Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

First-line therapy with gemcitabine and paclitaxel in locally, recurrent or metastatic breast cancer: A phase II study

BACKGROUND: This phase II study evaluated the efficacy and safety of gemcitabine (G) plus paclitaxel (T) as first-line therapy in recurrent or metastatic breast cancer. METHODS: Patients with locally, recurrent or metastatic breast cancer and no prior chemotherapy for metastatic disease received G 1200 mg/m(2 )on days 1 and 8, and T 175 mg/m(2 )on day 1 (before G) every 21 days for a maximum of 10 cycles. RESULTS: Forty patients, 39 metastatic breast cancer and 1 locally-advanced disease, were enrolled. Their median age was 61.5 years, and 85% had a World Health Organization performance status (PS) of 0 or 1. Poor prognostic factors at baseline included visceral involvement (87.5%) and ≥2 metastatic sites (70%). Also, 27 (67.5%) patients had prior adjuvant chemotherapy, 25 of which had prior anthracyclines. A total of 220 cycles (median 6; range, 1–10) were administered. Of the 40 enrolled patients, 2 had complete response and 12 partial response, for an overall response rate of 35.0% for intent-to-treat population. Among 35 patients evaluable for efficacy the response rate was 40%. Additional 14 patients had stable disease, and 7 had progressive disease. The median duration of response was 12 months; median time to progression, 7.2 months; median survival, 25.7 months. Common grade 3/4 toxicities were neutropenia in 17 (42.5%) patients each, grade 3 leukopenia in 19 (47.5%), and grade 3 alopecia in 30 (75.0%) patients; 1 (2.5%) patient had grade 4 thrombocytopenia. CONCLUSION: GT exhibited encouraging activity and tolerable toxicity as first-line therapy in metastatic breast cancer. Phase III trials for further evaluation are ongoing

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy

Engineering of cyclodextrin glucanotransferases and the impact for biotechnological applications

Cyclodextrin glucanotransferases (CGTases) are industrially important enzymes that produce cyclic α-(1,4)-linked oligosaccharides (cyclodextrins) from starch. Cyclodextrin glucanotransferases are also applied as catalysts in the synthesis of glycosylated molecules and can act as antistaling agents in the baking industry. To improve the performance of CGTases in these various applications, protein engineers are screening for CGTase variants with higher product yields, improved CD size specificity, etc. In this review, we focus on the strategies employed in obtaining CGTases with new or enhanced enzymatic capabilities by searching for new enzymes and improving existing enzymatic activities via protein engineering