Nomogram-Based Risk Stratification to Identify Patients with T3N0M0 Breast Cancer with Survival Benefit from Postmastectomy Radiotherapy.

BACKGROUND: The survival benefit of postmastectomy radiotherapy (PMRT) for patients with T3N0M0 breast cancer remains controversial. This study aimed to identify patients with a survival benefit from PMRT by developing a novel risk stratification model. PATIENTS AND METHODS: The study recruited 2062 patients with pT3N0M0 breast cancer from the Surveillance, Epidemiology, and End Results (SEER) database who underwent mastectomy between 2010 and 2019. Overall survival (OS) and breast-cancer-specific survival (BCSS) prognostic nomograms based on multivariate Cox regression were constructed to quantify the survival risk and classify patients into low- and high-risk groups. Subgroup analyses were undertaken to assess the role of PMRT according to age and risk stratification. RESULTS: In the overall cohort, PMRT was beneficial in improving OS in patients with pT3N0 breast cancer (5-year OS, non-PMRT versus PMRT: 76.6% vs. 84.2%, P < 0.001), while the benefit on BCSS was not significant (P = 0.084). On the basis of the risk stratification nomogram, in the high-risk group, PMRT improved OS in young patients by 10.1%, OS in elderly patients by 12.4%, and BCSS by 10.2% (P < 0.05), but the use of PMRT in the low-risk group did not improve OS and BCSS in all patients (P > 0.05). CONCLUSIONS: We presented a new method for quantifying risk using the nomogram to identify patients with high risk of pT3N0M0 breast cancer. This study found that older patients in the newly constructed high-risk group benefited from OS and BCSS benefits from PMRT, while for younger high-risk patients, there was only a benefit in terms of OS.

Autophagy-related tumor subtypes associated with significant gene expression profiles and immune cell infiltration signatures to reveal the prognosis of non-small cell lung cancer.

Autophagy plays an important role in non-small cell lung cancer (NSCLC). We aimed to establish novel autophagy-related tumor subtypes to distinguish the prognosis of NSCLC. In this study, gene expression profiles, mutation data and clinical information obtained from the Cancer Genome Atlas. Kaplan Meier-plotter could evaluate prognostic value of autophagy-related genes. Consensus clustering revealed autophagy-related tumor subtypes. Gene expression profiles, mutation data and immune infiltration signatures were identified, oncogenic pathways and gene-drug interactions were performed according to the clusters. Finally, a total of 23 prognostic genes were screened and consensus clustering analysis divided the NSCLC into 2 clusters. The mutation signature showed that 6 genes are special. Immune infiltration signatures showed that higher fraction of immune cells was associated with cluster 1. The oncogenic pathways and gene-drug interactions also showed different patterns. In conclusion, autophagy-related tumor subtypes have different prognosis. Understanding the subtypes of NSCLC are helpful to accurately identify the NSCLC and personalized treatment.

Conditional survival analysis and real-time prognosis prediction for cervical cancer patients below the age of 65 years.

