverse effects. Recent technological advances in high-throughput data generation allow for observing systems-wide molecular responses to cellular perturbations with nontoxic and dietary-relevant doses while considering the intrinsic differences between cancerous and noncancerous cells. In this chemical profile, we compared molecular responses of the colon cancer cell line HT29 and a noncancerous colon epithelial cell line (HCEC) to two widely encountered food components, sulforaphane and selenium. We conducted this comparison by generating new transcriptome data by microarray gene-expression profiling, analyzing them statistically on the single gene, network, and functional pathway levels, and integrating them with protein expression data. Sulforaphane and selenium, at doses that did not inhibit the growth of the tested cells, induced or repressed the transcription of a limited number of genes in a manner distinctly dependent on the chemical and the cell type. The genes that most strongly responded in cancer cells were observed after treatment with sulforaphane and were members of the aldo-keto reductase (AKR) superfamily. These genes were in high agreement in terms of fold change with their corresponding proteins (correlation coefficient r(2) = 0.98, p = 0.01). Conversely, selenium had little influence on the cancer cells. In contrast, in noncancerous cells, selenium induced numerous genes involved in apoptotic, angiogenic, or tumor proliferation pathways, whereas the influence of sulforaphane was very limited. These findings contribute to defining the significance of cell type in interpreting human cellular transcriptome-level responses to exposures to natural components of the diet.