Identifying Novel Necroptosis-Related lncRNAs: Prognostic &
Immunotherapy Insights for Head & Neck Cancer
- 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
Author Profileyuxiang chen
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
Author ProfileJunjie Bi
Shandong University of Traditional Chinese Medicine Affiliated Hospital
Author ProfileLu He
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
Author ProfileWenjian Hu
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University
Author ProfileAbstract
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