Meta-analyses of the effect of CYP1A1 and CYP2D6 polymorphisms on the risk of head and neck squamous cell carcinoma

Development and Validation of an ADME-Related Gene Signature for Survival, Treatment Outcome and Immune Cell Infiltration in Head and Neck Squamous Cell Carcinoma

ADME genes are a set of genes which are involved in drug absorption, distribution, metabolism, and excretion (ADME). However, prognostic value and function of ADME genes in head and neck squamous cell carcinoma (HNSCC) remain largely unclear. In this study, we established an ADME-related prognostic model through the least absolute shrinkage and selection operator (LASSO) analysis in the Cancer Genome Atla (TCGA) training cohort and its robustness was validated by TCGA internal validation cohort and a Gene Expression Omnibus (GEO) external cohort. The 14-gene signature stratified patients into high- or low-risk groups. Patients with high-risk scores exhibited significantly poorer overall survival (OS) and disease-free survival (DFS) than those with low-risk scores. Receiver operating characteristic (ROC) curve analysis was used to confirm the signature’s predictive efficacy for OS and DFS. Furthermore, gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses showed that immune-related functions and pathways were enriched, such as lymphocyte activation, leukocyte cell-cell adhesion and T-helper cell differentiation. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and other analyses revealed that immune cell (especially B cell and T cell) infiltration levels were significantly higher in the low-risk group. Moreover, patients with low-risk scores were significantly associated with immunotherapy and chemotherapy treatment benefit. In conclusion, we constructed a novel ADME-related prognostic and therapeutic biomarker associated with immune cell infiltration of HNSCC patients.

Association between the CYP1A1 MspI polymorphism and risk of head and neck cancer: a meta-analysis

The studies recommended the relationship between lots of polymorphisms with the head and neck cancers (HNCs) risk. Herein, we reported the association between the CYP1A1 MspI polymorphism and the risk of HNC in an updated meta-analysis. The PubMed/MEDLINE, Web of Science, Cochrane Library, and Scopus databases were searched until March 31, 2021, without any restrictions. Odds ratios (ORs) and 95% confidence intervals (CIs) were applied to assess a relationship between CYP1A1 MspI polymorphism and the HNC risk based on five applied genetic models by RevMan 5.3 software. Other analyses (sensitivity analysis, meta-regression, and bias analysis) were performed by CMA 2.0 software. Trial sequential analysis (TSA) was done by TSA software (version 0.9.5.10 beta). Among the databases and other sources, 501 recorded were identified that at last, 29 studies were obtained for the analysis. The pooled ORs were 1.28 (95%CI 1.09, 1.51; P = 0.003), 1.68 (95%CI 1.16, 2.45; P = 0.007), 1.24 (95%CI 1.03, 1.50; P = 0.02), 1.26 (95%CI 1.07, 1.48; P = 0.005), and 1.66 (95%CI 1.27, 2.16; P = 0.0002) for allelic, homozygous, heterozygous, recessive, and dominant models, respectively. Therefore, the m2 allele and m1/m2 and m2/m2 genotypes had significantly increased risks in HNC patients. With regards to stable results and enough samples, the findings of the present meta-analysis recommended that there was an association between CYP1A1 MspI polymorphism and the HNC risk.

Prognostic value of lipid metabolism-related genes in head and neck squamous cell carcinoma

BACKGROUND

Altered lipid metabolism is involved in the development of many tumors. However, the role of dissimilar lipid metabolism in head and neck squamous cell carcinoma (HNSCC) is not fully established.

AIMS

Here, we sought to determine the prognostic value of lipid metabolism-related genes in HNSCC.

METHODS

RNA-seq data and clinical features of 545 HNSCC cases were obtained from The Cancer Genome Atlas database. A regulatory network of transcription factors-lipid metabolism genes and a risk prognostic model of lipid metabolism-related genes was developed using bioinformatics and Cox regression modeling. We used tumor immune estimation resource to analyze immune cell infiltration in patients with HNSCC based on the prognostic index (PI) of lipid metabolism-related genes.

RESULTS

A total of 136 differentially expressed lipid metabolism genes were identified. Of these, 23 are related to prognosis. In addition to predicting HNSCC prognosis, 11 lipid metabolism-related genes (ARSI, CYP27B1, CYP2D6, DGKG, DHCR7, LPIN1, PHYH, PIP5K1B, PLA2G2D, RDH16, and TRIB3) also affect HNSCC clinical features (stage, gender, and pathological stage). The PI of lipid metabolism-related genes embodied the state of HNSCC tumor immune microenvironment.