Signature involved in immune-related lncRNA pairs for predicting the immune landscape of cervical cancer

Abstract

Background Immune-related long non-coding RNAs (irlncRNAs) are known to hold great promise as superior biomarkers for cervical cancer-related immunotherapeutic response and the tumor immune microenvironment. Here, we constructed a prognostic signature based on irlncRNA pairs (IRLPs). Methods The samples were downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. The least absolute shrinkage and selection operator Cox regression was performed to construct the prognostic model. Receiver operating characteristic (ROC) curve and nomogram were plotted to validate accuracy of the model. Next, we estimated the immune cell infiltration and the correlation between risk score and the expression of genes related to immune checkpoint. Finally, we calculated the score of the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and the half maximal inhibitory concentration of the chemotherapeutic agent to evaluate the response to immunotherapy and chemotherapy. Results We constructed a prognostic signature that consisted of 11 irlncRNAs. The area under the curve values of the 1-, 3-, and 5-year ROC curves were 0.844, 0.891, and 0.871, respectively. The expression of CTLA-4, HAVCR2, IDO1, LAG3, and PDCD1 were negatively correlated with risk scores. The score of TIDE in the high-risk group was significantly higher than in the low-risk group ( P < 0.01). Patients in the low-risk subgroup were more sensitive to chemotherapeutic agents, such as axitinib and docetaxel, whereas patients in the low-risk subgroup were more sensitive to mitomycin C. Conclusion Our study highlighted the value of the 11 IRLPs signatures to predict the prognosis and the response to immunotherapy and chemotherapeutics for patients with cervical cancer.

Mining immune-related LncRNAs in ovarian cancer for prognostic risk modelling and screening of potential target drugs

“…Ponatinib is a third-generation tyrosine kinase inhibitor (TKI), which is commonly used clinically in the treatment of adult chronic myelogenous leukemia, Philadelphia chromosome-positive, and acute lymphoblastic leukemia [13] .Axitinib is a VEGFR-TKI that precisely and e ciently inhibits the VEGFR-1, 2 and 3 signalling pathways, which are associated with tumour angiogenesis [14] . Blocking the VEGFR receptor pathway inhibits angiogenesis and thus tumour cell proliferation [15] . Tyrosine kinase inhibitors are a class of compounds that inhibit the activity of tyrosine kinases.…”

A risk prediction model mediated by genes of APOD/APOC1/SQLE associates with prognosis in cervical cancer

“…The pre-treatment immune-Inflammation Index was indicated as an independent predictor of both the prognosis of cervical squamous cell carcinoma prognosis patients and the pathological complete response [ 12 ]. It was reported that a prognostic signature consisting of immune-related long non-coding RNAs, such as CTLA-4, PDCD1, and so on, correspondingly predicted risk of cervical cancer and responded to cervical cancer patients’ immunotherapy of mitomycin C and chemotherapeutics of axitinib and docetaxel [ 13 ]. Wang et al found a series of hypoxia or immunity-related genes to establish a prognostic risk model to predict tumorigenesis and development along with chemotherapy sensitivity in cervical cancer [ 14 ].…”