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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Nov 23, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Macrophage imaging and subset analysis using single-cell RNA sequencing.

Sean Arlauckas¹, Nuri Oh¹, Ran Li^1,2

¹Center for Systems Biology, Massachusetts General Hospital Research Institute, Boston, MA 02114, USA.

Nanotheranostics

|January 4, 2021

Summary

This summary is machine-generated.

Macrophage imaging using nanoparticles can guide personalized cancer therapy. Single-cell RNA sequencing helps identify macrophage subsets and their roles in drug response, enhancing diagnostic capabilities.

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Last Updated: Nov 23, 2025

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Area of Science:

Biomedical Imaging
Nanotechnology
Immunology

Background:

Macrophages play a key role in drug response and resistance.
Nanoparticle contrast agents offer potential for macrophage-specific imaging.
Current imaging lacks molecular detail to identify targeted macrophage subsets and their functions.

Purpose of the Study:

To review the use of single-cell RNA sequencing (scRNAseq) to support companion macrophage imaging.
To explore how macrophage imaging can inform personalized treatment strategies.
To focus on dextran-based nanoparticles for predicting nanotherapy and antibody efficacy.

Main Methods:

Analysis of published single-cell RNA sequencing datasets.
Review of nanoparticle-based contrast agents for macrophage imaging.
Integration of imaging data with single-cell transcriptomics.

Main Results:

scRNAseq can identify specific macrophage subsets labeled by imaging agents.
Understanding macrophage subsets reveals their mechanistic role in drug response/resistance.
Dextran-based nanoparticles show promise in predicting therapeutic outcomes.

Conclusions:

Macrophage imaging, supported by scRNAseq, can serve as a companion diagnostic.
This approach can personalize cancer treatment by predicting drug efficacy.
Nanoparticle-based imaging offers a path toward precision oncology.