Cuproptosis is a newly form of cell death. Cuproptosis related lncRNA in lung adenocarcinoma (LUAD) has also not been fully elucidated. In the present study, we aimed to construct a prognostic signature based on cuproptosis-related lncRNA in LUAD and investigate its association with immunotherapy response. The RNA-sequencing data, clinical information and simple nucleotide variation of LUAD patients were obtained from TCGA database. The LASSO Cox regression was used to construct a prognostic signature. The CIBERSORT, ESTIMATE and ssGSEA algorithms were applied to assess the association between risk score and TME. TIDE score was applied to reflect the efficiency of immunotherapy response. The influence of overexpression of lncRNA TMPO-AS1 on A549 cell was also assessed by in vitro experiments. The lncRNA prognostic signature included AL606834.1, AL138778.1, AP000302.1, AC007384.1, AL161431.1, TMPO-AS1 and KIAA1671-AS1. Low-risk group exhibited much higher immune score, stromal score and ESTIMATE score, but lower tumor purity compared with high-risk groups. Also, low-risk group was associated with a much higher score of immune cells and immune related function sets, indicating an immune activation state. Low-risk patients had relative higher TIDE score and lower TMB. External validation using IMvigor210 immunotherapy cohort demonstrated that low-risk group had a better prognosis and might more easily benefit from immunotherapy. Overexpression of lncRNA TMPO-AS1 promoted the proliferation, migration and invasion of A549 cell line. The novel cuproptosis-related lncRNA signature could predict the prognosis of LUAD patients, and helped clinicians stratify patients appropriate for immunotherapy and determine individual therapeutic strategies.

Background: Aberrant DNA methylation is an early event during tumorigenesis. In the present study, we aimed to construct a methylation diagnostic tool using urine sediment for the detection of urothelial bladder carcinoma, and improved the diagnostic performance of the model by incorporating single-nucleotide polymorphism (SNP) sites. Methods: A three-stage analysis was carried out to construct the model and evaluate the diagnostic performance. In stage I, two small cohorts from Xiangya hospital were recruited to validate and identify the detailed regions of collected methylation biomarkers. In stage II, proof-of-concept study cohorts from the Hunan multicenter were recruited to construct a diagnostic tool. In stage III, a blinded cohort comprising suspicious UBC patients was recruited from Beijing single center to further test the robustness of the model. Results: In stage I, single NRN1 exhibited the highest AUC compared with six other biomarkers and the Random Forest model. At the best cutoff value of 5.16, a single NRN1 biomarker gave a diagnosis with a sensitivity of 0.93 and a specificity of 0.97. In stage II, the Random Forest algorithm was applied to construct a diagnostic tool, consisting of NRN1, TERT C228T and FGFR3 p.S249C. The tool exhibited AUC values of 0.953, 0.946 and 0.951 in training, test and all cohorts. At the best cutoff value, the model resulted in a sensitivity of 0.871 and a specificity of 0.947. In stage III, the diagnostic tool achieved a good discrimination in the external validation cohort, with an overall AUC of 0.935, sensitivity of 0.864 and specificity of 0.895. Additionally, the model exhibited a superior sensitivity and comparable specificity compared with conventional cytology and FISH. Conclusions: The diagnostic tool exhibited a highly specific and robust performance. It may be used as a replaceable approach for the detection of UBC.

Background: Although significant progress has been made in immunotherapy for lung adenocarcinoma (LUAD), there is an urgent need to identify effective indicators to screen patients who are suitable for immunotherapy. Systematically investigating the cuproptosis-related genes (CRGs) in LUAD may provide new ideas for patients’ immunotherapy stratification. Method: We comprehensively analyzed the landscape of 12 CRGs in a merged TCGA and GEO LUAD cohort. We investigated the associations between tumor microenvironment and immunophenotypes. We utilized a risk score to predict the prognosis and immunotherapy response for an individual patient. Additionally, we conducted CCK-8 experiments to evaluate the impact of DLGAP5 knockdown on A549 cell proliferation. Result: We utilized an integrative approach to analyze 12 CRGs and differentially expressed genes (DEGs) in LUAD samples, resulting in the identification of two distinct CRG clusters and two gene clusters. Based on these clusters, we generated immunophenotypes and observed that the inflamed phenotype had the most abundant immune infiltrations, while the desert phenotype showed the poorest immune infiltrations. We then developed a risk score model for individual patient prognosis and immunotherapy response prediction. Patients in the low-risk group had higher immune scores and ESTIMATE scores, indicating an active immune state with richer immune cell infiltrations and higher expression of immune checkpoint genes. Moreover, the low-risk group exhibited better immunotherapy response according to IPS, TIDE scores, and Imvigor210 cohort validation results. In addition, our in vitro wet experiments demonstrated that DLGAP5 knockdown could suppress the cell proliferation of A549. Conclusion: Novel cuproptosis molecular patterns reflected the distinct immunophenotypes in LUAD patients. The risk model might pave the way to stratify patients suitable for immunotherapy and predict immunotherapy response.