Rational design of on-chip gold plasmonic nanoparticles towards ctDNA screening.

This paper demonstrates the design, synthesis, simulation, and testing of three distinct geometries of plasmonic gold nanoparticles for on-chip DNA screening towards liquid biopsy. By employing a seed-mediated growth method, we have synthesized gold nanospheres, nanorods, and nanobipyramids. In parallel, we developed numerical simulations to understand the effects of nanoparticle geometry on the resonance features and refractive index sensitivity. Both experimental and simulation results were compared through a series of studies including in-solution and on-chip tests. We have thoroughly characterized the impact of nanoparticle geometry on the sensitivity to circulating tumor DNA, with immediate implications for liquid biopsy. The results agree well with theoretical predictions and simulations, including both bulk refractive index sensitivity and thin film sensitivity. Importantly, this work quantitatively establishes the link between nanoparticle geometry and efficacy in detecting rare circulating biomarkers. The nanobipyramids provided the highest sensitivity, approximately doubling the sensitivity compared to nanorods. To the best of our knowledge this is the first report carrying through geometric effects of simulation to clinically relevant biosensing. We put forth here synthesis and testing of three nanoparticle geometries, and a framework for both experimental and theoretical validation of plasmonic sensitivities towards liquid biopsy.

Developing a Portable Device for the Identification of miRNAs in Fluids.

In the present work we describe a novel system for the identification of microRNAs (miRNAs) in fluids. The method is based on combined novel 3D microarray technology using silk as scaffold and total internal reflection fluorescence microscopy (TIRFM), which allows for the rapid identification of miRNAs using a portable device.

Identifying multi-hit carcinogenic gene combinations: Scaling up a weighted set cover algorithm using compressed binary matrix representation on a GPU.

Despite decades of research, effective treatments for most cancers remain elusive. One reason is that different instances of cancer result from different combinations of multiple genetic mutations (hits). Therefore, treatments that may be effective in some cases are not effective in others. We previously developed an algorithm for identifying combinations of carcinogenic genes with mutations (multi-hit combinations), which could suggest a likely cause for individual instances of cancer. Most cancers are estimated to require three or more hits. However, the computational complexity of the algorithm scales exponentially with the number of hits, making it impractical for identifying combinations of more than two hits. To identify combinations of greater than two hits, we used a compressed binary matrix representation, and optimized the algorithm for parallel execution on an NVIDIA V100 graphics processing unit (GPU). With these enhancements, the optimized GPU implementation was on average an estimated 12,144 times faster than the original integer matrix based CPU implementation, for the 3-hit algorithm, allowing us to identify 3-hit combinations. The 3-hit combinations identified using a training set were able to differentiate between tumor and normal samples in a separate test set with 90% overall sensitivity and 93% overall specificity. We illustrate how the distribution of mutations in tumor and normal samples in the multi-hit gene combinations can suggest potential driver mutations for further investigation. With experimental validation, these combinations may provide insight into the etiology of cancer and a rational basis for targeted combination therapy.

Development of Gene Expression-Based Biomarkers on the nCounter® Platform for Immuno-Oncology Applications.

Biomarkers based on transcriptional profiling can be useful in the measurement of complex and/or dynamic physiological states where other profiling strategies such as genomic or proteomic characterization are not able to adequately measure the biology. One particular advantage of transcriptional biomarkers is the ease with which they can be measured in the clinical setting using robust platforms such as the NanoString nCounter system. The nCounter platform enables digital quantitation of multiplexed RNA from small amounts of blood, formalin-fixed, paraffin-embedded tumors, or other such biological samples that are readily available from patients, and the chapter uses it as the primary example for diagnostic assay development. However, development of diagnostic assays based on RNA biomarkers on any platform requires careful consideration of all aspects of the final clinical assay a priori, as well as design and execution of the development program in a way that will maximize likelihood of future success. This chapter introduces transcriptional biomarkers and provides an overview of the design and development process that will lead to a locked diagnostic assay that is ready for validation of clinical utility.

Coaxial sensing bio-amplifier for ultrasensitive detections of circulating tumor DNAs.

