Long noncoding RNAs AC026904.1 is essential for TGF-β-induced migration and epithelial-mesenchymal transition through functioning as an enhancer of Slug in lung cancer cells

Investigating the prognostic role of lncRNAs associated with disulfidptosis-related genes in clear cell renal cell carcinoma

INTRODUCTION

Renal cell carcinoma (RCC) is a grave malignancy that poses a significant global health burden with over 400,000 new cases annually. Disulfidptosis, a newly discovered programmed cell death process, is linked to the actin cytoskeleton, which plays a vital role in maintaining cell shape and survival. The role of disulfidptosis is poorly depicted in the clear cell histologic variant of RCC (ccRCC).

METHODS

Three sets of ccRCC cohorts, ICGC_RECA-EU (n = 91), GSE76207 (n = 32) and TCGA-KIRC (n = 607), were included in our study, the batch effect of which was removed using the "combat" function. Correlation was calculated using the "rcorr" function of the "Hmisc" package for Pearson analysis, which was visualized using the "pheatmap" package. Principal component analysis was performed by the "vegan" package, visualized using the "scatterplot3d" package. Long non-coding RNAs (lncRNAs) associated with disulfidptosis were screened out using least absolute shrinkage and selection operator (LASSO) and COX analysis. Tumor mutation, immune landscaping and immunotherapy prediction were performed for further characterization of two risk groups.

RESULTS

A total of 1822 disulfidptosis-related lncRNAs was selected, among which 308 lncRNAs were found to be significantly associated with the clinical outcome of ccRCC patients. We retained 11 disulfidptosis-related lncRNAs, namely, AP000439.3, RP11-417E7.1, RP11-119D9.1, LINC01510, SNHG3, AC156455.1, RP11-291B21.2, EMX2OS, AC093850.2, HAGLR and RP11-389C8.2, through LASSO and COX analysis for prognosis model construction, which displayed satisfactory accuracy (area under the curve, AUC, values all above 0.6 in multiple cohorts) in stratification of ccRCC prognosis. A nomogram model was constructed by integrating clinical factors with risk score, which further enhanced the prediction efficacy (AUC values all above 0.7 in multiple cohorts). We found that patients of male gender, higher clinical stages and advanced pathological T stage were inclined to have higher risk score values. Dactinomycin_1911, Vinblastine_1004, Daporinad_1248 and Vinorelbine_2048 were identified as promising candidate drugs for treating ccRCC patients of higher risk score value. Moreover, patients of higher risk value were prone to be resistant to immunotherapy.

CONCLUSION

We developed a prognosis predicting model based on 11 selected disulfidptosis-related lncRNAs, the efficacy of which was verified in different cohorts. Furthermore, we delineated an intricate portrait of tumor mutation, immune topography and pharmacosensitivity evaluations within disparate risk stratifications.

Improved prediction of prognosis and therapy response for lung adenocarcinoma after identification of DNA-directed RNA polymerase-associated lncRNAs

BACKGROUND

DNA-directed RNA polymerase (DDRP) related genes and long non-coding RNAs (lncRNAs) play an important role in the development of lung adenocarcinoma (LUAD), the leading cause of cancer-related death worldwide. Therefore, we aimed to construct a DDRP-associated lncRNA model to predict the prognosis of LUAD and to evaluate its sensitivity to immunotherapy and chemotherapy.

METHODS

To construct a predictive signature, we used univariate and multivariate Cox regression analyses, as well as the least absolute shrinkage and selection operator regression analysis. The prognostic model was verified by applying the ROC curve analysis, Kaplan-Meier analysis, GO/KEGG analysis, and a predictive nomogram. Eventually, immunotherapy and drug susceptibility were examined and stemness indices were analyzed.

RESULTS

24 DDRP-associated lncRNAs were found as independent prognosis factors, which may be further developed as potential therapeutic vaccines for LUAD. The area under the ROC curve and the conformance index showed that the constructed model can predict the prognosis of LUAD patients. The predicted incidences of overall survival showed perfect conformance. And there were significant changes in immunological markers between the two risk subgroups in the model. Finally, an analysis of 50% maximum inhibitory concentration between the two risk subgroups showed that the high-risk subgroup was more sensitive to certain chemotherapy drugs.

CONCLUSION

We constructed a model that accurately predicts the outcomes of LUAD based on 24 DDRP-related lncRNAs and provided promising treatment options for the future.

Keep your eyes peeled for long noncoding RNAs: Explaining their boundless role in cancer metastasis, drug resistance, and clinical application

Cancer metastasis and drug resistance are two major obstacles in the treatment of cancer and therefore, the leading cause of cancer-associated mortalities worldwide. Hence, an in-depth understanding of these processes and identification of the underlying key players could help design a better therapeutic regimen to treat cancer. Earlier thought to be merely transcriptional junk and having passive or secondary function, recent advances in the genomic research have unravelled that long noncoding RNAs (lncRNAs) play pivotal roles in diverse physiological as well as pathological processes including cancer metastasis and drug resistance. LncRNAs can regulate various steps of the complex metastatic cascade such as epithelial-mesenchymal transition (EMT), invasion, migration and metastatic colonization, and also affect the sensitivity of cancer cells to various chemotherapeutic drugs. A substantial body of literature for more than a decade of research evince that lncRNAs can regulate gene expression at different levels such as epigenetic, transcriptional, posttranscriptional, translational and posttranslational levels, depending on their subcellular localization and through their ability to interact with DNA, RNA and proteins. In this review, we mainly focus on how lncRNAs affect cancer metastasis by modulating expression of key metastasis-associated genes at various levels of gene regulation. We also discuss how lncRNAs confer cancer cells either sensitivity or resistance to various chemo-therapeutic drugs via different mechanisms. Finally, we highlight the immense potential of lncRNAs as prognostic and diagnostic biomarkers as well as therapeutic targets in cancer.

The role of exosomes in lung cancer metastasis and clinical applications: an updated review

Lung cancer is the leading cause of cancer-associated deaths accounting for 24% of all cancer deaths. As a crucial phase of tumor progression, lung cancer metastasis is linked to over 70% of these mortalities. In recent years, exosomes have received increasing research attention in their role in the induction of carcinogenesis and metastasis in the lung. In this review, recent studies on the contribution of exosomes to lung cancer metastasis are discussed, particularly highlighting the role of lung tumor-derived exosomes in immune system evasion, epithelial-mesenchymal transition, and angiogenesis, and their involvement at both the pre-metastatic and metastatic phases. The clinical application of exosomes as therapeutic drug carriers, their role in antitumor drug resistance, and their utility as predictive biomarkers in diagnosis and prognosis are also presented. The metastatic activity, a complex multistep process of cancer cell invasion, survival in blood vessels, attachment and subsequent colonization of the host's organs, is integrated with exosomal effects. Exosomes act as functional mediating factors in cell-cell communication, influencing various steps of the metastatic cascade. To this end, lung cancer cell-derived exosomes enhance cell proliferation, angiogenesis, and metastasis, regulate drug resistance, and antitumor immune activities during lung carcinogenesis, and are currently being explored as an important component in liquid biopsy assessment for diagnosing lung cancer. These nano-sized extracellular vesicles are also being explored as delivery vehicles for therapeutic molecules owing to their unique properties of biocompatibility, circulatory stability, decreased toxicity, and tumor specificity. The current knowledge of the role of exosomes highlights an array of exosome-dependent pathways and cargoes that are ripe for exploiting therapeutic targets to treat lung cancer metastasis, and for predictive value assessment in diagnosis, prognosis, and anti-tumor drug resistance.