Data from: Single-cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer

Hum, Nicholas, Lawrence Livermore National Laboratory, https://orcid.org/0000-0003-1605-3193

Sebastian, Aimy, Lawrence Livermore National Laboratory, https://orcid.org/0000-0002-7822-7040

Martin, Kelly, Lawrence Livermore National Laboratory

Gilmore, Sean, Lawrence Livermore National Laboratory

Byers, Stephen, Georgetown University

Wheeler, Elizabeth, Lawrence Livermore National Laboratory

Coleman, Matthew, Lawrence Livermore National Laboratory

Loots, Gabriela, Lawrence Livermore National Laboratory

hum3@llnl.gov, sebastian4@llnl.gov

Published Aug 08, 2020 on Dryad. https://doi.org/10.6071/M3238R

Cite this dataset

Hum, Nicholas et al. (2020). Data from: Single-cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer [Dataset]. Dryad. https://doi.org/10.6071/M3238R

Abstract

Cancer-associated fibroblasts (CAFs) are a prominent stromal cell type in solid tumors and molecules secreted by CAFs play an important role in tumor progression and metastasis. CAFs coexist as heterogeneous populations with potentially different biological functions. Although CAFs are a major component of the breast cancer stroma, molecular and phenotypic heterogeneity of CAFs in breast cancer is poorly understood. In this study, we investigated CAF heterogeneity in triple-negative breast cancer (TNBC) using a syngeneic mouse model, BALB/c-derived 4T1 mammary tumors. Using single-cell RNA sequencing (scRNA-seq), we identified six CAF subpopulations in 4T1 tumors including: 1) myofibroblastic CAFs, enriched for α-smooth muscle actin and several other contractile proteins; 2) ‘inflammatory’ CAFs with elevated expression of inflammatory cytokines; and 3) a CAF subpopulation expressing major histocompatibility complex (MHC) class II proteins that are generally expressed in antigen-presenting cells. Comparison of 4T1-derived CAFs to CAFs from pancreatic cancer revealed that these three CAF subpopulations exist in both tumor types. Interestingly, cells with inflammatory and MHC class II-expressing CAF profiles were also detected in normal breast/pancreas tissue, suggesting that these phenotypes are not tumor microenvironment-induced. This work enhances our understanding of CAF heterogeneity, and specifically targeting these CAF subpopulations could be an effective therapeutic approach for treating highly aggressive TNBCs.

Methods

We performed scRNA-seq of all viable cells from 4T1 tumors, immune-depleted stromal cells from 4T1-Thy1.1 tumor, immune-depleted cells from mT3 subcutaneous tumors and fibroblasts isolated from normal mammary fat pads. Tissues were processed to obtain single cell suspensions of cell populations of interest as described before (Hum et al, Cancers 2020; doi.org/10.3390/cancers12030690) and prepared for single cell sequencing using Chromium Single Cell 3ʹ GEM, Library & Gel Bead Kit v3 (10X Genomics, Pleasanton, CA, USA; Catalog no. 1000075) on a 10X Genomics Chromium Controller following manufacturers protocol. scRNA-Seq libraries were sequenced using Illumina NextSeq 500. The Cell Ranger Single-Cell Software Suite (10X Genomics, Pleasanton, CA, USA) was used to perform sample demultiplexing, barcode processing, and single-cell 3′gene counting. Samples were aligned to the mouse genome (mm10) using “cellranger mkfastq” with default parameters. Unique molecular identifier (UMI) counts were generated using “cellranger count”. Further analysis was performed in R using the Seurat package.

Usage notes

Raw gene expression counts are provided for:

all viable cells from 4T1 tumors (4T1_vaibale_raw_counts.txt),
CAFs from 4T1-Thy1.1 tumor (4T1_Thy1.1_CAF_raw.txt),
CAFs from mT3 tumor (MT3_CAF_raw.txt) and
normal mammary fibroblasts (Normal_mammary_fibroblasts_raw.txt).

Funding

Los Alamos National Laboratory, Award: 19-SI-003

Lawrence Livermore National Laboratory, Award: LDRD-19-SI-003, LDRD-17-ER-121

Foundation for the National Institutes of Health, Award: P30CA093373