We herein report the first attempt to engineer a coaxial-sensing 3D amplifier able to achieve dynamic self-assembly in response to a mutated-ctDNA target. A bio-nanofiber is firstly manufactured via an ingenious double-channel electrostatic spinning and DNA rolling circle replication (RCR) technology, which offered an ideal scaffold for assembly of 3D amplifier activated by target recognition. The coaxial-controllable signal amplifier presented several advantages. (1) Given its "coaxial sensing effect", the proposed bio-amplifier played the coaxial transduction for signal enrichment to vastly increase sensitivity, capable of discriminating a single-base mismatched sequence from the perfectly complementary one, using ctDNA-134A as a model analyte. (2) Due to "covalent bridges lock effect" in an identifying chip with locked nucleic acid beacons, this 3D amplifier expressed high specificity and biostability toward seven different mutated-ctDNAs. (3) Profiting from special configuration of bioactive nanofibers and DNA replication programming, this catalytic bio-amplifier possessed "signal enrichment effect", which enhanced dynamic range toward ctDNA-134A detection and hybridized without any external indicators. This innovative bio-amplifier has a detection limit of 5.1 aM for ctDNA-134A with superior specificity, excellent sensitivity, and good performance. This pioneered method was further applied for broadly differentiate cells and evaluate changes in the expression levels of intracellular mutated-ctDNAs.

Battery Powered Portable Thermal Cycler for Continuous-Flow Polymerase Chain Reaction Diagnosis by Single Thermostatic Thermoelectric Cooler and Open-Loop Controller.

Temperature control is the most important and fundamental part of a polymerase chain reaction (PCR). To date, there have been several methods to realize the periodic heating and cooling of the thermal-cycler system for continuous-flow PCR reactions, and three of them were widely used: the thermo-cycled thermoelectric cooler (TEC), the heating block, and the thermostatic heater. In the present study, a new approach called open-loop controlled single thermostatic TEC was introduced to control the thermal cycle during the amplification process. Differing from the former three methods, the size of this microdevice is much smaller, especially when compared to the microdevice used in the heating block method. Furthermore, the rising and cooling speed of this method is much rapider than that in a traditional TEC cycler, and is nearly 20-30% faster than a single thermostatic heater. Thus, a portable PCR system was made without any external heat source, and only a Teflon tube-wrapped TEC chip was used to achieve the continuous-flow PCR reactions. This provides an efficient way to reduce the size of the system and simplify it. In addition, through further experiments, the microdevice is not only found to be capable of amplification of a PCR product from Human papillomavirus type 49 (Genbank ref: X74480.1) and Rubella virus (RUBV), but also enables clinical diagnostics, such as a test for hepatitis B virus.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip.

High-throughput DNA sequencing techniques have enabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3 × 104 variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56 × 105 molecular variants of full-length human O6-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interaction networks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

Statistical Methods for Identifying Biomarkers from miRNA Profiles of Cancers.

Biomarkers play important roles in early diagnosis and treatment plan for cancer patients and the importance is growing. With advances in high-throughput molecular profiling technology for various types of molecules such as DNA, RNA, proteins, or metabolites, it is now possible to perform massive profiling analysis that allows accelerating discovery of novel biomolecules. Because no single marker is sufficiently accurate for clinical use, the cancer biomarker is developed in the form of multiple biomarker panels. No single marker is sufficiently accurate for clinical use, and thus cancer biomarkers are developed in the form of multiple biomarker panels. Of various types of molecular biomarkers, microRNA (miRNA) has emerged as a class of promising cancer biomarker recently. MiRNAs are small noncoding RNAs that regulate gene expression. The chapter overviews the process of identification of biomarker panels from miRNA profiles focusing on statistical methods. Introduction to molecular cancer biomarkers is touched first. From sample design to miRNA profiling process is reviewed in the method section.Statistical methods for biomarker development are introduced according to three typical purposes of molecular biomarkers: tumor subtype classification, early detection, and prediction of treatment response or prognosis of patients. Example codes for R program are provided as well for selected methods.

Analysis of KRAS, NRAS and BRAF mutational profile by combination of in-tube hybridization and universal tag-microarray in tumor tissue and plasma of colorectal cancer patients.

