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Composition of the stromal microenvironment of lung adenocarcinomas. A UMAPs based on the top 20 principal components of all stromal single-cell transcriptomes split by tissue type, color-coded by cell cluster; and relative quantification of endothelial and fibroblastic/muscle cell clusters per tissue type and, for tumor samples, per patient. B Average gene expression of selected marker genes for stromal cell clusters, for cell cluster color code see (A). C Differentially expressed genes of fibroblastic/muscle cell clusters, maximum top ten genes showed per cell cluster, for cell cluster color code see (A), black arrowheads indicate relevant marker genes of myofibroblast cluster 2 mentioned in the main text. D Mean pathway activity scores of different fibroblastic/muscle cell clusters, mesothelial cells excluded, black arrowheads indicate relevant pathways of myofibroblast clusters 1 and 2 mentioned in the main text. E Correlation of the relative quantity of myofibroblast clusters 1 and 2, color-coded by patient; Spearman's correlation statistics, linear regression line. F Immunohistochemical staining of CTHRC1 as marker for myofibroblast cluster 2 (see also (C)), quantification of proportion of stromal areal covered by CTHRC1+ cells, mean ± s.d., n = 10 per patient, for patient color code see (E); Pearson's correlation statistics and linear regression line using mean values per patient.

Composition of the stromal microenvironment of lung adenocarcinomas. A UMAPs based on the top 20 principal components of all stromal single-cell transcriptomes split by tissue type, color-coded by cell cluster; and relative quantification of endothelial and fibroblastic/muscle cell clusters per tissue type and, for tumor samples, per patient. B Average gene expression of selected marker genes for stromal cell clusters, for cell cluster color code see (A). C Differentially expressed genes of fibroblastic/muscle cell clusters, maximum top ten genes showed per cell cluster, for cell cluster color code see (A), black arrowheads indicate relevant marker genes of myofibroblast cluster 2 mentioned in the main text. D Mean pathway activity scores of different fibroblastic/muscle cell clusters, mesothelial cells excluded, black arrowheads indicate relevant pathways of myofibroblast clusters 1 and 2 mentioned in the main text. E Correlation of the relative quantity of myofibroblast clusters 1 and 2, color-coded by patient; Spearman's correlation statistics, linear regression line. F Immunohistochemical staining of CTHRC1 as marker for myofibroblast cluster 2 (see also (C)), quantification of proportion of stromal areal covered by CTHRC1+ cells, mean ± s.d., n = 10 per patient, for patient color code see (E); Pearson's correlation statistics and linear regression line using mean values per patient.

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Recent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microe...

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... further dissect interpatient variability within the epithelial cell compartment, epithelial transcriptomes were subset and reclustered ( Supplementary Fig. 3A). Clusters were defined as normal or tumor cell clusters, based on tissue origin ( Supplementary Fig. 3B), which was largely congruent with the copy-number status of cells ( Supplementary Fig. 4A, B), and demonstrated a tumor purity >90%. ...
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... further dissect interpatient variability within the epithelial cell compartment, epithelial transcriptomes were subset and reclustered ( Supplementary Fig. 3A). Clusters were defined as normal or tumor cell clusters, based on tissue origin ( Supplementary Fig. 3B), which was largely congruent with the copy-number status of cells ( Supplementary Fig. 4A, B), and demonstrated a tumor purity >90%. Within the normal cell clusters, we found alveolar type 1 and 2, club, ciliated, and even a small cluster of neuroendocrine cells ( Fig. 2A), which were characterized by expression of typical individual marker genes ( [13,14]. ...
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... quantified oncogenic signal strengths by pathway target gene signature expression and found highly variable activities for EGFR, TGFβ, JAK/STAT, Hypoxia, and PI3K signaling across the different patients (Fig. 2E). These signal strengths were largely unrelated to the mitotic activity of tumor epithelial cells (Supplementary Fig. 3C). p53 signaling was significantly reduced in tumors harboring TP53 mutations, whereas pathway activity scores for EGFR and MAPK signaling were not significantly higher in KRAS-mutated compared to KRAS-wildtype tumors (Supplementary Fig. 3D). ...
