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Composition of the immune microenvironment of lung adenocarcinomas
A UMAPs based on the top 20 principal components of all immune single-cell transcriptomes split by tissue type, color-coded by cell cluster; and relative quantification of myeloid and lymphoid cell clusters per tissue type and, for tumor samples, per patient. B Average gene expression of selected marker genes for immune cell clusters, for cell cluster color code see (A). C Module scores of gene signatures related to inflammation and M1/M2 polarization of different macrophage clusters, white and black arrowheads indicate monocyte-derived macrophage clusters 1 and 2, respectively, for cell cluster color code see (A). D Correlation of the relative quantity of selected myeloid immune cell clusters, for patient color code see (G); Spearman’s correlation statistics, linear regression line. E Immunohistochemical staining of CXCL9 and CD123 as markers for monocyte-derived macrophage cluster 2 and plasmacytoid dendritic cells, respectively, quantification of CXCL9+ or CD123+ cells per 0.48 mm², mean ± s.d., n = 10 per patient, for patient color code see (G); Pearson’s correlation statistics and linear regression line using mean values per patient. F Module scores of gene signatures related to cytotoxicity and exhaustion of different CD8+ T cell clusters, white and black arrowheads indicate cell clusters enriched in normal or tumor tissue, respectively, for cell cluster color code see (A). G Correlation of the relative quantity of selected lymphoid and myeloid immune cell clusters, color-coded by patient; Spearman’s correlation statistics, linear regression line.

Composition of the immune microenvironment of lung adenocarcinomas A UMAPs based on the top 20 principal components of all immune single-cell transcriptomes split by tissue type, color-coded by cell cluster; and relative quantification of myeloid and lymphoid cell clusters per tissue type and, for tumor samples, per patient. B Average gene expression of selected marker genes for immune cell clusters, for cell cluster color code see (A). C Module scores of gene signatures related to inflammation and M1/M2 polarization of different macrophage clusters, white and black arrowheads indicate monocyte-derived macrophage clusters 1 and 2, respectively, for cell cluster color code see (A). D Correlation of the relative quantity of selected myeloid immune cell clusters, for patient color code see (G); Spearman’s correlation statistics, linear regression line. E Immunohistochemical staining of CXCL9 and CD123 as markers for monocyte-derived macrophage cluster 2 and plasmacytoid dendritic cells, respectively, quantification of CXCL9+ or CD123+ cells per 0.48 mm², mean ± s.d., n = 10 per patient, for patient color code see (G); Pearson’s correlation statistics and linear regression line using mean values per patient. F Module scores of gene signatures related to cytotoxicity and exhaustion of different CD8+ T cell clusters, white and black arrowheads indicate cell clusters enriched in normal or tumor tissue, respectively, for cell cluster color code see (A). G Correlation of the relative quantity of selected lymphoid and myeloid immune cell clusters, color-coded by patient; Spearman’s correlation statistics, linear regression line.

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Article
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.