Identification of a novel immunogenic death-associated model for predicting the immune microenvironment in lung adenocarcinoma from single-cell and Bulk transcriptomes.

Background: Studies on immunogenic death (ICD) in lung adenocarcinoma are limited, and this study aimed to determine the function of ICD in LUAD and to construct a novel ICD-based prognostic model to improve immune efficacy in lung adenocarcinoma patients. Methods: The data for lung adenocarcinoma were obtained from the Cancer Genome Atlas (TCGA) database and the National Center for Biotechnology Information (GEO). The single-cell data were obtained from Bischoff P et al. To identify subpopulations, we performed descending clustering using TSNE. We collected sets of genes related to immunogenic death from the literature and identified ICD-related genes through gene set analysis of variance (GSVA) and weighted gene correlation network analysis (WGCNA). Lung adenocarcinoma patients were classified into two types using consistency clustering. The difference between the two types was analyzed to obtain differential genes. An immunogenic death model (ICDRS) was established using LASSO-Cox analysis and compared with lung adenocarcinoma models of other individuals. External validation was performed in the GSE31210 and GSE50081 cohorts. The efficacy of immunotherapy was assessed using the TIDE algorithm and the IMvigor210, GSE78220, and TCIA cohorts. Furthermore, differences in mutational profiles and immune microenvironment between different risk groups were investigated. Subsequently, ROC diagnostic curves and KM survival curves were used to screen ICDRS key regulatory genes. Finally, RT-qPCR was used to verify the differential expression of these genes. Results: Eight ICD genes were found to be highly predictive of LUAD prognosis and significantly correlated with it. Multivariate analysis showed that patients in the low-risk group had a higher overall survival rate than those in the high-risk group, indicating that the model was an independent predictor of LUAD. Additionally, ICDRS demonstrated better predictive ability compared to 11 previously published models. Furthermore, significant differences in biological function and immune cell infiltration were observed in the tumor microenvironment between the high-risk and low-risk groups. It is noteworthy that immunotherapy was also significant in both groups. These findings suggest that the model has good predictive efficacy. Conclusions: The ICD model demonstrated good predictive performance, revealing the tumor microenvironment and providing a new method for evaluating the efficacy of pre-immunization. This offers a new strategy for future treatment of lung adenocarcinoma.

Tuberculosis to lung cancer: application of tuberculosis signatures in identification of lung adenocarcinoma subtypes and marker screening.

Background: There is an association between LUAD and TB, and TB increases the risk of lung adenocarcinogenesis. However, the role of TB in the development of lung adenocarcinoma has not been clarified. Methods: DEGs from TB and LUAD lung samples were obtained to identify TB-LUAD-shared DEGs. Consensus Clustering was performed on the TCGA cohort to characterize unique changes in TB transcriptome-derived lung adenocarcinoma subtypes. Prognostic models were constructed based on TB signatures to explore the characterization of subgroups. Finally, experimental validation and single-cell analysis of potential markers were performed. Results: We characterized three molecular subtypes with unique clinical features, cellular infiltration, and pathway change manifestations. We constructed and validated TB-related Signature in six cohorts. TB-related Signature has characteristic alterations, and can be used as an effective predictor of immunotherapy response. Prognostically relevant novel markers KRT80, C1QTNF6, and TRPA1 were validated by RT-qPCR. The association between KRT80 and lung adenocarcinoma disease progression was verified in Bulk transcriptome and single-cell transcriptome. Conclusion: For the first time, a comprehensive bioinformatics analysis of tuberculosis signatures was used to identify subtypes of lung adenocarcinoma. The TB-related Signature predicted prognosis and identified potential markers. This result reveals a potential pathogenic association of tuberculosis in the progression of lung adenocarcinoma.

Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort.

