Development of six immune-related lncRNA signature prognostic model for smoking-positive lung adenocarcinoma

Decoding LncRNA in COPD: Unveiling Prognostic and Diagnostic Power and Their Driving Role in Lung Cancer Progression

Chronic obstructive pulmonary disease (COPD) and lung cancer represent formidable challenges in global health, characterized by intricate pathophysiological mechanisms and multifaceted disease progression. This comprehensive review integrates insights from diverse perspectives to elucidate the intricate roles of long non-coding RNAs (lncRNAs) in the pathogenesis of COPD and lung cancer, focusing on their diagnostic, prognostic, and therapeutic implications. In the context of COPD, dysregulated lncRNAs, such as NEAT1, TUG1, MALAT1, HOTAIR, and GAS5, emerge as pivotal regulators of genes involved in the disease pathogenesis and progression. Their identification, profiling, and correlation with the disease severity present promising avenues for prognostic and diagnostic applications, thereby shaping personalized disease interventions. These lncRNAs are also implicated in lung cancer, underscoring their multifaceted roles and therapeutic potential across both diseases. In the domain of lung cancer, lncRNAs play intricate modulatory roles in disease progression, offering avenues for innovative therapeutic approaches and prognostic indicators. LncRNA-mediated immune responses have been shown to drive lung cancer progression by modulating the tumor microenvironment, influencing immune cell infiltration, and altering cytokine production. Their dysregulation significantly contributes to tumor growth, metastasis, and chemo-resistance, thereby emphasizing their significance as therapeutic targets and prognostic markers. This review summarizes the transformative potential of lncRNA-based diagnostics and therapeutics for COPD and lung cancer, offering valuable insights into future research directions for clinical translation and therapeutic development.

Building endoplasmic reticulum stress-related LncRNAs signatures of lung adenocarcinoma

BACKGROUND

Endoplasmic reticulum stress (ERS) could be a strategy for treating malignant tumors. Moreover, long noncoding RNAs (lncRNAs) can promote tumorigenesis and progression, and forecast the prognosis of cancers. Nevertheless, the prognostic value of ERS-related lncRNAs has not been reported in lung adenocarcinoma (LUAD).

METHODS

The messenger RNA (mRNA), microRNA (miRNA) and lncRNA expression data related to LUAD were obtained in public databases (TCGA and GEO databases). Prognostic ERS-related differentially expressed lncRNAs (ERS-DELs) were obtained and used to build an ERS-related model by Cox regression analysis. Moreover, we further screened independent prognostic elements and built a nomogram. Furthermore, enrichment analysis of genes was conducted to investigate the functions. A lncRNA-miRNA-mRNA network was built to explore mechanism of lncRNAs. Finally, qRT-PCR was utilized to examine the expression levels of lncRNAs.

RESULTS

30 ERS-DELs were identified, and an ERS-related signature was built based on AF131215.2, LINC00472, LINC01352, RP1-78O14.1, RP11-253E3.3, RP11-98D18.9, and SNHG12. Gene set enrichment analysis indicated that genes in the high-risk group were chiefly focused on the regulation of mRNA binding, and genes in the low-risk group were significantly focused on protein localization to cilia. A lncRNA-miRNA-mRNA network, containing 7 signature lncRNAs, 23 miRNAs, and 128 mRNAs, was also established. Eventually, quantitative real-time polymerase chain reaction was used to confirm that seven prognostic lncRNAs had a consistent expression with the analysis.

CONCLUSIONS

An ERS-related signature containing seven prognostic lncRNAs was built, which offered new thinking concerning the role of ERS-related lncRNAs in LUAD.

Comprehensive analysis of m6A modification patterns and m6A-related lncRNAs as potential biomarkers in lung adenocarcinoma

BACKGROUND

N6-methyladenosine (m6A) methylation is considered to induce tumor cell proliferation, migration, and apoptosis. Understanding the mechanism of m6A-related lncRNAs in the development of lung adenocarcinoma (LUAD) may help predict prognosis.

