The role of 5-methylcytosine-related long noncoding RNAs (m5C-lncRNAs) in bladder cancer (BLCA) remains unclear. This study explored the association between RNA modification writer-related lncRNAs and SOC prognosis, providing a potential complement for the clinical management of SOC patients. Lastly, we validated the predictive reliability and sensitivity of the lncRNA-based model via a nomogram. Our risk prediction model could effectively predict the prognosis of SOC patients with different clinical characteristics and their responses to immunotherapy.
We established a risk prediction model based on these six lncRNAs and evaluated its prognostic value in multiple groups (training set, testing set, and entire set). Six writer-related lncRNAs were ultimately selected following multivariate Cox analysis. Through the pearson correlation analysis, univariate Cox regression analysis, and LASSO-penalized Cox regression analysis, we identified nine lncRNAs significantly associated with four types of RNA modification writers (m6A, m1A, APA, and A-I) and with the prognosis of SOC patients (P <0.05). Here, we analyzed SOC RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify prognostic biomarkers. Currently, there is a lack of reliable biomarkers for accurate SOC patient prognosis. Serous ovarian carcinoma (SOC) is a gynecological malignancy with high mortality rates. In general, the cancer-specific and cancer-common lncRNA biomarkers identified in this study may aid in cancer diagnosis and treatment. Two lncRNAs HOXA-AS2 and AC007228 were identified as pan-cancer biomarkers. 29 lncRNAs were identified as diagnostic biomarkers for their corresponding cancer types, with lncRNA AC027601 was identified as a new KIRC-associated biomarker, and lncRNA ACTA2-AS1 was regarded as a carcinogenic factor of KIRP. Then, we screened aberrantly methylated lncRNAs that negatively regulated lncRNA expression and mapped them to the ceRNA relationship for further validation. In this study, we integrated lncRNA methylation, lncRNA expression and mRNA expression data to illuminate specific and common lncRNA methylation patterns in 23 cancer types. While long non-coding RNAs (lncRNAs) are key cancer modulators, there is still a lack of pan-cancer analysis for lncRNA methylation dysregulation. Pan-cancer analysis can help understand the similarities and differences among cancer types by systematically describing different patterns in cancers and identifying cancer-specific and cancer-common molecular biomarkers. The mechanism of these specific and common characteristics is still unclear. The five lncRNAs, especially ENSG00000206567, ENSG00000257989 and LOC388282 that never reported before, may serve as viable molecular targets common among diverse cancers.ĭifferent cancer types not only have common characteristics but also have their own characteristics respectively. In silico functional analysis indicated that the lncRNAs are associated with common biological processes driving human cancers. An indexing system was developed to map the 5-lncRNA signature to prognoses of pan-cancer patients.
Moreover, the signature was further evaluated on two independent external cohorts (TARGET, n=1,122 CPTAC, n=391 National Cancer Institute) which yielded similar prognostic values (AUC of 0.60 and 0.75 log-rank P=8.6E-09 and P=2.7E-06). After routine clinical factors involved, the signature demonstrated a better performance for long-term prognostic estimation (AUC of 0.72). The signature stratified the cohort into low- and high-risk groups with significantly distinct survival outcomes (median OS of 9.84 years versus 4.37 years, log-rank P=1.48E-38) and achieved a time-dependent ROC/AUC of 0.66 at 5 years. The identified lncRNAs are significantly associated (all P1.48E-11) with overall survival (OS) of the TCGA cohort (n=4,231). In this study, we proposed a framework to incorporate statistical power, biological rationale and machine learning models for pan-cancer prognosis analysis. However, the value of lncRNAs as prognostic markers among diverse human cancers is still under investigation, and a systematic signature based on these transcripts that related to pan-cancer prognosis has yet to be reported. Long noncoding RNAs (lncRNAs) have emerged as potential prognostic markers in various human cancers as they participate in many malignant behaviors.
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