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Although immune checkpoint and targeted therapies offer remarkable benefits for lung cancer treatment, some patients do not qualify for these regimens or do not exhibit consistent benefit. Provided that lung cancer appears to be driven by transforming growth factor beta signaling, we investigated the single drug potency of Pirfenidone, an approved drug for the treatment of lung fibrosis. Five human lung cancer cell lines and one murine line were investigated for transforming growth factor beta inhibition via Pirfenidone by using flow cytometry, In-Cell western analysis, proliferation assays as well as comprehensive analyses of the transcriptome with subsequent bioinformatics analysis. Overall, Pirfenidone induced cell cycle arrest, down-regulated SMAD expression and reduced proliferation in lung cancer. Furthermore, cell stress pathways and pro-apoptotic signaling may be mediated by reduced expression of Survivin. A murine subcutaneous model was used to assess the in vivo drug efficacy of Pirfenidone and showed reduced tumor growth and increased infiltration of T cells and NK cells. This data warrant further clinical evaluation of Pirfenidone with advanced non-small cell lung cancer. The observed in vitro and in vivo effects point to a substantial benefit for using Pirfenidone to reactivate the local immune response and possible application in conjunction with current immunotherapies.
The lung tumor microenvironment plays a critical role in the tumorigenesis and metastasis of lung cancer, resulting from the crosstalk between cancer cells and microenvironmental cells. Therefore, comprehensive identification and characterization of cell populations in the complex lung structure is crucial for development of novel targeted anti-cancer therapies. Here, a hierarchical clustering approach with multispectral flow cytometry was established to delineate the cellular landscape of murine lungs under steady-state and cancer conditions. Fluorochromes were used multiple times to be able to measure 24 cell surface markers with only 13 detectors, yielding a broad picture for whole-lung phenotyping. Primary and metastatic murine lung tumor models were included to detect major cell populations in the lung, and to identify alterations to the distribution patterns in these models. In the primary tumor models, major altered populations included CD324+ epithelial cells, alveolar macrophages, dendritic cells, and blood and lymph endothelial cells. The number of fibroblasts, vascular smooth muscle cells, monocytes (Ly6C+ and Ly6C–) and neutrophils were elevated in metastatic models of lung cancer. Thus, the proposed clustering approach is a promising method to resolve cell populations from complex organs in detail even with basic flow cytometers.
Background: Breast cancer is the leading cause of cancer-related deaths in women, demanding new treatment options. With the advent of immune checkpoint blockade, immunotherapy emerged as a treatment option. In addition to lymphocytes, tumor-associated macrophages exert a significant, albeit controversial, impact on tumor development. Pro-inflammatory macrophages are thought to hinder, whereas anti-inflammatory macrophages promote tumor growth. However, molecular markers to identify prognostic macrophage populations remain elusive. Methods: We isolated two macrophage subsets, from 48 primary human breast tumors, distinguished by the expression of CD206. Their transcriptomes were analyzed via RNA-Seq, and potential prognostic macrophage markers were validated by PhenOptics in tissue microarrays of patients with invasive breast cancer. Results: Normal human breast tissue contained mainly CD206+ macrophages, while increased relative amounts of CD206− macrophages were observed in tumors. The presence of CD206+ macrophages correlated with a pronounced lymphocyte infiltrate and subsets of CD206+ macrophages, expressing SERPINH1 and collagen 1, or MORC4, were unexpectedly associated with improved survival of breast cancer patients. In contrast, MHCIIhi CD206− macrophages were linked with a poor survival prognosis. Conclusion: Our data highlight the heterogeneity of tumor-infiltrating macrophages and suggest the use of multiple phenotypic markers to predict the impact of macrophage subpopulations on cancer prognosis. We identified novel macrophage markers that correlate with the survival of patients with invasive mammary carcinoma.