Dive into Single, Seek Out Multiple: Probing Cancer Metastases via Single-Cell Sequencing and Imaging Techniques

Abstract

Metastasis is the cause of most cancer deaths and continues to be the biggest challenge in clinical practice and laboratory investigation. The challenge is largely due to the intrinsic heterogeneity of primary and metastatic tumor populations and the complex interactions among cancer cells and cells in the tumor microenvironment. Therefore, it is important to determine the genotype and phenotype of individual cells so that the metastasis-driving events can be precisely identified, understood, and targeted in future therapies. Single-cell sequencing techniques have allowed the direct comparison of the genomic and transcriptomic changes among different stages of metastatic samples. Single-cell imaging approaches have enabled the live visualization of the heterogeneous behaviors of malignant and non-malignant cells in the tumor microenvironment. By applying these technologies, we are achieving a spatiotemporal precision understanding of cancer metastases and clinical therapeutic translations.

Single-Cell RNA Sequencing of Cerebrospinal Fluid as an Advanced Form of Liquid Biopsy for Neurological Disorders

“…However, the type of library preparation kit, presence of multiple operational steps, prolonged analysis times, low throughout analysis systems, and inexperience of personnel can add variability to results. Simple, high-throughput, inexpensive and reproducible methods are needed to standardize the sequencing process [24,35]. Downstream data processing primarily involves the conversion of raw reads into standardized FASTQ files (text-based files used to store nucleotide sequences), demultiplexing, quality control, filtering, alignment and finally data visualization and interpretation.…”

“…However, the type of library preparation kit, presence of multiple operational steps, prolonged analysis times, low throughout analysis systems, and inexperience of personnel can add variability to results. Simple, high-throughput, inexpensive and reproducible methods are needed to standardize the sequencing process [ 24 , 35 ].…”

“…Downstream data processing primarily involves the conversion of raw reads into standardized FASTQ files (text-based files used to store nucleotide sequences), demultiplexing, quality control, filtering, alignment and finally data visualization and interpretation. Several scRNA-seq analysis pipelines have been developed to assess gene expression and interpret single-cell transcriptomics [ 35 ]. As discussed, the downstream data largely depends on upstream processing, and this variability should be accounted for when interpreting data.…”

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing – Review

“…That allows an unprecedented dissection of transcription within millions of individual cells. Both single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq) have exciting applications [65][66][67][68][69][70][71][72][73][74][75][76][77], for instance: (i) discovering and characterizing cell type in health and diseases, such as cancer [13,[78][79][80][81][82][83][84][85][86][87][88][89], with implications in immunology [90], immune-mediated diseases [91], immunotherapy [92][93][94][95][96][97][98][99][100] and drug resistance [101]; (ii) deciphering the roles of such specific cell types in health and disease [102], including mitochondrial heteroplasmy [33]; and (iii) analyzing cell emergence, development and plasticity in tissues and organisms. These studies are also applied to study plant biology [103,104].…”

Differential gene expression analysis of spatial transcriptomic experiments using spatial mixed models

“…Of special importance has been the use of ST to assess tissue heterogeneity in many cancerous tissues 6,[12][13][14][15][16][17][18][19][20][21] , as well as infected tissues 22 . Spatial transcriptomics has also enabled a better understanding of cell-to-cell communication [23][24][25] and the identification of potential druggable targets 18,26,27 .…”