Introduction: The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies are needed to investigate the prognostic significance of the interaction between immune-related genes and cell death in LUAD. Methods: In this study, 10 clustering algorithms were applied to perform molecular typing based on cell death-related genes, immune-related genes, methylation data and somatic mutation data. And a powerful computational framework was used to investigate the relationship between immune genes and cell death patterns in LUAD patients. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations, and we constructed an immune-associated programmed cell death model (PIGRS) using the machine learning model that exhibited the best performance. Finally, based on a series of in vitro experiments used to explore the role of PSME3 in LUAD. Results: We used 10 clustering algorithms and multi-omics data to categorize TCGA-LUAD patients into three subtypes. patients with the CS3 subtype had the best prognosis, whereas patients with the CS1 and CS2 subtypes had a poorer prognosis. PIGRS, a combination of 15 high-impact genes, showed strong prognostic performance for LUAD patients. PIGRS has a very strong prognostic efficacy compared to our collection. In conclusion, we found that PSME3 has been little studied in lung adenocarcinoma and may be a novel prognostic factor in lung adenocarcinoma. Discussion: Three LUAD subtypes with different molecular features and clinical significance were successfully identified by bioinformatic analysis, and PIGRS was constructed using a powerful machine learning framework. and investigated PSME3, which may affect apoptosis in lung adenocarcinoma cells through the PI3K/AKT/Bcl-2 signaling pathway.

Identification and validation of tryptophan-related gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma reveals a critical role for PTTG1.

Introduction: Tryptophan metabolism is strongly associated with immunosuppression and may influence lung adenocarcinoma prognosis as well as tumor microenvironment alterations. Methods: Sequencing datasets were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Two different clusters were identified by consensus clustering, and prognostic models were established based on differentially expressed genes (DEGs) in the two clusters. We investigated differences in mutational landscapes, enrichment pathways, immune cell infiltration, and immunotherapy between high- and low-risk scoring groups. Single-cell sequencing data from Bischoff et al. were used to identify and quantify tryptophan metabolism, and model genes were comprehensively analyzed. Finally, PTTG1 was analyzed at the pan-cancer level by the pan-TCGA cohort. Results: Risk score was defined as an independent prognostic factor for lung adenocarcinoma and was effective in predicting immunotherapy response in patients with lung adenocarcinoma. PTTG1 is one of the key genes, and knockdown of PTTG1 in vitro decreases lung adenocarcinoma cell proliferation and migration and promotes apoptosis and down-regulation of tryptophan metabolism regulators in lung adenocarcinoma cells. Discussion: Our study revealed the pattern and molecular features of tryptophan metabolism in lung adenocarcinoma patients, established a model of tryptophan metabolism-associated lung adenocarcinoma prognosis, and explored the roles of PTTG1 in lung adenocarcinoma progression, EMT process, and tryptophan metabolism.

Investigating the mechanism and the effect of aquaporin 5 (AQP5) on the self-renewal capacity of gastric cancer stem cells.

Aquaporin 5 (AQP5) has been shown to have a pro-carcinogenic effect in numerous types of malignancies. This research intends to investigate the role and the molecular mechanism of AQP5 on enriched gastric cancer stem cells (GCSCs). Methods: Immunohistochemistry, western blot (WB), and RT-qPCR techniques were employed to identify the presence of AQP5 in gastric cancer (GC) and the neighboring paracancerous tissues. Additionally, a statistical analysis was conducted to determine the correlation between AQP5 expression and the pathological and histological parameters. Furthermore, the study aimed to assess the predictive value of AQP5 expression in long-term survival after GC surgery. GCSCs were enriched using the serum-free culture method. The expression of AQP5 in enriched GCSCs was explored using RT-qPCR and WB. Plate cloning, transwell, WB, RT-qPCR, and the sphere-forming assay were utilized to monitor the proliferation, migration, and self-renewal capability of GCSCs after AQP5 knockdown. WB and Immunofluorescence for Detecting the Effect of AQP5 on Autophagy. WB, RT-qPCR, and other experiments were used for in-depth investigation of the potential molecular regulatory mechanism of AQP5 in GC. Results: AQP5 was highly expressed in GC tissues and GC cells, and overexpression of AQP5 was associated with lymph node metastasis, increased tumor size, and low 5-year postoperative survival in GC patients; other studies have shown that the AQP5 was highly expressed in GCSCs. Knockdown of AQP5 suppressed tumorigenesis in vivo and inhibited the proliferative, migratory, and self-renewal capability of GCSCs. It was also found that AQP5 could activate the autophagy phenomenon of GCSCs, and mechanistically, we found that AQP5 could regulate TRPV4 to affect the self-renewal ability of GCSCs. Conclusion: AQP5 can be further explored for GC therapy, as it has shown a significant impact on the self-renewal capability of GCSCs, which prevents GC progression.

