Comprehensive analysis of cuproptosis-related lncRNAs in the prognosis and therapy response of patients with bladder cancer

Research progress of N1-methyladenosine RNA modification in cancer

N1-methyladenosine (m1A) is a post-transcriptionally modified RNA molecule that plays a pivotal role in the regulation of various biological functions and activities. Especially in cancer cell invasion, proliferation and cell cycle regulation. Over recent years, there has been a burgeoning interest in investigating the m1A modification of RNA. Most studies have focused on the regulation of m1A in cancer enrichment areas and different regions. This review provides a comprehensive overview of the methodologies employed for the detection of m1A modification. Furthermore, this review delves into the key players in m1A modification, known as the "writers," "erasers," and "readers." m1A modification is modified by the m1A methyltransferases, or writers, such as TRMT6, TRMT61A, TRMT61B, TRMT10C, NML, and, removed by the demethylases, or erasers, including FTO and ALKBH1, ALKBH3. It is recognized by m1A-binding proteins YTHDF1, TYHDF2, TYHDF3, and TYHDC1, also known as "readers". Additionally, we explore the intricate relationship between m1A modification and its regulators and their implications for the development and progression of specific types of cancer, we discuss how m1A modification can potentially facilitate the discovery of novel approaches for cancer diagnosis, treatment, and prognosis. Our summary of m1A methylated adenosine modification detection methods and regulatory mechanisms in various cancers provides useful insights for cancer diagnosis, treatment, and prognosis. Video Abstract.

Four types of adenine-related RNA modification writers -mediated molecular subtypes contribute to predicting clinical outcomes and treatment options in bladder cancer

Rationale

RNA modifications, containing m6A, m1A, alternative polyadenylation and adenosine-to-inosine RNA editing, involve in critical cancerous immunity and cancerous processes. However, the functional roles of RNA modification writers in bladder cancer (BLCA) are largely unknown.

Methods

In this study, unsupervised clustering was used to identify novel RNA modification writers -mediated molecular subtypes in BLCA. A corresponding quantitative indicator called WriterScore was developed using univariate Cox and Least absolute shrinkage and selection operator (LASSO) analysis. Then, we systematically analyzed the correlation between RNA modification writer-related clusters (WriterScore) and immunological characteristics, classical molecular subtypes, clinicopathologic features and treatment options in BLCA. Finally, we validated the WriterScore in multiple other external BLCA datasets, clinical sample dataset in Shengjing Hospital and pancancer.

Results

Two RNA modification writer-related clusters and three DEGclusters were obtained. These RNA modification writer-related clusters (WriterScore) were strongly associated with immunological characteristics, classical molecular subtypes, clinicopathologic features of BLCA. Moreover, WriterScore can properly predict the clinical outcomes and immunotherapy of BLCA patients.

Conclusion

Our study systematically investigated the role of RNA modification writers and developed a significant WriterScore to guide several treatment options in BLCA, which might bring some potential benefits for BLCA patients.

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.

Construction of prognostic risk model of bladder cancer based on cuproptosis-related long non-coding RNAs

OBJECTIVES

To construct a prognosis risk model based on long noncoding RNAs (lncRNAs) related to cuproptosis and to evaluate its application in assessing prognosis risk of bladder cancer patients.

METHODS

RNA sequence data and clinical data of bladder cancer patients were downloaded from the Cancer Genome Atlas database. The correlation between lncRNAs related to cuproptosis and bladder cancer prognosis was analyzed with Pearson correlation analysis, univariate Cox regression, Lasso regression, and multivariate Cox regression. Then a cuproptosis-related lncRNA prognostic risk scoring equation was constructed. Patients were divided into high-risk and low-risk groups based on the median risk score, and the immune cell abundance between the two groups were compared. The accuracy of the risk scoring equation was evaluated using Kaplan-Meier survival curves, and the application of the risk scoring equation in predicting 1, 3 and 5-year survival rates was evaluated using receiver operating characteristic (ROC) curves. Univariate and multivariate Cox regression were used to screen for prognostic factors related to bladder cancer patients, and a prognostic risk assessment nomogram was constructed, the accuracy of which was evaluated with calibration curves.

RESULTS

A prognostic risk scoring equation for bladder cancer patients was constructed based on nine cuproptosis-related lncRNAs. Immune infiltration analysis showed that the abundances of M0 macrophages, M1 macrophages, M2 macrophages, resting mast cells and neutrophils in the high-risk group were significantly higher than those in the low-risk group, while the abundances of CD8+ T cells, helper T cells, regulatory T cells and plasma cells in the low-risk group were significantly higher than those in the high-risk group (all P<0.05). Kaplan-Meier survival curve analysis showed that the total survival and progression-free survival of the low-risk group were longer than those of the high-risk group (both P<0.01). Univariate and multivariate Cox analysis showed that the risk score, age and tumor stage were independent factors for patient prognosis. The ROC curve analysis showed that the area under the curve (AUC) of the risk score in predicting 1, 3 and 5-year survival was 0.716, 0.697 and 0.717, respectively. When combined with age and tumor stage, the AUC for predicting 1-year prognosis increased to 0.725. The prognostic risk assessment nomogram for bladder cancer patients constructed based on patient age, tumor stage, and risk score had a prediction value that was consistent with the actual value.

CONCLUSIONS

A bladder cancer patient prognosis risk assessment model based on cuproptosis-related lncRNA has been successfully constructed in this study. The model can predict the prognosis of bladder cancer patients and their immune infiltration status, which may also provide a reference for tumor immunotherapy.