Gene signature driving invasive mucinous adenocarcinoma of the lung

Research Article2 March 2017Open Access Source DataTransparent process Gene signature driving invasive mucinous adenocarcinoma of the lung Minzhe Guo Minzhe Guo Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Department of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH, USA Search for more papers by this author Koichi Tomoshige Koichi Tomoshige Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Michael Meister Michael Meister Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany Search for more papers by this author Thomas Muley Thomas Muley Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany Search for more papers by this author Takuya Fukazawa Takuya Fukazawa Department of General Surgery, Kawasaki Medical School, Okayama, Japan Search for more papers by this author Tomoshi Tsuchiya Tomoshi Tsuchiya Department of Surgical Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan Search for more papers by this author Rebekah Karns Rebekah Karns Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Arne Warth Arne Warth Institute of Pathology, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany Search for more papers by this author Iris M Fink-Baldauf Iris M Fink-Baldauf Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Takeshi Nagayasu Takeshi Nagayasu Department of Surgical Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan Search for more papers by this author Yoshio Naomoto Yoshio Naomoto Department of General Surgery, Kawasaki Medical School, Okayama, Japan Search for more papers by this author Yan Xu Yan Xu Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Marcus A Mall Marcus A Mall Department of Translational Pulmonology, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany Search for more papers by this author Yutaka Maeda Corresponding Author Yutaka Maeda [email protected] orcid.org/0000-0002-9537-3971 Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Minzhe Guo Minzhe Guo Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Department of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH, USA Search for more papers by this author Koichi Tomoshige Koichi Tomoshige Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Michael Meister Michael Meister Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany Search for more papers by this author Thomas Muley Thomas Muley Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany Search for more papers by this author Takuya Fukazawa Takuya Fukazawa Department of General Surgery, Kawasaki Medical School, Okayama, Japan Search for more papers by this author Tomoshi Tsuchiya Tomoshi Tsuchiya Department of Surgical Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan Search for more papers by this author Rebekah Karns Rebekah Karns Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Arne Warth Arne Warth Institute of Pathology, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany Search for more papers by this author Iris M Fink-Baldauf Iris M Fink-Baldauf Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Takeshi Nagayasu Takeshi Nagayasu Department of Surgical Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan Search for more papers by this author Yoshio Naomoto Yoshio Naomoto Department of General Surgery, Kawasaki Medical School, Okayama, Japan Search for more papers by this author Yan Xu Yan Xu Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Marcus A Mall Marcus A Mall Department of Translational Pulmonology, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany Search for more papers by this author Yutaka Maeda Corresponding Author Yutaka Maeda [email protected] orcid.org/0000-0002-9537-3971 Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Author Information Minzhe Guo1,2,‡, Koichi Tomoshige1,‡, Michael Meister3, Thomas Muley3, Takuya Fukazawa4, Tomoshi Tsuchiya5, Rebekah Karns6, Arne Warth7, Iris M Fink-Baldauf1, Takeshi Nagayasu5, Yoshio Naomoto4, Yan Xu1, Marcus A Mall8 and Yutaka Maeda *,1 1Perinatal Institute, Divisions of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA 2Department of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH, USA 3Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany 4Department of General