Microarray technology fails in detecting point mutations present in a small fraction of cells from heterogeneous tissue samples or in plasma in a background of wild-type cell-free circulating tumor DNA (ctDNA). The aim of this study is to overcome the lack of sensitivity and specificity of current microarray approaches introducing a rapid and sensitive microarray-based assay for the multiplex detection of minority mutations of oncogenes (KRAS, NRAS and BRAF) with relevant diagnostics implications in tissue biopsies and plasma samples in metastatic colorectal cancer patients. In our approach, either wild-type or mutated PCR fragments are hybridized in solution, in a temperature gradient, with a set of reporters with a 5' domain, complementary to the target sequences and a 3' domain complementary to a surface immobilized probe. Upon specific hybridization in solution, which occurs specifically thanks to the temperature gradients, wild-type and mutated samples are captured at specific location on the surface by hybridization of the 3' reporter domain with its complementary immobilized probe sequence. The most common mutations in KRAS, NRAS and BRAF genes were detected in less than 90 minutes in tissue biopsies and plasma samples of metastatic colorectal cancer patients. Moreover, the method was able to reveal mutant alleles representing less than 0,3% of total DNA. We demonstrated detection limits superior to those provided by many current technologies in the detection of RAS and BRAF gene superfamily mutations, a level of sensitivity compatible with the analysis of cell free circulating tumor DNA in liquid biopsy.

A Novel Multi-Gene Detection Platform for the Analysis of miRNA Expression.

The study of miRNAs and their roles as non-invasive biomarkers has been intensely conducted in cancer diseases over the past decade. Various platforms, ranging from conventional qPCRs to Next Generation Sequencers (NGS), have been widely used to analyze miRNA expression. Here we introduced a novel platform, PanelChip™ Analysis System, which provides a sensitive solution for the analysis of miRNA levels in blood. After conducting miRQC analysis, the system's analytical performance compared favorably against similar nanoscale qPCR-based array technologies. Because PanelChip™ requires only a minimal amount of miRNA for analysis, we used it to screen for potential diagnostic biomarkers in the plasma of patients with oral cavity squamous cell carcinoma (OSCC). Combining the platform with a machine learning algorithm, we were able to discover miRNA expression patterns capable of separating healthy subjects from patients with OSCC.

Immunoprofiling of Chlamydia trachomatis using whole-proteome microarrays generated by on-chip in situ expression.

Using Chlamydia trachomatis (Ct) as a complex model organism, we describe a method to generate bacterial whole-proteome microarrays using cell-free, on-chip protein expression. Expression constructs were generated by two successive PCRs directly from bacterial genomic DNA. Bacterial proteins expressed on microarrays display antigenic epitopes, thereby providing an efficient method for immunoprofiling of patients and allowing de novo identification of disease-related serum antibodies. Through comparison of antibody reactivity patterns, we newly identified antigens recognized by known Ct-seropositive samples, and antigens reacting only with samples from cervical cancer (CxCa) patients. Large-scale validation experiments using high-throughput suspension bead array serology confirmed their significance as markers for either general Ct infection or CxCa, supporting an association of Ct infection with CxCa. In conclusion, we introduce a method for generation of fast and efficient proteome immunoassays which can be easily adapted for other microorganisms in all areas of infection research.

Differential Coexpression Network Analysis for Gene Expression Data.

Gene expression profiling by microarray has been used to uncover molecular variations in many areas. The traditional analysis method to gene expression profiling just focuses on the individual genes, and the interactions among genes are ignored, while genes play their roles not by isolations but by interactions with each other. Consequently, gene-to-gene coexpression analysis emerged as a powerful approach to solve the above problems. Then complementary to the conventional differential expression analysis, the differential coexpression analysis can identify gene markers from the systematic level. There are three aspects for differential coexpression network analysis including the network global topological comparison, differential coexpression module identification, and differential coexpression genes and gene pairs identification. To date, the coexpression network and differential coexpression analysis are widely used in a variety of areas in response to environmental stresses, genetic differences, or disease changes. In this chapter, we reviewed the existing methods for differential coexpression network analysis and discussed the applications to cancer research.

Data Analysis in Single-Cell Transcriptome Sequencing.

