Defining the Activated Fibroblast Population in Lung Fibrosis Using Single-Cell Sequencing.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disorder driven by unrelenting extracellular matrix deposition. Fibroblasts are recognized as the central mediators of extracellular matrix production in IPF; however, the characteristics of the underlying fibroblast cell populations in IPF remain poorly understood. Here, we use an unbiased single-cell RNA sequencing analysis of a bleomycin-induced pulmonary fibrosis model to characterize molecular responses to fibrotic injury. Lung cells were isolated on Day 11 to capture emerging fibrosis and gene expression was analyzed by three complementary techniques, which, together, generated a 49-gene signature that defined an activated subpopulation of fibroblasts. However, none of the identified genes were specific to the activated cells or to the disease setting, implying that the activated fibroblasts are not uniquely defined, but exhibit a similar, yet amplified, gene expression pattern to control cells. Our findings have important implications for fibrosis research, including: 1) defining myofibroblasts with any single marker will fail to capture much of the underlying biology; 2) fibroblast activation is poorly correlated with expression of transforming growth factor-ß pathway genes; 3) single-cell analysis provides insight into the mechanism of action of effective therapies (nintedanib); 4) early events in lung fibrosis need not involve significant changes in fibroblast number; populations that do increase in number, such as macrophages, dendritic cells, and proliferating myeloid cells, may merit closer examination for their role in pathogenesis.

Methylation-mediated BMPER expression in fibroblast activation in vitro and lung fibrosis in mice in vivo.

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease. Although the pathogenesis is poorly understood, evidence suggests that genetic and epigenetic alterations, such as DNA methylation, may play a key role. Bone morphogenetic proteins (BMPs) are members of the transforming growth factor-ß (TGF-ß) superfamily and are important regulators in IPF. Here we identified BMP endothelial cell precursor-derived regulator (BMPER) as a key regulator of fibroblast activation. BMPER is a secreted glycoprotein that binds directly to BMPs and may regulate TGF-ß/BMP signaling, but its role in lung fibrosis is not clear. BMPER is highly expressed in human IPF lung fibroblasts compared to normal lung fibroblasts. Demethylation agent 5'-azacytidine decreased BMPER expression in fibroblasts, and attenuated the invasion and migration of IPF lung fibroblasts. Furthermore, siRNA-mediated reduction of BMPER in the human lung fibroblasts impaired cell migration and invasion. 5'-azacytidine treatment additionally regulated BMPER expression and reduced lung fibrosis in mice in vivo. These findings demonstrate that methylation of specific genes in fibroblasts may offer a new therapeutic strategy for IPF by modulating fibroblast activation.

ASSIGN: context-specific genomic profiling of multiple heterogeneous biological pathways.

MOTIVATION: Although gene-expression signature-based biomarkers are often developed for clinical diagnosis, many promising signatures fail to replicate during validation. One major challenge is that biological samples used to generate and validate the signature are often from heterogeneous biological contexts-controlled or in vitro samples may be used to generate the signature, but patient samples may be used for validation. In addition, systematic technical biases from multiple genome-profiling platforms often mask true biological variation. Addressing such challenges will enable us to better elucidate disease mechanisms and provide improved guidance for personalized therapeutics. RESULTS: Here, we present a pathway profiling toolkit, Adaptive Signature Selection and InteGratioN (ASSIGN), which enables robust and context-specific pathway analyses by efficiently capturing pathway activity in heterogeneous sets of samples and across profiling technologies. The ASSIGN framework is based on a flexible Bayesian factor analysis approach that allows for simultaneous profiling of multiple correlated pathways and for the adaptation of pathway signatures into specific disease. We demonstrate the robustness and versatility of ASSIGN in estimating pathway activity in simulated data, cell lines perturbed pathways and in primary tissues samples including The Cancer Genome Atlas breast carcinoma samples and liver samples exposed to genotoxic carcinogens. AVAILABILITY AND IMPLEMENTATION: Software for our approach is available for download at: http://www.bioconductor.org/packages/release/bioc/html/ASSIGN.html and https://github.com/wevanjohnson/ASSIGN.