Surgery, Kawasaki Medical School, Okayama, Japan 5Department of Surgical Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan 6Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH, USA 7Institute of Pathology, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany 8Department of Translational Pulmonology, Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany ‡These authors contributed equally to this work *Corresponding author. Tel: +1 513 803 5066; Fax: +1 513 636 7868; E-mail: [email protected] EMBO Mol Med (2017)9:462-481https://doi.org/10.15252/emmm.201606711 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Though invasive mucinous adenocarcinoma of the lung (IMA) is pathologically distinctive, the molecular mechanism driving IMA is not well understood, which hampers efforts to identify therapeutic targets. Here, by analyzing gene expression profiles of human and mouse IMA, we identified a Mucinous Lung Tumor Signature of 143 genes, which was unexpectedly enriched in mucin-producing gastrointestinal, pancreatic, and breast cancers. The signature genes included transcription factors FOXA3, SPDEF, HNF4A, mucins MUC5AC, MUC5B, MUC3, and an inhibitory immune checkpoint VTCN1/B7-H4 (but not PD-L1/B7-H1). Importantly, induction of FOXA3 or SPDEF along with mutant KRAS in lung epithelium was sufficient to develop benign or malignant mucinous lung tumors, respectively, in transgenic mice. FOXA3 and SPDEF induced MUC5AC and MUC5B, while HNF4A induced MUC3 in human mucinous lung cancer cells harboring a KRAS mutation. ChIP-seq combined with CRISPR/Cas9 determined that upstream enhancer regions of the mucin genes MUC5AC and MUC5B, which were bound by SPDEF, were required for the expression of the mucin genes. Here, we report the molecular signature and gene regulatory network driving mucinous lung tumors. Synopsis Invasive mucinous adenocarcinoma of the lung (IMA) is now defined not only pathologically but also at the molecular level. A novel gene IMA signature characterizes human IMA cases that bear KRAS mutations. The immune checkpoint VTCN1/B7-H4 but not PD-L1/B7-H1 correlates with mucinous markers. The anti-mucous transcription factor NKX2-1 induces PD-L1/B7-H1 and suppresses the pro-mucous transcription factors FOXA3, SPDEF, and HNF4A. Distal enhancers bound by SPDEF are required for the expression of MUC5AC and MUC5B. Introduction Lung cancer is the leading cause of cancer death. Lung cancer is pathologically classified into two main types, non-small cell lung cancer (NSCLC, the most common type) and small cell lung cancer (SCLC). Lung adenocarcinoma (LUAD) is the most frequent type of NSCLC followed by lung squamous cell carcinoma (SqCC) and large cell carcinoma (LCC). Invasive mucinous adenocarcinoma of the lung (IMA) comprises ~5–10% of LUAD (estimated approximately 5,000 deaths/year by IMA in the US) whose tumor cells display goblet cell morphology containing abundant intracytoplasmic mucin (Hata et al, 2010; Kunii et al, 2011; Travis et al, 2011). Recent RNA-seq analyses demonstrated that KRAS mutation was the most frequent genetic alteration seen in IMA (40–62%) followed by NRG1 fusion (7–27%; Fernandez-Cuesta et al, 2014; Nakaoku et al, 2014). IMA expresses mucins such as MUC5AC and MUC5B while lacking the transcription factor NKX2-1 (also known as TTF-1; Travis et al, 2011) that normally suppresses those mucin genes (Maeda et al, 2012). Since the majority of IMA carries "undruggable" KRAS mutations, few therapeutics have been identified other than chemotherapy. Determining the molecular mechanisms driving IMA is required to identify novel therapeutic targets. Previously, we and others demonstrated that Kras lung cancer mouse models with reduced expression of Nkx2-1 (KrasG12D; Nkx2-1+/− or KrasG12D; Nkx2-1flox/flox) developed mucinous lung tumors mimicking human IMA (Maeda et al, 2012; Snyder et al, 2013). Independent analyses of gene expression profiles using cDNA microarrays identified 287 genes (KrasG12D;Nkx2-1+/−; Maeda et al, 2012) and 1381 genes (KrasG12D; Nkx2-1flox/flox; Snyder et al, 2013) as genes induced in mucinous lung tumors in the mouse models. However, it remains unknown which genes are indeed expressed in human IMA. In the present study, we analyzed gene expression