Background: Chronic obstructive pulmonary disease (COPD) is one of the world’s leading causes of death and a major chronic disease, highly prevalent in the aging population exposed to tobacco smoke and airborne pollutants, which calls for early and useful biomolecular predictors. Roles of noncoding RNAs in COPD have been proposed, however, not many studies have systematically investigated the crosstalk among various transcripts in this context. The construction of RNA functional networks such as lncRNA-mRNA, and circRNA-miRNA-mRNA interaction networks could therefore facilitate our understanding of RNA interactions in COPD. Here, we identified the expression of RNA transcripts in RNA sequencing from COPD patients, and the potential RNA networks were further constructed. Methods: All fresh peripheral blood samples of three patients with COPD and three non-COPD patients were collected and examined for mRNA, miRNA, lncRNA, and circRNA expression followed by qRT-PCR validation. We also examined mRNA expression to enrich relevant biological pathways. lncRNA-mRNA coexpression network and circRNA-miRNA-mRNA network in COPD were constructed. Results: In this study, we have comprehensively identified and analyzed the differentially expressed mRNAs, lncRNAs, miRNAs, and circRNAs in peripheral blood of COPD patients with high-throughput RNA sequencing. 282 mRNAs, 146 lncRNAs, 85 miRNAs, and 81 circRNAs were differentially expressed. GSEA analysis showed that these differentially expressed RNAs correlate with several critical biological processes such as “ncRNA metabolic process”, “ncRNA processing”, “ribosome biogenesis”, “rRNAs metabolic process”, “tRNA metabolic process” and “tRNA processing”, which might be participating in the progression of COPD. RT-qPCR with more clinical COPD samples was used for the validation of some differentially expressed RNAs, and the results were in high accordance with the RNA sequencing. Given the putative regulatory function of lncRNAs and circRNAs, we have constructed the co-expression network between lncRNA and mRNA. To demonstrate the potential interactions between circRNAs and miRNAs, we have also constructed a competing endogenous RNA (ceRNA) network of differential expression circRNA-miRNA-mRNA in COPD. Conclusions: In this study, we have identified and analyzed the differentially expressed mRNAs, lncRNAs, miRNAs, and circRNAs, providing a systematic view of the differentially expressed RNA in the context of COPD. We have also constructed the lncRNA-mRNA co-expression network, and for the first time constructed the circRNA-miRNA-mRNA in COPD. This study reveals the RNA involvement and potential regulatory roles in COPD, and further uncovers the interactions among those RNAs, which will assist the pathological investigations of COPD and shed light on therapeutic targets exploration for COPD.

Over the past decades, low‐dose computed tomography (LD‐CT) screening has been widely used for the early detection of lung cancer. Increasing numbers of indeterminate pulmonary nodules are now being discovered. However, it remains challenging to distinguish malignant from benign pulmonary nodules, especially those considered to be small or ground‐glass (GGN) nodules. Liquid biopsies have been successfully applied in the diagnosis of advanced lung cancer, and the potential value for early detection of lung cancer has made great progress. Recent studies have demonstrated the value of various blood‐based tumor biomarkers in determining the nature of pulmonary nodules, including cell‐free DNA (cfDNA), microRNAs (miRNAs), circulating tumor cells (CTCs) and tumor‐associated autoantibodies (AAbs). In this review, we summarize the latest progress of liquid biopsies, and their potential applications and challenges in the diagnosis of malignant pulmonary nodules.

Cell‐free methylated DNA immunoprecipitation and high‐throughput sequencing (cfMeDIP‐seq) is a new bisulfite‐free technique, which can detect the whole‐genome methylation of blood cell‐free DNA (cfDNA). Using this technique, we identified differentially methylated regions (DMR) of cfDNA between lung tumors and normal controls. Based on the top 300 DMR, we built a random forest prediction model, which was able to distinguish malignant lung tumors from normal controls with high sensitivity and specificity of 91.0% and 93.3% (AUROC curve of 0.963). In summary, we reported a non–invasive prediction model that had good ability to distinguish malignant pulmonary nodules.