METHODS

m6A-related lncRNAs related to lung cancer were identified and combined with the MeRIP-Seq dataset. The consensus clustering method was utilized to divide LUAD patients, and prognostic model was constructed using the Lasso Cox algorithm. The cluster profiler package was used for gene ontology and KEGG enrichment. The proportion of immune infiltration was estimated using the CIBERSORT algorithm. The decision tree was constructed by the rpart package, and nomograms were built by the rms package. The Connectivity Map database was analyzed for the therapeutic effects of small molecule drugs for LUAD. In addition, qPCR, colony formation and transwell assays were performed to validate functions of m6A-associated lncRNAs.

RESULTS

Nineteen m6A-modified lncRNAs in LUAD were identified. LUAD patients were divided into two categories based on the expression of 19 m6A-related lncRNAs. Cluster 2 patients had better antigen production and expression, while naive B cells, plasma cells, and activated NK cells were lower in cluster 1. Nine m6A-related lncRNAs were selected to establish a risk model for evaluating the prognosis of LUAD patients. The high-risk group had higher tumor mutational burden and lower TIDE scores with more gamma delta T cells and neutrophils. Nomograms showed that the prognostic model had predominant predictive ability for LUAD patients based on the risk score analyzed by the decision tree model. Benzo(a)pyrene and neurodazine might improve the prognosis of LUAD patients. The qRT-PCR results confirmed the reliability of the analytical results.

CONCLUSION

The establishment of a prognostic model of m6A-related lncRNAs can independently predict overall survival in LUAD and may help to develop personalized immunotherapy strategies.

Epigenetic mechanisms of nicotine dependence

Smoking continues to be a leading cause of preventable disease and death worldwide. Nicotine dependence generates a lifelong propensity towards cravings and relapse, presenting an ongoing challenge for the development of treatments. Accumulating evidence supports a role for epigenetics in the development and maintenance of addiction to many drugs of abuse, however, the involvement of epigenetics in nicotine dependence is less clear. Here we review evidence that nicotine interacts with epigenetic mechanisms to enable the maintenance of nicotine-seeking across time. Research across species suggests that nicotine increases permissive histone acetylation, decreases repressive histone methylation, and modulates levels of DNA methylation and noncoding RNA expression throughout the brain. These changes are linked to the promoter regions of genes critical for learning and memory, reward processing and addiction. Pharmacological manipulation of enzymes that catalyze core epigenetic modifications regulate nicotine reward and associative learning, demonstrating a functional role of epigenetic modifications in nicotine dependence. These findings are consistent with nicotine promoting an overall permissive chromatin state at genes important for learning, memory and reward. By exploring these links through next-generation sequencing technologies, epigenetics provides a promising avenue for future interventions to treat nicotine dependence.

Prediction of Prognosis and Chemotherapeutic Sensitivity Based on Cuproptosis-Associated lncRNAs in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is the fourth most common cancer. The 5-year survival rate for metastatic cervical cancer is less than 10%. The survival time of patients with recurrent cervical cancer is approximately 13-17 months. Cuproptosis is a novel type of cell death related to mitochondrial respiration. Accumulative studies showed that long non-coding RNAs (lncRNAs) regulated cervical cancer progression. Compressive bioinformatic analysis showed that nine cuproptosis-related lncRNAs (CRLs), including C002128.2, AC002563.1, AC009237.14, AC048337.1, AC145423.1, AL117336.1, AP001542.3, ATP2A1-AS1, and LINC00426, were independently correlated with the overall survival (OS) of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients. The time-dependent area under curve value reached 0.716 at 1 year, 0.718 at 3 years, and 0.719 at 5 years. Notably, CESC patients in the low-risk group had increased immune cell infiltration and expression of several immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade therapy. In addition, we also used the model for drug sensitivity analysis. Several drug sensitivities were more sensitive in high-risk patients and showed significant correlations with the risk models, such as Bortezomib_1191, Luminespib_1559, and Rapamycin_1084, suggesting that these drugs may be candidate clinical drugs for patients with a high risk of CESC. In summary, this study further explored the mechanism of CRLs in CESC and provided a more optimized prognostic model and some insights into chemotherapy of CESC.