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... signal strengths were largely unrelated to the mitotic activity of tumor epithelial cells (Supplementary Fig. 3C). p53 signaling was significantly reduced in tumors harboring TP53 mutations, whereas pathway activity scores for EGFR and MAPK signaling were not significantly higher in KRAS-mutated compared to KRAS-wildtype tumors (Supplementary Fig. 3D). ...
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... order to emphasize similarities between tumors, epithelial transcriptomes were embedded in lowdimensional UMAPs (4, 6, 8 instead of 20 dimensions). Here, tumor cells clustered by histological subtype rather than by Supplementary Fig. 3E), and the first principal component (PC1) displayed a gradient along histological grades (Fig. 2F, Supplementary Fig. 3E, F). Interestingly, SCGB3A1 and SCGB3A2 (Fig. 2C, white arrowheads), two genes that were previously associated with lung development [15], were positively correlated with PC1 ( Supplementary Fig. 3G, arrowheads). ...
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... order to emphasize similarities between tumors, epithelial transcriptomes were embedded in lowdimensional UMAPs (4, 6, 8 instead of 20 dimensions). Here, tumor cells clustered by histological subtype rather than by Supplementary Fig. 3E), and the first principal component (PC1) displayed a gradient along histological grades (Fig. 2F, Supplementary Fig. 3E, F). Interestingly, SCGB3A1 and SCGB3A2 (Fig. 2C, white arrowheads), two genes that were previously associated with lung development [15], were positively correlated with PC1 ( Supplementary Fig. 3G, arrowheads). ...
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... tumor cells clustered by histological subtype rather than by Supplementary Fig. 3E), and the first principal component (PC1) displayed a gradient along histological grades (Fig. 2F, Supplementary Fig. 3E, F). Interestingly, SCGB3A1 and SCGB3A2 (Fig. 2C, white arrowheads), two genes that were previously associated with lung development [15], were positively correlated with PC1 ( Supplementary Fig. 3G, arrowheads). Moreover, gene signature scores of normal lung cell types [13] along PC1 showed a strong positive correlation with gene expression profiles of alveolar type 1 and 2 as well as club cells (Fig. 2G). ...
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... this indicates that PC1 reflects the degree of differentiation of tumor epithelial cells. Hence, the top 30 genes positively and negatively correlated with PC1 were defined as an "alveolar/club-like" and "undifferentiated" tumor cell signature, respectively ( Fig. 2F-H, Supplementary Fig. 3G, H). While tumor cells with different degrees of differentiation exhibited no clear differences in mitotic activity ( Supplementary Fig. 3I), we found high pathway activity scores for JAK/STAT, Hypoxia, EGFR and TGFβ signaling in "undifferentiated", and high scores for PI3K signaling in "alveolar/club cell-like" tumor epithelial cells, respectively (Fig. 2H). ...
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... the top 30 genes positively and negatively correlated with PC1 were defined as an "alveolar/club-like" and "undifferentiated" tumor cell signature, respectively ( Fig. 2F-H, Supplementary Fig. 3G, H). While tumor cells with different degrees of differentiation exhibited no clear differences in mitotic activity ( Supplementary Fig. 3I), we found high pathway activity scores for JAK/STAT, Hypoxia, EGFR and TGFβ signaling in "undifferentiated", and high scores for PI3K signaling in "alveolar/club cell-like" tumor epithelial cells, respectively (Fig. 2H). We conclude that tumor epithelial cells of different lung adenocarcinoma patients exhibit transcriptional patterns along a spectrum ranging from undifferentiated to alveolar/club cell-like phenotypes correlating with distinct oncogenic pathway activity. ...
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... subset and analyzed stromal cells from both normal and tumor tissue samples. Different clusters of endothelial and lymphatic endothelial cells, fibroblasts, myofibroblasts and smooth muscle cells and mesothelial cells (Fig. 3A, Supplementary Fig. 6A) were identified by marker genes (Fig. 3B) and gene signatures ( Supplementary Fig. 5A, B) [13,14]. Tumor endothelial cells were mainly represented by clusters 2 and 4 ( Fig. 3A), and showed high expression of angiogenesis markers such as VWA1 and HSPG2, as well as INSR, encoding an endothelial marker protein and ...
