Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells

High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery

The development of new drugs is multidisciplinary and systematic work. High-throughput techniques based on “-omics” have driven the discovery of biomarkers in diseases and therapeutic targets of drugs. A transcriptome is the complete set of all RNAs transcribed by certain tissues or cells at a specific stage of development or physiological condition. Transcriptome research can demonstrate gene functions and structures from the whole level and reveal the molecular mechanism of specific biological processes in diseases. Currently, gene expression microarray and high-throughput RNA-sequencing have been widely used in biological, medical, clinical, and drug research. The former has been applied in drug screening and biomarker detection of drugs due to its high throughput, fast detection speed, simple analysis, and relatively low price. With the further development of detection technology and the improvement of analytical methods, the detection flux of RNA-seq is much higher but the price is lower, hence it has powerful advantages in detecting biomarkers and drug discovery. Compared with the traditional RNA-seq, scRNA-seq has higher accuracy and efficiency, especially the single-cell level of gene expression pattern analysis can provide more information for drug and biomarker discovery. Therefore, (sc)RNA-seq has broader application prospects, especially in the field of drug discovery. In this overview, we will review the application of these technologies in drug, especially in natural drug and biomarker discovery and development. Emerging applications of scRNA-seq and the third generation RNA-sequencing tools are also discussed.

Dynamically Monitoring the Clonal Evolution of Lung Cancer Based on the Molecular Characterization of Circulating Tumor Cells Using Aptamer Cocktail-Modified Nanosubstrates

Dynamically monitoring the clonal evolution of lung cancer and performing molecular analyses on tumor cells are challenging but necessary tasks to adjust therapeutic interventions and evaluate treatment efficacy. Circulating tumor cells (CTCs), as a "liquid biopsy", may offer an auxiliary tool to identify phenotypic transformation of solid tumors at primary or metastatic sites and uncover their corresponding molecular variation. Herein, we developed an aptamer-modified PEG-PLGA-nanofiber (PPN) microfluidic system optimized for recognizing rare CTC subtypes in lung cancer patients. This unique purification system can be adopted to monitor the clonal evolution of solid tumors by following the intrinsic immunophenotypes of CTCs, while significantly enhancing capture efficiency for polyclonal-derived tumor cells, further facilitating therapeutic evaluation via dynamic CTC enumeration. Combining with downstream single-cell sequencing, the aptamer-modified-PPN microfluidic system was able to provide early insight into tumor heterogeneity and predict histologic transformation in advance, broadening its clinical applications in lung cancer patients.

Single-cell RNA-sequencing of migratory breast cancer cells: discovering genes associated with cancer metastasis

Considerable evidence suggests breast cancer metastasis arises from cells undergoing epithelial-to-mesenchymal-transition (EMT) and cancer stem-like cells (CSCs). Using a microfluidic device that enriches migratory breast cancer cells with enhanced capacity for tumor formation and metastasis, we identified genes differentially expressed in migratory cells by high-throughput single-cell RNA-sequencing. Migratory cells exhibited overall signatures of EMT and CSCs with variable expression of marker genes, and they retained expression profiles of EMT over time. With single-cell resolution, we discovered intermediate EMT states and distinct epithelial and mesenchymal sub-populations of migratory cells, indicating breast cancer cells can migrate rapidly while retaining an epithelial state. Migratory cells showed differential profiles for regulators of oxidative stress, mitochondrial morphology, and the proteasome, revealing potential vulnerabilities and unexpected consequences of drugs. We also identified novel genes correlated with cell migration and outcomes in breast cancer as potential prognostic biomarkers and therapeutic targets to block migratory cells in metastasis.

