scholarly journals Fragmentation of Small-cell Lung Cancer Regulatory States in Heterotypic Microenvironments

2020 ◽  
Author(s):  
Dylan L. Schaff ◽  
Shambhavi Singh ◽  
Kee-Beom Kim ◽  
Matthew D. Sutcliffe ◽  
Kwon-Sik Park ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Single Cell ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Neuroendocrine Cells ◽  
Fluctuation Analysis ◽  
Alveolar Type ◽  
Small Cell Lung ◽  
Primary Tumors

AbstractSmall-cell lung cancers derive from pulmonary neuroendocrine cells, which have stemlike properties to reprogram into other cell types upon lung injury. It is difficult to uncouple the plasticity of these transformed cells from heritable changes that evolve in primary tumors or select in metastases to distant organs. Approaches to single-cell profiling are also problematic if the required sample dissociation activates injury-like signaling and reprogramming. Here, we defined cell-state heterogeneities in situ through laser capture microdissection-based 10-cell transcriptomics coupled with stochastic-profiling fluctuation analysis. Using labeled cells from a small-cell lung cancer mouse model initiated by neuroendocrine deletion of p53 and Rb, we profiled cell-to-cell transcriptional-regulatory heterogeneity in spheroid cultures and liver colonies seeded intravenously. Fluctuating transcripts in vitro were partly shared with other epithelial-spheroid models, and candidate heterogeneities increased considerably when cells were delivered to the liver. Colonization of immunocompromised animals drove the fractional appearance of alveolar type II-like markers and poised cells for paracrine stimulation from immune cells and hepatocytes. Immunocompetency further exaggerated the fragmentation of tumor states in the liver, yielding mixed stromal signatures evident in bulk sequencing from autochthonous tumors and metastases. We identified dozens of transcript heterogeneities that recur irrespective of biological context; their mapped orthologs brought together observations of murine and human small-cell lung cancer. Candidate heterogeneities recurrent in the liver also stratified primary human tumors into discrete groups not readily explained by molecular subtype. We conclude that heterotypic interactions in the liver and lung are an accelerant for intratumor heterogeneity in small-cell lung cancer.Statement of significanceThe single-cell regulatory heterogeneity of small-cell lung cancer becomes increasingly elaborate in the liver, a common metastatic site for the disease.

scholarly journals Cell-autonomous immune gene expression is repressed in pulmonary neuroendocrine cells and small cell lung cancer

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ling Cai ◽  
Hongyu Liu ◽  
Fang Huang ◽  
Junya Fujimoto ◽  
Luc Girard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Neuroendocrine Cells ◽  
Immune Gene ◽  
Small Cell Lung ◽  
Immune Gene Expression ◽  
Pulmonary Neuroendocrine Cells

AbstractSmall cell lung cancer (SCLC) is classified as a high-grade neuroendocrine (NE) tumor, but a subset of SCLC has been termed “variant” due to the loss of NE characteristics. In this study, we computed NE scores for patient-derived SCLC cell lines and xenografts, as well as human tumors. We aligned NE properties with transcription factor-defined molecular subtypes. Then we investigated the different immune phenotypes associated with high and low NE scores. We found repression of immune response genes as a shared feature between classic SCLC and pulmonary neuroendocrine cells of the healthy lung. With loss of NE fate, variant SCLC tumors regain cell-autonomous immune gene expression and exhibit higher tumor-immune interactions. Pan-cancer analysis revealed this NE lineage-specific immune phenotype in other cancers. Additionally, we observed MHC I re-expression in SCLC upon development of chemoresistance. These findings may help guide the design of treatment regimens in SCLC.

scholarly journals Establishment of a non-small-cell lung cancer-liver metastasis patient-derived tumor xenograft model for the evaluation of patient-tailored chemotherapy

2019 ◽  
Vol 39 (7) ◽  
Author(s):  
Xue Yang ◽  
Gaopei Meng
Keyword(s):  
Lung Cancer ◽  
Liver Metastasis ◽  
Tumor Growth ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Tumor Xenograft ◽  
Small Cell Lung ◽  
Primary Tumors ◽  
Ifn Γ

