Autophagy-related long-chain noncoding ribonucleic acids play a vital role in the development of esophageal adenocarcinoma. This study aimed to construct a prognostic model of autophagy-related long-chain noncoding ribonucleic acids and identify potential therapeutical targets for esophageal adenocarcinoma. We downloaded 261 long-chain noncoding RNA transcript samples and clinical data of 87 esophageal adenocarcinoma patients from the Cancer Genome Atlas and 307 autophagy-related genes from www.autophagy.com. We performed Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses and Gene Set Enrichment Analysis to determine risk characteristics and bioinformatics functions of signal transduction pathways. Univariate and multivariate Cox regression analyses were used to determine the correlation between autophagy-related long-chain noncoding ribonucleic acids and independent risk factors. The receiver operating characteristic analysis was used to evaluate the feasibility of the prognostic model. Finally, we performed survival analysis, risk analysis and independent prognostic analysis to verify the prognostic model of esophageal adenocarcinoma. We identified 22 autophagic long-chain noncoding ribonucleic acids that were highly correlated with the overall survival of esophageal adenocarcinoma patients. The areas under the receiver operating characteristic curve (0.941) and the calibration curve were significantly similar. Moreover, univariate and multivariate Cox regression analyses indicated that autophagy-related long-chain noncoding ribonucleic acids were independent predictors of esophageal adenocarcinoma. We found that autophagy-related long-chain noncoding ribonucleic acids might affect tumor development and prognosis in esophageal adenocarcinoma patients. The findings indicate that the prognostic model of esophageal adenocarcinoma has potential therapeutic applications in patients with esophageal adenocarcinoma.

Objective: The RNA-binding protein RBM10 can regulate apoptosis during the proliferation and migration of pancreatic cancer, endometrial cancer, and osteosarcoma cells; however, the molecular mechanism underlying lung adenocarcinoma is rarely reported. Recent studies have detected multiple truncated and missense mutations in RBM10 in lung adenocarcinoma, but the role of RBM10 in lung adenocarcinoma is unclear. This study mainly explored the immune regulation mechanism of RBM10 in the development of lung adenocarcinoma and its influence on sensitivity to targeted therapy drugs. Methods: The transcriptome data of CGAP were used to analyze the RNA-seq data of lung adenocarcinoma patients from different subgroups by using the CIBERSORT algorithm to infer the relative proportion of various immune infiltrating cells, and Spearman correlation analysis was performed to determine the gene expression and immune cell content. In addition, this study utilized drug trial data from the GDSC database. The IC50 estimates for each specific targeted therapy were obtained by using a regression method, and the regression and prediction accuracy were tested via ten cross-validations with the GDSC training set. An immunohistochemical test was performed on the samples of 20 patients with lung adenocarcinoma in the subcomponent analysis of immune cells, and the protein expression of RBM10 in lung adenocarcinoma tissues was verified by cellular immunofluorescence assays. Nucleic acids were extracted at low temperatures, and qRT-PCR was used to verify the expression levels of the mRNA of RBM10 in lung adenocarcinoma tissues and normal tissues (p < 0.05). Results: After screening and inclusion using a machine language, the results showed that RBM10 was significantly highly expressed in the lung adenocarcinoma tissues. The related signaling pathways were mainly concentrated in ncRNA processing, rRNA metabolic processes, ribosome biogenesis, and the regulation of translation. The qRT-PCR for 20 lung adenocarcinoma tissues showed that the expression of RBM10 in these tissues was significantly different from that in normal tissues (p = 0.0255). Immunohistochemistry analysis and cell immunofluorescence staining also confirmed that RBM10 was involved in the immune regulation of lung adenocarcinoma tissues, and the number of immune cell aggregations was significantly higher than that of the control group. RBM10 regulates B cell memory-CIBERSORT (p = 0.042) and B cell memory-CIBERSOTRT-abs (p = 0.027), cancer-associated fibroblast-EPIC (p = 0.001), cancer-associated fibroblast- MCPCounter (p = 0.0037), etc. The risk score was significantly associated with the sensitivity of patients to lapatinib (p = 0.049), nilotinib (p = 0.015), pazopanib (p = 0.001), and sorafenib (p = 0.048). Conclusions: RBM10 can inhibit the proliferation and invasion of lung adenocarcinoma cells through negative regulation and promote the apoptosis of lung adenocarcinoma cells through immunomodulatory mechanisms. The expression level of RBM10 affects the efficacy of targeted drug therapy and the survival prognosis of lung adenocarcinoma patients, which has a certain guiding significance for the clinical treatment of these patients.

