Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer

Abstract

Background: Cervical cancer (CC) is a major health threat to females, and distal metastasis is common in patients with advanced CC. Anoikis is necessary for the development of distal metastases. Understanding the mechanisms associated with anoikis in CC is essential to improve its survival rate.Methods: The expression matrix of long non-coding RNAs (lncRNAs) from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients was extracted from The Cancer Genome Atlas (TCGA), and highly relevant anoikis-related lncRNAs (ARLs) were identified by the single sample gene set enrichment analysis (ssGSEA) method. ARLs-related molecular subtypes were discerned based on prognosis-related ARLs. ARLs-related prognostic risk score (APR_Score) was calculated and risk model was constructed using LASSO COX and COX models. In addition, we also assessed immune cell activity in the immune microenvironment (TME) for both subtypes and APR_Score groups. A nomogram was utilized for predicting improved clinical outcome. Finally, this study also discussed the potential of ARLs-related signatures in predicting response to immunotherapy and small molecular drugs.Results: Three ARLs-related subtypes were identified from TCGA-CESC (AC1, AC2, and AC3), with AC3 patients having the highest ARG scores, higher angiogenesis scores, and the worst prognosis. AC3 had lower immune cell scores in TME but higher immune checkpoint gene expression and higher potential for immune escape. Next, we constructed a prognostic risk model consisting of 7-ARLs. The APR_Score exhibited a greater robustness as an independent prognostic indicator in predicting prognosis, and the nomogram was a valuable tool for survival prediction. ARLs-related signatures emerged as a potential novel indicator for immunotherapy and small molecular drug selection.Conclusion: We firstly constructed novel ARLs-related signatures capable of predicting prognosis and offered novel ideas for therapy response in CC patients.

Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma

“…Liang et al conducted a study where they developed a signature consisting of seven lncRNAs associated with anoikis. Their primary objective was to utilise this signature to predict the survival of patients with CC [23]. Similarly, Chen et al identified five prognostic anoikis-related lncRNAs (TSPOAP1-AS1, CCNT2-AS1, LINC01094, AL033527.2 and LINC00460) and utilised them to establish a risk-predictive model for stomach adenocarcinoma [22].…”

“…conducted a study where they developed a signature consisting of seven lncRNAs associated with anoikis. Their primary objective was to utilise this signature to predict the survival of patients with CC [ 23 ]. Similarly, Chen et al.…”

“…lncRNA HOX transcript antisense intergenic RNA (HOTAIR) influenced the migration, invasion and drug resistance of ovarian cancer cells by recruiting EZH2 and upregulting the H3K27 methylation level, leading to the loss of anoikis functions [ 18 ]. Meanwhile, anoikis‐Related lncRNAs based prognostic models have been established in gastric cancer (GC), bladder cancer and cervical cancer (CC) [ 21 , 22 , 23 ].…”