Commentary: Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma.

Machine learning has made great progress in the field of medicine, especially in oncology research showing significant potential. In this paper, the application of machine learning in the study of cholangiocarcinoma was discussed. By developing a novel intra-tumor heterogeneity feature, the study successfully achieved accurate prediction of prognosis and immunotherapy effect in patients with cholangiocarcinoma. This study not only provides strong support for personalized treatment, but also provides key information for clinicians to develop more effective treatment strategies. This breakthrough marks the continuous evolution of machine learning in cancer research and brings new hope for the future development of the medical field. Our study lays a solid foundation for deepening the understanding of the biological characteristics of cholangiocarcinoma and improving the therapeutic effect, and provides a useful reference for more extensive cancer research.

NR5A2 gene affects the overall survival of LUAD patients by regulating the activity of CSCs through SNP pathway by OCLR algorithm and immune score.

Objective: Differentially expressed genes (DEGs) in lung adenocarcinoma (LUAD) tumor stem cells were screened, and the biological characteristics of NR5A2 gene were investigated. Methods: The expression and prognosis of NR5A2 in human LUAD were predicted and analyzed through bioinformatics analysis from a human cancer database. Gene expression and clinical data of LUAD tumor and normal lung tissues were obtained from The Cancer Genome Atlas (TCGA) database, and DEGs associated with lung cancer tumor stem cells (CSCs) were screened. Univariate and multivariate Cox regression models were used to screen and establish prognostic risk prediction models. The immune function of the patients was scored according to the model, and the relative immune functions of the high- and low-risk groups were compared to determine the difference in survival prognosis between the two groups. In addition, we calculated the index of stemness based on the transcriptome of the samples using one-class linear regression (OCLR). Results: Bioinformatics analysis of a clinical cancer database showed that NR5A2 was significantly decreased in human LUAD tissues than in normal lung tissues, and the decrease in NR5A2 gene expression shortened the overall survival and progression-free survival of patients with LUAD. Conclusion: The NR5A2 gene may regulate LUAD tumor stem cells through selective splicing mutations, thereby affecting the survival and prognosis of patients with lung cancer, and the NR5A2 gene may regulate CSCs through single nucleotide polymorphism.

Enhanced recovery after surgery in elderly patients with non-small cell lung cancer who underwent video-assisted thoracic surgery.

BACKGROUND: This study was designed to investigate the clinical outcomes of enhanced recovery after surgery (ERAS) in the perioperative period in elderly patients with non-small cell lung cancer (NSCLC). AIM: To investigate the potential enhancement of video-assisted thoracic surgery (VATS) in postoperative recovery in elderly patients with NSCLC. METHODS: We retrospectively analysed the clinical data of 85 elderly NSCLC patients who underwent ERAS (the ERAS group) and 327 elderly NSCLC patients who received routine care (the control group) after VATS at the Department of Thoracic Surgery of Peking University Shenzhen Hospital between May 2015 and April 2017. After propensity score matching of baseline data, we analysed the postoperative stay, total hospital expenses, postoperative 48-h pain score, and postoperative complication rate for the 2 groups of patients who underwent lobectomy or sublobar resection. RESULTS: After propensity score matching, ERAS significantly reduced the postoperative hospital stay (6.96 ± 4.16 vs 8.48 ± 4.18 d, P = 0.001) and total hospital expenses (48875.27 ± 18437.5 vs 55497.64 ± 21168.63 CNY, P = 0.014) and improved the satisfaction score (79.8 ± 7.55 vs 77.35 ± 7.72, P = 0.029) relative to those for routine care. No significant between-group difference was observed in postoperative 48-h pain score (4.68 ± 1.69 vs 5.28 ± 2.1, P = 0.090) or postoperative complication rate (21.2% vs 27.1%, P = 0.371). Subgroup analysis showed that ERAS significantly reduced the postoperative hospital stay and total hospital expenses and increased the satisfaction score of patients who underwent lobectomy but not of patients who underwent sublobar resection. CONCLUSION: ERAS effectively reduced the postoperative hospital stay and total hospital expenses and improved the satisfaction score in the perioperative period for elderly NSCLC patients who underwent lobectomy but not for patients who underwent sublobar resection.

Lipid Nanoparticle (LNP) Delivery Carrier-Assisted Targeted Controlled Release mRNA Vaccines in Tumor Immunity.