Abstract In order to optimize patient-tailored chemotherapy, a non-small-cell lung cancer (NSCLC)-liver metastasis patient-derived tumor xenograft (PDTX) model is developed. Computed tomography (CT)-guided NSCLC percutaneous biopsy was subcutaneously inoculated into the flank of non-obese diabetic/severe combined immunodeficiency (NOD/SCID) female mice (PDTX F1) and allowed to reach 500 mm3 volume. Then, the tumors were re-transplanted into Balb/c nude mice and liver metastasis was confirmed (PDTX F2), which were further assigned into doxorubicin (DOX), docetaxel (DTX), and non-treatment control group. H&E staining and Keratin 20 (CK20) staining were applied to determine the consistency of PDTX models and primary tumors. Tumor growth curve, body weight, and the expression of p65 nuclear factor (NF)-κB and the secretion of interferon (IFN)-γ were investigated. The successive transplant procedure can induce the NSCLC-liver metastasis PDTX model, and morphological and structural characteristics of PDTX models (F2) were in accordance with primary tumors. DOX and DTX could delay tumor growth, activate the NF-κB pathway, and promote IFN-γ secretion in the PDTX models. The NSCLC-liver metastasis PDTX model is established and provides a powerful mean to assess chemotherapeutic efficacy.

scholarly journals Imaging Features and Patterns of Metastasis in Non-Small Cell Lung Cancer with RET Rearrangements

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 693 ◽  
Author(s):  
Subba R. Digumarthy ◽  
Dexter P. Mendoza ◽  
Jessica J. Lin ◽  
Marguerite Rooney ◽  
Andrew Do ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Imaging Features ◽  
Small Cell Lung ◽  
Primary Tumors ◽  
Imaging Characteristics ◽  
Metastatic Patterns ◽  
Pre Treatment

Rearranged during transfection proto-oncogene (RET) fusions represent a potentially targetable oncogenic driver in non-small cell lung cancer (NSCLC). Imaging features and metastatic patterns of advanced RET fusion-positive (RET+) NSCLC are not well established. Our goal was to compare the imaging features and patterns of metastases in RET+, ALK+ and ROS1+ NSCLC. Patients with RET+, ALK+, or ROS1+ NSCLC seen at our institution between January 2014 and December 2018 with available pre-treatment imaging were identified. The clinicopathologic features, imaging characteristics, and the distribution of metastases were reviewed and compared. We identified 215 patients with NSCLC harboring RET, ALK, or ROS1 gene fusion (RET = 32; ALK = 116; ROS1 = 67). Patients with RET+ NSCLC were older at presentation compared to ALK+ and ROS1+ patients (median age: RET = 64 years; ALK = 51 years, p < 0.001; ROS = 54 years, p = 0.042) and had a higher frequency of neuroendocrine histology (RET = 12%; ALK = 2%, p = 0.025; ROS1 = 0%, p = 0.010). Primary tumors in RET+ patients were more likely to be peripheral (RET = 69%; ALK = 47%, p = 0.029; ROS1 = 36%, p = 0.003), whereas lobar location, size, and density were comparable across the three groups. RET+ NSCLC was associated with a higher frequency of brain metastases at diagnosis compared to ROS1+ NSCLC (RET = 32%, ROS1 = 10%; p = 0.039. Metastatic patterns were otherwise similar across the three molecular subgroups, with high incidences of lymphangitic carcinomatosis, pleural metastases, and sclerotic bone metastases. RET+ NSCLC shares several distinct radiologic features and metastatic spread with ALK+ and ROS1+ NSCLC. These features may suggest the presence of RET fusions and help identify patients who may benefit from further molecular genotyping.

scholarly journals Sunlight may increase the FDG uptake value in primary tumors of patients with non-small cell lung cancer

2013 ◽  
Vol 5 (3) ◽  
pp. 773-776 ◽  
Author(s):  
HASAN MUTLU ◽  
ABDULLAH BÜYÜKÇELIK ◽  
ESER KAYA ◽  
MUSTAFA KIBAR ◽  
ERTUĞRUL SEYREK ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Primary Tumors ◽  
Fdg Uptake

scholarly journals Gene mutations in primary tumors and corresponding patient-derived xenografts derived from non-small cell lung cancer