Human Umbilical Cord Mesenchymal Stem Cell-derived Exosomes Induce Macrophage M2 Polarization by Antagonizing LPS-mediated Stimulation of the NF-κB and STAT3 Pathways.

BACKGROUND: Many studies have documented the protective effects of regulating macrophage M1/M2 polarization in inflammatory diseases characterized by their imbalance state. In pathological diseases associated with inflammation, mesenchymal stem cells (MSCs) regulate macrophages, thereby having anti-inflammatory and tissue regenerative effects. Exosomes have been suggested as an alternative mechanism that underlies the paracrine function of MSCs. Thus, this study explored the anti-inflammatory impact of human umbilical cord MSCssecreted exosomes (hucMSCs-EX) by influencing macrophage polarization in normal and inflammatory environments in vitro. METHODS: In this study, hucMSCs-conditioned medium (hucMSCs-CM) and hucMSCs- EX were used to treat RAW264.7 macrophages with or without LPS. The expressions of TNF- α, IL-10, IL-6, IL-1ß, and Arg-1 were quantified by qPCR. The expressions of IL-6 and IL-10 were evaluated by ELISAs. Western blots (WB) were performed to observe the expressions of CD206, NF-κB P65, NF-κB p-p65, p-STAT3, STAT3, and NF-κB phosphorylation. The number of cells expressing CD206 and the fluorescence intensity were measured via flow cytometry (FC) and immunofluorescence staining. Cell propagation and migration were examined via MTT and transwell assays, respectively. RESULTS: The inhibition of LPS-induced inflammatory polarization by hucMSCs-EX or hucMSCs- CM led to increases in IL-10 and arginase (Arg) levels and decreases in those of IL-6 and TNF-α. Moreover, hucMSCs-EX enhanced the CD206 expression in RAW264.7 cells and accelerated the propagation and migration of LPS-induced cells. The suppressive impact of hucMSCs-EX on the LPS-induced phenotypic polarization of M1 macrophages was linked with the reduction of NF-κB signaling. They stimulated the transition of M2 macrophages by enhancing the activity of STAT3 in RAW264.7 cells. CONCLUSION: This study indicated that hucMSCs-EX enhances the macrophage transition into the M2 phenotype by inhibiting the NF-κB p65 axis and stimulating that of STAT3.

Elucidating the mechanism of action of Isobavachalcone induced autophagy and apoptosis in non-small cell lung cancer by network pharmacology and experimental validation methods.

BACKGROUND: Lung cancer is the leading cause of cancer deaths, and non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer-related mortality. In recent years, there have been numerous treatments for non-small cell lung cancer, but the cure and survival rates are still extremely low. Isobavachalcone (IBC) belongs to the chalcone component of the traditional Chinese medicine Psoralea corylifolia L., and is a unique Protein kinase B (AKT) pathway inhibitor with significant anticancer effects. Previous studies have shown that IBC possess a variety of biological properties, including anti-cancer, anti-inflammatory, and antioxidant properties. This study focused on the use of network pharmacology analysis, molecular docking technology and experimental validation to elucidate the potential mechanisms of IBC for the treatment of NSCLC. METHODS: Screening key genes and pathways of IBC action in NSCLC using network pharmacology. The IBC target genes were from The Encyclopedia of Traditional Chinese Medicine (ETCM) and BATMAN-TCM databases, the NSCLC target genes were from GeneCards, Online Mendelian Inheritance in Man (OMIM) and The Therapeutic Target database (TTD) databases, both of which were taken as intersecting genes for protein-protein interaction network analysis and enrichment analysis, and the binding energies of the compounds to the core targets were further verified by molecular docking. Cell lines in vitro experiments were then performed to further unravel the mechanism of IBC for NSCLC. RESULTS: A total of 279 potential targets were retrieved by searching the intersection of IBC and NSCLC targets. Protein-protein interaction (PPI) network analysis indicated that 6 targets, including AKT1, RXRA, NCOA1, RXRB, RARA, PPARG were hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that IBC treatment of NSCLC mainly involves steroid binding, transcription factor activity, Pathways in cancer, cAMP signaling pathway, Adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway. Among them, the AMPK signaling pathway, which contained the largest number of enriched genes, may play a greater role in the treatment of NSCLC. Then, the results of in vitro experiment indicated that IBC could inhibit proliferation of NSCLC cells and induce cell autophagy and apoptosis. The results also showed that IBC could increase the protein expression of AMPK and decrease the protein expression of AKT and mammalian target of rapamycin (mTOR), suggesting that IBC can treat NSCLC by inducing cellular autophagy and apoptosis as well as modulating AMPK and AKT signaling pathways. CONCLUSIONS: In summary, this study provided a new insight into the protective mechanism of IBC against NSCLC through network pharmacology and experimental validation.

