Cuproptosis-related LncRNAs are potential prognostic and immune response markers for patients with HNSCC via the integration of bioinformatics analysis and experimental validation

Abstract

IntroductionHead and neck squamous cell carcinoma (HNSCC) is a malignant neoplasm typically induced by alcohol and tobacco consumption, ranked the sixth most prevalent cancer globally. This study aimed to establish a cuproptosis-related lncRNA predictive model to assess the clinical significance in HNSCC patients.MethodsThe Cancer Genome Atlas (TCGA) database was utilized to download cuproptosis-related genes, lncRNAs profiles, and selected clinical information of 482 HNSCC samples. Cuproptosis-related lncRNAs were analyzed by Pearson correlation method, with the least absolute shrinkage and selection operator (LASSO) and univariate/multivariate Cox analyses performed to establish the cuproptosis-related lncRNA predictive model. Subsequently, the time-dependent receiver operating characteristics (ROC) and Kaplan-Meier analysis were applied to assess its prediction ability, and the model was verified by a nomogram, univariate/multivariate Cox analysis, and calibration curves. Furthermore, the principal component analysis (PCA), immune analysis, and gene set enrichment analyses (GSEA) were performed, and the 50% inhibitory concentration (IC50) prediction in the risk groups was calculated. Furthermore, the expression of six cuproptosis-related lncRNAs in HNSCC and paracancerous tissues was detected by quantitative real-time PCR (qRT-PCR).ResultsA total of 467 lncRNAs were screened as cuproptosis-associated lncRNAs in HNSCC tissues to establish an eight cuproptosis-related lncRNA prognostic signature consisting of AC024075.3, AC090587.2, AC116914.2, AL450384.2, CDKN2A-DT, FAM27E3, JPX, and LNC01089. For the high-risk group, the results demonstrated a satisfactory predicting performance with considerably worse overall survival (OS). Multivariate Cox regression confirmed that the risk score was a reliable predictive factor (95% CI: 1.089–1.208, hazard ratio =1.147), with the area of 1-, 3-, and 5-year OS under the ROC curve of 0.690, 0.78524, and 0.665, respectively. The differential analysis revealed that JPX was significantly upregulated in HNSCC tissues, while AC024075.3, AC090587.2, AC116914.2, AL450384.2, CDKN2A-DT were downregulated in HNSCC tissues by qRT-PCR assays. In addition, this gene signature was also associated with some immune-related pathways and immune cell infiltration and affected the anti-cancer immune response. Furthermore, Bexarotene, Bleomycin, Gemcitabine, etc., were identified as potential therapeutic compounds for HNSCC.DiscussionsThis novel cuproptosis-related lncRNAs prognostic signature could predict prognosis and help propose novel individual therapeutic targets for HNSCC.

Bioinformatic analysis and experimental validation of cuproptosis-related LncRNA as a novel biomarker for prognosis and immunotherapy of oral squamous cell carcinoma

“…In the subsequent research analysis, the superior predictive power of the risk model is verified. In the 8-CRLs studied, THAP9-AS1, CDKN2A-DT, GCC2-AS1, AL132800.1, STARD4 − AS1, and WDFY3-AS2 were reported to be biomarkers related with cuproptosis in HNSCC [ 18 – 23 ]. LINC00847 is engaged in the regulation of pyroptosis in the occurrence and development of OSCC [ 24 ].…”

Sensitivity Analysis for Survival Prognostic Prediction with Gene Selection: A Copula Method for Dependent Censoring

“…Usually, a multi-gene predictor is more accurate than a single-gene predictor as the prognostic ability of a single gene is limited. A predictor optimally constructed from the selected genes becomes a useful biomarker for predicting survival in breast cancer [ 10 , 11 , 12 , 13 , 14 , 15 ], lung cancer [ 6 , 7 , 8 , 9 , 16 , 17 ], gastric cancer [ 18 , 19 ], ovarian cancer [ 20 , 21 , 22 , 23 , 24 ], skin cancer [ 25 ], liver cancer [ 26 , 27 ], bladder cancer [ 28 ], head and neck cancer [ 29 , 30 ], glioma [ 31 ], myeloproliferative neoplasms [ 32 ], kidney cancer [ 33 ], and cancers of mixed types [ 34 , 35 ]. These analyses were performed mostly based on univariate Cox regression with the significance scaling of p -values, such as 0.05, 0.01, and 0.001, followed by cross-validation and/or external validation.…”

Novel cuproptosis-related lncRNAs can predict the prognosis of patients with multiple myeloma

“…LncRNAs can induce many important cancer phenotypes by interacting with other cellular macromolecules, DNAs, proteins, and RNAs ( 24 ). Some lncRNAs have been shown to regulate apoptosis ( 25 , 26 ), ferroptosis ( 27 - 29 ), and cuproptosis ( 30 , 31 ) of cancer cells. Furthermore, the expression of lncRNAs usually changes and is related to the prognosis of various cancer patients.…”