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... subset and analyzed stromal cells from both normal and tumor tissue samples. Different clusters of endothelial and lymphatic endothelial cells, fibroblasts, myofibroblasts and smooth muscle cells and mesothelial cells (Fig. 3A, Supplementary Fig. 6A) were identified by marker genes (Fig. 3B) and gene signatures ( Supplementary Fig. 5A, B) [13,14]. Tumor endothelial cells were mainly represented by clusters 2 and 4 ( Fig. 3A), and showed high expression of angiogenesis markers such as VWA1 and HSPG2, as well as INSR, encoding an endothelial marker protein and possible therapeutic target [9] (Supplementary Fig. 6B, ...
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... Different clusters of endothelial and lymphatic endothelial cells, fibroblasts, myofibroblasts and smooth muscle cells and mesothelial cells (Fig. 3A, Supplementary Fig. 6A) were identified by marker genes (Fig. 3B) and gene signatures ( Supplementary Fig. 5A, B) [13,14]. Tumor endothelial cells were mainly represented by clusters 2 and 4 ( Fig. 3A), and showed high expression of angiogenesis markers such as VWA1 and HSPG2, as well as INSR, encoding an endothelial marker protein and possible therapeutic target [9] (Supplementary Fig. 6B, ...
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... the fibroblastic/muscle cell clusters, we detected a shift from fibroblast to myofibroblast cell clusters in tumor tissues (Fig. 3A), which we also observed in an independent dataset ( Supplementary Fig. 7A). Myofibroblast clusters were characterized by expression of both fibroblastic marker genes, such as PDGFRA and LUM, and smooth muscle marker genes, such as MYLK and ACTA2 (Fig. 3B). Notably, myofibroblast cluster 2 was almost exclusively found in tumor tissues ...
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... we detected a shift from fibroblast to myofibroblast cell clusters in tumor tissues (Fig. 3A), which we also observed in an independent dataset ( Supplementary Fig. 7A). Myofibroblast clusters were characterized by expression of both fibroblastic marker genes, such as PDGFRA and LUM, and smooth muscle marker genes, such as MYLK and ACTA2 (Fig. 3B). Notably, myofibroblast cluster 2 was almost exclusively found in tumor tissues while myofibroblast cluster 1 encompassed normal and tumor tissues. Myofibroblast cluster 2 displayed high expression of collagens such as COL3A1, COL5A1, COL5A2 and COL6A3, other matrix proteins such as VCAN, as well as matrix-degrading enzymes such as ...
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... found in tumor tissues while myofibroblast cluster 1 encompassed normal and tumor tissues. Myofibroblast cluster 2 displayed high expression of collagens such as COL3A1, COL5A1, COL5A2 and COL6A3, other matrix proteins such as VCAN, as well as matrix-degrading enzymes such as SULF1 and MMP11, suggesting roles in extracellular matrix remodeling (Fig. 3C, arrowheads). Myofibroblast cluster 2 was also characterized by high activity of TGFβ and JAK/STAT signaling as well as hypoxia-induced pathways ( Fig. 3D), which are known features of cancer-associated myofibroblasts [16,17]. In contrast, myofibroblast cluster 1 exhibited low activities of these pathways. Relative proportions of ...
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... such as COL3A1, COL5A1, COL5A2 and COL6A3, other matrix proteins such as VCAN, as well as matrix-degrading enzymes such as SULF1 and MMP11, suggesting roles in extracellular matrix remodeling (Fig. 3C, arrowheads). Myofibroblast cluster 2 was also characterized by high activity of TGFβ and JAK/STAT signaling as well as hypoxia-induced pathways ( Fig. 3D), which are known features of cancer-associated myofibroblasts [16,17]. In contrast, myofibroblast cluster 1 exhibited low activities of these pathways. Relative proportions of myofibroblast clusters 1 and 2 within the fibroblastic/muscle cell compartment correlated inversely across patients (Fig. 3E). The distribution of myofibroblast ...