2015 ◽  
Vol 357 (1) ◽  
pp. 179-185 ◽  
Author(s):  
Chuncheng Hao ◽  
Li Wang ◽  
Shaohua Peng ◽  
Mengru Cao ◽  
Hongyu Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Gene Mutations ◽  
Small Cell ◽  
Small Cell Lung ◽  
Primary Tumors

scholarly journals Morphological Subtypes of Tumor Spread Through Air Spaces in Non-Small Cell Lung Cancer: Prognostic Heterogeneity and Its Underlying Mechanism

2021 ◽  
Vol 11 ◽  
Author(s):  
Huikang Xie ◽  
Hang Su ◽  
Erjia Zhu ◽  
Chang Gu ◽  
Shengnan Zhao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prospective Study ◽  
Small Cell Lung Cancer ◽  
Single Cell ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Tumor Spread ◽  
Specimen Handling ◽  
Spread Through Air Spaces

BackgroundTumor spread through air spaces (STAS) has three morphologic subtypes: single cells, micropapillary clusters, and solid nests. However, whether their respective clinical significance is similar remains unclear.MethodsWe retrospectively reviewed 803 patients with resected non-small cell lung cancer (NSCLC) from January to December 2009. Recurrence-free survival (RFS) and overall survival (OS) were compared among patients stratified by STAS subtypes. We also performed a prospective study of NSCLC resection specimens to evaluate the influence of a prosecting knife on the presence of STAS subtypes during specimen handling (83 cases).ResultsSTAS was found in 370 NSCLCs (46%), including 47 single cell STAS (13%), 187 micropapillary cluster STAS (50%), and 136 solid nest STAS (37%). STAS-negative patients had significantly better survival than patients with micropapillary cluster STAS (RFS: P &lt; 0.001; OS: P &lt; 0.001) and solid nest STAS (RFS: P &lt; 0.001; OS: P &lt; 0.001), but similar survival compared with those with single cell STAS (RFS: P = 0.995; OS: P = 0.71). Multivariate analysis revealed micropapillary cluster (RFS: P &lt; 0.001; OS: P &lt; 0.001) and solid nest STAS (RFS: P = 0.001; OS: P = 0.003) to be an independent prognostic indicator, but not for single cell STAS (RFS: P = 0.989; OS: P = 0.68). Similar results were obtained in subgroup analysis of patients with adenocarcinoma. The prospective study of NSCLC specimens suggested that 18 cases were considered as STAS false-positive, and most were singe cell pattern (13/18, 72%).ConclusionsSingle cell STAS was the common morphologic type of artifacts produced by a prosecting knife. A precise protocol of surgical specimen handling is required to minimize artifacts as much as possible.

scholarly journals How Mathematical Modeling Could Contribute to the Quantification of Metastatic Tumor Burden Under Therapy: Insights in Immunotherapeutic Treatment of Non-Small Cell Lung Cancer

2020 ◽  
Author(s):  
Pirmin Schlicke ◽  
Christina Kuttler ◽  
Christian Schumann
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Primary Diagnosis ◽  
Small Cell ◽  
Small Cell Lung ◽  
Primary Tumors ◽  
Prognostic Features ◽  
Therapeutic Decisions ◽  
Platinum Based Chemotherapy

Abstract Background: Cancer is one of the leading death causes globally with about 8.2 million deaths per year and an increase in numbers in recent years. About 90% of cancer deaths do not occur due to primary tumors but due to metastases, of which most are not clinically identifiable because of their relatively small size at primary diagnosis and limited technical possibilities. However, therapeutic decisions are formed depending on the existence of metastases and their properties. Therefore non-identified metastases might have huge influence in the treatment outcome. The quantification of clinically visible and invisible metastases is important for the choice of an optimal treatment of the individual patient as it could clarify the burden of non identifiable tumors as well as the future behavior of the cancerous disease. Results: The mathematical model presented in this study gives insights in how this could be achieved, taking into account different treatment possibilities and therefore being able to compare therapy schedules for individual patients with different clinical parameters. The framework was tested on three patients with non-small cell lung cancer, one of the deadliest types of cancer worldwide, and clinical history including platinum-based chemotherapy and PD-L1-targeted immunotherapy. Results yield promising insights into the framework to establish methods to quantify effects of different therapy methods and prognostic features for individual patients already at stage of primary diagnosis.

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