scholarly journals Identifying Lung Cancer Cell Markers with Machine Learning Methods and Single-Cell RNA-Seq Data

Life ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 940
Author(s):  
Guo-Hua Huang ◽  
Yu-Hang Zhang ◽  
Lei Chen ◽  
You Li ◽  
Tao Huang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Single Cell ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Computational Method ◽  
High Morbidity ◽  
Small Cell Lung ◽  
Qualitative Classification ◽  
Matthew’S Correlation Coefficient

Non-small cell lung cancer is a major lethal subtype of epithelial lung cancer, with high morbidity and mortality. The single-cell sequencing technique plays a key role in exploring the pathogenesis of non-small cell lung cancer. We proposed a computational method for distinguishing cell subtypes from the different pathological regions of non-small cell lung cancer on the basis of transcriptomic profiles, including a group of qualitative classification criteria (biomarkers) and various rules. The random forest classifier reached a Matthew’s correlation coefficient (MCC) of 0.922 by using 720 features, and the decision tree reached an MCC of 0.786 by using 1880 features. The obtained biomarkers and rules were analyzed in the end of this study.

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 A computational method for the identification of candidate drugs for non-small cell lung cancer

PLoS ONE ◽  
2017 ◽  
Vol 12 (8) ◽  
pp. e0183411
Author(s):  
Lei Chen ◽  
Jing Lu ◽  
Tao Huang ◽  
Yu-Dong Cai
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Computational Method ◽  
Small Cell Lung

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 < 0.001; OS: P < 0.001) and solid nest STAS (RFS: P < 0.001; OS: P < 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 < 0.001; OS: P < 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 Research Progress and Challenges in the Treatment of Central Nervous System Metastasis of Non-Small Cell Lung Cancer

Cells ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2620
Author(s):  
Bin Wang ◽  
Hanfei Guo ◽  
Haiyang Xu ◽  
Hongquan Yu ◽  
Yong Chen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Central Nervous System ◽  
Nervous System ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Research Progress ◽  
High Morbidity ◽  
Small Cell Lung ◽  
Cns Metastasis

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors and has high morbidity and mortality rates. Central nervous system (CNS) metastasis is one of the most frequent complications in patients with NSCLC and seriously affects the quality of life (QOL) and overall survival (OS) of patients, with a median OS of untreated patients of only 1–3 months. There are various treatment methods for NSCLC CNS metastasis, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, which do not meet the requirements of patients in terms of improving OS and QOL. There are still many problems in the treatment of NSCLC CNS metastasis that need to be solved urgently. This review summarizes the research progress in the treatment of NSCLC CNS metastasis to provide a reference for clinical practice.

scholarly journals Synergistic Effect of Network-Based Multicomponent Drugs: An Investigation on the Treatment of Non-Small-Cell Lung Cancer with Compound Liuju Formula

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Xing Su ◽  
Meng Jiang ◽  
Yueping Li ◽  
Jinglin Zhu ◽  
Chunli Zheng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Synergistic Effect ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Target Prediction ◽  
Small Cell ◽  
High Morbidity ◽  
Systems Pharmacology ◽  
Small Cell Lung ◽  
Apoptosis Pathway

Lung cancer is the most common cause of cancer death with high morbidity and mortality, which non-small-cell lung cancer (NSCLC) accounting for the majority. Traditional Chinese Medicine (TCM) is effective in the treatment of complex diseases, especially cancer. However, TCM is still in the conceptual stage. The interaction between different components remains unknown due to its multicomponent and multitarget characteristics. In this study, compound Liuju formula was taken as an example to isolate compounds with synergistic biological activity through systems pharmacology strategy. Through pharmacokinetic evaluation, 37 potentially active compounds were screened out. Meanwhile, 116 targets of these compounds were obtained by combing with the target prediction model. Through network analysis, we found that multicomponent drugs can present a synergistic effect through regulating inflammatory signaling pathway, invasion pathway, proliferation, and apoptosis pathway. Finally, it was confirmed that the bioactive compounds of compound Liuju formula have not only a killing effect on NSCLC tumor cells but also a synergistic effect on inhibiting the secretion of correlative inflammatory mediators, including TNF-α and IL-1β. The systems pharmacology method was applied in this study, which provides a new direction for analyzing the mechanism of TCM.

scholarly journals Publisher Correction: Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing

2018 ◽  
Vol 24 (10) ◽  
pp. 1628-1628 ◽  
Author(s):  
Xinyi Guo ◽  
Yuanyuan Zhang ◽  
Liangtao Zheng ◽  
Chunhong Zheng ◽  
Jintao Song ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Small Cell Lung Cancer ◽  
Single Cell ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Single Cell Sequencing
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