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Single-cell RNA sequencing (scRNA-Seq) provides a valuable platform for characterising multicellular ecosystems. Fibroblasts are a heterogeneous cell type involved in many physiological and pathological processes, but remain poorly-characterised. Analysis of fibroblasts is challenging: these cells are difficult to isolate from tissues, and are therefore commonly under-represented in scRNA-seq datasets. Here, we describe an optimised approach for fibroblast isolation from human lung tissues. We demonstrate the potential for this procedure in characterising stromal cell phenotypes using scRNA-Seq, analyse the effect of tissue disaggregation on gene expression, and optimise data processing to improve clustering quality. We also assess the impact of in vitro culture conditions on stromal cell gene expression and proliferation, showing that altering these conditions can skew phenotypes.

Cancer-associated fibroblasts (CAF) remain a poorly characterized, heterogeneous cell population. Here we characterized two previously described tumor-promoting CAF sub-types, smooth muscle actin (SMA)-positive myofibroblasts and senescent fibroblasts, identifying a novel link between the two. Analysis of CAF cultured ex vivo , showed that senescent CAF are predominantly SMA-positive; this was confirmed by immunochemistry in head & neck (HNSCC) and esophageal (EAC) cancers. In vitro , we found that fibroblasts induced to senesce develop molecular, ultrastructural and contractile features typical of myofibroblasts and this is dependent on canonical TGF-β signaling. Similar to TGF-β1-generated myofibroblasts, these cells secrete soluble factors that promote tumor cell motility. However, RNA-sequencing revealed significant transcriptomic differences between the two SMA-positive CAF groups, particularly in genes associated with extracellular matrix (ECM) deposition and organization, which differentially promote tumor cell invasion. Notably, second harmonic generation imaging and bioinformatic analysis of SMA-positive human HNSCC and EAC showed that collagen fiber organization correlates with poor prognosis, indicating that heterogeneity within the SMA-positive CAF population differentially impacts on survival. These results show that non-fibrogenic, SMA-positive myofibroblasts can be directly generated through induction of fibroblast senescence and suggest that senescence and myofibroblast differentiation are closely linked processes.

Collagen structure has been shown to influence tumor cell invasion, metastasis and clinical outcome in breast cancer. However, it remains unclear how it affects other solid cancers. Here we utilized multi-photon laser scanning microscopy and Second Harmonic Generation to identify alterations to collagen fiber structure within the tumor stroma of head & neck, esophageal and colorectal cancers. Image segmentation algorithms were then applied to quantitatively characterize these morphological changes, showing that elongated collagen fibers significantly correlated with poor clinical outcome (Log Rank p < 0.05). We used TGF-β treatment to model fibroblast conversion to smooth muscle actin SMA-positive cancer associated fibroblasts (CAFs) and found that these cells induce the formation of elongated collagen fibers in vivo. However, proteomic/transcriptomic analysis of SMA-positive CAFs cultured ex-vivo showed significant heterogeneity in the expression of genes with collagen fibril organizing gene ontology. Notably, stratifying patients according to stromal SMA-positivity and collagen fiber elongation was found to provide a highly significant correlation with poor survival in all 3 cancer types (Log Rank p ≤ 0.003). In summary, we show that increased collagen fiber length correlates with poor patient survival in multiple tumor types and that only a sub-set of SMA-positive CAFs can mediate the formation of this collagen structure.