Background: Detailed catalog of lung cancer-associated gene mutations provides valuable information for lung cancer diagnosis and treatment. In China, there has never been a wide-ranging study cataloging lung cancer-associated gene mutations. This study aims to reveal a comprehensive catalog of lung cancer gene mutations in china, focusing on EGFR, ALK, KRAS, HER2, PIK3CA, MET, BRAF, HRAS, and CTNNB1 as major targets. Additionally, we also aim to correlate smoking history, gender, and age distribution and pathological types with various types of gene mutations. Patients and Methods: A retrospective data acquisition was conducted spanning 6 years (2013–2018) among all patients who underwent lung cancer surgeries not bronchial or percutaneous lung biopsy at three major tertiary hospitals. Finally, we identified 1,729 patients who matched our inclusion criteria. Results: 1081 patients (62.49%) harbored EGFR mutation. ALK (n = 42, 2.43%), KRAS (n = 201, 11.62%), CTNNB1 (n = 28, 1.62%), BRAF (n = 31, 1.79%), PIK3CA (n = 51, 2.95%), MET (n = 14, 0.81%), HER2 (n = 47, 2.72%), HRAS (n = 3, 0.17%), and other genes(n = 232, 13.4%). Females expressed 55.38% vs. males 44.62% mutations. Among subjects with known smoking histories, 32.82% smokers, 67.15% non-smokers were observed. Generally, 51.80% patients were above 60 years vs. 48.20% in younger patients. Pathological types found includes LUADs 71.11%, SQCCs 1.68%, ASC 0.75%, LCC 0.58%, SCC 0.35%, ACC 0.17%, and SC 0.06%, unclear 25.19%. Conclusion: We offer a detailed catalog of the distribution of lung cancer mutations. Showing how gender, smoking history, age, and pathological types are significantly related to the prevalence of lung cancer in China.

Lung cancer is the most common cause of cancer-related deaths worldwide and is caused by multiple factors, including high-fat diet (HFD). CD36, a fatty acid receptor, is closely associated with metabolism-related diseases, including cardiovascular disease and cancer. However, the role of CD36 in HFD-accelerated non-small-cell lung cancer (NSCLC) is unclear. In vivo, we fed C57BL/6J wild-type (WT) and CD36 knockout (CD36^−/−) mice normal chow or HFD in the presence or absence of pitavastatin 2 weeks before subcutaneous injection of LLC1 cells. In vitro, A549 and NCI-H520 cells were treated with free fatty acids (FFAs) to mimic HFD situation for exploration the underlying mechanisms. We found that HFD promoted LLC1 tumor growth in vivo and that FFAs increased cell proliferation and migration in A549 and NCI-H520 cells. The enhanced cell or tumor growth was inhibited by the lipid-lowering agent pitavastatin, which reduced lipid accumulation. More importantly, we found that plasma soluble CD36 (sCD36) levels were higher in NSCLC patients than those in healthy ones. Compared to that in WT mice, the proliferation of LLC1 cells in CD36^−/− mice was largely suppressed, which was further repressed by pitavastatin in HFD group. At the molecular level, we found that CD36 inhibition, either with pitavastatin or plasmid, reduced proliferation- and migration-related protein expression through the AKT/mTOR pathway. Taken together, we demonstrate that inhibition of CD36 expression by pitavastatin or other inhibitors may be a viable strategy for NSCLC treatment. Graphical abstract 1) Pitavastatin reduces NSCLC progression by inhibiting CD36. 2) Inhibition of CD36 can improve HFD- or FFA-induced NSCLC. 3) AKT/mTOR pathway is involved in CD36-regulated NSCLC. 4) Inhibition of CD36 by pitavastatin or other inhibitors may be a strategy for NSCLC treatment.