The critical role of residues Phe120 and Val161 of (2 R,3 R)­2,3­butanediol dehydrogenase from Neisseria gonorrhoeae as probed by molecular docking and site-directed mutagenesis.

NAD+-dependent (2 R,3 R)­2,3­butanediol dehydrogenase (BDH) from Neisseria gonorrhoeae (NgBDH) is a representative member of the medium-chain dehydrogenase/reductase (MDR) superfamily. To date, little information is available on the substrate binding sites and catalytic residues of BDHs from this superfamily. In this work, according to molecular docking studies, we found that conserved residues Phe120 and Val161 form strong hydrophobic interactions with both (2 R,3 R)­2,3­butanediol (RR-BD) and meso-2,3­butanediol (meso-BD) and that mutations of these residues to alanine or threonine impair substrate binding. To further evaluate the roles of these two residues, Phe120 and Val161 were mutated to alanine or threonine. Kinetic analysis revealed that, relative to those of wild type, the apparent KM values of the Phe120Ala mutant for RR-BD and meso-BD increased 36- and 369-fold, respectively; the catalytic efficiencies of this mutant with RR-BD and meso-BD decreased approximately 586- and 3528-fold, respectively; and the apparent KM values of the Val161Ala mutant for RR-BD and meso-BD increased 4- and 37-fold, respectively, the catalytic efficiencies of this mutant with RR-BD and meso-BD decreased approximately 3- and 28-fold, respectively. Additionally, the Val161Thr mutant slightly decreased catalytic efficiencies (twofold with RR-BD; 7.3-fold with meso-BD) due to an increase in KM (sixfold for RR-BD; 24-fold for meso-BD) and a slight increase (2.8-fold with RR-BD; 3.3-fold with meso-BD) in kcat. These findings validate the critical roles of Phe120 and Val161 of NgBDH in substrate binding and catalysis. Overall, the current study provides a better understanding of the substrate binding and catalysis of BDHs within the MDR superfamily.

Identification of T-cell exhaustion-related genes and prediction of their immunotherapeutic role in lung adenocarcinoma.

Background: Lung adenocarcinoma ranks as the second most widespread form of cancer globally, accompanied by a significant mortality rate. Several studies have shown that T cell exhaustion is associated with immunotherapy of tumours. Consequently, it is essential to comprehend the possible impact of T cell exhaustion on the tumor microenvironment. The purpose of this research was to create a TEX-based model that would use single-cell RNA-seq (scRNA-seq) and bulk-RNA sequencing to explore new possibilities for assessing the prognosis and immunotherapeutic response of LUAD patients. Methods: RNA-seq data from LUAD patients was downloaded from the Cancer Genome Atlas (TCGA) database and the National Center for Biotechnology Information (GEO). 10X scRNA sequencing data, as reported by Bischoff P et al., was utilized for down-sampling clustering and subgroup identification using TSNE. TEX-associated genes were identified through gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). We utilized LASSO-Cox analysis to establish predicted TEX features. External validation was conducted in GSE31210 and GSE30219 cohorts. Immunotherapeutic response was assessed in IMvigor210, GSE78220, GSE35640 and GSE100797 cohorts. Furthermore, we investigated differences in mutational profiles and immune microenvironment between various risk groups. We then screened TEXRS key regulatory genes using ROC diagnostic curves and KM survival curves. Finally, we verified the differential expression of key regulatory genes through RT-qPCR. Results: Nine TEX genes were identified as highly predictive of LUAD prognosis and strongly correlated with disease outcome. Univariate and multivariate analysis revealed that patients in the low-risk group had significantly better overall survival rates compared with those in the high-risk group, highlighting the model's ability to independently predict LUAD prognosis. Our analysis revealed significant variation in the biological function, mutational landscape, and immune cell infiltration within the tumor microenvironment of both high-risk and low-risk groups. Additionally, immunotherapy was found to have a significant impact on both groups, indicating strong predictive efficacy of the model. Conclusions: The TEX model showed good predictive performance and provided a new perspective for evaluating the efficacy of preimmunization, which provides a new strategy for the future treatment of lung adenocarcinoma.

