Role and Clinical Significance of LncRNA16 in the Malignant Proliferation of Lung Cancer Cells.

The highest mortality rate among cancer patients is lung cancer. A large proportion of cancer patients are lung cancer patients. The incidence rate of lung cancer is the highest in the world. In recent years, long-chain non-coding RNA, or LncRNA, has become more and more closely related to cancer and has gradually attracted the attention of many cancer researchers. LncRNA is the proto-oncogene of cancer. We can find out the cause of cancer and put forward effective methods to inhibit the occurrence of cancer by studying LncRNA. This study aimed to investigate the effect of noncoding long-chain RNA16 on the proliferation and molecular mechanism of lung cancer cells. During the operation, the distance between the excised lung cancer block and the adjacent tissue is 2cm from the corresponding lung cancer block. Then, the total RNA in lung cancer cells and tissues is extracted with a Trizole reagent. Then, the expression profile of LncRNA in three cases of lung cancer and the corresponding adjacent tissue is identified by RNA chip technology. The LncRNA related to proliferation and the expression difference is significant through bioinformatics. The conclusion was that the A549 and H1299 groups of shLncRNA16 could significantly reduce the incidence by 64% and 40% percentage points compared with the experimental group, which indicates that LncRNA16 can be used as a potential treatment target for patients.

Exploring the nucleotide molecular mechanism of compound kushen injection for lung adenocarcinoma based on network pharmacology and molecular docking.

Compound kushen injection is an effective traditional Chinese medicine for the treatment of lung cancer. However, its influence on the survival and prognosis of patients with lung adenocarcinoma patients was less studied; especially its pharmacological mechanism remains to be further elucidated. In the present study, we adopted a network pharmacology (NP)-based approach to screening effective compounds, screening and predicting target genes, analyzing biological functions and pathways, constructing a regulatory network and protein interaction network, and screening the key targets. Moreover, mass survival analysis and molecular docking were conducted. In the end, 35 key compounds and four possible central target genes were screened out, which could be used for the treatment of lung adenocarcinoma and affected the survival and prognosis of patients with lung adenocarcinoma. In addition, their key compounds had good docking affinity. Enrichment analysis showed that CKI might affect the treatment and prognosis of lung adenocarcinoma patients by regulating the PI3K-Akt signaling pathway, TNF signaling pathway, non-small cell lung cancer, Hepatitis C, etc. We discussed the pharmacological mechanisms and potential therapeutic targets of CKI in the treatment of lung adenocarcinoma, which verified the effect of CKI on the prognosis and survival of patients. The present study might promote the further clinical application of CKI and provide a theoretical basis for further experimental studies.

Autophagy characteristics and establishment of autophagy prognostic models in lung adenocarcinoma and lung squamous cell carcinoma.

BACKGROUND: Non-small cell lung cancer (NSCLC), which makes up the majority of lung cancers, remains one of the deadliest malignancies in the world. It has a poor prognosis due to its late detection and lack of response to chemoradiaiton. Therefore, it is urgent to find a new prognostic marker. METHODS: We evaluated biological function and immune cell infiltration in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients from TCGA and GEO databases between different clusters based on autophagy related hub genes. Autophagy scores were used to assess the degree of autophagy in each individual by using component analysis. RESULTS: Three different clusters were obtained. Gene set variation analysis, single-sample gene set enrichment analysis and survive analysis showed differences among these three clusters. We demonstrated that the autophagy score of each patient could predict tumor stage and prognosis. Patients with a high autophagy score had a better prognosis, higher immune infiltration, and were more sensitive to immunotherapy and conventional chemotherapy. CONCLUSION: It was uncovered that autophagy played an irreplaceable role in NSCLC. Quantified autophagy scores for each NSCLC patient would help guide effective treatment strategies.