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Ubiquitin modification and alternative polyadenylation play crucial roles in the onset and progression of cancer. Hence, this study aims to comprehensively and deeply understand gene regulation and associated biological processes in lung adenocarcinoma (LUAD) by integrating both mechanisms. Alternative polyadenylation (APA)-related E3 ubiquitin ligases in LUAD were identified through multiple databases, and the association between selected genetic loci influencing gene expression (apaQTL-SNPs) and LUAD risk were evaluated through the GWAS database of the Female Lung Cancer Consortium in Asia (FLCCA). Subsequently, the interaction between RNF213 and ZBTB20, as well as their functional mechanisms in LUAD, were investigated using bioinformatics analysis, Western blot, co-immunoprecipitation, and colony formation experiments. A total of five apaQTL-SNPs (rs41301932, rs4494603, rs9890400, rs56066320, and rs41301932), located on RNF213, were significantly associated with LUAD risk (p < 0.05), and they inhibit tumor growth through ubiquitin-mediated degradation of ZBTB20. [ABSTRACT FROM AUTHOR]

Alternative polyadenylation (APA) plays a crucial role in cancer biology. Here, we used data from the 3′aQTL-atlas, GTEx, and the China Nanjing Lung Cancer GWAS database to explore the association between apaQTL/eQTL-SNPs and the risk of lung adenocarcinoma (LUAD). The variant T allele of rs277646 in NIT2 is associated with an increased risk of LUAD (OR = 1.12, P = 0.015), lower PDUI values, and higher NIT2 expression. The 3′RACE experiment showed multiple poly (A) sites in NIT2, with the rs277646-T allele causing preferential use of the proximal poly (A) site, resulting in a shorter 3′UTR transcript. This leads to the loss of the hsa-miR-650 binding site, thereby affecting LUAD malignant phenotypes by regulating the expression level of NIT2. Our findings may provide new insights into understanding and exploring APA events in LUAD carcinogenesis. The authors explore alternative polyadenylation (APA) related genes in lung adenocarcinoma(LUAD). By integrating APA-related LUAD genes, 3′aQTL-atlas and eQTL analysis, they identify 28 candidate LUAD-related apaQTL/eQTL-SNPs. [ABSTRACT FROM AUTHOR]

Ferroptosis is a newly identified form of non-apoptotic programmed cell death resulting from iron-dependent lipid peroxidation. It is controlled by integrated oxidation and antioxidant systems. Ferroptosis exerts a crucial effect on the carcinogenesis of several cancers, including pulmonary cancer. Herein, a ferroptosis-associated gene signature for lung cancer prognosis and diagnosis was identified using integrative bioinformatics analyses. From the FerrDB database, 256 ferroptotic regulators and markers were identified. Of these, 25 exhibited differential expression between lung cancer and non-cancerous samples, as evidenced by the GSE19804 and GSE7670 datasets from the GEO database. Utilizing LASSO Cox regression analysis on TCGA-LUAD data, a potent 3-gene risk signature comprising CAV1, RRM2, and EGFR was established. This signature adeptly differentiates various survival outcomes in lung cancer patients, including overall survival and disease-specific intervals. Based on the 3-gene risk signature, lung cancer patients were categorized into high-risk and low-risk groups. Comparative analysis revealed 69 differentially expressed genes between these groups, with UBE2Z significantly associated with overall survival in TCGA-LUAD. UBE2Z was found to be upregulated in LUAD tissues and cells compared to normal controls. Functionally, the knockdown of UBE2Z curtailed aggressive behaviors in LUAD cells, including viability, migration, and invasion. Moreover, this knockdown led to a decrease in the mesenchymal marker vimentin while elevating the epithelial marker E-cadherin within LUAD cell lines. In conclusion, the ferroptosis-associated 3-gene risk signature effectively differentiates prognosis and clinical features in patients with lung cancer. UBE2Z was identified through this model, and it is upregulated in LUAD samples. Its knockdown inhibits aggressive cellular behaviors, suggesting UBE2Z's potential as a therapeutic target for lung cancer treatment. [Display omitted] • The 3-gene risk score model can effectively stratify lung cancer patients based on various clinical characteristics. • UBE2Z is increased within LUAD tissues and cells. • UBE2Z knockdown inhibits aggressive phenotypes of lung cancer cell. [ABSTRACT FROM AUTHOR]

