Abstract 5084: Characterizing heterogeneity in the cancer-associated fibroblast population in non-small cell lung cancer: Relating phenotype to function
Authors: Sara Waise, Christopher Hanley, Rachel Parker, Matthew Rose-Zerilli, Christian Ottensmeier, Gareth Thomas
Journal: Cancer Research (2018)

Abstract The aim of this work is to examine the heterogeneity in the cancer-associated fibroblast (CAF) population in non-small cell lung cancer through single-cell RNA sequencing. Fresh primary lung tissue was obtained directly from surgery, and the disaggregation process optimised to extract the highest number of fibroblasts (using collagenase P for sixty minutes). Single-cell RNA sequencing was performed using a droplet-barcoded sequencing (Drop-seq) platform. Quality control was performed on the raw sequencing data and the resulting digital gene expression matrix. Initial bioinformatic analysis, including cluster identification, was performed using the Seurat package in R. Subsequent cell type identification and gene set enrichment analysis were carried out with the ToppFun tool and GSEA program respectively. Correlations between the presence of fibroblast subtypes and clinical parameters were analysed using CIBERSORT. Our preliminary analysis of 11 non-small cell lung cancer (NSCLC) tumors and 5 samples of matched non-involved lung revealed the presence of 6 discrete CAF subtypes with differential prognostic impact. Four of the subgroups showed transcriptomic overlap with normal fibroblasts. Of the distinct CAF subtypes, one showed higher expression of genes normally associated with the ‘myofibroblastic' CAF phenotype, including multiple collagens, and was enriched for genes associated with the ‘extracellular structure organisation' gene ontology (GO) term. The second CAF cluster showed higher expression of genes encoding growth factors and regulators of cell growth, with enrichment of genes in the ‘regulation of epithelial cell proliferation' and ‘negative regulation of cell death' GO terms. The remaining four subtypes also showed enrichment of genes in keeping with previously-described fibroblast functions: two subtypes were enriched for genes associated with tissue remodelling, including in the ‘regulation of proteolysis' and ‘regulation of peptidase activity' GO terms. The fifth and sixth clusters showed enrichment for genes in the ‘innate immune response' and ‘angiogenesis' GO terms, respectively. Despite their abundance in most solid cancers, CAF remain a poorly characterised cell population. No single molecular marker identifies all CAF, and it is not yet clear whether different CAF phenotypes exist or whether such subgroups have different functions. Our analysis has identified six discrete CAF subtypes in NSCLC. These subtypes have differential gene set enrichment, suggestive of functional differences. In keeping with this, we found that the CAF subgroups differentially impact on patient prognosis. Identification of CAF subgroups associated with aggressive tumor progression may facilitate the development of more specific stromal targeting strategies. Citation Format: Sara Waise, Christopher Hanley, Rachel Parker, Matthew Rose-Zerilli, Christian Ottensmeier, Gareth Thomas. Characterizing heterogeneity in the cancer-associated fibroblast population in non-small cell lung cancer: Relating phenotype to function [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5084.