profiles of human IMA using RNA-seq and determined genes commonly expressed in the mouse models and human IMA as a gene signature for IMA. The signature included potential therapeutic target genes such as the immune checkpoint VTCN1/B7-H4. The uniqueness of the signature was further assessed using RNA-seq data from 230 LUAD specimens from The Cancer Genome Atlas (TCGA; Cancer Genome Atlas Research Network, 2014) and 598 human cancer cell lines from 20 different organs/tissues, including NSCLC cell lines (Klijn et al, 2015). The analysis using the signature and human IMA specimens further revealed that pro-mucous transcription factors FOXA3, SPDEF, and HNF4A in addition to the anti-mucous transcription factor NKX2-1 differentially regulate the expression of mucins and IMA-related genes in human lung cancer cells in vitro. Importantly, induction of FOXA3 or SPDEF along with KRASG12D in lung epithelium was sufficient to develop mucinous lung tumors in vivo. ChIP-seq analysis determined that SPDEF directly bound to the non-coding loci of the mucin genes MUC5AC and MUC5B, two major mucins expressed in the lung. Deletion of the SPDEF-bound regions using CRISPR/Cas9 significantly reduced the expression of the two mucins, indicating that these non-coding regions are functionally indispensable in inducing the expression of mucins in IMA. Here, we report the novel gene signature and gene regulatory mechanisms for IMA. Results Mucinous Lung Tumor Signature is enriched in specific cancer types In order to identify genes that are highly expressed in human IMA, we performed mRNA-seq analysis using RNAs extracted from six human IMA and adjacent normal lung tissues and determined genes differentially expressed in human IMA (Figs 1A and EV1, and Datasets EV1 and EV2). We compared the genes induced in human IMA (Dataset EV2) with the genes induced in mouse mucinous lung tumors (Mouse IMA; Maeda et al, 2012; Snyder et al, 2013; Dataset EV3) and identified 143 genes that were commonly expressed in both mouse and human IMA as a "Mucinous Lung Tumor Signature" (Figs 1B and EV2, red rectangles). In order to assess whether the signature indeed represents gene expression profiles of human IMA, we retrieved the RNA-seq data of nine human IMA and nine normal lung specimens (Dataset EV4) from TCGA (Cancer Genome Atlas Research Network, 2014) and performed Gene Set Enrichment Analysis (GSEA; Subramanian et al, 2005). The signature (141 genes out of the 143 genes since MUC5AC and MUC3A/B were not included in the TCGA datasets) was highly enriched in human IMA (Enrichment Score = 0.81; Fig 1C), confirming that the signature can be used to assess human IMA. Interestingly, the signature selectively clustered the TCGA-human IMA cases that harbored KRAS mutations, which separated the cases harboring other genetic alterations, including fusion genes (Fig 1D and E). These results suggest that this signature represents human IMA cases, especially the ones that harbor a KRAS mutation, which is the most frequent driver mutation in the human IMA. Figure 1. Mucinous lung tumor gene signature for human invasive mucinous adenocarcinoma of the lung (IMA) Shown are differentially expressed genes in human IMA. RNA-seq was performed using six human IMA patient cases (case 1–6) along with adjacent normal lung tissues. 143 genes of the Mucinous Lung Tumor Signature (three red rectangles) are in common between genes expressed in mouse IMA (Maeda et al, 2012; Snyder et al, 2013) and genes induced in human IMA (see Dataset EV2). Gene Set Enrichment Analysis (GSEA) shows that the Mucinous Lung Tumor Signature is significantly enriched in TCGA-human IMA specimens (nine cases) compared to TCGA-normal lung specimens (nine cases). 141 genes out of the 143 genes were used for the analysis since the TCGA LUAD data do not include MUC5AC and MUC3A/B. ES and P were the "Enrichment Score" and "Nominal P-value", respectively, generated by GSEA. Five out of the nine cases of TCGA-human IMA patient cases were highly clustered in 230 TCGA LUAD cases, including IMA and non-IMA cases, based on the Mucinous Lung Tumor Signature of the 141 genes. Top panel, pathology (red indicates IMA cases), driver gene mutations (fusion or mutation), sex, smoking status, and tumor stage are shown in y-axis. X-axis indicates 230 patient cases from the TCGA LUAD datasets. Bottom panel, expression level of the 141 genes in the Mucinous Lung Tumor Signature is shown (y-axis, the 141 genes). X-axis is as described above. The nine human IMA patient cases from the TCGA LUAD datasets expressed the 140 genes out of the 141 genes (TNFSF18 was not expressed). The Mucinous Lung Tumor Signature of the 141 genes clustered the IMA cases harboring KRAS mutation differentially from those harboring fusions and wild-type KRAS. