A Mechanism Exploration for the Yi-Fei-San-Jie Formula against Non-Small-Cell Lung Cancer Based on UPLC-MS/MS, Network Pharmacology, and In Silico Verification.

Non-small-cell lung cancer (NSCLC) is one of the most prevalent cancers worldwide. A Yi-Fei-San-Jie formula (YFSJF), widely used in NSCLC treatment in south China, has been validated in clinical studies. However, the pharmacological mechanism behind it remains unclear. In this study, 73 compounds were identified using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), with 58 enrolled in network pharmacology. The protein-protein interaction network, functional enrichment analysis, and compound-target-pathway network were constructed using 74 overlapping targets from 58 drugs and NSCLC. YFSJF has many targets and pathways in the fight against NSCLC. PIK3R1, PIK3CA, and AKT1 were identified as key targets, and the PI3K/AKT pathway was identified as the key pathway. According to the Human Protein Atlas (THPA) database and the Kaplan-Meier Online website, the three key targets had varying expression levels in normal and abnormal tissues and were linked to prognosis. Molecular docking and dynamics simulations verified that hub compounds have a strong affinity with three critical targets. This study revealed multiple compounds, targets, and pathways for YFSJF against NSCLC and suggested that YFSJF might inhibit PIK3R1, PIK3CA, and AKT1 to suppress the PI3K/AKT pathway and play its pharmacological role.

Comprehensive analysis of somatic mutator-derived and immune infiltrates related lncRNA signatures of genome instability reveals potential prognostic biomarkers involved in non-small cell lung cancer.

Background: The function and features of long non-coding RNAs (lncRNAs) are already attracting attention and extensive research on their role as biomarkers of prediction in lung cancer. However, the signatures that are both related to genomic instability (GI) and tumor immune microenvironment (TIME) have not yet been fully explored in previous studies of non-small cell lung cancer (NSCLC). Method: The clinical characteristics, RNA expression profiles, and somatic mutation information of patients in this study came from The Cancer Genome Atlas (TCGA) database. Cox proportional hazards regression analysis was performed to construct genomic instability-related lncRNA signature (GIrLncSig). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the potential functions of lncRNAs. CIBERSORT was used to calculate the proportion of immune cells in NSCLC. Result: Eleven genomic instability-related lncRNAs in NSCLC were identified, then we established a prognostic model with the GIrLncSig ground on the 11 lncRNAs. Through the computed GIrLncSig risk score, patients were divided into high-risk and low-risk groups. By plotting ROC curves, we found that patients in the low-risk group in the test set and TCGA set had longer overall survival than those in the high-risk group, thus validating the survival predictive power of GIrLncSig. By stratified analysis, there was still a significant difference in overall survival between high and low risk groups of patients after adjusting for other clinical characteristics, suggesting the prognostic significance of GIrLncSig is independent. In addition, combining GIrLncSig with TP53 could better predict clinical outcomes. Besides, the immune microenvironment differed significantly between the high-risk and the low-risk groups, patients with low risk scores tend to have upregulation of immune checkpoints and chemokines. Finally, we found that high-risk scores were associated with increased sensitivity to chemotherapy. Conclusion: we provided a new perspective on lncRNAs related to GI and TIME and revealed the worth of them in immune infiltration and immunotherapeutic response. Besides, we found that the expression of AC027288.1 is associated with PD-1 expression, which may be a potential prognostic marker in immune checkpoint inhibitor response to improve the prediction of clinical survival in NSCLC patients.

Efficacy of treatment for acneiform eruptions related to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) for non-small cell lung cancer (NSCLC): A protocol of systematic review and network meta-analysis.

BACKGROUND: Acneiform eruptions from epidermal growth factor receptor tyrosine kinase inhibitors is a frequent adverse event in non-small cell lung cancer patients but the efficacy of its treatment including antibiotics, corticosteroid, sunscreen is still poorly understood. METHODS: Eight electronic databases (PubMed, EMBASE, ClinicalTrials.gov, etc) will be searched from inception to April 2020. Risk of bias of randomized controlled trials will be assessed in terms of the Risk of Bias 2 (RoB 2) tool. Eligible randomized controlled trials will be enrolled for a Bayesian network meta-analysis using R software. RESULTS: This study is still ongoing and the results will be submitted and published in a peer-reviewed scientific journal. CONCLUSION: We hope the results of this study will provide reliable evidence for the management of acneiform due to epidermal growth factor receptor tyrosine kinase inhibitors for non-small cell lung cancer. ETHICS AND DISSEMINATION: Ethical approval is not applicable for this study is based on published trials. PROTOCOL REGISTRATION NUMBER: CRD42020206724.

Shen fu injection for patients with septic shock: Protocol for an updated systematic review.

BACKGROUND: Septic shock is a serious disease with high morbidity, which will lead to organ dysfunction. Shen fu injection (SFI) has been widely used for septic shock as a treatment in China. Many clinical trials have been reported that it could assess the efficacy and safety of SFI to cure septic shock and accelerate resuscitation. Reassessing the efficacy and safety of SFI as a treatment of patients with septic shock is the objective of this updated systematic review. METHODS: The following electronic databases major in English and Chinese will be conducted a systematic search until September 2018: PubMed, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, Chinese Science and Technology Periodical Database, Chinese BioMedical Literature Database, and Wan-fang Database. Randomized controlled trials of SFI will be included. Review Manager 5.2 software will be used for assessment of risk of bias, data synthesis, and subgroup analysis. We will conduct the GRADE system to assess the quality of evidence, if possible. RESULTS: This study will provide a rational synthesis of current evidences for SFI on septic shock. CONCLUSION: We hope our research results will provide an objective and reliable evidence to patients, clinicians and healthcare policymakers who are concerning the treatment options of SFI in septic shock. REGISTRATION: PROSPERO CRD42016049332.