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Identifying Novel Necroptosis-Related lncRNAs: Prognostic & Immunotherapy Insights for Head & Neck Cancer
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  • JI YIN,
  • yuxiang chen,
  • Junjie Bi,
  • Lu He,
  • Wenjian Hu,
  • Fengfeng Qin
JI YIN
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
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yuxiang chen
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
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Junjie Bi
Shandong University of Traditional Chinese Medicine Affiliated Hospital
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Lu He
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
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Wenjian Hu
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
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Fengfeng Qin
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University

Corresponding Author:[email protected]

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Abstract

Background Necroptosis could be a trigger and amplifier of anti-tumor immunity in cancer therapy. LncRNAs are vital in controlling immune system gene expression. We designed to establish a NRlncRNA signature for evaluation and prognosis prediction in HNSCC, ultimately providing a new perspective for clinical application. Materials and methods We acquired RNA-seq and clinical data for HNSCC and 67 NRGs. Subsequently, diverse analytical methods were utilized to discern predictive NRlncRNAs, calculate the risk score, and construct a meticulous risk evaluation model. Furthermore, the predictive capability of the risk model was confirmed through survival analysis, ROC curves, PCA, DCA, C-index, and nomograms. We endeavored to discern disparities among distinct cohorts concerning clinical characteristics, the infiltration of immune cells, the sensitivity to pharmaceutical agents, as well as molecules associated with immune response. Results A risk signature for 12 NRlncRNAs was developed, and the signature had high sensitivity and specificity in predicting survival rates. The established model exhibited a strong association with both survival outcomes and clinical features. Notably, the low-risk group demonstrated a substantially elevated survival probability and displayed a significant positive correlation with diverse immune cell infiltrations. Lastly, we selected different clinical drug regimens based on the different risk groups. Conclusion A prognostic model of NRlncRNAs has been developed for HNSCC that enables the estimation of the TME and the response to cancer immunotherapy. The model also has the potential to predict the prognosis, which may pave the way for novel clinical applications.
29 Aug 2024Submitted to Cancer Reports
04 Sep 2024Submission Checks Completed
04 Sep 2024Assigned to Editor
04 Sep 2024Review(s) Completed, Editorial Evaluation Pending
11 Sep 2024Reviewer(s) Assigned