Bioinformatics analysis reveals VEGFC's prognostic significance in head and neck squamous cell carcinoma and its association with immune cell infiltration

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis due to late diagnosis and complex molecular mechanisms. Vascular endothelial growth factor C (VEGFC) is associated with angiogenesis and lymphangiogenesis. This study aimed to investigate VEGFC's prognostic value in HNSCC and its correlation with immune cell infiltration.

Methods: VEGFC gene expression was analyzed in HNSCC patients using Tumor Immune Estimation Resource 2.0 (TIMER2.0), Gene Expression Profiling Interactive Analysis (GEPIA), and University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) databases, focusing on differential expression and clinical-pathological correlations. The impact of VEGFC on overall survival (OS) and disease-free survival (DFS) was assessed using GEPIA. RNA-seq profiles and clinical information from 503 HNSCC tumor tissues and 44 normal control tissues obtained from The Cancer Genome Atlas (TCGA) database were subjected to univariate and multivariate Cox regression analyses to develop a prognostic nomogram. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used for a protein-protein interaction (PPI) network, while the Tumor-Immune System Interaction Database (TISIDB) for immune-related associations. Expression was further validated with the Gene Expression Omnibus dataset (GSE6631) and reverse transcription quantitative polymerase chain reaction (RT-qPCR).

Results: VEGFC was significantly upregulated in HNSCC and closely correlated with age, gender, race, and tumor stage (P<0.05). PPI and co-expression gene analysis identified ITGA3, NT5E, and PXN as highly associated with VEGFC (R>0.6, P<0.05), which are mainly enriched in PI3K/Akt, MAPK signaling pathway, and cancer-associated glycoproteins. High VEGFC expression predicted poor OS (P=0.003) and DFS (P=0.03). Univariate and multivariate Cox regression analyses confirmed VEGFC as an independent prognostic factor for HNSCC. The prognostic nomogram accurately predicted 1-, 3-, and 5-year survival and calibration curve was very close to ideal 45-degree diagonal line. VEGFC also correlated with immune cells infiltration, including B cells, CD4⁺ T cells, CD8⁺ T cells, as well as immune-related markers such as tumor-infiltrating lymphocytes (TILs) markers, immune modulators, and inflammatory chemokines (P<0.05).

Conclusions: VEGFC may serve as an independent prognostic factor and potential immunotherapeutic target in HNSCC, offering insights into patient risk stratification and personalized treatment strategies.

Keywords: Vascular endothelial growth factor C (VEGFC); bioinformatics; head and neck squamous cell carcinoma (HNSCC); immune infiltration; prognosis.

Figure 1

Differential expression of VEGFC in tumor and normal tissues. (A) VEGFC gene expression in various common tumor tissues and normal tissues in the TIMER 2.0 database; (B) VEGFC gene expression in various common tumor tissues and normal tissues in the GEPIA database. *, P<0.05; **, P<0.01; ***, P<0.001. “T” and “N” in Figure 1B represent tumor tissue and normal control tissue, respectively. VEGFC, vascular endothelial growth factor C; TPM, transcripts per million; ACC, adrenocortical carcinoma; BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL, cholangiocarcinoma; COAD, colon adenocarcinoma; DLBC, diffuse large B-cell lymphoma; ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; HNSCC, head and neck squamous cell carcinoma; KICH, kidney chromophobe; KIRC, kidney renal clear cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LAML, acute myeloid leukemia; LGG, brain lower grade glioma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; MESO, mesothelioma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; READ, rectum adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; TGCT, testicular germ cell tumors; THCA, thyroid carcinoma; THYM, thymoma; UCEC, uterine corpus endometrial carcinoma; UCS, uterine carcinosarcoma; UVM, uveal melanoma; GEPIA, Gene Expression Profiling Interactive Analysis.

Figure 2

Differential expression of VEGFC gene in HNSCC and normal control tissues. (A) Expression differences of VEGFC gene in HNSCC and normal control tissues in the UALCAN database. (B) Expression differences of VEGFC gene in HNSCC and normal control tissues in the GEPIA database. In the figure, “T” represents tumor tissue, “N” represents normal control tissue, and “*” indicates P<0.05. TPM, transcripts per million; HNSCC, head and neck squamous cell carcinoma; VEGFC, vascular endothelial growth factor C; UALCAN, University of ALabama at Birmingham CANcer data analysis Portal.

