An annual review of the remarkable advances in lung cancer  clinical research in 2019

Cheng, Bo; Xiong, Shan; Li, Caichen; Liang, Hengrui; Zhao, Yi; Li, Jianfu; Shi, Jiang; Ou, Limin; Chen, Zisheng; Peng, Liang; Liang, Wenhua; He, Jianxing

doi:10.21037/jtd.2020.03.11

Cited by 26 publications

(20 citation statements)

References 51 publications

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“…Other known risk factors for lung cancer include exposure to secondhand smoke, mineral, metal dusts, and radon, as well as asbestos, which is the main risk factor for the development of malignant mesothelioma [ 4 ]. With the introduction of screening guidelines and decrease in tobacco use in the United States, the mortality rate for lung cancer has recently decreased by 48% in males and 23% in females [ 5 ], while a significant increase in the LC five-year survival rates by an average of 1.3% a year has been observed in China over the past 12 years [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Molecular Epidemiology of the Main Druggable Genetic Alterations in Non-Small Cell Lung Cancer

Fois

Paliogiannis

Zinellu

et al. 2021

IJMS

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Lung cancer is the leading cause of death for malignancy worldwide. Its molecular profiling has enriched our understanding of cancer initiation and progression and has become fundamental to provide guidance on treatment with targeted therapies. Testing the presence of driver mutations in specific genes in lung tumors has thus radically changed the clinical management and outcomes of the disease. Numerous studies performed with traditional sequencing methods have investigated the occurrence of such mutations in lung cancer, and new insights regarding their frequency and clinical significance are continuously provided with the use of last generation sequencing technologies. In this review, we discuss the molecular epidemiology of the main druggable genetic alterations in non-small cell lung cancer, namely EGFR, KRAS, BRAF, MET, and HER2 mutations or amplification, as well as ALK and ROS1 fusions. Furthermore, we investigated the predictive impact of these alterations on the outcomes of modern targeted therapies, their global prognostic significance, and their mutual interaction in cases of co-occurrence.

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Section: Introductionmentioning

confidence: 99%

Molecular Epidemiology of the Main Druggable Genetic Alterations in Non-Small Cell Lung Cancer

Fois

Paliogiannis

Zinellu

et al. 2021

IJMS

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“…We contend that the expanded concept of lung cancer screening may have resulted in increased numbers of lung cancer patients detected at earlier stages or with treatable disease 39 . Also, drastic improvements in treatments such as immunotherapy in the last decade may have increased the number of patients indicated for treatment 40 . Furthermore, as our survey was performed in outpatient clinics of secondary or tertiary hospitals, the patients enrolled in our study may have been more frequently followed-up and adhered to treatment.…”

Section: Discussionmentioning

confidence: 99%

Awareness and Use of Complementary and Alternative Medicine in Korean Lung Cancer Patients

Choi

Chung

et al. 2021

Tuberc Respir Dis

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Background Complementary and alternative medicine (CAM) has been used frequently, and its use continues to increase in lung cancer patients, despite insufficient scientific of its efficacy. To investigate this situation, we analyzed the current awareness and use of CAM in Korean lung-cancer patients. Methods This prospective survey–based study was performed at seven medical centers in South Korea between August and October 2019. The survey assessed general patient characteristics and the awareness and use of CAM. We analyzed differences in the clinical parameters of patients aware and not aware of CAM and of CAM non-users and users. Results Of the 434 patients included in this study, 68.8% responded that they were aware of CAM and 30.9% said they had experienced it. In univariate analysis, the patients aware of CAM were younger with poor performance status, had advanced-stage lung cancer, received more systemic therapy, and received concurrent chemoradiation therapy (CCRT). By multiple logistic regression, younger age, poor performance status, advanced stage, and prior CCRT were identified as independent risk factors for CAM awareness. There were no significant differences in the general characteristics and cancer-associated clinical parameters of CAM non-users and users. Conclusion Specific clinical parameters were associated with patients’ awareness of CAM, although there were no significantly different characteristics between CAM users and non-users.

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“…Lung cancer is the most common malignant tumour, with the highest cancer-related mortality rate (22%) 19 and a ve-year overall survival rate of approximately 15% 1 . For these reasons, lung cancer has become of major interest in clinical research 20 . The two main hystotypes of lung cancer include nonsmall cell lung cancer (NSCLC) (85%) and small cell lung cancer (SCLC) (15%).…”

Section: Discussionmentioning

confidence: 99%

Identification of Hub Genes, Modules and Metabolic Pathways Associated With Lung Adenocarcinoma: A System Biology Approach

Roudi¹,

Beikzadeh²,

Roviello³

et al. 2020

Preprint

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Lung cancer is the most common and fatal malignant tumour worldwide with a five‐year overall survival rate of only 15%. Lung adenocarcinoma (LUAD) is a heterogeneous disease. The use of microarray datasets along with bioinformatics knowledge might help to clarify the expression profile of cancer, molecular markers for the initial screening of tumour and the underlying biological mechanisms. The present study is designed to identify differential expression genes and molecular mechanisms of LUAD compared to normal lung tissues using systems biology approaches.Methods Four GSE datasets (GSE75037, GSE63459, GSE32863 and GSE10072) were selected from the Gene Expression Omnibus (GEO) database. Data processing and meta-analysis were performed using the R statistical programming language, The differentially expressed genes (DEGs) associated with each stage were obtained. The common and unique DEGs between stages of LUAD and adjacent normal lung tissues were initiated by Venny tool. Common genes, including upregulated and downregulated genes, were then analyzed to a STRING database to obtain protein-protein interaction (PPI). STRING output was analyzed by MCODE and CytoHubba applications of Cytoscape to identify modules of co-expression and hub genes, respectively.Results The shared upregulated and downregulated DEGs among LUAD stages were 22 and 140 genes, respectively, when compared to normal lung tissues. Unique genes for each stage were also identified. The hub genes were PECAM1, TEK, CDH5, VWF and ANGPT1. Most of the top cluster genes were enriched for Gα(s) signalling events, GPCR ligand binding, class B/2 (Secretin family receptors), platelet activation, signalling and aggregation in the main three co-expression clusters. Most of the shared genes (16 genes) were enriched in the metabolic pathway of hemostasis. Meaningful signaling pathways for unique genes were found at each stage.Conclusions In the present study main three co-expression clusters, metabolic pathways and biological processes were identified to understand mechanisms underlying LUAD pathogenesis, development and progression at different stages. Unique upregulated and downregulated DEGs at each stage were identified with FERMT1 and SIX1 as specific early-stage diagnostic biomarkers for stage IB and IIB. 5 hub genes were observed, including PECAM1, TEK, CDH5, vWF and ANGPT1 which might be crucial for the onset and progression of LUAD.

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An annual review of the remarkable advances in lung cancer clinical research in 2019

Cited by 26 publications

References 51 publications

Molecular Epidemiology of the Main Druggable Genetic Alterations in Non-Small Cell Lung Cancer

Molecular Epidemiology of the Main Druggable Genetic Alterations in Non-Small Cell Lung Cancer

Awareness and Use of Complementary and Alternative Medicine in Korean Lung Cancer Patients

Identification of Hub Genes, Modules and Metabolic Pathways Associated With Lung Adenocarcinoma: A System Biology Approach

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