In recent years, lipid nanoparticles (LNPs) have attracted extensive attention in tumor immunotherapy. Targeting immune cells in cancer therapy has become a strategy of great research interest. mRNA vaccines are a potential choice for tumor immunotherapy, due to their ability to directly encode antigen proteins and stimulate a strong immune response. However, the mode of delivery and lack of stability of mRNA are key issues limiting its application. LNPs are an excellent mRNA delivery carrier, and their structural stability and biocompatibility make them an effective means for delivering mRNA to specific targets. This study summarizes the research progress in LNP delivery carrier-assisted targeted controlled release mRNA vaccines in tumor immunity. The role of LNPs in improving mRNA stability, immunogenicity, and targeting is discussed. This review aims to systematically summarize the latest research progress in LNP delivery carrier-assisted targeted controlled release mRNA vaccines in tumor immunity to provide new ideas and strategies for tumor immunotherapy, as well as to provide more effective treatment plans for patients.

Pathological diagnosis and immunohistochemical analysis of giant retrosternal goiter in the elderly: A case report.

BACKGROUND: Elderly giant retrosternal thyroid goiter is a rare yet significant medical condition, often presenting clinical symptoms that can be confused with other diseases, posing diagnostic and therapeutic challenges. This study aims to delve into the characteristics and potential mechanisms of this ailment through pathological diagnosis and immunohistochemical analysis, providing clinicians with more precise diagnostic and treatment strategies. CASE SUMMARY: A 77-year-old male, was admitted to hospital with the chief complaint of finding a goiter in the semilunar month during physical examination, accompanied by dyspnea. Locally protruding into the superior mediastinum, the adjacent structure was compressed, the trachea was compressed to the right, and the local lumen was slightly narrowed. The patient was diagnosed with giant retrosternal goiter. Considering dyspnea caused by trachea compression, our department planned to perform giant retrosternal thyroidectomy. Immunohistochemical results: Tg (+), TTF-1 (+), Calcitonin (CT) (I), Ki-67 (+, about 20%), CD34 (-). Retrosternal goiter means that more than 50% of the volume of the thyroid gland is below the upper margin of the sternum. As retrosternal goiter disease is a relatively rare disease, once the disease is diagnosed, it should be timely surgical treatment, and the treatment is more difficult, the need for professional medical team for comprehensive treatment. CONCLUSION: The imaging manifestations of giant retrosternal goiter are atypical, histomorphology and immunohistochemistry can assist in its diagnosis. This article reviews the relevant literature of giant retrosternal goiter immunohistochemistry and shows that giant retrosternal goiter is positive for Tg, TTF-1, and Ki-67.

Pathological diagnosis and immunohistochemical analysis of minute pulmonary meningothelial-like nodules: A case report.

BACKGROUND: Minute Pulmonary Meningothelial-like Nodules (MPMNs) are rare benign pulmonary nodules, which are more common in elderly women and have a higher detection rate in lung tissues of patients with lung malignant diseases. Its origin is not yet clear. At present, there are few reports on the diagnostic methods such as imaging and pathological manifestations of MPMNs. This article reports a 70-year-old female patient with pulmonary adenocarcinoma combined with MPMNs and reviews of the relevant literature. CASE SUMMARY: A 70-year-old women was admitted to our institution with feeling sour in her back and occasional cough for more than 2 mo. Computerized electronic scanning scan and 3D reconstruction images in our institution showed there were multiple ground-glass nodules in both of her two lungs. The biggest one was in the apicoposterior segment of left upper lobe, about 2.5 mm × 9 mm in size. We performed thoracoscopic resection of the left upper lung apicoposterior segment of the patient, and the final pathological report was minimally invasive adenocarcinoma. Re-examination of high resolution computed tomography 21 mo after surgery showed multiple ground-glass nodules in both lungs, and a new ground-glass nodule was found in the superior segment of the right lower lobe. We took pathological biopsy of the right upper lung and right lower lung nodules for the patient under thoracoscopy. The histomorphology of the right lower lobe nodule showed multiple lesions in the lung tissue, and the small foci in the alveolar septum were distributed in mild form of the aggregation of short spindle cells. The immunohistochemistry showed that the lesion was epithelial membrane antigen (EMA) (+), somatostatin receptor 2a (SSTR2a) (+), S-100 (-), chromogranin A (-), Syn (-), cytokeratin (-) and HMB-45 (-). The final diagnosis was minimally invasive adenocarcinoma, accompanied by MPMNs. We recommend that patients continue to receive treatment after surgery and to do regular follow-up observations. CONCLUSION: The imaging manifestations of MPMNs are atypical, histomorphology and immunohistochemistry can assist in its diagnosis. This article reviews the relevant literature of MPMNs immunohistochemistry and shows that MPMNs are positive for EMA, SSTR2a, and progesterone receptor.