We aimed to determine participation in low‐dose computed tomography (LDCT) of individuals with a family history of common cancers in a population‐based screening program to provide timely evidence in high‐risk populations in China. The analysis was conducted using data from the Cancer Screening Program in Urban China (CanSPUC), which recruited 282 377 participants aged 40 to 74 years from eight cities in the Henan province. Using the CanSPUC risk score system, 55 428 participants were evaluated to have high risk for lung cancer and were recommended for LDCT. We calculated the overall and group‐specific participation rates using family history of common cancers and compared differences in participation rates between different groups. Odds ratios (ORs) and 95% confidence intervals were derived by multivariable logistic regression. Of the 55 428 participants, 22 260 underwent LDCT (participation rate, 40.16%). Family history of lung, esophageal, stomach, liver and colorectal cancer was associated with increased participation in LDCT screening. The odds of participants with a family history of one, two, three and four or more cancer cases undergoing LDCT screening were 1.9, 2.7, 2.8 and 3.5 times, respectively, than those without a family history of cancer. Compared to those without a history of cancer, participation in LDCT gradually increased as the number of cancer cases in the family increased (P <.001). Our findings suggest that there is room for improvement in lung cancer screening given the relatively low participation rate. Lung cancer screening in populations with a family history of cancer may improve efficiency and cost‐effectiveness; however, this requires further verification. [ABSTRACT FROM AUTHOR]

Background: About 15% of lung cancers in men and 53% in women are not attributable to smoking worldwide. The aim was to develop and validate a simple and non-invasive model which could assess and stratify lung cancer risk in non-smokers in China. Methods: A large-sample size, population-based study was conducted under the framework of the Cancer Screening Program in Urban China (CanSPUC). Data on the lung cancer screening in Henan province, China, from October 2013 to October 2019 were used and randomly divided into the training and validation sets. Related risk factors were identified through multivariable Cox regression analysis, followed by establishment of risk prediction nomogram. Discrimination [area under the curve (AUC)] and calibration were further performed to assess the validation of risk prediction nomogram in the training set, and then validated by the validation set. Results: A total of 214,764 eligible subjects were included, with a mean age of 55.19 years. Subjects were randomly divided into the training (107,382) and validation (107,382) sets. Elder age, being male, a low education level, family history of lung cancer, history of tuberculosis, and without a history of hyperlipidemia were the independent risk factors for lung cancer. Using these six variables, we plotted 1-year, 3-year, and 5-year lung cancer risk prediction nomogram. The AUC was 0.753, 0.752, and 0.755 for the 1-, 3- and 5-year lung cancer risk in the training set, respectively. In the validation set, the model showed a moderate predictive discrimination, with the AUC was 0.668, 0.678, and 0.685 for the 1-, 3- and 5-year lung cancer risk. Conclusions: We developed and validated a simple and non-invasive lung cancer risk model in non-smokers. This model can be applied to identify and triage patients at high risk for developing lung cancers in non-smokers. [ABSTRACT FROM AUTHOR]

