Single‐Cell RNA Sequencing for Precision Oncology: Current State‑of‑Art

Abstract

Tumors exhibit genetic and phenotypic diversity leading to
intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and
immune cells) of tumors contributes into the ITH. This ITH allows tumors
to overcome various selection pressures such as anti-cancer therapies
and metastasis at distant organs. Single-cell RNA-seq (scRNA-seq) has
provided unprecedented insights into ITH and its implications in drug
resistance and metastasis. As scRNA-seq technology grows and provides
many new findings, new tools on different programming platforms
are frequently generated. Here, we aim to provide a framework and
guidelines for new entrants into the field of scRNA-seq. In this review,
we discuss the current state-of-art of scRNA-seq analysis step-by-step
including filtering, normalization and analysis. First, we discuss the brief
history of experimental methods, followed by data processing and implications
in precision oncology.