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Taqman qPCR validation of differentially regulated genes in human IMA compared to normal lung tissues Mucin genes (MUC5AC, MUC5B, and MUC3A/B) were significantly induced in human IMA (n = 7) compared to normal lung tissues (n = 6). Transcription factors SPDEF, FOXA3, and HNF4A but not NKX2-1 were significantly induced in human IMA (n = 7) compared to normal lung tissues (n = 6). Immune checkpoint gene VTCN1 but not PD-L1 was significantly induced in human IMA (n = 7) compared to normal lung tissues (n = 6). Data information: See patient information in Dataset EV1. Taqman gene expression qPCR analysis was performed as described in Materials and Methods. Each gene expression was normalized by comparison with the constitutive expression of ACTB (GAPDH was not used for normalization since GAPDH was induced in human IMA compared to normal lung tissue; see Dataset EV2). Results are expressed as mean ± SEM of biological replicates for each group. P < 0.05 versus normal was considered significant (Mann–Whitney test). Download figure Download PowerPoint Click here to expand this figure. Figure EV2. 143 genes that were commonly expressed in both mouse and human IMA constitute the Mucinous Lung Tumor SignatureShown are the 143 genes induced in the two IMA mouse models (Maeda et al, 2012; Snyder et al, 2013) and human IMA. Download figure Download PowerPoint Since mouse IMA is considered to be a lung tumor with gastric differentiation (Snyder et al, 2013), we sought to determine whether the Mucinous Lung Tumor Signature is enriched in human gastric cancers. We retrieved the RNA-seq data of 598 cancer cell lines, including gastric and other cancer cell lines (Dataset EV4; Klijn et al, 2015), assessed the expression of the signature genes in the groups of the cell lines (Fig 2A) and calculated the GSEA enrichment for the signature in different cancer types (Fig 2B). Consistent with a previous report (Snyder et al, 2013), the signature was highly enriched in human stomach and colorectal cancer cells (Enrichment Score = 0.79 and 0.81, respectively). The signature was also highly enriched in human LUAD (Enrichment Score = 0.76), suggesting that human IMA maintains a lung lineage though it is morphologically distinct from non-mucinous LUAD. Unexpectedly, the signature was also highly enriched in human pancreatic and breast cancers (Enrichment Score = 0.78 and 0.73, respectively). Similar to IMA, pancreatic and breast cancers produce mucins (Kufe, 2009). These results suggest that human IMA harbors a unique gene expression profile including not only gastric genes but also other genes expressed in mucin-producing cancers. Figure 2. The Mucinous Lung Tumor Signature is highly enriched in colorectal, stomach, pancreatic, lung (adenocarcinoma; LUAD), and breast cancers Expression of the Mucinous Lung Tumor Signature genes (143 genes) in different cancers is shown. RNA-seq data from different cancers were obtained from multiple cancer cell lines (n = 598, Dataset EV4), which were reported previously (Klijn et al, 2015). Gene expression was measured in RPKM quantile-normalized and log2-transformed. The minimum of log2-transformed values was set to 0. The expression of a signature gene in a tissue group (cancer type) was measured as the average of the log2-transformed gene expression in the cell lines of the tissue group. Hierarchical clustering was performed using Pearson's correlation-based distance and average linkage. Mucinous Lung Tumor Signature enrichment score for different cancers using Gene Set Enrichment Analysis (GSEA) is shown. Using the lymphoid cell lines as control, colorectal, stomach, lung AD, pancreas, breast, urinary bladder, head–neck, lung