Single-Cell Analysis Using Droplet Microfluidics

Droplet microfluidics has revolutionized the study of single cells. The ability to compartmentalize cells within picoliter droplets in microfluidic devices has opened up a wide range of strategies to extract information at the genomic, transcriptomic, proteomic, or metabolomic level from large numbers of individual cells. Studying the different molecular landscapes at single-cell resolution has provided the authors with a detailed picture of intracellular heterogeneity and the resulting changes in cellular phenotypes. In addition, these technologies have aided in the discovery of rare cells in tumors or in the immune system, and left the authors with a deeper understanding of the fundamental biological processes that determine cell fate. This review aims to provide a detailed overview of the various droplet microfluidic strategies reported in the literature, taking into account the sometimes subtle differences in workflow or reagents that enable or improve certain protocols. Specifically, approaches to targeted- and whole-genome analysis, as well as whole-transcriptome profiling techniques, are reviewed. In addition, an up-to-date overview of new methods to characterize and quantify single-cell protein levels, and of developments to screen secreted molecules such as antibodies, cytokines, or metabolites at the single-cell level, is provided.

Circulating Tumor Cells in Pancreatic Cancer: Current Perspectives

Pancreatic cancer is the fourth leading cause of cancer-related death in the USA and Europe; early symptoms and screenings are lacking, and it is usually diagnosed late with a poor prognosis. Circulating tumor cells (CTCs) have been promising new biomarkers in solid tumors. In the last twenty years (1999-2019), 140 articles have contained the key words "Circulating tumor cells, pancreatic cancer, prognosis and diagnosis." Articles were evaluated for the use of CTCs as prognostic markers and their correlation to survival in pancreatic ductal adenocarcinoma (PDAC). In the final selected 17 articles, the CTC detection rate varied greatly between different enrichment methodologies and ranged from 11% to 92%; the majority of studies used the antigen-dependent CellSearch^© system for CTC detection. Fifteen of the reviewed studies showed a correlation between CTC presence and a worse overall survival. The heterogeneity of CTC-detection methods and the lack of uniform results hinder a comparison of the evaluated studies. However, CTCs can be detected in pancreatic cancer and harbor a hope to serve as an early detection tool. Larger studies are needed to corroborate CTCs as valid biomarkers in pancreatic cancer.

Single-Cell Analysis of Circulating Tumor Cells: Why Heterogeneity Matters

Unlike bulk-cell analysis, single-cell approaches have the advantage of assessing cellular heterogeneity that governs key aspects of tumor biology. Yet, their applications to circulating tumor cells (CTCs) are relatively limited, due mainly to the technical challenges resulting from extreme rarity of CTCs. Nevertheless, recent advances in microfluidics and immunoaffinity enrichment technologies along with sequencing platforms have fueled studies aiming to enrich, isolate, and sequence whole genomes of CTCs with high fidelity across various malignancies. Here, we review recent single-cell CTC (scCTC) sequencing efforts, and the integrated workflows, that have successfully characterized patient-derived CTCs. We examine how these studies uncover DNA alterations occurring at multiple molecular levels ranging from point mutations to chromosomal rearrangements from a single CTC, and discuss their cellular heterogeneity and clinical consequences. Finally, we highlight emerging strategies to address key challenges currently limiting the translation of these findings to clinical practice.

Engineered models to parse apart the metastatic cascade

While considerable progress has been made in studying genetic and cellular aspects of metastasis with in vitro cell culture and in vivo animal models, the driving mechanisms of each step of metastasis are still relatively unclear due to their complexity. Moreover, little progress has been made in understanding how cellular fitness in one step of the metastatic cascade correlates with ability to survive other subsequent steps. Engineered models incorporate tools such as tailored biomaterials and microfabrication to mimic human disease progression, which when coupled with advanced quantification methods permit comparisons to human patient samples and in vivo studies. Here, we review novel tools and techniques that have been recently developed to dissect key features of the metastatic cascade using primary patient samples and highly representative microenvironments for the purposes of advancing personalized medicine and precision oncology. Although improvements are needed to increase tractability and accessibility while faithfully simulating the in vivo microenvironment, these models are powerful experimental platforms for understanding cancer biology, furthering drug screening, and facilitating development of therapeutics.