Background: The increasing incidence and unique biological features of lung cancer in women has prompted renewed interest in the role of sex hormones in this disease. We previously showed that progesterone (P4) inhibited lung cancer tumorigenesis and progression. Here, we investigated the effects of P4 on expression of long noncoding RNAs (lncRNAs) and target mRNAs in lung cancer cells. Methods: We performed high‐throughput microarray and bioinformatics analysis to identify differentially expressed lncRNAs and mRNAs in the untreated and the P4‐treated A549 human lung cancer cells. Results: In total, 692 lncRNAs and 268 mRNAs were significantly differentially expressed in the P4‐treated A549 cells compared to the untreated A549 cells (> 2‐fold change, p < 0.05). Of the lncRNAs, 82 and 610 were up‐regulated and down‐regulated, respectively. Gene ontology, pathway and network analyses showed that many of the mRNAs were involved in the regulation of classical pathways, including Notch signaling. Differential expression of a lncRNA signature composed of NONHSAT000264, FR075921, FR324124, linc‐TRIM58, RP1‐93H18.7, RP11‐120 K9.2, RP11‐134F2.2 and NONHSAG024980 was validated by quantitatuve reverse transcriptase‐polymerase chain reaction analysis. Conclusions: This is the first report of differentially expressed lncRNAs in the P4‐treated lung cancer cells. The results suggest that lncRNAs could serve as potential therapeutic targets for P4‐sensitive lung cancer. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to determine whether progesterone could inhibit the growth of lung adenocarcinoma cells via membrane progesterone receptor alpha (mPRα) and elucidate its potential mechanism. The relationship between mPRα expression and the survival prognosis of lung adenocarcinoma patients was studied. Methods: A mPRα knockdown lung adenocarcinoma cell line was constructed and treated with P4 and Org (a derivative of P4 and specific agonist of mPRα). Cell proliferation was assessed using CCK‐8 and plate colony formation assays. Protein expression was detected by western blotting. A nude mouse model of lung adenocarcinoma was established to assess the antitumor effect of P4/Org in vivo. Results: We initially determined that mPRα could promote the development of lung adenocarcinoma through the following lines of evidence. High expression of mPRα both at the mRNA and protein level was significantly associated with the poor prognosis of lung adenocarcinoma patients. The downregulation of mPRα inhibited the proliferation of lung adenocarcinoma cells. We further showed that mPRα mediates the ability of P4 to inhibit the growth of lung adenocarcinoma cells through the following lines of evidence: P4/Org inhibited the proliferation of lung adenocarcinoma cells; mPRα mediated the ability of P4/Org to inhibit lung adenocarcinoma cell proliferation; mPRα mediated the ability of P4/Org to inhibit the PKA (cAMP‐dependent protein kinase)/CREB (cAMP responsive element binding protein) and PKA/β‐catenin signaling pathways; and P4/Org inhibited the growth of a lung adenocarcinoma tumor model in vivo. Conclusions: In summary, the results of our study show that progesterone can inhibit lung adenocarcinoma cell growth via mPRα. [ABSTRACT FROM AUTHOR]

Multidrug resistance (MDR) is a major obstacle in the effective chemotherapeutic treatment of cancers. Triptolide (TPL) is a diterpenoid isolated from Tripterygium wilfordii Hook. f., a traditional Chinese medicine. It was demonstrated in our previous study that TPL exerts anti-MDR cancers on various MDR cell lines (including A549/Taxol, MCF-7/ADR and Bel7402/5-Fu). The present study was designed to investigate its anti-proliferative activity on A549/Taxol cells, and explore the underlying mechanism of action. The anti-proliferative activity of TPL on A549/Taxol cells was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Its pro-apoptosis and cell cycle arrest activities were analyzed by flow cytometry. Western blot assay was employed to investigate the levels of mitogen-activated protein kinases (MAPKs) and apoptosis-related proteins in cells. TPL efficiently suppressed the proliferation of A549/Taxol cells. Co-treatment with MAPK inhibitors in the MTT assay indicated that the extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) pathways were involved in the process. Upregulation of p-p38, p-ERK, p-GSK-3β, Bax and cleaved caspases-3 and -9, and downregulation of p-JNK, p-Akt and Bcl-2 were observed upon treatment with TPL in the A549/Taxol cells. The results from flow cytometry assay revealed that TPL induced apoptosis and S-phase arrest in A549/Taxol cells. This occurred as a result of the upregulation of p-ERK and p-GSK-3β, and the downregulation of p-JNK and p-Akt, and was responsible for the subsequent anti-proliferative activity. [ABSTRACT FROM AUTHOR]

