Entering the Pantheon of 21st Century Molecular Biology Tools: A Perspective on Digital PCR.

After several decades of relatively modest use, in the last several years digital PCR (dPCR) has grown to become the new gold standard for nucleic acid quantification. This coincides with the commercial availability of scalable, affordable, and reproducible droplet-based dPCR platforms in the past five years and has led to its rapid dissemination into diverse research fields and testing applications. Among these, it has been adopted most vigorously into clinical oncology where it is beginning to be used for plasma genotyping in cancer patients undergoing treatment. Additionally, innovation across the scientific community has extended the benefits of reaction partitioning beyond DNA and RNA quantification alone, and demonstrated its usefulness in evaluating DNA size and integrity, the physical linkage of colocalized markers, levels of enzyme activity and specific cation concentrations in a sample, and more. As dPCR technology gains in popularity and breadth, its power and simplicity can often be taken for granted; thus, the reader is reminded that due diligence must be exercised in order to make claims not only of precision but also of accuracy in their measurements.

Introduction to digital PCR.

Digital PCR (dPCR) is a molecular biology technique going through a renaissance. With the arrival of new instrumentation dPCR can now be performed as a routine molecular biology assay. This exciting new technique provides quantitative and detection capabilities that by far surpass other methods currently used. This chapter is an overview of some of the applications currently being performed using dPCR as well as the fundamental concepts and techniques this technology is based on.

Clinical applications using digital PCR.

Molecular diagnostics and disease-specific tailored treatments are now being introduced to patients at many hospitals and clinics throughout the world (Strain and Richman, Curr Opin HIV AIDS 8:106-110, 2013) and becoming prevalent in the nonscientific literature. Instead of generically using a "one treatment fits all" approach that may have varying levels of effectiveness to different patients, patient-specific molecular profiling based on the genetic makeup of the disease and/or a more accurate pathogen titer could provide more effective treatments with fewer unwanted side effects. One commonly known example of this scenario is epidermal growth factor receptor (EGFR). EGFR is upregulated in many cancers, including many lung and colorectal cancers. Commonly used treatments for these include the receptor blockers cetuximab or panitumumab and tyrosine kinase inhibitors erlotinib or gefitinib. These agents are effective at reducing out-of-control cell cycling and tumor proliferation, but only if downstream signaling kinases and phosphatases are not mutated. Known oncogenes such as BRAF V600E and KRAS G12/13 that are constitutively activated render these treatments ineffective. The use of known ineffective drugs and treatments can thus be avoided reducing time to more effective treatments, reducing cost, and increasing patient well-being. Although digital PCR is for all practical purposes a "new" technology, there is already tremendous interest in its potential for the clinical diagnostics arena. Specificity of the information acquired, accuracy of results, time to results, and cost per sample analyzed are making dPCR an attractive tool for this field. Three areas where dPCR will have a noticeable impact are pathogen/viral detection and quantitation, copy number variations, and rare mutation detection and abundance, but it will inevitably expand from these as the technology becomes more and more prevalent. This chapter discusses digital PCR assay optimization and validation, pathogen/viral detection and quantitation, copy number variation, and rare mutation abundance assays. The sample methods described below utilize the QX100/QX200 methodologies, but with the exception of reaction sub-partitioning (dependent on the instrumentation used) most other parameters remain the same.

RhoB, not RhoA, represses the transcription of the transforming growth factor beta type II receptor by a mechanism involving activator protein 1.

The transforming growth factor-beta (TGF-beta) type I (T beta R-I) and type II (T beta R-II) receptors are responsible for transducing TGF-beta signals. We have previously shown that inhibition of farnesyltransferase activity results in an increase in T beta R-II expression, leading to enhanced TGF-beta binding, signaling, and inhibition of tumor cell growth, suggesting that a farnesylated protein(s) exerts a repressive effect on T beta R-II expression. Likely candidates are farnesylated proteins such as Ras and RhoB, which are both farnesylated and involved in cell growth control. Neither a dominant negative Ha-Ras, constitutively activated Ha-Ras, or a pharmacological inhibitor of MEK1 affected T beta R-II transcription. However, ectopic expression of RhoB, but not the closely related family member RhoA, resulted in a 5-fold decrease of T beta R-II promoter activity. Furthermore, ectopic expression of RhoB, but not RhoA, resulted in a significant decrease of T beta R-II protein expression and resistance of tumor cells to TGF-beta-mediated cell growth inhibition. Deletion analysis of the T beta R-II promoter identified a RhoB-responsive region, and mutational analysis of this region revealed that a site for the transcription factor activator protein 1 (AP1) is critical for RhoB-mediated repression of T beta R-II transcription. Electrophoretic mobility shift assays clearly showed that the binding of AP1 to its DNA-binding site is strongly inhibited by RhoB. Consequently, transcription assays using an AP1 reporter showed that AP1-mediated transcription is down-regulated by RhoB. Altogether, these results identify a mechanism by which RhoB antagonizes TGF-beta action through transcriptional down-regulation of AP1 in T beta R-II promoter.