Identification of molecular subgroups and establishment of risk model based on the response to oxidative stress to predict overall survival of patients with lung adenocarcinoma.

OBJECTIVE: Oxidative stress is associated with the occurrence and development of lung cancer. However, the specific association between lung cancer and oxidative stress is unclear. This study aimed to investigate the role of oxidative stress in the progression and prognosis of lung adenocarcinoma (LUAD). METHODS: The gene expression profiles and corresponding clinical information were collected from GEO and TCGA databases. Differentially expressed oxidative stress-related genes (OSRGs) were identified between normal and tumor samples. Consensus clustering was applied to identify oxidative stress-related molecular subgroups. Functional enrichment analysis, GSEA, and GSVA were performed to investigate the potential mechanisms. xCell was used to assess the immune status of the subgroups. A risk model was developed by the LASSO algorithm and validated using TCGA-LUAD, GSE13213, and GSE30219 datasets. RESULTS: A total of 40 differentially expressed OSRGs and two oxidative stress-associated subgroups were identified. Enrichment analysis revealed that cell cycle-, inflammation- and oxidative stress-related pathways varied significantly in the two subgroups. Furthermore, a risk model was developed and validated based on the OSRGs, and findings indicated that the risk model exhibits good prediction and diagnosis values for LUAD patients. CONCLUSION: The risk model based on the oxidative stress could act as an effective prognostic tool for LUAD patients. Our findings provided novel genetic biomarkers for prognosis prediction and personalized clinical treatment for LUAD patients.

Multiple Omics Analysis of the Role of RBM10 Gene Instability in Immune Regulation and Drug Sensitivity in Patients with Lung Adenocarcinoma (LUAD).

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.

Immunomodulatory Factor TIM3 of Cytolytic Active Genes Affected the Survival and Prognosis of Lung Adenocarcinoma Patients by Multi-Omics Analysis.

[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.

Selective poly adenylation predicts the efficacy of immunotherapy in patients with lung adenocarcinoma by multiple omics research.

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.

Construction of a lung adenocarcinoma prognostic model based on N6-methyl-adenosine-related long noncoding RNA and screening of potential drugs based on this model.

Lung adenocarcinoma (LUAD) has a high mortality rate. N6-methyl-adenosine (m6A)-related long noncoding RNA (lncRNA) is associated with tumor prognosis. Our objective was to construct an m6A-related lncRNA prognostic model and screen potential drugs for the treatment of LUAD. The LUAD sequencing data were randomly divided into Train and Test cohorts. In the Train group, the LASSO Cox regression was used to construct the m6A-related lncRNA prognostic model. The LUAD tumor immune dysfunction and exclusion model was used to evaluate immunotherapy efficacy in LUAD. The 'pRRophetic' package was utilized to screen potential drugs for the treatment of LUAD. Eleven m6A-related lncRNAs were identified by LASSO Cox regression and were used to construct the risk model to calculate sample risk scores. Patients were divided into high- and low-risk groups based on their median risk scores. The LUAD data of The Cancer Genome Atlas database showed that the overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group in both cohorts. Multivariate Cox regression analysis showed that this risk model could serve as an independent prognostic factor of LUAD, and receiver operating characteristic curves suggested that m6A-related lncRNA prognostic signature has a good ability in predicting OS. Finally, nine potential drugs for LUAD treatment were screened based on this prognostic model. The prognostic model constructed based on the m6A-related lncRNAs facilitated prognosis prediction in LUAD patients. The screened therapeutic agents have potential application values and provide a reference for the clinical treatment of LUAD.

Long-chain noncoding ribonucleic acids affect the survival and prognosis of patients with esophageal adenocarcinoma through the autophagy pathway: construction of a prognostic model.

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.

Comprehensive evaluation of the efficacy and safety of LPV/r drugs in the treatment of SARS and MERS to provide potential treatment options for COVID-19.

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.