FAM13A polymorphisms are associated with a specific susceptibility to clinical progression of oral cancer in alcohol drinkers

This study collected data on 290 oral cancer cases and 290 cancer-free cases over an eight-year period from 2013 to 2021. The study was awarded to the Institutional Review Board of Changhua Christian Hospital (CCH) and Changhua Christian Hospital Biobank (IRB No. 200211), indicating that ethical considerations were considered. The study also noted that clinical staging, lymph node metastasis, and tumour cell differentiation in oral squamous cell carcinoma (OSCC) were explained using the standard TNM staging system of the American Joint Committee on Cancer (AJCC). The TNM system is a widely accepted method to describe the extent of cancer in a patient and is used by physicians to guide treatment decisions and predict patient outcomes. It involves assessing the size and extent of the primary tumour (T), the involvement of nearby lymph nodes (N), and the presence of distant metastases (M). By using the system, the study can more accurately classify and compare oral cancer cases with cancer-free cases [19]. The definition of chewing and drinking classifies people according to whether they chew betel nuts or drink alcohol. In this case, people who chewed betel quid or drank alcohol would be classified as having positive binary outcomes for these behaviours, not necessarily at the time of the study or survey. Definitions classify individuals according to whether they have smoked at least one cigarette per day in the past 3 months, indicating that they have a smoking habit.

Whole blood samples were collected during the hospitalisation of the patient and placed in sterile tubes containing EDTA. The collected samples were immediately centrifuged and stored at -80 °C. Genomic DNA was extracted from peripheral blood leukocytes using previously published methods using the QIAamp DNA Blood Mini Kit (Qiagen, Valencia, CA, USA) [20]. The extracts were dissolved in TE buffer (containing 10 mM trisaminomethane and 1 mM ethylenediaminetetraacetic acid; pH 7.8) and finally quantified by measuring optical density at a wavelength of 260 nm and stored at -20.

Real-time PCR, also known as quantitative PCR (qPCR), uses fluorescent probes to monitor the amplification of the target sequence in real time during the PCR reaction. When the probe binds to the target sequence, the polymerase cleaves the probe, which converts the reporter molecule to the quencher. The reagent molecules are separated, resulting in fluorescence. The quantitative fluorescent PCR instrument detects the fluorescence intensity in each cycle of the PCR reaction, to achieve the quantification of the target nucleic acid [21]. Three FAM13A gene polymorphisms (rs3017895, rs3756050, and rs7657817) were detected in a previous study with Genesky's proprietary improved Multiligase Detection Reaction (iMLDR) [14]. Furthermore, the polymorphism of the FAM13A gene rs1059122 has been significantly reported in cirrhosis risk disease [17]. However, the role of FAM13A polymorphisms in oral cancer is unclear. The study systematically selected four SNPs from the FAM13A gene polymorphism (rs1059122, rs3017895, rs3756050 and rs7657817), which were analysed using quantitative real-time PCR with the ABI StepOne real-time PCR System (Applied Biosystems, Foster City, CA, USA), and the data was analysed using StepOne software v2.3. The final volume of each reaction was 5 μL and the contents were 2.5 μL TaqMan Genotyping Master Mix, 0.125 μL TaqMan probe mix, and 30 ng of genomic DNA. Real-time PCR experiments were setup with an initial denaturation step at 95° C for 10 min, followed by 40 cycles of amplification at 95° C for 15 s and 60° C for 1 min. Polymorphisms of the FAM13A gene were assessed by PCR as previously described [22].

This study aimed to analyse the association between the expression of the FAM13A gene and the clinical characteristics of head and neck squamous cell carcinoma (HNSCC) by downloading data from the Cancer Genome Atlas (TCGA) database through the University of California Santa Cruz (UCSC) Xena Functional Genomics Explorer, a web-based tool to explore and visualise genomic data. It is worth noting that users of the UCSC Xena Browser website ( https://​xenabrowser.​net/​) [23] can access and analyse various genomic data sets through it. The article uses a browser search and retrieval of relevant TCGA data to analyse FAM13A gene expression and clinical features in HNSCC.

