Development of a novel signature derived from single cell RNA-sequencing for preoperative prediction of lymph node metastasis in head and neck squamous cell carcinoma

Abstract

Background: Lymph node metastasis (LNM) is considered as an adverse prognostic indicator for cancer patients. Preoperative knowledge of LNM is valuable for pretreatment decision making. Here, we sought to develop and validate an LNM signature for preoperative prediction of LNM in patients with head and neck squamous cell carcinoma (HNSCC).

Methods: By studying single cell RNA-sequencing data (scRNA-seq), differentially expressed mRNA were selected and analyzed through univariate logistic regression and least absolute shrinkage and selection operator (LASSO) to identify an LNM signature. Multivariate logistic regression was utilized to establish an LNM nomogram incorporating LNM signature and T-classification.

Results: The LNM signature was significantly associated with lymph node status and prognosis. The LNM signature and LNM nomogram displayed a robust predictive effect.

Conclusion: Our study reveals that LNM signature is a powerful biomarker for preoperative prediction of LNM in patients with HNSCC, which may be effective to realize individualized outcome prediction.

Keywords: LNM nomogram; gene signature; head and neck squamous cell carcinoma; lymph node metastasis; preoperative prediction.