Forkhead box D1 (FOXD1) is a new member of FOX transcription factor family. FOXD1 has demonstrated multilevel roles during normal development, and several diseases' pathogenesis. However, little is known about the role of FOXD1 in the progression of head and neck squamous cancer (HNSC). In the present study, we analyzed FOXD1 expression pattern using The Cancer Genome Atlas (TCGA) dataset, Gene Expression Omnibus (GEO) datasets, HNSC cell lines, and HNSC tissues. Then, we analyzed the correlation between FOXD1 expression and clinical characteristics, and evaluated the prognostic value of FOXD1 in HNSC. Moreover, we assessed the relationship between FOXD1 expression and tumor microenvironment (TME) and immune cell infiltration using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Cell-type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) algorithms. Finally, we predicted the FOXD1-related biological processes (BPs) and signal pathways. FOXD1 was up-regulated in HNSC tissues in TCGA datasets, validated by GEO datasets, HNSC cell lines and HNSC tissues. FOXD1 expression was significantly associated with tumor site and HPV infection. Univariate and multivariate Cox regression analyses showed that FOXD1 expression was an independent prognostic factor. Moreover, we found that the proportions of naïve B cells, plasma cells, and resting dendritic cells (DCs) were negatively correlated with FOXD1 expression, otherwise, the proportion of activated mast cells was positively correlated with FOXD1 expression using CIBERSORT algorithm. Gene Set Enrichment Analyses (GSEAs) revealed that FOXD1 was mainly involved in cancer-related signaling pathway and metabolism-related pathways. FOXD1 was a potential oncogene, and might represent an indicator for predicting overall survival (OS) of HNSC patients. Moreover, many cancer-related pathways and metabolism-related processes may be regulated by FOXD1.
Keywords: Head and neck cancer; Immune; Prognosis; Tumor environment; bioinformatics.
© 2021 The Author(s).