Single-cell transcriptome sequencing, often referred to as single-cell RNA sequencing (scRNA-seq), is used to measure gene expression at the single-cell level and provides a higher resolution of cellular differences than bulk RNA-seq. With more detailed and accurate information, scRNA-seq will greatly promote the understanding of cell functions, disease progression, and treatment response. Although the scRNA-seq experimental protocols have been improved very quickly, many challenges in the scRNA-seq data analysis still need to be overcome. In this chapter, we focus on the introduction and discussion of the research status in the field of scRNA-seq data normalization and cluster analysis, which are the two most important challenges in the scRNA-seq data analysis. Particularly, we present a protocol to discover and validate cancer stem cells (CSCs) using scRNA-seq. Suggestions have also been made to help researchers rationally design their scRNA-seq experiments and data analysis in their future studies.

Detection and Quantification of MicroRNAs in Esophageal Adenocarcinoma.

MicroRNAs (miRNAs) are a class of small, noncoding RNAs that have been emerging as novel regulators in esophageal adenocarcinoma. Their role has been established in various aspects of esophageal adenocarcinoma including carcinogenesis, progression, treatment, and prognosis. Therefore, miRNA detection, profiling, and quantification have become extremely important for scientists and clinicians. As miRNAs are small, their detection can be challenging. There have been various methods developed to detect and/or quantify miRNAs. This chapter aims to introduce the fundamentals and methods of the most commonly used approaches including miRNA microarrays and quantitative real-time polymerase chain reaction (RT-qPCR) to detect and quantify miRNAs in esophageal adenocarcinoma.

Methods for CpG Methylation Array Profiling Via Bisulfite Conversion.

DNA methylation is a key factor in epigenetic regulation, and contributes to the pathogenesis of many diseases, including various forms of cancers, and epigenetic events such X inactivation, cellular differentiation and proliferation, and embryonic development. The most conserved epigenetic modification in plants, animals, and fungi is 5-methylcytosine (5mC), which has been well characterized across a diverse range of species. Many technologies have been developed to measure modifications in methylation with respect to biological processes, and the most common method, long considered a gold standard for identifying regions of methylation, is bisulfite conversion. In this technique, DNA is treated with bisulfite, which converts cytosine residues to uracil, but does not affect cytosine residues that have been methylated, such as 5-methylcytosines. Following bisulfite conversion, the only cytosine residues remaining in the DNA, therefore, are those that have been methylated. Subsequent sequencing can then distinguish between unmethylated cytosines, which are displayed as thymines in the resulting amplified sequence of the sense strand, and 5-methylcytosines, which are displayed as cytosines in the resulting amplified sequence of the sense strand, at the single nucleotide level. In this chapter, we describe an array-based protocol for identifying methylated DNA regions. We discuss protocols for DNA quantification, bisulfite conversion, library preparation, and chip assembly, and present an overview of current methods for the analysis of methylation data.

Multiple single cell screening and DNA MDA amplification chip for oncogenic mutation profiling.

The oncogenic mutation heterogeneity of the cancer cell population has been proven to be essential for predicting both drug-response and drug-resistance of targeted therapies, such as tyrosine kinase inhibitors. It is necessary to accurately evaluate the mutation heterogeneity, oncogenic mutation and resistant mutation profiling at a single cell level. However, there are two major hurdles in the process. First, majority of the cells in tumor tissue are non-cancer cells, which cause background noise. Second, the work load and cost of next generation sequencing on dozens of single cells are prohibitive. To address both these issues, we developed a microfluidic chip for profiling of dozens of selected cells. With the help of a novel tri-states valve structure, which performs precise controlling of the cell/reagent movement, as well as active mixing of different reagents, trapping/identification/lysis and in situ MDA amplification was achieved at a single cell level on the same chip. Using a proof-of-concept assay mimicking EGFR targeting drug Gefitinib treatment of lung cancer cells, the new method was validated as capable of not only detecting the existence of multiple mutations, but also providing complete information of the mutation scenario at the single cell level by using cost-effective Sanger's sequencing.

Application of digital PCR with chip-in-a-tube format to analyze Adenomatous polyposis coli (APC) somatic mosaicism.

