Identification and Verification of Metabolism-related Immunotherapy Features and Prognosis in Lung Adenocarcinoma.

BACKGROUND: Lung cancer is a frequent malignancy with a poor prognosis. Extensive metabolic alterations are involved in carcinogenesis and could, therefore, serve as a reliable prognostic phenotype. AIMS: Our study aimed to develop a prognosis signature and explore the relationship between metabolic characteristic-related signature and immune infiltration in lung adenocarcinoma (LUAD). OBJECTIVE: TCGA-LUAD and GSE31210 datasets were used as a training set and a validation set, respectively. METHOD: A total of 513 LUAD samples collected from The Cancer Genome Atlas database (TCGA-LUAD) were used as a training dataset. Molecular subtypes were classified by consensus clustering, and prognostic genes related to metabolism were analyzed based on Differentially Expressed Genes (DEGs), Protein-Protein Interaction (PPI) network, the univariate/multivariate- and Lasso- Cox regression analysis. RESULTS: Two molecular subtypes with significant survival differences were divided by the metabolism gene sets. The DEGs between the two subtypes were identified by integrated analysis and then used to develop an 8-gene signature (TTK, TOP2A, KIF15, DLGAP5, PLK1, PTTG1, ECT2, and ANLN) for predicting LUAD prognosis. Overexpression of the 8 genes was significantly correlated with worse prognostic outcomes. RiskScore was an independent factor that could divide LUAD patients into low- and high-risk groups. Specifically, high-risk patients had poorer prognoses and higher immune escape. The Receiver Operating Characteristic (ROC) curve showed strong performance of the RiskScore model in estimating 1-, 3- and 5-year survival in both training and validation sets. Finally, an optimized nomogram model was developed and contributed the most to the prognostic prediction in LUAD. CONCLUSION: The current model could help effectively identify high-risk patients and suggest the most effective drug and treatment candidates for patients with LUAD.

Regulation of tumorigenesis and ferroptosis in non-small cell lung cancer by a novel BBOX1-AS1/miR-326/PROM2 axis.

Dysregulation of long non-coding RNAs (lncRNAs) is associated with the tumorigenesis and ferroptosis of non-small cell lung cancer (NSCLC). BBOX1 antisense RNA 1 (BBOX1-AS1) functions as an oncogenic driver in NSCLC. Here, we aim to investigate the regulation effect and underlying mechanism of BBOX1-AS1 in NSCLC progression and ferroptosis. RNA expression was detected by quantitative real-time PCR (qRT-PCR), and protein expression was measured by immunoblotting. Cell growth was assessed by CCK-8 and colony formation assays. Transwell assay was applied to evaluate cell invasion and migration. RNA pull-down and dual-luciferase reporter assays were applied to verify the relationship between miR-326 and BBOX1-AS1 or prominin 2 (PROM2). The role of BBOX1-AS1 in NSCLC tumorigenicity was also analyzed by xenograft assays. Silencing BBOX1-AS1 or PROM2 impeded NSCLC cell growth, migration, and invasion. Silencing BBOX1-AS1 induced cell apoptosis and ferroptosis. BBOX1-AS1 up-regulated PROM2 expression, and re-expression of PROM2 reversed the effects of BBOX1-AS1 depletion on cell malignant phenotypes and ferroptosis. BBOX1-AS1 post-transcriptionally modulated PROM2 expression by sponging miR-326. MiR-326 was validated as a mediator of BBOX1-AS1 in regulating NSCLC cell malignant phenotypes and ferroptosis. Additionally, BBOX1-AS1 deficiency in vivo resulted in the suppression of xenograft tumor growth. Together, our study defines a novel BBOX1-AS1/miR-326/PROM2 axis in regulating NSCLC malignant progression and ferroptosis, offering new evidence for the oncogenic role of BBOX1-AS1 in NSCLC. These findings may provide a basis for the future usage of targeting BBOX1-AS1 in NSCLC treatment.

Metabolic heterogeneity in early-stage lung adenocarcinoma revealed by RNA-seq and scRNA-seq.

