Abstract 909: Single-cell transcriptomic profiling of non-small cell lung cancer uncovers inter- and intracell population structure across TCGA lung adenocarcinoma and lung squamous cancer subtypes

2019 ◽  
Author(s):  
Kofi E. Gyan ◽  
Aditya Deshpande ◽  
Shaham Beg ◽  
Huasong Tian ◽  
Joel Rosiene ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Population Structure ◽  
Lung Adenocarcinoma ◽  
Small Cell Lung Cancer ◽  
Single Cell ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cancer Subtypes ◽  
Squamous Cancer

Pemetrexed-induced severe rhabdomyolysis in lung cancer: A case report

2018 ◽  
Vol 25 (8) ◽  
pp. 2007-2009 ◽  
Author(s):  
Kevin Sullivan ◽  
Chung-Shien Lee
Keyword(s):  
Lung Cancer ◽  
Case Report ◽  
Lung Adenocarcinoma ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

Pemetrexed is an antifolate metabolite used to treat non-small cell lung cancer in the adjuvant and advanced setting. It is commonly known to cause rash, diarrhea, fatigue, mucositis, and myelosuppression. We report a case of a patient receiving adjuvant cisplatin and pemetrexed for non-small cell lung adenocarcinoma and experienced severe rhabdomyolysis.

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 Identifying Cross-Scale Associations between Radiomic and Pathomic Signatures of Non-Small Cell Lung Cancer Subtypes: Preliminary Results

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3663
Author(s):  
Charlems Alvarez-Jimenez ◽  
Alvaro A. Sandino ◽  
Prateek Prasanna ◽  
Amit Gupta ◽  
Satish E. Viswanath ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Density ◽  
Squamous Cell ◽  
Cell Lung Cancer ◽  
Ct Images ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cancer Subtypes ◽  
Initial Results

(1) Background: Despite the complementarity between radiology and histopathology, both from a diagnostic and a prognostic perspective, quantitative analyses of these modalities are usually performed in disconnected silos. This work presents initial results for differentiating two major non-small cell lung cancer (NSCLC) subtypes by exploring cross-scale associations between Computed Tomography (CT) images and corresponding digitized pathology images. (2) Methods: The analysis comprised three phases, (i) a multi-resolution cell density quantification to identify discriminant pathomic patterns for differentiating adenocarcinoma (ADC) and squamous cell carcinoma (SCC), (ii) radiomic characterization of CT images by using Haralick descriptors to quantify tumor textural heterogeneity as represented by gray-level co-occurrences to discriminate the two pathological subtypes, and (iii) quantitative correlation analysis between the multi-modal features to identify potential associations between them. This analysis was carried out using two publicly available digitized pathology databases (117 cases from TCGA and 54 cases from CPTAC) and a public radiological collection of CT images (101 cases from NSCLC-R). (3) Results: The top-ranked cell density pathomic features from the histopathology analysis were correlation, contrast, homogeneity, sum of entropy and difference of variance; which yielded a cross-validated AUC of 0.72 ± 0.02 on the training set (CPTAC) and hold-out validation AUC of 0.77 on the testing set (TCGA). Top-ranked co-occurrence radiomic features within NSCLC-R were contrast, correlation and sum of entropy which yielded a cross-validated AUC of 0.72 ± 0.01. Preliminary but significant cross-scale associations were identified between cell density statistics and CT intensity values using matched specimens available in the TCGA cohort, which were used to significantly improve the overall discriminatory performance of radiomic features in differentiating NSCLC subtypes (AUC = 0.78 ± 0.01). (4) Conclusions: Initial results suggest that cross-scale associations may exist between digital pathology and CT imaging which can be used to identify relevant radiomic and histopathology features to accurately distinguish lung adenocarcinomas from squamous cell carcinomas.

scholarly journals Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Fei Long ◽  
Jia-Hang Su ◽  
Bin Liang ◽  
Li-Li Su ◽  
Shu-Juan Jiang
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Expression Patterns ◽  
Small Cell ◽  
Normal Lung ◽  
Specific Gene ◽  
Small Cell Lung ◽  
Cancer Subtypes ◽  
Gene Modules

Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

Synchronous Bilateral Retinal Metastases from Lung Adenocarcinoma

2005 ◽  
Vol 91 (3) ◽  
pp. 287-289 ◽  
Author(s):  
Antonio Rossi ◽  
Andrea Manto ◽  
Paolo Maione ◽  
Cesare Gridelli
Keyword(s):  
Lung Cancer ◽  
Central Nervous System ◽  
Lung Adenocarcinoma ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Adrenal Glands ◽  
Palliative Radiotherapy ◽  
Small Cell ◽  
Small Cell Lung ◽  
Heavily Pretreated

Hematogenous retinal metastases from non-small cell lung cancer are rare, and are even more uncommonly observed bilaterally. Non-small cell lung cancer usually metastasizes to the liver, adrenal glands, lung, bone, central nervous system, and kidney. We report the case of a 41-year-old male patient with advanced lung adenocarcinoma heavily pretreated with polychemotherapy and palliative radiotherapy up to June 2003, when synchronous bilateral retinal metastases were diagnosed. The patient's prognosis was worsened by the onset of the retinal metastases and he died three months later.

TGF-beta specifically enhances the metastatic attributes of murine lung adenocarcinoma: implications for human non-small cell lung cancer

2013 ◽  
Vol 30 (8) ◽  
pp. 993-1007 ◽  
Author(s):  
Paula Fernanda Vázquez ◽  
María José Carlini ◽  
María Cecilia Daroqui ◽  
Lucas Colombo ◽  
Mercedes Liliana Dalurzo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Tgf Beta ◽  
Small Cell Lung ◽  
Murine Lung

scholarly journals The Prognostic Value of Preoperative Serum Tumor Markers in Non-Small Cell Lung Cancer Varies With Radiological Features and Histological Types

2021 ◽  
Vol 11 ◽  
Author(s):  
Haiqing Chen ◽  
Fangqiu Fu ◽  
Yue Zhao ◽  
Haoxuan Wu ◽  
Hong Hu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Small Cell Lung Cancer ◽  
Tumor Markers ◽  
Cell Lung Cancer ◽  
Carbohydrate Antigen ◽  
Small Cell ◽  
Small Cell Lung ◽  
Serum Tumor Markers ◽  
Preoperative Serum

ObjectivesTo assess the association between common-used serum tumor markers and recurrence of lung adenocarcinoma and squamous cell carcinoma separately and determine the prognostic value of serum tumor markers in lung adenocarcinoma featured as ground glass opacities.MethodsA total of 2,654 non-small cell lung cancer patients undergoing surgical resection between January 2008 and September 2014 were analyzed. The serum levels of carcinoma embryonic antigen (CEA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153) and carbohydrate antigen 199 (CA199) were tested preoperatively. Survival analyses were performed with COX proportional hazard regression.ResultsAmong patients with lung adenocarcinoma, elevated preoperative serum CEA(HR=1.246, 95%CI:1.043-1.488, P=0.015), CYFRA21-1(HR=1.209, 95%CI:1.015-1.441, P=0.034) and CA125(HR=1.361, 95%CI:1.053-1.757, P=0.018) were significantly associated with poorer recurrence free survival (RFS). Elevated preoperative serum CA199 predicted worse RFS in patients diagnosed with lung squamous cell carcinoma (HR=1.833, 95%CI: 1.216-2.762, P=0.004). Preoperative serum CYFRA21-1(HR=1.256, 95%CI:1.044-1.512, P=0.016) and CA125(HR=1.373, 95%CI: 1.050-1.795, P=0.020) were independent prognostic factors for patients with adenocarcinoma presenting as solid nodules while serum CEA (HR=2.160,95%CI:1.311-3.558, P=0.003) and CA125(HR=2.475,95%CI:1.163-5.266, P=0.019) were independent prognostic factors for patients with adenocarcinoma featured as ground glass opacities.ConclusionsThe prognostic significances of preoperative serum tumor markers in non-small cell lung cancer were associated with radiological features and histological types.

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