Background: MiR-924 has been reported to be a tumor suppressor in hepatocellular carcinoma. However, the functions and mechanisms of miR-924 in non-small cell lung cancer (NSCLC) remain unclear. Methods: The expression of miR-924 was determined in NSCLC tissues and cell lines using quantitative real time PCR. The Chi-squared test was used to evaluate the correlation between miR-924 levels and clinicopathological parameters in patients with NSCLC. Cell proliferation was assessed by CCK-8 assay. Cell migration and invasion were detected by transwell assay. The combination of miR-924 and RHBDD1 was analyzed via the luciferase reporter assay. The expression level of RHBDD1 was evaluated in lung cancer tissues using public microarray datasets form Oncomine and its prognostic value was assessed by Kaplan–Meier Plotter databases. A tumor xenograft mouse model was established to illustrate the effects of miR-924 on the tumorigenesis of NSCLC in vivo. Results: In this study, we found miR-924 was strikingly decreased in NSCLC tissues and cell lines. Decreased miR-924 was closely correlated with advanced tumor-node-metastasis (TNM) stage and lymphatic metastasis in NSCLC patients. Noticeably, rhomboid domain-containing protein 1 (RHBDD1) was predicted and confirmed as a direct target of miR-924. Moreover, the expression level of RHBDD1 was significantly increased and inversely associated with prognosis using public microarray datasets form Oncomine and Kaplan–Meier Plotter databases. MiR-924 overexpression suppressed cell proliferation, migration and invasion. The in vivo experiments further demonstrated that miR-924 overexpression reduced NSCLC xenograft growth through inhibiting RHBDD1/Wnt/β-catenin signaling pathway. Conclusions: In summary, these findings demonstrated that miR-924 blocked the progression of NSCLC by targeting RHBDD1 and miR-924/RHBDD1 axis might provide a novel therapeutic target for the treatment of NSCLC. [ABSTRACT FROM AUTHOR]

• In a large prospective lung cancer screening cohort study, we developed and internally validated a simple risk prediction model for lung cancer. • Our results showed that the model has moderate discriminatory accuracy and goodness-of-fit for both men and women, smokers and never-smokers. • The model has potential utility for shared decision-making and individualized risk assessment for tailored lung cancer screening. Two large randomized controlled trials (RCTs) have demonstrated that low dose computed tomography (LDCT) screening reduces lung cancer mortality. Risk-prediction models have been proved to select individuals for lung cancer screening effectively. With the focus on established risk factors for lung cancer routinely available in general cancer screening settings, we aimed to develop and internally validated a risk prediction model for lung cancer. Using data from the Cancer Screening Program in Urban China (CanSPUC) in Henan province, China between 2013 and 2019, we conducted a prospective cohort study consisting of 282,254 participants including 126,445 males and 155,809 females. Detailed questionnaire, physical assessment and follow-up were completed for all participants. Using Cox proportional risk regression analysis, we developed the Henan Lung Cancer Risk Models based on simplified questionnaire. Model discrimination was evaluated by concordance statistics (C-statistics), and model calibration was evaluated by the bootstrap sampling, respectively. By 2020, a total of 589 lung cancer cases occurred in the follow-up yielding an incident density of 64.91/100,000 person-years (pyrs). Age, gender, smoking, history of tuberculosis and history of emphysema were included into the model. The C-index of the model for 1-year lung cancer risk was 0.766 and 0.741 in the training set and validation set, respectively. In stratified analysis, the model showed better predictive power in males, younger participants, and former or current smoking participants. The model calibrated well across the deciles of predicted risk in both the overall population and all subgroups. We developed and internally validated a simple risk prediction model for lung cancer, which may be useful to identify high-risk individuals for more intensive screening for cancer prevention. [ABSTRACT FROM AUTHOR]