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... signaling as well as hypoxia-induced pathways ( Fig. 3D), which are known features of cancer-associated myofibroblasts [16,17]. In contrast, myofibroblast cluster 1 exhibited low activities of these pathways. Relative proportions of myofibroblast clusters 1 and 2 within the fibroblastic/muscle cell compartment correlated inversely across patients (Fig. 3E). The distribution of myofibroblast cluster 2 cells could be validated by immunostaining for the cluster-specific marker CTHRC1 (Fig. 3F, see also Fig. 3C). We conclude that myofibroblasts cluster 1 and 2 represent "normal-like" and "cancer-associated" phenotypes of myofibroblasts, respectively, and either of them can predominate the ...
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... myofibroblast cluster 1 exhibited low activities of these pathways. Relative proportions of myofibroblast clusters 1 and 2 within the fibroblastic/muscle cell compartment correlated inversely across patients (Fig. 3E). The distribution of myofibroblast cluster 2 cells could be validated by immunostaining for the cluster-specific marker CTHRC1 (Fig. 3F, see also Fig. 3C). We conclude that myofibroblasts cluster 1 and 2 represent "normal-like" and "cancer-associated" phenotypes of myofibroblasts, respectively, and either of them can predominate the stromal ...
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... 1 exhibited low activities of these pathways. Relative proportions of myofibroblast clusters 1 and 2 within the fibroblastic/muscle cell compartment correlated inversely across patients (Fig. 3E). The distribution of myofibroblast cluster 2 cells could be validated by immunostaining for the cluster-specific marker CTHRC1 (Fig. 3F, see also Fig. 3C). We conclude that myofibroblasts cluster 1 and 2 represent "normal-like" and "cancer-associated" phenotypes of myofibroblasts, respectively, and either of them can predominate the stromal ...

Citations

... Initially, it seemed that cDC1 was the only DC subset involved in tumor immunity, however a more extensive analysis revealed the presence of other DC subsets [98] and the limited prevalence of cDC1 in human tumors [99]. Additionally, CD8+ T cells are not the only lymphocyte population involved in tumor immunity, and CD4+ T cells are known to be required in many tumor models [31,[100][101][102][103][104]. ...
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... The cluster of fibroblasts was found to be divided into seven known cell types by scRNA-seq in NSCLC (43,54), with COL13A1 + and COL14A1 + fibroblasts being the major fibroblast types in early NSCLC tissues (43). Moreover, myofibroblasts were found to replace fibroblasts in the TME (43,95), which may promote extensive tissue reconstruction (114), angiogenesis (115), and tumor progression (116). Myofibroblasts were characterized by expression of both fibroblastic marker genes, such as PDGFRA and LUM, and smooth muscle marker genes, such as MYLK and ACTA2 (95). ...
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Lung carcinoid tumors, also referred to as pulmonary neuroendocrine tumors or lung carcinoids, are rare neoplasms of the lung with a more favorable prognosis than other subtypes of lung cancer. Still, some patients suffer from relapsed disease and metastatic spread. Several recent single‐cell studies have provided detailed insights into the cellular heterogeneity of more common lung cancers, such as adeno‐ and squamous cell carcinoma. However, the characteristics of lung carcinoids on the single‐cell level are yet completely unknown. To study the cellular composition and single‐cell gene expression profiles in lung carcinoids, we applied single‐cell RNA sequencing to three lung carcinoid tumor samples and normal lung tissue. The single‐cell transcriptomes of carcinoid tumor cells reflected intertumoral heterogeneity associated with clinicopathological features, such as tumor necrosis and proliferation index. The immune microenvironment was specifically enriched in non‐inflammatory monocyte‐derived myeloid cells. Tumor‐associated endothelial cells were characterized by distinct gene expression profiles. A spectrum of vascular smooth muscle cells and pericytes predominated the stromal microenvironment. We found a small proportion of myofibroblasts exhibiting features reminiscent of cancer‐associated fibroblasts. Stromal and immune cells exhibited potential paracrine interactions which may shape the microenvironment via NOTCH, VEGF, TGFβ and JAK/STAT signaling. Moreover, single‐cell gene signatures of pericytes and myofibroblasts demonstrated prognostic value in bulk gene expression data. Here, we provide first comprehensive insights into the cellular composition and single‐cell gene expression profiles in lung carcinoids, demonstrating the non‐inflammatory and vessel‐rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets. This article is protected by copyright. All rights reserved.