Multi-omics identification of GPCR gene features in lung adenocarcinoma based on multiple machine learning combinations.

Background: Lung adenocarcinoma is a common malignant tumor that ranks second in the world and has a high mortality rate. G protein-coupled receptors (GPCRs) have been reported to play an important role in cancer; however, G protein-coupled receptor-associated features have not been adequately investigated. Methods: In this study, GPCR-related genes were screened at single-cell and bulk transcriptome levels based on AUcell, single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network (WGCNA) analysis. And a new machine learning framework containing 10 machine learning algorithms and their multiple combinations was used to construct a consensus G protein-coupled receptor-related signature (GPCRRS). GPCRRS was validated in the training set and external validation set. We constructed GPCRRS-integrated nomogram clinical prognosis prediction tools. Multi-omics analyses included genomics, single-cell transcriptomics, and bulk transcriptomics to gain a more comprehensive understanding of prognostic features. We assessed the response of risk subgroups to immunotherapy and screened for personalized drugs targeting specific risk subgroups. Finally, the expression of key GPCRRS genes was verified by RT-qPCR. Results: In this study, we identified 10 GPCR-associated genes that were significantly associated with the prognosis of lung adenocarcinoma by single-cell transcriptome and bulk transcriptome. Univariate and multivariate showed that the survival rate was higher in low risk than in high risk, which also suggested that the model was an independent prognostic factor for LUAD. In addition, we observed significant differences in biological function, mutational landscape, and immune cell infiltration in the tumor microenvironment between high and low risk groups. Notably, immunotherapy was also relevant in the high and low risk groups. In addition, potential drugs targeting specific risk subgroups were identified. Conclusion: In this study, we constructed and validated a lung adenocarcinoma G protein-coupled receptor-related signature, which has an important role in predicting the prognosis of lung adenocarcinoma and the effect of immunotherapy. It is hypothesized that LDHA, GPX3 and DOCK4 are new potential targets for lung adenocarcinoma, which can achieve breakthroughs in prognosis prediction, targeted prevention and treatment of lung adenocarcinoma and provide important guidance for anti-tumor.

PBK correlates with prognosis, immune escape and drug response in LUAD.

PBK (PDZ-binding kinase) is a protein-coding gene that encodes a serine/threonine protein kinase associated with the dual-specific mitogen-activated protein kinase (MAPKK) family. Overexpression of this gene is closely linked to tumor development. In this study, we aimed to investigate the role of PBK in lung adenocarcinoma (LUAD) progression, prognosis, and immune evasion. We conducted a pan-cancer analysis of PBK to examine its expression and prognostic value. In the LUAD cohort, we analyzed PBK expression, prognosis, mutational features, and immune infiltration in groups with different PBK expression levels. We constructed a PBK-associated genomic model, integrated it into a nomogram, and compared high and low-risk subgroups. In our pan-cancer analysis, PBK was significantly upregulated, particularly in LUAD patients, and displayed poor prognosis. The high PBK expression group had many deletion mutations but still showed gene upregulation. Immune infiltration analysis indicated that PBK-triggered immune escape in the high expression group might relate to antigen presentation, dendritic cell, and CD8+ T cell infiltration. We constructed a 5-gene prognostic model and a nomogram to quantify individual survival probabilities. The PBK-associated gene prognostic model reliably predicted patient prognosis and drug response. Our findings offer new insights into PBK-induced immune escape and targeted therapy during LUAD development, providing valuable suggestions for clinical treatment approaches.