The aim of this study was to find the application value of selective polyadenylation in immune cell infiltration, biological transcription function and risk assessment of survival and prognosis in lung adenocarcinoma (LUAD). The processed original mRNA expression data of LUAD were downloaded, and the expression profiles of 594 patient samples were collected. The (APA) events in TCGA-NA-SEQ data were evaluated by polyadenylation site use Index (PDUI) values, and the invasion of stromal cells and immune cells and tumor purity were calculated to group and select the differential genes. Lasso regression and stratified analysis were used to examine the role of risk scores in predicting patient outcomes. The study also used the GDSC database to predict the chemotherapeutic sensitivity of each tumor sample and used a regression method to obtain an IC50 estimate for each specific chemotherapeutic drug treatment. Then CIBERSORT algorithm was used to conduct Spearman correlation analysis, immune regulatory factor analysis and TIDE immune system function analysis for gene expression level and immune cell content. Finally, the Kaplan–Meier curve was used to analyze the correlation between stromal score and the immune score of LUAD. In this study, APA’s LUAD risk score prognostic model was constructed. KM survival analysis showed that immune score affected the prognosis of LUAD patients (P = 0.027) but the matrix score was not statistically significant (P = 0.1). We extracted 108 genes with APA events from 827 different genes and based on PUDI clustering and heat map, the survival rate of patients in the four groups was significantly different (P = 0.05). Multiple omics studies showed that risk score was significantly positively correlated with Macrophages M0, T cells Follicular helper, B cells naive and NK cells resting. It is significantly negatively correlated with dendritic cells resting, mast cells resting, monocyte, T cells CD4 memory resting and B cells memory. We further explored the relationship between the expression of immunosuppressor genes and risk score and found that ADORA2A, BTLA, CD160, CD244, CD274, CD96, CSF1R and CTLA4 genes were highly correlated with the risk score. Selective poly adenylation plays an important role in the development and progression of LUAD, immune invasion, tumor cell invasion and metastasis and biological transcription, and affects the survival and prognosis of LUAD patients.

Coronavirus disease 2019 (COVID-19) experienced an outbreak that expanded worldwide. Lopinavir/ritonavir (LPV/r), which is used effectively for severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronavirus infections, was applied for COVID-19 treatment given similarities in the molecular structures of these viruses. We performed a systematic review and meta-analysis to evaluate the efficacy and safety of lopinavir/ritonavir antiviral treatment in patients with SARS, MERS, and COVID-19. After registration with INPLASY, a search was conducted in PubMed, Embase, China National Knowledge Infrastructure (CNKI), Cochrane Library, WanFang Data, China Biomedical Literature Database (CBM) and other databases for all relevant literature on lopinavir/ritonavir treatment of SARS, MERS and COVID-19. The Cochrane Collaboration's bias risk assessment tool and the Newcastle-Ottawa Scale (NOS) were used to evaluate the quality of the literature, and RevMan 5.3 software was used to evaluate the relevant outcome indicators of the efficacy and safety of lopinavir/ritonavir in the treatment of COVID-19. A total of 18 eligible studies (including randomized controlled studies, cohort studies, and case-control studies) were retrieved and included with a total of 2273 patients. The lopinavir/ritonavir group exhibited an increased nucleic acid conversion rate (P=0.004), higher virus clearance rate (P<0.0001), lower mortality rate (P=0.002), and reduced incidence of acute respiratory distress syndrome (ARDS) (P=0.02) compared with the control group. No significant benefit in the improvement rate of chest CT (P=0.08) or incidence of adverse events (P=0.45) was noted. The lopinavir/ritonavir group had a lower incidence of acute respiratory distress syndrome (P=0.02). According to the clinical prognostic results, the incidence of adverse events between the two groups was not statistically significant (P<0.0001). The efficacy of lopinavir/ritonavir in the treatment of patients with SARS, MERS and COVID-19 was significantly better than that of the control. Furthermore, the incidence of adverse events did not significantly increase. Lopinavir/ritonavir is effective in the treatment of COVID-19, and this combination should be further assessed in RCT studies. In addition, when we analyzed the differences in age and sex, we found that the differences were statistically significant in the safety and effectiveness of lopinavir/ritonavir in patients with COVID-19, and both of these factors played a significant role in the trial.

