Advances in single-cell RNA sequencing and its applications in cancer research

Abstract

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

Aortic Cellular Heterogeneity in Health and Disease: Novel Insights Into Aortic Diseases From Single-Cell RNA Transcriptomic Data Sets

“…Commonly used approaches include: microdroplet-based (ie, 10× Genomics and Dropseq), micromanipulation (ie, CEL-seq and MATQ-seq), or FACS (MARs-seq and FLASH-seq). 43 RNA is then extracted from each cell, cDNA synthesized and amplified for library construction. Libraries are then sequenced and data are computationally analyzed using a reference genome that aligns to the sequenced cDNA.…”

A review on trends in development and translation of omics signatures in cancer

“…To tackle the challenges of tumor heterogeneity, single-cell techniques have emerged, facilitating personalized treatment based on the specific heterogeneity of the tumor. Single-cell RNA-seq has proven successful in dissecting tumor heterogeneity and microenvironment with unparalleled resolution in both solid tumors and hematological malignancies such as leukemia and lymphoma [251] . For example, scRNA-seq has been utilized to identify drug-tolerant cell populations in NSCLC tumors, as well as quiescent stem-like cells that contribute to chemoresistance and poor outcomes in AML.…”

Metabolic heterogeneity of colorectal cancer as a prognostic factor: insights gained from fluorescence lifetime imaging

“…Clinical imaging modalities, such as metabolic PET with radiolabeled tracers ( 18 F, 11 C) and MRI/MRS, allow to capture inter– and intratumor heterogeneity among patients with low (∼4.5 mm) spatial resolution (Plathow and Weber, 2008). Recently evolved methods of single-cell sequencing deliver comprehensive information about the metabolic landscape of a tumor with a resolution up to 55–100 µm based on the expression of the metabolic genes, but these approaches are rather complex, laborious and not widely available (Evers et al, 2019; Huang et al, 2023).…”