ArticleOncology research2023
Identification and verification of aging-related lncRNAs for prognosis prediction and immune microenvironment in patients with head and neck squamous carcinoma.
Article in Oncology research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Intratumoral Microbiota Correlates with AP-2 Expression: A Pan-Cancer Map with Cohort-Specific Prognostic and Molecular Footprints.International journal of molecular sciences · 2025Article
- Immunosenescence and cancer: molecular hallmarks, tumor microenvironment remodeling, and age-specific immunotherapy challenges.Journal of hematology & oncology · 2025Review
- The interplay of p16INK4a and non-coding RNAs: bridging cellular senescence, aging, and cancer.Biogerontology · 2025Review
- Characterization of Cuproptosis-Related LncRNAs Prognostic Signature and Identification of LINC02285 as a Novel Biomarker for Ovarian Cancer.Journal of inflammation research · 2025Article
- Molecular Characterization of Cuproptosis-related lncRNAs: Defining Molecular Subtypes and a Prognostic Signature of Ovarian Cancer.Biological trace element research · 2024Article
- Chronobiology of the Tumor Microenvironment: Implications for Therapeutic Strategies and Circadian-Based Interventions.Aging and disease · 2024Review
- Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients.Oncology research · 2024Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aging is highly associated with tumor formation and progression. However, little research has explored the association of aging-related lncRNAs (ARLs) with the prognosis and tumor immune microenvironment (TIME) of head and neck squamous cell carcinoma (HNSCC). RNA sequences and clinicopathological data of HNSCC patients and normal subjects were downloaded from The Cancer Genome Atlas. In the training group, we used Pearson correlation, univariate Cox regression, least absolute shrinkage/selection operator regression analyses, and multivariate Cox regression to build a prognostic model. In the test group, we evaluated the model. Multivariate Cox regression was done to screen out independent prognostic factors, with which we constructed a nomogram. Afterward, we demonstrated the predictive value of the risk scores based on the model and the nomogram using time-dependent receiver operating characteristics. Gene set enrichment analysis, immune correlation analysis, and half-maximal inhibitory concentration were also performed to reveal the different landscapes of TIME between risk groups and to predict immuno- and chemo-therapeutic responses. The most important LINC00861 in the model was examined in HNE1, CNE1, and CNE2 nasopharyngeal carcinoma cell lines and transfected into the cell lines CNE1 and CNE2 using the LINC00861-pcDNA3.1 construct plasmid. In addition, CCK-8, Edu, and SA-β-gal staining assays were conducted to test the biofunction of LINC00861 in the CNE1 and CNE2 cells. The signature based on nine ARLs has a good predictive value in survival time, immune infiltration, immune checkpoint expression, and sensitivity to multiple drugs. LINC00861 expression in CNE2 was significantly lower than in the HNE1 and CNE1 cells, and LINC00861 overexpression significantly inhibited the proliferation and increased the senescence of nasopharyngeal carcinoma cell lines. This work built and verified a new prognostic model for HNSCC based on ARLs and mapped the immune landscape in HNSCC. LINC00861 is a protective factor for the development of HNSCC.
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