BACKGROUND: Over the past decade, digital PCR (dPCR) technology has significantly improved, and its application in clinical diagnostics is rapidly advancing. The Clarity™ dPCR platform, which employs the chip-in-a-tube format to broaden its range of applications, has been used to determine gene copy number. However, detection of mutations in human samples, the most demanding task in clinical practice, has not yet been reported using this platform. METHODS: The Clarity™ dPCR platform was used to detect somatic Adenomatous polyposis coli mosaicism c.834+2T>C, which had been identified using next-generation sequencing (NGS) technology in a patient with sporadic familial adenomatous polyposis. In addition, we were able to determine the size of the dPCR product. RESULTS: The mutation rate in the peripheral blood of the patient calculated using the dPCR platform was 13.2%. This was similar to that determined using NGS (12.7%). In contrast, in healthy donors, the mutation rate was <0.1%. Furthermore, it was confirmed that the dPCR product size was consistent with its theoretical value. CONCLUSION: Our results show that the dPCR platform with the chip-in-a-tube format is suitable for the analysis of mosaicism and enables the validation of the dPCR product size.

Cytogenomic assessment of the diagnosis of 93 patients with developmental delay and multiple congenital abnormalities: The Brazilian experience

OBJECTIVE: The human genome contains several types of variations, such as copy number variations, that can generate specific clinical abnormalities. Different techniques are used to detect these changes, and obtaining an unequivocal diagnosis is important to understand the physiopathology of the diseases. The objective of this study was to assess the diagnostic capacity of multiplex ligation-dependent probe amplification and array techniques for etiologic diagnosis of syndromic patients. METHODS: We analyzed 93 patients with developmental delay and multiple congenital abnormalities using multiplex ligation-dependent probe amplifications and arrays. RESULTS: Multiplex ligation-dependent probe amplification using different kits revealed several changes in approximately 33.3% of patients. The use of arrays with different platforms showed an approximately 53.75% detection rate for at least one pathogenic change and a 46.25% detection rate for patients with benign changes. A concomitant assessment of the two techniques showed an approximately 97.8% rate of concordance, although the results were not the same in all cases. In contrast with the array results, the MLPA technique detected ∼70.6% of pathogenic changes. CONCLUSION: The obtained results corroborated data reported in the literature, but the overall detection rate was higher than the rates previously reported, due in part to the criteria used to select patients. Although arrays are the most efficient tool for diagnosis, they are not always suitable as a first-line diagnostic approach because of their high cost for large-scale use in developing countries. Thus, clinical and laboratory interactions with skilled technicians are required to target patients for the most effective and beneficial molecular diagnosis.

Simultaneous Profiling of DNA Mutation and Methylation by Melting Analysis Using Magnetoresistive Biosensor Array.

Epigenetic modifications, in particular DNA methylation, are gaining increasing interest as complementary information to DNA mutations for cancer diagnostics and prognostics. We introduce a method to simultaneously profile DNA mutation and methylation events for an array of sites with single site specificity. Genomic (mutation) or bisulphite-treated (methylation) DNA is amplified using nondiscriminatory primers, and the amplicons are then hybridized to a giant magnetoresistive (GMR) biosensor array followed by melting curve measurements. The GMR biosensor platform offers scalable multiplexed detection of DNA hybridization, which is insensitive to temperature variation. The melting curve approach further enhances the assay specificity and tolerance to variations in probe length. We demonstrate the utility of this method by simultaneously profiling five mutation and four methylation sites in human melanoma cell lines. The method correctly identified all mutation and methylation events and further provided quantitative assessment of methylation density validated by bisulphite pyrosequencing.

[Current methods of extracellular DNA methylation analysis].

The discovery of the enormous role methylated cytosine plays in regulating gene expression has led to the development of a variety of techniques for detecting cytosine modification. A majority of these techniques are geared towards analyzing genomic DNA, which is typically available in large quantities. The concentration of cell-free DNAs (cfDNA) extracted from biological fluids including plasma, saliva, tears, or urine is relatively low and their degree of the fragmentation is high. Moreover, for noninvasive diagnostics of cancer, methylation patterns must be studied in minor cancer-specific fractions of DNA molecules substantially diluted by excess unmethylated molecules. The above limitations complicate the application of traditional techniques for cfDNA methylation analysis. In this manuscript, we review the state-of-art analysis of cfDNA methylation, hydroxymethylation, and noncanonical methylation (outside of CpG islands). The review covers methodological approaches to studying individual CpGs and genomic loci, as well as techniques for the large-scale analysis of methylation.