Background: Survival prediction for cervical cancer is usually based on its stage at diagnosis or a multivariate nomogram. However, few studies cared whether long-term survival improved after they survived for several years. Meanwhile, traditional survival analysis could not calculate this dynamic outcome. We aimed to assess the improvement of survival over time using conditional survival (CS) analysis and developed a novel conditional survival nomogram (CS-nomogram) to provide individualized and real-time prognostic information. Methods: Cervical cancer patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier method estimated cancer-specific survival (CSS) and calculated the conditional CSS (C-CSS) at year y+x after giving x years of survival based on the formula C-CSS(y|x) =CSS(y+x)/CSS(x). y indicated the number of years of further survival under the condition that the patient was determined to have survived for x years. The study identified predictors by the least absolute shrinkage and selection operator (LASSO) regression and used multivariate Cox regression to demonstrate these predictors' effect on CSS and to develop a nomogram. Finally, the CSS possibilities predicted by the nomogram were brought into the C-CSS formula to create the CS-nomogram. Results: A total of 18,511 patients aged <65 years with cervical cancer from 2004 to 2019 were included in this study. CS analysis revealed that the 15-year CSS increased year by year from the initial 72.6% to 77.8%, 84.5%, 88.8%, 91.5%, 93.5%, 94.8%, 95.7%, 96.4%, 97.3%, 98.0%, 98.5%, 99.1%, and 99.4% (after surviving for 1-13 years, respectively), and found that when survival exceeded 5-6 years, the risk of death from cervical cancer would be less than 5% in 10-15 years. The CS-nomogram constructed using tumor size, lymph node status, distant metastasis status, and histological grade showed strong predictive performance with a concordance index (C-index) of 0.805 and a stable area under the curve (AUC) between 0.795 and 0.816 over 15 years. Conclusions: CS analysis in this study revealed the gradual improvement of CSS over time in long-term survived cervical cancer patients. We applied CS to the nomogram and developed a CS-nomogram successfully predicting individualized and real-time prognosis.

Comprehensive Bioinformatics Analysis of Lipopolysaccharide-Induced Altered Autophagy in Acute Lung Injury and Construction of Underlying Competing Endogenous RNA Regulatory Mechanism.

BACKGROUND: Acute lung injury (ALI) is a fatal syndrome frequently induced by lipopolysaccharide (LPS) released from the bacterial cell wall. LPS could also trigger autophagy of lung bronchial epithelial cell to relieve the inflammation, while the overwhelming LPS would impair the balance of autophagy consequently inducing serious lung injury. METHODS: We observed the autophagy variation of 16HBE, human bronchial epithelial cell, under exposure to different concentrations of LPS through western blot, immunofluorescence staining, and electron microscopy. Eight strands of 16HBE were divided into two groups upon 1000 ng/ml LPS stimulation or not, which were sent to be sequenced at whole transcriptome. Subsequently, we analyzed the sequencing data in functional enrichment, pathway analysis, and candidate gene selection and constructed a hsa-miR-663b-related competing endogenous RNA (ceRNA) network. RESULTS: We set a series of concentrations of LPS to stimulate 16HBE and observed the variation of autophagy in related protein expression and autophagosome count. We found that the effective concentration of LPS was 1000 ng/ml at 12 hours of exposure and sequenced the 1000 ng/ml LPS-stimulated 16HBE. As a result, a total of 750 differentially expressed genes (DEGs), 449 differentially expressed lncRNAs (DElncRNAs), 76 differentially expressed circRNAs (DEcircRNAs), and 127 differentially expressed miRNAs (DEmiRNAs) were identified. We constructed the protein-protein interaction (PPI) network to visualize the interaction between DEGs and located 36 genes to comprehend the core discrepancy between LPS-stimulated 16HBE and the negative control group. In combined analysis of differentially expressed RNAs (DERNAs), we analyzed all the targeted relationships of ceRNA in DERNAs and figured hsa-miR-663b as a central mediator in the ceRNA network to play when LPS induced the variation of autophagy in 16HBE. CONCLUSION: Our research indicated that the hsa-miR-663b-related ceRNA network may contribute to the key regulatory mechanism in LPS-induced changes of autophagy and ALI.

AURKA and FAM83A are prognostic biomarkers and correlated with Tumor-infiltrating Lymphocytes in smoking related Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) has become the main histologic type, which account for nearly 40% of lung cancer. The present study aimed to investigate the gene expression signature in smoking related LUAD. A total of 45 smoking related DEGs in LUAD were identified and functional enrichment analysis was also performed. Then Cox's regression model and Kaplan-Meier analysis were used to screen potential prognostic genes. Finally, AURKA and FAM83A were left for further immune-related mechanism exploration. Kaplan-Meier analysis indicated survival rates are related to different immune cell (B cell and Dendritic cell) infiltration levels. Mechanistically, we further explore the correlation between AURKA and FAM83A gene expression levels and tumor-infiltrating lymphocytes (TILs) level as well as their response to immunomodulators. The results suggested that AURKA and FAM83A are highly expressed in smoking related LUAD, and negatively correlated to B cell and Dendritic cell infiltration levels. At the same time, B cell and Dendritic cell infiltration levels also related to the prognosis of LUAD. We further revealed AURKA and FAM83A could be novel targets to improve the prognosis of LUAD through regulated the response to immunomodulators.