Predicting lung adenocarcinoma prognosis, immune escape, and pharmacomic profile from arginine and proline-related genes.

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease that ranks first in morbidity and mortality. Abnormal arginine metabolism is associated with inflammatory lung disease and may influence alterations in the tumor immune microenvironment. However, the potential role of arginine and proline metabolic patterns and immune molecular markers in LUAD is unclear. Gene expression, somatic mutations, and clinicopathological information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was performed to identify metabolic genes associated with overall survival (OS). Unsupervised clustering divided the sample into two subtypes with different metabolic and immunological profiles. Gene set enrichment analysis (GESA) and gene set variation analysis (GSVA) were used to analyze the underlying biological processes of the two subtypes. Drug sensitivity between subtypes was also predicted; then prognostic features were developed by multivariate Cox regression analysis. In addition, validation was obtained in the GSE68465, and GSE50081 dataset. Then, gene expression, and clinical characterization of hub genes CPS1 and SMS were performed; finally, in vitro validation experiments for knockdown of SMS were performed in LUAD cell lines. In this study, we first identified 12 arginine and proline-related genes (APRGs) significantly associated with OS and characterized the clinicopathological features and tumor microenvironmental landscape of two different subtypes. Then, we established an arginine and proline metabolism-related scoring system and identified two hub genes highly associated with prognosis, namely CPS1, and SMS. In addition, we performed CCK8, transwell, and other functional experiments on SMS to obtain consistent results. Our comprehensive analysis revealed the potential molecular features and clinical applications of APRGs in LUAD. A model based on 2 APRGs can accurately predict survival outcomes in LUAD, improve our understanding of APRGs in LUAD, and pave a new pathway to guide risk stratification and treatment strategy development for LUAD patients.

Nosip is a potential therapeutic target in hepatocellular carcinoma cells.

Nitric oxide synthase-interacting protein (Nosip) interacts with nitric oxide synthase (NOS) and regulates NO synthesis and release, which participates in various critical physiological and pathological processes. However, the role of Nosip in hepatocellular carcinoma (HCC) is unclear. In this study, Nosip expression was found to be elevated in HCC tissues and cells. Nosip siRNA transfection inhibited the proliferation and motility of HCC cells and promoted apoptosis. In contrast, overexpression of Nosip promoted proliferation and migration and invasion, and inhibited apoptosis of HCC cells. As a natural compound, quercetin exerted the effect of inhibiting the proliferation and motility of HCC cells, and this anticancer activity probably via repressing the expression of Nosip. Our results suggest that Nosip could act as an oncogene in the progression of HCC and that quercetin may be a potential natural compound for treating HCC by inhibiting the expression of Nosip.

Nitidine Chloride Triggers Autophagy and Apoptosis of Ovarian Cancer Cells through Akt/mTOR Signaling Pathway.

OBJECTIVE: Ovarian cancer (OC) is the eighth most common cancer with high mortality in women worldwide. Currently, compounds derived from Chinese herbal medicine have provided a new angle for OC treatment. METHODS: In this study, the cell proliferation and migration of ovarian cancer A2780/SKOV3 cells were inhibited after being treated with nitidine chloride (NC) by using MTT and Wound-Healing Assay. Flow cytometry analysis indicated NC-induced apoptosis of ovarian cancer cells, and AO and MDC staining showed that NC treatment induced the appearance of autophagosomes and autophagic lysosomes in ovarian cancer cells. RESULTS: Through the autophagy inhibition experiment of chloroquine, it was proved that NC significantly further promoted apoptosis in ovarian cancer cells. Furthermore, NC proved that it could significantly decrease the expression of autophagy-related genes such as Akt, mTOR, P85 S6K, P70 S6K, and 4E-BP1. CONCLUSION: Therefore, we suggest that NC could trigger autophagy and apoptosis of ovarian cancer cells through Akt/mTOR signaling pathway, and NC may potentially be a target for chemotherapy against ovarian cancer.

Regulation of early diagnosis and prognostic markers of lung adenocarcinoma in immunity and hypoxia.

