Colorectal cancer interleukin-10 blockade scRNA-seq
Data files
Jun 01, 2022 version files 73.57 GB
Abstract
Objective: PD-1 checkpoint inhibition and adoptive cellular therapy have limited success in patients with microsatellite stable colorectal cancer liver metastases (CRLM). We demonstrate that interleukin-10 (IL-10) blockade enhances endogenous T cell and chimeric antigen receptor T (CAR-T) cell anti-tumor function in CRLM slice cultures.
Design: We created organotypic slice cultures from human CRLM (n = 38) and tested the anti-tumor effects of a neutralizing antibody against IL-10 (αIL-10). We evaluated slice cultures with single and multiplex immunohistochemistry, in situ hybridization, single cell RNA sequencing, and time-lapse fluorescent microscopy. In addition, we studied the effects of αIL-10 on carcinoembryonic antigen (CEA)-specific CAR-T cells exogenously administered to both human CRLM slice cultures and a CRLM murine model.
Results: There was little effect of PD-1 blockade in CRLM slice cultures. In contrast, αIL-10 generated 1.8-fold increase in T cell-mediated carcinoma cell death, and increased proportion of CD8+ T cells and inflammatory polarization of macrophages. In addition to effects on endogenous immune cells in human CRLM, αIL-10 also rescued murine CAR-T cell proliferation and cytotoxicity from myeloid cell-mediated immunosuppression. In human CRLM slices, αIL-10 dramatically improved CEA-specific CAR-T cell cytotoxicity, generating nearly 70% carcinoma apoptosis across multiple human tumors. We saw a less dramatic, but similar effect of pretreatment of CAR-T cells with an IL-10 receptor blocking antibody, demonstrating that IL-10 inhibits CAR-T function in the CRLM tumor microenvironment.
Conclusion: Neutralizing the effects of IL-10 in human CRLM has therapeutic potential as a stand-alone treatment and to augment the function of adoptively transferred CAR-T cells.
Methods
Following surgical resection of CRLM specimens greater than 2 cm in diameter, sterile 6 mm tumor tissue cores were punch biopsied and immediately placed in BELZER-UW solution on ice. Within hours, cores were cut into 250 μm thick slices by vibratome and placed with media onto Millicell Cell Culture Inserts in a 24-well cell culture plate. Tumor slices were treated with anti-IL-10 antibody (20 µg/mL, #501407, Biolegend), with FOLFOX (1 µg/ml 5-Fluorouracil in combination with 1 µg/ml oxaliplatin) or or with FOLFIRI (1 µg/ml 5-Fluorouracil in combination with 2 µg/ml irinotecan). Control group consisted of slices treated with 0.2% DMSO in medium.
The dose of anti-IL-10 was chosen based upon a dose titration experiment using 5, 10, and 20 µg/ml concentrations of antibody, showing a maximal effect at 20 µg/ml.
For single-cell analysis, tumor slices were dissociated using the MACS Tumor Dissociation Kit according to the Miltenyi Biotec “dissociation of soft tumors” protocol. Cells were processed by 10xGenomics Chromium using the single-cell 3' RNA version 2 protocol. RNAseq libraries were sequenced on the NextSeq500 instrument for 150 cycles (26 bp for Read 1 and 124 bp for Read 2). Reads were aligned to the human genome (GRCh38) and quantified using the Cell Ranger version 2.0 with default settings. The data from two tumors treated with anti-IL-10R was combined with the data of Jabbari et al. (2020) from eight tumors treated with FOLFOX/FOLFIRI available at <https://doi.org/10.5061/dryad.pvmcvdngt>. Gene expression data was aggregated and saved as a single AnnData object in HDF5 format (H5AD).
For bulk tumor analysis, RNA was extracted from slices using Qiagen RNEasy kit per the manufacturer’s instructions. Samples were submitted to the Northwest Genomics Center for sequencing on a NovaSeq6000 instrument. Demultiplexed, unaligned BAM files were produced by Picard ExtractIlluminaBarcodes and IlluminaBasecallsToSam were converted to FASTQ format using SamTools bam2fq (v1.4). Sequence read and base quality was checked using the FASTX-toolkit (v0.0.13). Sequences were aligned to GRCh38 with reference transcriptome GENCODE release 29 using STAR. Gene level expression quantification was generated with RNA-SeQC (v2.3.3) and RSEM (v1.3.1). RPKM and TPM for transcript isoforms were quantified on the merged lane-level data with RSEM (v1.3.1). Gene-level RPKMs were quantified with RNA-SeQC (v2.3.3) on a standard collapsed reference annotation.
Usage notes
Bulk RNAseq alignments and gene expression tables are contained in gzipped archives (sample.tar.gz). Single-cell RNAseq data is contained in an H5AD file that can be read, analyzed, and converted using ScanPy (https://scanpy.readthedocs.io) with its "read_h5ad" function. We also provide a CSV files (sample_identification_singlecell.csv and sample_identification_bulk.csv) with sample and treatment information.