PURPOSE: Cancer cells maintain cell growth, division, and survival through altered energy metabolism. However, research on metabolic reprogramming in lung adenocarcinoma (LUAD) is limited METHODS: We downloaded TCGA and GEO sequencing data. Consistent clustering with the ConsensusClusterPlus package was employed to detect the scores for four metabolism-related pathways. The LUAD samples in the TCGA dataset were clustered with ConsensusClusterPlus, and the optimal number of clusters was determined according to the cumulative distribution function (CDF). The cell score for each sample in the TCGA dataset was calculated using the MCPcounter estimate function of the MCPcounter package. RESULTS: We identified two subtypes by scoring the samples based on the 4 metabolism-related pathways and cluster dimensionality reduction. The prognosis of cluster B was obviously poorer than that of cluster A in patients with LUAD. The analysis of single-nucleotide variation (SNV) data showed that the top 15 genes in the four metabolic pathways with the most mutations were TKTL2, PGK2, HK3, EHHADH, GLUD2, PKLR, TKTL1, HADHB, CPT1C, HK1, HK2, PFKL, SLC2A3, PFKFB1, and CPT1A. The IFNγ score of cluster B was significantly higher than that of cluster A. The immune T-cell lytic activity score of cluster B was significantly higher than that of cluster A. We further identified 5 immune cell subsets from single-cell sequencing data. The top 5 marker genes of B cells were IGHM, JCHAIN, IGLC3, IGHA1, and IGKC. The C0 subgroup of monocytes had a higher pentose phosphate pathway (PPP) score than the C6 subgroup. CONCLUSIONS: Metabolism-related subtypes could be potential biomarkers in the prognosis prediction and treatment of LUAD.

Regulatory mechanisms and potential medical applications of HNF1A-AS1 in cancers.

Long noncoding RNAs (lncRNAs) are defined as a class of non-protein-coding RNAs that are longer than 200 nucleotides. Previous studies have shown that lncRNAs play a vital role in the progression of multiple diseases, which highlights their potential for medical applications. The lncRNA hepatocyte nuclear factor 1 homeobox A (HNF1A) antisense RNA 1 (HNF1A-AS1) is known to be abnormally expressed in multiple cancers. HNF1A-AS1 exerts its oncogenic roles through a variety of molecular mechanisms. Moreover, aberrant HNF1A-AS1 expression is associated with diverse clinical features in cancer patients. Therefore, HNF1A-AS1 is a promising biomarker for tumor diagnosis and prognosis and thus a potential candidate for tumor therapy. This review summarizes current studies on the role and the underlying mechanisms of HNF1A-AS1 various cancer types, including gastric cancer, liver cancer, glioma, lung cancer, colorectal cancer, breast cancer, bladder cancer, osteosarcoma, esophageal adenocarcinoma, hemangioma, oral squamous cell carcinoma, laryngeal squamous cell carcinoma, cervical cancer, as well as gastroenteropancreatic neuroendocrine neoplasms. We also describe the diagnostic, prognostic, and therapeutic value of HNF1A-AS1 for multiple cancer patients.

Ganoderic acid B attenuates LPS-induced lung injury.

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is a serious respiratory disease, the mechanism is unclear. This paper revealed the mechanism of ganoderic acid B (BB) on lipopolysaccharide-induced pneumonia in mice. Pneumonia model was induced by LPS in mice and A549 cells. Lung dry/wet weight (W/D) and myeloperoxidase (MPO) activity in lung were examined. Lung histopathological changes was observed by HE staining. Superoxide dismutase (SOD), malondialdehyde (MDA) and proinflammatory cytokines, including tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß) and interleukin-6 (IL-6) in mice and A549 cells were detected. Rho/NF-κB pathway in mice and A549 cells were examined by Western Blot. BB significantly reduced W/D and MPO activity, restored lung histopathological changes. BB also increased SOD, decreased MDA, TNF-α, IL-1ß and IL-6 in mice and A549 cells. In addition, BB inhibited Rho/NF-κB pathway in mice and A549 cells. BB has protective effect on LPS-induced pneumonia in mice, and its mechanism is related to the regulation of Rho/NF-κB signaling pathway.