Cigarette smoke extract induces pyroptosis in human bronchial epithelial cells through the ROS/NLRP3/caspase-1 pathway.

AIMS: Pyroptosis and inflammation are involved in the development of chronic obstructive pulmonary disease (COPD). However, the cigarette smoke-mediated mechanism of COPD remains unclear. In this study, we aimed to investigate the role of nucleotide-binding domain-like receptor protein-3 (NLRP3) inflammasome-mediated pyroptosis in the death of human bronchial epithelial (HBE) cells after cigarette smoke extract (CSE) exposure. MAIN METHODS: The protein level of NLRP3 in lung tissue was measured after cigarette smoke exposure in vivo. In vitro, HBE cells were treated with CSE. Subsequently, the activity of caspase-1, lactate dehydrogenase (LDH) release, release of interleukin (IL)-1ß and NLRP3 expression levels were measured. The involvement of reactive oxygen species (ROS) was also explored. KEY FINDINGS: After exposure to CSE, increased release of LDH, the transcriptional and translational upregulation of NLRP3, the caspase-1 activity levels, and enhanced IL-1ß and IL-18 release were observed in 16HBE cells. In addition, NLRP3 was required to activate the caspase-1. Our results suggested that pre-stimulated of 16HBE with a caspase-1 inhibitor, or using NLRP3 siRNA to silence NLRP3 expression, also caused the decrease of IL-1ß release and pyroptosis. SIGNIFICANCES: CSE induced inflammation and contributed to pyroptosis through the ROS/NLRP3/caspase-1 pathway in 16HBE cells. The NLRP3 inflammasome participates in CSE-induced HBE cell damage and pyroptosis, which could provide new insights into COPD.

RETRACTED: Down-regulation of miR-373 increases the radiosensitivity of lung cancer cells by targeting TIMP2.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief. The image analysis run on the Western blots in Figures 4 and 6 revealed that the images have been manipulated. Manipulating images in any part of a publication is ethically not acceptable.

Gamma Irradiation Upregulates B-cell Translocation Gene 2 to Attenuate Cell Proliferation of Lung Cancer Cells Through the JNK and NF-κB Pathways.

Gamma ray can promote cancer cell apoptosis and cell cycle arrest. It is often used in the clinical treatment of tumors, including lung cancer. In this study, we aimed to explore the role of gamma ray treatment and its correlation with BTG2 in cell proliferation, apoptosis, and cell cycle arrest regulation in a lung cancer cell line. A549 cell viability, apoptosis rate, and cell cycle were investigated after gamma ray treatment. We then used siRNA for BTG2 to detect the effect of BTG2 knockdown on the progress of gamma ray-treated lung cancer cells. Finally, we investigated the signaling pathway by which gamma ray might regulate BTG2. We found that gamma ray inhibited A549 cell viability and promoted apoptosis and cell cycle arrest, while BTG2 knockdown could relieve the effect caused by gamma ray on A549 cells. Moreover, we confirmed that the effect of BTG2 partly depends on p53 expression and gamma ray-promoting BTG2 expression through the JNK/NF-κB signaling pathway. Our study assessed the possible mechanism of gamma ray in tumor treatment and also investigated the role of BTG2 in gamma ray therapy. All these findings might give a deep understanding of the effect of gamma ray on the progression of lung cancer involving BTG2.