SqCC, and ovarian cancers were highly enriched with the Mucinous Lung Tumor Signature. Lung_AD: lung adenocarcinoma; Lung_LCC: lung large cell carcinoma; Lung_SqCC: lung squamous cell carcinoma; Lung_SCLC: small cell lung cancer. Download figure Download PowerPoint An immune checkpoint VTCN1 but not PD-L1 is expressed in human IMA Among the signature genes (Figs 1B and EV2, red rectangles), we identified an immune checkpoint VTCN1 (also known as B7-H4). Recent successes on cancer immunotherapy targeting the immune checkpoint PD-1 and/or PD-L1 (also known as B7-H1 or CD274) by therapeutic antibodies indicate that activating the immune system is beneficial for treating NSCLC in patients whose lung tumors express PD-L1 (Herbst et al, 2014; Garon et al, 2015; Hirsch et al, 2016; Smyth et al, 2016). VTCN1 is also expected to be an antibody-mediated therapeutic target for breast cancer (Leong et al, 2015; Smyth et al, 2016). Thus, we further investigated the expression of the immune checkpoints VTCN1 together with PD-L1 in human IMA. The expression of VTCN1 mRNA was higher in human IMA than in normal control lung tissues; however, the expression of PD-L1 mRNA was not induced in human IMA compared to normal control lung tissues (Figs 1A and EV1). The expression of VTCN1 protein was observed in 64% of human IMA, while the expression of PD-L1 protein was not observed in a majority of human IMA (< 10%; Fig 3A and B, and Dataset EV1). A binomial test indicates that the absence of PD-L1 but not that of VTCN1 is significant in human IMA (one-tailed binomial test: P-value = 1.794E-05). Next, we investigated the association of VTCN1 or PD-L1 with genes expressed in human IMA using two RNA-seq datasets from 105 NSCLC cell lines (Klijn et al, 2015) and 230 TCGA LUAD cases (Cancer Genome Atlas Research Network, 2014). 38 genes out of the top 200 VTCN1-highly correlated genes in the 105 NSCLC cell lines were induced in human IMA, while only seven out of the top 200 PD-L1-highly correlated genes in the 105 NSCLC cell lines were induced in human IMA (Fig 3C, left panel and Dataset EV5). A similar association was observed using the 230 TCGA LUAD cases (Fig 3C, right panel and Dataset EV5), suggesting a gene signature associated with VTCN1, rather than with PD-L1, is related to human IMA. An unbiased clustering analysis using the RNA-seq dataset from the 105 NSCLC cell lines indicated that VTCN1 positively correlated with a mucinous marker MUC5B while PD-L1 negatively correlated with HNF4A, another mucinous marker (Fig 3D and E). A similar analysis using the RNA-seq dataset from the 230 TCGA LUAD cases indicated that VTCN1 positively correlated with HNF4A, while PD-L1 negatively correlated with FOXA3 and SPDEF (Fig 3F and G). These results suggest that VTCN1 is a better cancer immunotherapeutic target for human IMA than PD-L1. Figure 3. VTCN1 but not PD-L1 is expressed in human IMA Shown is immunohistochemistry (IHC) detecting VTCN1 but not PD-L1 in human IMA. Alcian blue detects mucus. Scale bar: 50 μm. Insets show higher magnification of regions indicated by arrows. 64% of the human IMA expressed VTCN1 but most of the human IMA did not express PD-L1 as determined by IHC. Left panel, genes highly correlated with VTCN1 or PD-L1 in NSCLC cell lines (n = 105; Klijn et al, 2015) were assessed as to whether they are expressed in human IMA. 38 genes highly correlated with VTCN1 were expressed in human IMA. However, only seven genes highly correlated with PD-L1 were expressed in human IMA. Right panel, likewise, 28 genes highly correlated with VTCN1 in the TCGA LUAD cases (n = 230; Cancer Genome Atlas Research Network, 2014) were expressed in human IMA but only 1 gene highly correlated with PD-L1 was expressed in human IMA. Red indicates genes in the Mucinous Lung Tumor Signature (the 143 genes). Hierarchical clustering of the expression of IMA-related genes and cell type markers in the NSCLC cell lines (n = 105; Klijn et al, 2015). Genes in red color: pro-mucous genes. Genes in green color: anti-mucous genes. VTCN1 but not PD-L1 positively correlates with a mucous gene marker MUC5B in the NSCLC cell lines (n = 105; Klijn et al, 2015). Of note, the anti-mucous transcription factor NKX2-1 was correlated with the pro-mucous