[Objective] Using multi-omics research methods to explore cytolytic activity-related genes through the immunoregulatory factors HAVCR2 (TIM3) affecting the survival and prognosis of lung adenocarcinoma. [Methods] We combined Cox single factor regression and lasso regression feature selection algorithm to screen out the key genes of cytolytic activity in lung adenocarcinoma, and applied multi-omics research to explore the clinical predictive value of the model, including onset risk, independent prognosis, clinical relevance, signal transduction pathways, drug sensitivity, and the correlation of immune regulatory factors, etc. TCGA data are used as the experimental group, and GEO data is used as the external data control group to verify the stability of the model. The survival curve was generated by the Kaplan–Meier method and compared by log-rank, and the Cox proportional hazard model was used for multivariate analysis. In this study, 10 fresh tissue samples of lung adenocarcinoma were collected for cellular immunohistochemical experiments to analyze the expression of immunoregulatory factors in cancer tissues, and the key immunoregulatory factors were verified and screened out. [Results] A total of 450 genes related to cytolytic activity were differentially expressed, of which 273 genes were up-regulated and 177 genes were down-regulated. A total of 91 key genes related to cytolytic activity related to the prognosis of lung adenocarcinoma were screened through Cox single factor regression. The ROC curve results showed that the AUC values of 1, 3, and 5 years in the training set and test set were all greater than 0.7, indicating that the model has a valid verification. The level of risk score is significantly related to the sensitivity of patients to AKT inhibitor VIII, Lenalidomide, and Tipifarnib. In addition, our study also found that receptor and MHC genes related to immunomodulatory, and chemokines, including HAVCR2, are more highly expressed in the low-risk group. [Conclusions] HAVCR2 (TIM3) immunoregulatory factors affect the expression of key genes that affect cytolytic activity in lung adenocarcinoma cells, and to some extent indirectly affect the survival and prognosis of patients with lung adenocarcinoma.

The proteins encoded by the excision repair cross-complementing (ERCC) family are pivotal in DNA damage repair and maintaining genome stability. However, the precise role of the ERCC family in tumor prognosis and the effectiveness of immune checkpoint inhibitors (ICI) therapy remain uncertain. This study aimed to explore the connection between ERCC mutations and prognosis as well as the response to ICI. We observed that patients with ERCC mutations exhibited enhanced progression-free survival (PFS) and overall survival (OS) in two independent pan-cancer cohorts. Furthermore, this mutant subgroup showed higher tumor mutation burden (TMB) compared to the wild-type subgroup. Notably, ERCC mutations were associated with better OS (HR 0.54, 95% CI 0.42–0.70; P < 0.001) in pan-cancer patients who underwent ICI therapy (N = 1661). These findings were validated in a separate cohort, where patients in the ERCC mutant subgroup demonstrated improved clinical outcomes (HR 0.56, 95% CI 0.37–0.84; P = 0.03) and higher response rates (51.9% vs. 26.8%) than the wild-type subgroup. Further analysis revealed that patients with ERCC mutations displayed elevated tumor neoantigen burden (TNB) levels and increased infiltration of immune-response cells. Our study suggests that ERCC mutations are linked to enhanced immunogenicity and improved ICI efficacy, thus potentially serving as a biomarker for ICI therapy.