Breast cancer is the most common cancer among women and a leading cause of death worldwide. Female breast cancer has now surpassed lung cancer as the leading cause of global cancer incidence in 2020, with an estimated 2.3 million new cases, representing 11.7% of all cancer cases (1).

Most cancers usually result from the interaction between several factors including genetic, environmental, reproductive and lifestyle factors (2, 3). Although breast cancer has not been traditionally considered as an immunogenic tumor, studies suggest that the immune system and its interaction with tumor cells and the tumor environment may play an important role in this malignancy (4).

Cytokines are small proteins (usually less than 30 kDa) that are released by various types of cells with important roles in immune processes (5). Interleukin-16 (IL-16) gene in humans is located on chromosome 15q25.1. The gene is 153 kb in length and consists of 22 exons and 21 introns (6). Today, one of the most interesting topics for scientists is the study of single-nucleotide polymorphisms (SNPs) and their association with cancer (7). These mutations can be found in different parts of the genome, such as the coding or non-coding regions (8) and can provide information on population histories and the form of gene selection (7). Several studies have shown that some of the IL-16 polymorphisms are significantly associated with cancers such as gastric, colorectal, nasopharyngeal and hepatocellular cancers. Some important polymorphisms of the IL-16 gene are rs11556218 and rs4072111, which might have a significant role in the development of cancer (9). In a study in Taiwan, the distribution of genotypic and allelic frequencies of IL-16 rs11556218 differed significantly between oral cancer patients and healthy individuals (10). In another study, the distribution of genotypic and allelic frequencies of IL-16 rs11556218 differed significantly between lung cancer patients and healthy individuals (11). 

In this study, peripheral blood samples (5 ml) were taken from 80 breast cancer patients and 80 healthy individuals who were referred to the Ayatollah Khansari Hospital in Arak, Iran. The study was approved by the Research Ethics Committee of Arak University (IR.ARAKMU.REC.1395.288). Written consent was obtained from all participants. Information about age, marital status, occupation, diet, number of children and Age at menarche were collected. All pariticpants were female and the mean age of the patients was 50 years.

DNA extraction was performed with the Iraizol DNA Extraction kit (RNA Biotechnology Company, Iran) according to the manufacturer's instruction. The quality of the extracted DNA was evaluated using a spectrophotometer (v-gene, USA). Finally, the extracted DNA was stored at -20 ˚C for next experiments.

Polymorphisms rs11556218 T/G and rs4072111 C/T were investigated by the RFLP-PCR technique using primers used in a previous study (12)(Table 1). The primers were checked in the National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/tools/primer-blast). Finally, the cutting site, the type of restriction enzymes and the cutting parts were investigated by NEBcutter (http://nc2.neb.com/NEBcutter2/).

First, PCR reaction was carried out in a total volume of 25 μg containing 14 ng DNA, 18.9 μl distilled water, 0.5 μl of forward and reverse primers (TAG Copenhagen, Denmark), 1 μl MgCl2, 0.4 μl dNTP (Sina Gene, Iran), 2.5 μl buffer and 0.2 μl Taq polymerase (Sina Gene, Iran). Thermal cycling conditions consisted of 35 cycles with an annealing temperature of 58˚C and 62˚C for rs11556218 T/G and rs4072111 C/T, respectively. PCR products (5 μl) were analyzed by agarose gel (4%) electrophoresis. Finally, the enzymatic digestion of the PCR products was performed using BsmAI (Thermo Scientific) and NdeI (Jena Bioscience) according to the manufacturer's instructions (Table 2).

The Hardy–Weinberg Equilibrium (HWE) was used with the X2 test to compare distribution of the observed genotype frequencies in the study groups with the expected genotype frequencies. The SPSS software (version 24) was used for statistical analysis of data. The relationship between numeric variables (nonparametric) and cancer risk was evaluated using the Student’s t-test. Also, genotype and allele frequency distributions were compared using odds ratios (OR). The significance level was set at 0.05. Power analysis was performed using the G* Power software (version 3.1.9.2).

The age at menstruation and family history of cancer were significantly associated with the risk of breast cancer (P <0.05) (Table 3).

Table 1. Primer sequences used in the study

Table 2. RFLP conditions used in the study

Incubation temperature (˚C)/Time

Table 3. The association of variables with risk of breast cancer in the patients and controls

Student’s t-test.

Table 4. The relationship between the two SNPs (T/G rs11556218 and rs4072111 C/T) in the IL-16 gene and risk of breast cancer