Lung adenocarcinoma is still cancer with the highest mortality. Hypoxia and immunity play an essential role in the occurrence and development of tumors. Therefore, this study is mainly to find new early diagnosis and prognosis markers and explore the relationship among the markers and immunity and hypoxia, to improve the prognosis of patients. Firstly, based on the clinical database in TCGA, we determined the most critical clinicopathological parameters affecting the prognosis of patients through a variety of analysis methods. According to pathological parameters, logistic most minor absolute contraction selection operator (lasso), univariate and multivariate regression analysis, the risk genes related to early prognosis were screened, and the risk model was established. Then, in different risk groups, GSEA and CIBERSORT algorithms were used to analyze the distribution and enrichment of the immune cells and hypoxia, to study the effects of early prognostic indicators on hypoxia and immunity. At the same time, we analyzed the different levels of risk genes in normal cells (BSEA-2B) and tumor cells (H1299, A549, PC9, and H1975). Finally, A549 and PC9 cells were induced by CoCl2 to establish a hypoxic environment, and the correlation between risk genes and HIF1A was analyzed. The risk model based on risk genes (CYP4B1, KRT6A, and FAM83A) was accurate and stable for the prognosis of patients. It is closely related to immunity and hypoxia. In BSEA-2B cells, the mRNA and protein expression of CYP4B1 was higher, while the expression of KRT6A and FAM83A was lower. Finally, we found that FAM83A and HIF1A showed a significant positive correlation when A549 and PC9 cells were exposed to hypoxia. The discovery of early diagnostic markers related to immunity, hypoxia, and prognosis, provides a new idea for early screening and prognostic treatment of lung adenocarcinoma.

B cell-related tertiary lymphoid structure may exert inhibitory effects on lung adenocarcinoma and SARS-COV-2.

Background: The prognosis of lung adenocarcinoma (LUAD) is poor. Infection with coronavirus disease 2019 (COVID-19) may further worsen the outcome of LUAD. This study utilized the immune model and the COVID-19 receptor signal to identify the potential immune structure affecting the prognosis of COVID-19 and LUAD. Methods: A prognostic model was established and verified. The correlation between immune cells and risk score was examined through a variety of immune calculation methods. Gene set variation analysis (GSVA) was used to explore the correlation between the immune signaling pathway, risk model, COVID-19 binding receptor (CO19ORS) signal, and different clinicopathological factors. Results: The analysis showed that the prognosis of patients was better in the low-risk group versus the high-risk group. The tertiary lymphoid structure dominated by T and B cells (TLS1) can improve the prognosis of patients in the low-risk group. Interestingly, the CO19ORS was enriched only in females and aged >65 years. The age group >65 years is closely related to the tertiary lymphatic structure of the newborn (TLS2), while the female sex is closely related to the TLS2 and TLS1 signature. The two groups exhibited a high level of inflammation-related signal distribution. In the near future, I will collect LUAD and COVID-19 related organizations to verify the changes of 8 risk protein. Conclusion: TLS1 structure may improve the prognosis of patients with LUAD and SARS-COV-2 (Severe acute respiratory syndrome coronavirus 2). This unexpected discovery provides new insight into the comprehensive treatment of patients with LUAD and SARS-COV-2.

PDS5B inhibits cell proliferation, migration, and invasion via upregulation of LATS1 in lung cancer cells.

PDS5B (precocious dissociation of sisters 5B) plays a pivotal role in carcinogenesis and progression. However, the biological functions of PDS5B in lung cancer and its underlying mechanisms are not fully elucidated. In the present study, we used MTT assays, wound-healing assays, and transwell migration and invasion approach to examine the cell viability, migration, and invasion of non-small cell lung cancer (NSCLC) cells after PDS5B modulation. Moreover, we investigated the function of PDS5B overexpression in vivo. Furthermore, we detected the expression of PDS5B in tissue samples of lung cancer patients by immunohistochemical study. We found that upregulation of PDS5B repressed cell viability, migration, and invasion in NSCLC cells, whereas downregulation of PDS5B had the opposite effects. We also observed that PDS5B overexpression retarded tumor growth in nude mice. Notably, PDS5B positively regulated LATS1 expression in NSCLC cells. Strikingly, low expression of PDS5B was associated with lymph node metastasis in lung cancer patients. Our findings suggest that PDS5B might be a therapeutic target for lung cancer.