transcription factor SPDEF in the 105 human NSCLC cell lines; however, NKX2-1 was not correlated with SPDEF when 41 cell lines that lack the expression of both NKX2-1 and SPDEF (RPKM ≤ 1) were excluded from the calculation, suggesting that the positive correlation was seen due to the large number of the cell lines that lack the expression of both NKX2-1 and SPDEF. Genes in red color: pro-mucous genes. Genes in green color: anti-mucous genes. Hierarchical clustering of the expression of IMA-related genes and cell type markers in the TCGA LUAD cases (n = 230; Cancer Genome Atlas Research Network, 2014). Red indicates specimens with IMA pathology. Genes in red color: pro-mucous genes. Genes in green color: anti-mucous genes. VTCN1 but not PD-L1 positively correlates with a mucinous tumor marker HNF4A in the TCGA LUAD cases (n = 230; Cancer Genome Atlas Research Network, 2014). Overall, VTCN1 but not PD-L1 associates with mucous gene markers. Genes in red color: pro-mucous genes. Genes in green color: anti-mucous genes. Download figure Download PowerPoint NKX2-1 induces PD-L1 in human mucinous lung cancer cells In the analysis using the RNA-seq data from the 105 NSCLC cell lines, PD-L1 positively correlated with NKX2-1 (Fig 3E), a transcription factor absent in human IMA (Travis et al, 2011). Our ChIP-seq and cDNA microarray analyses indicated that ectopic NKX2-1 bound to the locus of PD-L1/PD-L2 (Fig 4A and Appendix Fig S1) and induced the expression of PD-L1 and PD-L2 in mucus-producing A549 human lung carcinoma cells (Fig 4B; Maeda et al, 2012), which was also confirmed at the protein level in A549 cells and other mucus-producing lung cancer cell lines (Fig 4C and D). Next, we assessed whether PD-L1 is expressed in NKX2-1-expressing tumor cells in human NSCLC specimens (Dataset EV1). Among the NKX2-1-positive tumor cases, 29% (20 out of 68) expressed PD-L1 (Fig 4E and F). Among the NKX2-1-negative tumor cases, only 12% (nine out of 72) expressed PD-L1 (Fig 4E and F). These results indicate that NKX2-1 co-localizes with PD-L1 in a significant portion of human NSCLC cells (two-tailed Fisher's exact test: P-value = 2.078E-02). Using immunohistochemistry, it has been shown that IMA lacks the expression of NKX2-1 (Travis et al, 2011). We found that 23% (27 out of 116) of human non-IMA cases expressed PD-L1 (Fig 4G and H), while only 8% (two out of 24) of human IMA cases expressed PD-L1 (Fig 4G and H, excluding non-mucinous tumor cells heterogeneously existing with mucinous tumor cells), suggesting that PD-L1 is rarely expressed in human IMA. In addition, HNF4A (a negative downstream gene of NKX2-1; Maeda et al, 2012) that is expressed in human IMA was negatively correlated with NKX2-1 and PD-L1 in the 105 NSCLC cell lines (Fig 3E) and the 230 TCGA LUAD cases (Fig 3G), further suggesting a negative association of PD-L1 with human IMA. Figure 4. NKX2-1 induces PD-L1 in human mucinous lung cancer cell lines A549 cells were infected with Nkx2-1-expressing lentivirus as previously reported (Maeda et al, 2012). ChIP-seq indicates that NKX2-1 bound to the locus of PD-L1 and PD-L2. PD-L1 and PD-L2 mRNAs were significantly induced by NKX2-1. Results are expressed as mean ± SEM of biological triplicates for each group. P < 0.05 versus control was considered significant (Student's t-test). Gene expression was normalized by comparison with the constitutive expression of GAPDH. Control: control lentivirus; Nkx2-1: Nkx2-1-expressing lentivirus. A549 cells stably expressing Nkx2-1 were developed as described in (A) and (B). Protein expression was confirmed by IB. PD-L1 was detected by antibodies from Cell Signaling (CST), Spring Bioscience (Spring) and Sino Biological (Sino) as described in Materials and Methods. ACTA1 was used as a loading control. Shown is a representative image from three independent experiments. NKX2-1 induced PD-L1 in A549 cells. H2122, Calu-3, and H292 mucus-producing lung cancer cells were infected with control lentivirus or Nkx2-1-expressing lentivirus. Protein expression was confirmed by IB. PD-L1 antibody from Cell Signaling (CST) was used to detect PD-L1 protein. ACTA1 was used as a loading control. Shown is a representative image from two independent experiments. NKX2-1 induced PD-L1 in t