Exploring the Prognostic Significance and Immunotherapeutic Potential of Single-Cell Sequencing-Identified Long Noncoding RNA (LncRNA) in Patients With Non-small Cell Lung Cancer.

BACKGROUND: Single-cell RNA sequencing technology can provide insight into lung cancer. The purpose of this study was to analyze the relationship between long noncoding RNA (lncRNA) discovered by RNA sequencing and immunotherapy in patients with non-small cell lung cancer (NSCLC). METHODS: In this study, we utilized data from The Cancer Genome Atlas (TCGA) to extract gene expression data and prognostic information from patients with NSCLC. We employed univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analyses to construct risk models, and Kaplan-Meier (KM) analysis to compare survival differences between high- and low-risk groups. To evaluate the accuracy of our risk model predictions, we utilized a nomogram, calibration curve, correlation index curve (C-index), and receiver operating characteristic (ROC). Additionally, we conducted Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to investigate the differential expression of lncRNA genes. We also used the tumor immune dysfunction and exclusivity (TIDE) algorithm and the R package "pRRophetic" to analyze the tumor microenvironment. Finally, we utilized stem cell indices based on mRNA expression-based stemness index (mRNAsi) expression to better assess patient prognosis. RESULTS: Our analysis identified a set of 28 lncRNAs with prognostic risk profiles in patients with lung adenocarcinoma. Notably, patients in the low-risk group exhibited significantly better overall survival (OS) compared to those in the high-risk group. Kaplan-Meier (KM) survival curves revealed that these prognostic risk markers accurately predicted survival outcomes in non-small cell lung cancer (NSCLC) patients. MerCK18 and myeloid-derived suppressor cells (MDSC) were strongly associated with immune escape and immunotherapy in high- and low-risk subgroups. In our investigation of potential chemotherapeutic agents for the treatment of NSCLC, we screened a total of 60 agents and found that PPM1D was more effective in the low-risk group. However, we did not observe a strong correlation between the stem cell index mRNAsi and OS. CONCLUSION: Our study highlights the close association between lncRNAs and prognostic risk profiles and the prognosis of patients with non-small cell lung cancer, offering a promising avenue for the clinical implementation of immunotherapy.

Development and application of oncolytic viruses as the nemesis of tumor cells.

Viruses and tumors are two pathologies that negatively impact human health, but what occurs when a virus encounters a tumor? A global consensus among cancer patients suggests that surgical resection, chemotherapy, radiotherapy, and other methods are the primary means to combat cancer. However, with the innovation and development of biomedical technology, tumor biotherapy (immunotherapy, molecular targeted therapy, gene therapy, oncolytic virus therapy, etc.) has emerged as an alternative treatment for malignant tumors. Oncolytic viruses possess numerous anti-tumor properties, such as directly lysing tumor cells, activating anti-tumor immune responses, and improving the tumor microenvironment. Compared to traditional immunotherapy, oncolytic virus therapy offers advantages including high killing efficiency, precise targeting, and minimal side effects. Although oncolytic virus (OV) therapy was introduced as a novel approach to tumor treatment in the 19th century, its efficacy was suboptimal, limiting its widespread application. However, since the U.S. Food and Drug Administration (FDA) approved the first OV therapy drug, T-VEC, in 2015, interest in OV has grown significantly. In recent years, oncolytic virus therapy has shown increasingly promising application prospects and has become a major research focus in the field of cancer treatment. This article reviews the development, classification, and research progress of oncolytic viruses, as well as their mechanisms of action, therapeutic methods, and routes of administration.

Correlation between chromatin epigenetic-related lncRNA signature (CELncSig) and prognosis, immune microenvironment, and immunotherapy in non-small cell lung cancer.

Chromatin regulators drive cancer epigenetic changes, and lncRNA can play an important role in epigenetic changes as chromatin regulators. We used univariate Cox, LASSO, and multivariate Cox regression analysis to select epigenetic-associated lncRNA signatures. Twenty-five epigenetic-associated lncRNA signatures (CELncSig) were identified to establish the immune prognostic model. According to Kaplan-Meier analysis, the overall survival of the high-risk group was significantly lower than the low-risk group. Receiver operating characteristic (ROC) curves, C-index, survival curve, nomogram, and principal component analysis (PCA) were performed to validate the risk model. In GO/KEGG analysis, differentially expressed lncRNAs were correlated with the PI3K-Akt pathway, suggesting that they were highly associated with the metastasis of LUAD. Interestingly, in the immune escape analysis, the TIDE score was lower, and the possibility of immune dysfunction is also slighter in the high-risk group, which means they still have the potential to receive immunotherapy. And CELncsig is highly correlated with immune pathways T_cell_co-inhibition and Check-point. Also, the IMvigor210 cohort analysis indicated that our risk-scoring model has significant potential clinical application value in lung cancer immunotherapy. And we also screened out ten potential chemotherapy agents using the 'pRRophetic' package.

Risk score = LncRNAs associated with doxorubicin metabolism can be used as molecular markers for immune microenvironment and immunotherapy in non-small cell lung cancer.

Doxorubicin is the most effective anthracycline chemotherapy drug in the treatment of cancer, and it is an effective single agent in the treatment of non-small cell lung cancer (NSCLC). There is a lack of studies on the differentially expressed doxorubicin metabolism-related lncRNAs in NSCLC. In this study, we extracted related genes from the TCGA database and matched them with lncRNAs. Doxorubicin metabolism-related lncRNA-based gene signatures (DMLncSig) were gradually screened from univariate regression, LASSO regression, and multivariate regression analysis, and the risk score model was constructed. These DMLncSig were subjected to a GO/KEGG analysis. We then used the risk model to construct the TME model and analyze drug sensitivity. The IMvigor 210 immunotherapy model was cited for validation. Eventually, we performed tumor stemness index differences, survival, and clinical correlation analyses.

Comprehensive transcriptomic and co-expression analysis of ABL1 gene and molecularly targeted drugs in hepatocellular carcinoma based on multi-database mining.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. Consequently, it is essential to identify biomarkers for treatment response and the prognosis prediction. We investigated whether ABL1 can function as a biomarker or a drug target for HCC. We assessed the ABL1 expression, genetic alterations and patients' survival from LinkedOmics, GEO, TCGA and Human Protein Atlas. We analyzed PPI, GO and KEGG pathways. GSEA was analyzed for functional comparison. The current drugs targeting ABL1 were statistically analyzed using DRUGSURV and DGIdb database. We found ABL1 is overexpressed in HCC and its higher expression reduces survival probability. Genetic changes of ABL1 are not frequent. We screened out 25 differentially expressed genes correlated with ABL1. The top functions of ABL1 are biological regulation, metabolic process, protein-containing, and protein binding. KEGG pathways showed that ABL1 and correlated with ABL1 significantly genes markedly enriched in the ErbB signaling pathway, and pathways in cancer. We counted the existing drugs targeting ABL1, which indicates that inhibiting ABL1 expression may improve the survival probability of HCC. In conclusion, ABL1 plays a crucial role in the development and progression of this cancerization and is a potential drug target.