Orlistat induces ferroptosis-like cell death of lung cancer cells.

Aberrant de novo lipid synthesis is involved in the progression and treatment resistance of many types of cancers, including lung cancer; however, targeting the lipogenetic pathways for cancer therapy remains an unmet clinical need. In this study, we tested the anticancer activity of orlistat, an FDA-approved anti-obesity drug, in human and mouse cancer cells in vitro and in vivo, and we found that orlistat, as a single agent, inhibited the proliferation and viabilities of lung cancer cells and induced ferroptosis-like cell death in vitro. Mechanistically, we found that orlistat reduced the expression of GPX4, a central ferroptosis regulator, and induced lipid peroxidation. In addition, we systemically analyzed the genome-wide gene expression changes affected by orlistat treatment using RNA-seq and identified FAF2, a molecule regulating the lipid droplet homeostasis, as a novel target of orlistat. Moreover, in a mouse xenograft model, orlistat significantly inhibited tumor growth and reduced the tumor volumes compared with vehicle control (P < 0.05). Our study showed a novel mechanism of the anticancer activity of orlistat and provided the rationale for repurposing this drug for the treatment of lung cancer and other types of cancer.

Purification and Characterization of (2R,3R)-2,3-Butanediol Dehydrogenase of the Human Pathogen Neisseria gonorrhoeae FA1090 Produced in Escherichia coli.

2,3-Butanediol dehydrogenase (BDH), also known as acetoin/diacetyl reductase, is a pivotal enzyme for the formation of 2,3-butanediol (2,3-BD), a chiral compound with potential roles in the virulence of certain pathogens. Here, a NAD(H)-dependent (2R,3R)-BDH from Neisseria gonorrhoeae FA1090 (NgBDH), the causative agent of gonorrhoea, was functionally characterized. Sequence analysis indicated that it belongs to zinc-containing medium-chain dehydrogenase/reductase family. The recombinant NgBDH migrated as a single band with a size of around 45 kDa on SDS-PAGE and could be confirmed by Western blotting and mass spectrometry. For the oxidation of either (2R,3R)-2,3-BD or meso-2,3-BD, the enzyme exhibited a broad pH optimum between pH 9.5 to 11.5. For the reduction of (3R/3S)-acetoin, the pH optimum was around 6.5. The enzyme could catalyze the stereospecific oxidation of (2R,3R)-2,3-BD (Km = 0.16 mM, kcat/Km = 673 s-1 · mM-1) and meso-BD (Km = 0.72 mM, kcat/Km = 165 s-1 · mM-1). Moreover, it could also reduce (3R/3S)-acetoin with a Km of 0.14 mM and a kcat/Km of 885 s-1 · mM-1. The results presented here contribute to understand the 2,3-BD metabolism in N. gonorrhoeae and pave the way for studying the influence of 2,3-BD metabolism on the virulence of this pathogen in the future.

Nitidine chloride suppresses NEDD4 expression in lung cancer cells.

Nitidine chloride (NC) possesses anticancer properties in various types of human malignancies. However, the effects of NC on lung cancer cells have not been elucidated. Moreover, the molecular mechanism of NC-involved antitumor activity is unclear. Therefore, we aimed to determine the biological effect of NC and the underlying molecular insights in lung cancer cells. The antineoplastic function of NC was assessed by MTT assays, Annexin V-FITC/PI apoptosis assay, wound healing analysis, and Transwell chamber migration and invasion assay in lung cancer cells. NEDD4 modulation was evaluated by western blotting assays of lung cancer cells after NC treatments. NEDD4 overexpression and downregulation were employed to validate the critical role of NEDD4 in the NC-mediated tumor suppressive effects. We found that NC suppressed cell viability, migration and invasion, but induced apoptosis in lung cancer cells. Mechanistic exploration revealed that NC exhibited its antitumor effects by reducing NEDD4 expression. Furthermore, our rescue experiments dissected that overexpression of NEDD4 abrogated the NC-mediated antineoplastic effects in lung cancer cells. Consistently, downregulation of NEDD4 enhanced the NC-induced anticancer effects. Thus, NC is a promising antitumor agent in lung cancer, indicating that NC might have potential therapeutic applications in the treatment of lung cancer.