Affiliation:
1. The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, Hubei Province, China
2. Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, Wuhan, Hubei Province, China
Abstract
Objective:
The role of lipid droplets (LDs) and lipid droplet-associated genes (LD-AGs)
remains unclear in head and neck squamous cell carcinoma (HNSCC). This study aimed to investigate
LDs in HNSCC and identify LD-AGs essential for the diagnosis and prognosis of HNSCC
patients.
Methods:
The LDs in the HNSCC and normal cell lines were stained with oil red O. Bioinformatic
analysis was used to find LD-AGs in HNSCC that had diagnostic and prognostic significance.
Results:
LDs accumulation was increased in HNSCC cell lines compared with normal cell lines
(P<0.05). Fifty-three differentially expressed genes, including 34 upregulated and 19 downregulated,
were found in HNSCC based on the TCGA platform (P<0.05). Then, 53 genes were proved to
be functionally enriched in lipid metabolism and LDs. Among them, with an AUC value > 0.7, 34
genes demonstrated a high predictive power. Six genes (AUP1, CAV1, CAV2, CAVIN1, HILPDA, and
SQLE) out of 34 diagnostic genes were linked to overall survival in patients with HNSCC (P<0.05).
The significant prognostic factors AUP1, CAV1, CAV2, and SQLE were further identified using the
univariate and multivariate cox proportional hazard models (P<0.05). The protein expression of
CAV2 and SQLE was significantly increased in the HNSCC tissue compared to normal tissues
(P<0.05). Finally, the knockdown of the four LD-AGs decreased LDs accumulation, respectively.
Conclusions:
Increased LDs accumulation was a hallmark of HNSCC, and AUP1, CAV1, CAV2,
and SQLE were discovered as differentially expressed LD-AGs with diagnostic and prognostic
potential in HNSCC.
Funder
National Natural Science Foundation of China
Publisher
Bentham Science Publishers Ltd.
Subject
Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine
Cited by
2 articles.
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