As in the previous study [24], the collected data were analysed for clinical characteristics using IBM SPSS Statistics v22.0 (IBM, Armonk, NY, USA). We used Mann-Whitney U validation to assess demographically significant differences between OSCC cases and noncancer controls, and further analysed the variation of FAM13A levels in TCGA's HNSCC dataset. Furthermore, logistic regression was used to determine the odds ratio (OR) distribution of the FAM13A SNP distribution in OSCC cases versus noncancer controls. Multiple regression was used to calculate adjusted odds ratios (AOR) with 95% confidence intervals (CI) for the FAM13A SNP distribution, while logistic regression was used to evaluate the SNP after adjustment for chewing, smoking, and alcohol consumption of betel quid. A significance level of p < 0.05 was used to determine statistical significance.

This study explores the collection and analysis of 290 OSCC patients and 290 cancer-free controls. The study found that there were no significant differences in age distribution between the control group (people without oral cancer) and OSCC patients (p = 0.0751). As for the gender distribution, the percentage showed significant difference between control group and the OSCC patients (p < 0.0001). It might due to the incidence rate of male is much higher than female [25]. However, the study found that chewing, smoking, and drinking were significantly different between the two groups. This suggests that these lifestyle habits may be associated with an increased risk of developing oral cancer. Based on the eighth edition of the AJCC and TNM staging scheme [26], the patients had primary tumour predistribution (68.3%), lymph node metastases (76.2%) and no distant organ metastases (93.8%). Furthermore, Table 1 shows that around 83.1% of OSCC cases had moderate to poor cellular differentiation.

To explore the distribution of FAM13A genotypes, four SNPs (rs1059122, rs3017895, rs3756050, and rs7657817) and clinical symptoms were separately analysed. The statistical analysis used was the estimation of the OR and its 95% CI using a logistic regression model. Additionally, we use personal habits (drinking, chewing nut beets, and smoking) as AOR as a secondary analysis target and incorporate different variables into the calculation results. We revealed, by estimating the OR and AOR, that FAM13A exhibited different genotypic variables in four SNPs that were not statistically significant between controls and patients with oral cancer, as shown in Table 2. We then further explored whether there is an association between different variants of SNP rs3017895 and specific characteristics of patients with OSCC, such as tumour size or lymph node involvement. By examining these relationships, we aim to determine whether the SNP could be used as a marker to predict the development and progression of OSCC. The results of this analysis would have been presented in Table 3, which likely lists the various categories of clinical and pathological characteristics that were studied. The study found that different variants (allele types) of SNP rs3017895 were not significantly associated with various clinicopathological characteristics such as clinical stage, tumour size, lymph node invasion, distant metastasis, metastasis, and pathological differentiation status of patients with OSCC. This means that the distribution of different types does not appear to have any effect on the development or progression of OSCC or tumour characteristics in patients with OSCC. The lack of a significant association suggests that this particular SNP may not be a useful marker to predict the severity of OSCC or the clinical outcome. To further explore whether drinking alcohol, chewing betel nuts, and smoking are considered risk factors for SNP rs3017895 and OSCC, we calculated the correlation between patients with different genotypes. Our study indicated that subjects who chewed betel quid and smoked were not associated with clinical stage, tumour size, lymph node metastasis, distant metastasis, or cell differentiation status FAM13A SNP subgroup rs3017895. Especially in the alcohol drinking group, patients with the SNP G genotype were found to have a 3.17-fold increase in the highly differentiated state of cells (95% CI, 1.102-9.116; p = 0.032) and a significantly lower incidence of distant metastases (95% CI, 0.056-0.876; p = 0.032) compared to patients with the A allele, as shown in Table 4. The above results suggest that the characteristics of patients with different habits are associated with FAM13A SNP and environmental risk and oral cancer progression.

Previous studies have shown a genetic association between FAM13A and oral cancer, and we explore the clinical features of this gene using the TCGA dataset, as shown in Fig. 1. We did not observe significant differences in the FAM13A gene between various clinical characteristics, including clinical stage (p = 0.1371), tumour (p = 0.6249), and lymph node metastasis (p = 0.1923). However, we did find that the cell differentiation status was significantly different between the good and poor status (p = 0.0132), as well as between the intermediate and poor status (p = 0.0105). These findings suggest that the degree of cell differentiation may be a more important predictor of severity and clinical outcome than the expression of the FAM13A gene.