Identification of cuproptosis-related lncRNA for predicting prognosis and immunotherapeutic response in cervical cancer

Abstract

Patients diagnosed with advanced cervical cancer (CC) have poor prognosis after primary treatment, and there is a lack of biomarkers for predicting patients with an increased risk of recurrence of CC. Cuproptosis is reported to play a role in tumorigenesis and progression. However, the clinical impacts of cuproptosis-related lncRNAs (CRLs) in CC remain largely unclear. Our study attempted to identify new potential biomarkers to predict prognosis and response to immunotherapy with the aim of improving this situation. The transcriptome data, MAF files, and clinical information for CC cases were obtained from the cancer genome atlas, and Pearson correlation analysis was utilized to identify CRLs. In total, 304 eligible patients with CC were randomly assigned to training and test groups. LASSO regression and multivariate Cox regression were performed to construct a cervical cancer prognostic signature based on cuproptosis-related lncRNAs. Afterwards, we generated Kaplan–Meier curves, receiver operating characteristic curves and nomograms to verify the ability to predict prognosis of patients with CC. Genes for assessing differential expression among risk subgroups were also evaluated by functional enrichment analysis. Immune cell infiltration and the tumour mutation burden were analysed to explore the underlying mechanisms of the signature. Furthermore, the potential value of the prognostic signature to predict response to immunotherapy and sensitivity to chemotherapy drugs was examined. In our study, a risk signature containing eight cuproptosis-related lncRNAs (AL441992.1, SOX21-AS1, AC011468.3, AC012306.2, FZD4-DT, AP001922.5, RUSC1-AS1, AP001453.2) to predict the survival outcome of CC patients was developed, and the reliability of the risk signature was appraised. Cox regression analyses indicated that the comprehensive risk score is an independent prognostic factor. Moreover, significant differences were found in progression-free survival, immune cell infiltration, therapeutic response to immune checkpoint inhibitors, and IC50 for chemotherapeutic agents between risk subgroups, suggesting that our model can be well employed to assess the clinical efficacy of immunotherapy and chemotherapy. Based on our 8-CRLs risk signature, we were able to independently assess the outcome and response to immunotherapy of CC patients, and this signature might benefit clinical decision-making for individualized treatment.

Why Is Surgery Still Done after Concurrent Chemoradiotherapy in Locally Advanced Cervical Cancer in Romania?

“…An analysis was conducted to assess the potential efficacy of the prognostic signature in predicting the response to immunotherapy and the susceptibility to chemotherapeutic medicines. Kong [34] generated a risk signature consisting of eight long non-coding RNAs (lncRNAs) associated with cuproptosis (AL441992.1, SOX21-AS1, AC011468.3, AC012306.2, FZD4-DT, AP001922.5, RUSC1-AS1, AP001453.2) to predict the survival outcome of patients with cervical cancer. We then assessed the reliability of this risk signature.…”

Noncoding RNAs as an emerging resistance mechanism to immunotherapies in cancer: basic evidence and therapeutic implications

“…Patients in low-risk group would benefit from immunotherapy. According to a risk signature comprising eight lncRNAs (AC011468.3, AC012306.2, AL441992.1, AP001453.2, AP001922.5, FZD4-DT, RUSC1-AS1 and SOX21-AS1), patients with cervical cancer were classified into different risk groups ( 121 ). High-risk patients were less sensitive to ICIs.…”

SRY-box transcription factor 21 antisense divergent transcript 1: Regulatory roles and clinical significance in neoplastic conditions and Alzheimer's Disease

“…Additionally, its role in driving cancer progression has recently attracted substantial attention. Across a spectrum of human tumors, including oral [13], lung [14][15][16], hepatocellular [17], pancreatic [18], endometrial [19], cervical [20][21][22][23][24], and breast cancers [25][26][27], as well as nephroblastoma [28], glioma [29], and osteosarcoma [30,31], SOX21-AS1 experiences aberrant regulatory patterns. Abnormal expression of SOX21-AS1 in tumor patients has been correlated with clinicopathological characteristics and survival outcomes, encompassing aspects like lymph node metastasis, tumor dimensions, clinical stage, and overall survival.…”

“…Notably, SOX21-AS1-related prognostic models may also be useful tools for assessing the prognosis and providing new ideas for the treatment of tumors. For instance, in cervical cancer [20], a risk signature comprising eight cuproptosis-related lncRNAs (AL441992.1, SOX21-AS1, AC011468.3, AC012306.2, FZD4-DT, AP001922.5, RUSC1-AS1, AP001453.2) has been developed, enabling the prediction of prognosis and immunotherapeutic responses. Furthermore, a prognostic signature model linked to m6A-related lncRNAs (AC005229.3, SOX21-AS1, AL133523.1, and AC004847.1) has been constructed for glioblastoma multiforme [71], offering insights into prognosis and immunomodulatory effects.…”