Genomic pathway analysis reveals that EZH2 and HDAC4 represent mutually exclusive epigenetic pathways across human cancers.

BACKGROUND: Alterations in epigenetic marks, including methylation or acetylation, are common in human cancers. For many epigenetic pathways, however, direct measures of activity are unknown, making their role in various cancers difficult to assess. Gene expression signatures facilitate the examination of patterns of epigenetic pathway activation across and within human cancer types allowing better understanding of the relationships between these pathways. METHODS: We used Bayesian regression to generate gene expression signatures from normal epithelial cells before and after epigenetic pathway activation. Signatures were applied to datasets from TCGA, GEO, CaArray, ArrayExpress, and the cancer cell line encyclopedia. For TCGA data, signature results were correlated with copy number variation and DNA methylation changes. GSEA was used to identify biologic pathways related to the signatures. RESULTS: We developed and validated signatures reflecting downstream effects of enhancer of zeste homolog 2(EZH2), histone deacetylase(HDAC) 1, HDAC4, sirtuin 1(SIRT1), and DNA methyltransferase 2(DNMT2). By applying these signatures to data from cancer cell lines and tumors in large public repositories, we identify those cancers that have the highest and lowest activation of each of these pathways. Highest EZH2 activation is seen in neuroblastoma, hepatocellular carcinoma, small cell lung cancer, and melanoma, while highest HDAC activity is seen in pharyngeal cancer, kidney cancer, and pancreatic cancer. Across all datasets studied, activation of both EZH2 and HDAC4 is significantly underrepresented. Using breast cancer and glioblastoma as examples to examine intrinsic subtypes of particular cancers, EZH2 activation was highest in luminal breast cancers and proneural glioblastomas, while HDAC4 activation was highest in basal breast cancer and mesenchymal glioblastoma. EZH2 and HDAC4 activation are associated with particular chromosome abnormalities: EZH2 activation with aberrations in genes from the TGF and phosphatidylinositol pathways and HDAC4 activation with aberrations in inflammatory and chemokine related genes. CONCLUSION: Gene expression patterns can reveal the activation level of epigenetic pathways. Epigenetic pathways define biologically relevant subsets of human cancers. EZH2 activation and HDAC4 activation correlate with growth factor signaling and inflammation, respectively, and represent two distinct states for cancer cells. This understanding may allow us to identify targetable drivers in these cancer subsets.

SIRT1 pathway dysregulation in the smoke-exposed airway epithelium and lung tumor tissue.

Cigarette smoke produces a molecular field of injury in epithelial cells lining the respiratory tract. However, the specific signaling pathways that are altered in the airway of smokers and the signaling processes responsible for the transition from smoking-induced airway damage to lung cancer remain unknown. In this study, we use a genomic approach to study the signaling processes associated with tobacco smoke exposure and lung cancer. First, we developed and validated pathway-specific gene expression signatures in bronchial airway epithelium that reflect activation of signaling pathways relevant to tobacco exposure, including ATM, BCL2, GPX1, NOS2, IKBKB, and SIRT1. Using these profiles and four independent gene expression datasets, we found that SIRT1 activity is significantly upregulated in cytologically normal bronchial airway epithelial cells from active smokers compared with nonsmokers. In contrast, this activity is strikingly downregulated in non-small cell lung cancer. This pattern of signaling modulation was unique to SIRT1, and downregulation of SIRT1 activity is confined to tumors from smokers. Decreased activity of SIRT1 was validated using genomic analyses of mouse models of lung cancer and biochemical testing of SIRT1 activity in patient lung tumors. Together, our findings indicate a role of SIRT1 in response to smoke and a potential role in repressing lung cancer. Furthermore, our findings suggest that the airway gene expression signatures derived in this study can provide novel insights into signaling pathways altered in the "field of injury" induced by tobacco smoke and thus may impact strategies for prevention of tobacco-related lung cancer.