Figure 3

VEGFC genes expression across clinicopathological features of HNSCC. (A) Relative expression of VEGFC mRNA in HNSCC patients of different stages. (B) Relative expression of VEGFC mRNA in HNSCC patients of different gender. (C) Relative expression of VEGFC mRNA in HNSCC patients of different age. (D) Relative expression of VEGFC mRNA in HNSCC patients of different race. (E) Relative expression of VEGFC mRNA in HNSCC patients with axillary lymph node metastasis. (F) Relative expression of VEGFC mRNA in HNSCC patients of different degrees of differentiation. *, P<0.05; **, P<0.01; ***, P<0.001. VEGFC, vascular endothelial growth factor C; HNSCC, head and neck squamous cell carcinoma.

Figure 4

Prognostic value of VEGFC gene in HNSCC. (A) Impact of VEGFC gene expression on overall survival of HNSCC patients. (B) Impact of VEGFC gene expression on disease-free survival of HNSCC patients. (C) Univariate Cox regression forest plot of VEGFC gene with clinical characteristics. (D) Multivariate Cox regression forest plot of VEGFC gene with clinical characteristics. (E) Column chart representing the prediction model. (F) Risk factor diagram of the prediction model. (G-I) Calibration plots of the prediction model for 1-, 3-, and 5-year overall survival prediction, respectively. VEGFC, vascular endothelial growth factor C; HR, hazard ratio; CI, confidence interval; HNSCC, head and neck squamous cell carcinoma.

Figure 5

VEGFC interacting proteins and co-expressed genes. (A) Protein-protein interaction network of VEGFC. (B) Scatter plot depicting the correlation between VEGFC gene and select co-expressed genes in HNSCC (representative genes shown). VEGFC, vascular endothelial growth factor C; TPM, transcripts per million.

Figure 6

GO and KEGG enrichment analysis of VEGFC interacting and co-expressed genes. (A) Top 20 enriched KEGG pathways. (B) Top 20 biological processes. (C) Top 20 cellular components. (D) Top 20 molecular functions. KEGG, Kyoto Encyclopedia of Genes and Genomes; HIF, hypoxia inducible factor; EGFR, epidermal growth factor receptor; GO, Gene Ontology; VEGFC, vascular endothelial growth factor C.

Figure 7

Correlation of VEGFC gene abundance with immune cell infiltration, TILs, immune modulators, and inflammatory chemokines and their receptor. (A) Correlation of VEGFC gene abundance with immune cell infiltration, depicted through scatter plots for tumor purity, B-cells, CD4⁺ T-cells, CD8⁺ T-cells, macrophages, neutrophils, and dendritic cells infiltration, in that order. (B) Correlation between TILs and VEGFC gene expression; (C-E) Correlation between immunostimulators, including immunostimulators, immunoinhibitors, and MHC class-related molecules with VEGFC gene expression. (F,G) Correlation between chemokines and their receptors with VEGFC gene expression. VEGFC, vascular endothelial growth factor C; TPM, transcripts per million; TILs, tumor-infiltrating lymphocytes; MHC, major histocompatibility complex; ACC, adrenocortical carcinoma; BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL, cholangiocarcinoma; COAD, colon adenocarcinoma; ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; HNSCC, head and neck squamous cell carcinoma; KICH, kidney chromophobe; KIRC, kidney renal clear cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LGG, brain lower grade glioma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; MESO, mesothelioma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; READ, rectum adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; TGCT, testicular germ cell tumors; THCA, thyroid carcinoma; UCEC, uterine corpus endometrial carcinoma; UCS, uterine carcinosarcoma; UVM, uveal melanoma.

Figure 8

Validation of VEGFC gene expression using GEO dataset and RT-qPCR. (A) Relative expression levels of VEGFC gene in normal control tissues and HNSCC tumor tissues. (B) RT-qPCR validation of relative VEGFC mRNA expression in the human immortalized nasopharyngeal epithelial cell line NP69SV40T and the nasopharyngeal carcinoma cell line CNE2. **, P<0.01. VEGFC, vascular endothelial growth factor C; HNSCC, head and neck squamous cell carcinoma; GEO, Gene Expression Omnibus; RT-qPCR, reverse transcription quantitative polymerase chain reaction.