Colorectal cancer (CRC) arises from a complex interaction of genetic, immunological, environmental and microbiome-related factors. It typically originates from adenomatous polyps formed by intestinal stem cells and may result from genetic alterations, such as mutations in the Adenomatous polyposis coli gene (associated with familial adenomatous polyposis) or mismatch repair genes, as observed in Lynch syndrome [1]. The progression of Colorectal cancer, referred to as “multi-step carcinogenesis”, involves a series of progressive alterations [2]. Globally, CRC is one of the most prevalent malignancies, differences in incidence and outcomes among populations are likely influenced by variations in lifestyle and environmental variables associated with CRC [3]. Also, epigenetic regulation serves as a vital molecular marker in cancer, playing a significant role in the pathophysiological interaction between genetics and the environment [4]. In Iraq, colorectal cancer is the second most prevalent malignancy [5].   Cancer Testis Antigens (CTAs) exhibit varied expression profiles in various types of malignancies such as melanoma, prostate, lung, breast, GIT, renal cell adenocarcinoma, immune cell malignancies and Colorectal. Melanoma-associated antigens (MAGE), belong to the cancer/testis antigen CTA family and were first discovered by Weon and Potts [6] comprise a minimum of 55 members, categorized into sub-families: MAGE-I comprises MAGE-A, B and C, whereas MAGE-II includes MAGE- D, E, F, G, H and L.   The MAGE-A gene is located at the chromosomal location Xq28 and it has been associated with certain hereditary disorders, such as dyskeratosis congenita [7] and its expression is usually linked to poor prognosis and metastasis in cancer patients [8]. Melanoma-associated antigen A3, it is normally expressed in germline and trophoblast cells but demonstrates aberrant expression in some tumors, including melanoma, brain tumor, breast cancer, lung cancer and colorectal cancer due to hypomethylation of its promoter region [9]. The main player in MAGE-A3 hypomethylation is DNA methyltransferase enzymes (DNMTs), which mainly work in the gene promoter area. In colorectal cancer, demethylation of the MAGE-A3 promoter facilitates the advancement of cancer cells. The expression pattern of MAGEA3 in Colorectal cancer correlates with patient prognosis, particularly in microsatellite-stable (MSS) subtypes, its expression is associated with immune response and might be a possible immunotherapy target in MSS CRC patients [10].   Also, Histone modifications critically regulate MAGE-A3 expression in colorectal cancer (CRC) cells. Active transcription is linked to elevated histone H3 acetylation and H3K4 tri-methylation at the MAGE-A3 promoter, while restrictive modifications such as H3K27 tri-methylation are associated with gene silencing, indicating a role for histone alterations in the epigenetic control of MAGE-A3 [11].   The expression of CT antigens such as MAGEA3 in a subset of CRC patients induces readily detectable T cell responses, which could be boosted by active vaccination in a small subset of CRC patients [12].   Research shows that in colorectal cancer patient samples, MAGE-A3/6 expression is associated with reduced AMPK activity and enhanced mTOR signalling, underscoring the oncogenic function of MAGE-A3/6 in tumour metabolism [13].   Furthermore, MAGE-A3 specifically reduces the production and release of vascular endothelial growth factor in colorectal cancer via the mechanistic target of rapamycin pathway, without influencing other angiogenic factors. It also decreases mitochondrial function, facilitating tumor growth [8].   MAGE-A proteins in clinical tumor samples were observed to inhibit p53 activity, even with the presence of wild-type p53. Marcar et al. [14] established that MAGE-A antigens impede p53 functionality by blocking its association with chromatin, thus diminishing p53-mediated apoptosis and cell cycle arrest. These data underscore the therapeutic potential of addressing the p53/Mage-A interaction.   MAGE-A3 has emerged as a potential biomarker for predicting responses to immunotherapy. Szincsak et al. [15] performed a systematic evaluation and meta-analysis of machine learning models utilizing tumors RNA expression data from gastrointestinal cancer patients undergoing treatment with immune checkpoint inhibitors.   Despite research on MAGE-A3 in colorectal cancer in other populations, its expression has not yet been investigated in Iraqi patients. this is the first study to evaluate MAGE-A3 mRNA expression in blood samples from Iraqi CRC patients, providing novel molecular insight and assessing its potential as a diagnostic biomarker.   The objectives of this study to evaluate MAGE-A3 mRNA expression in blood samples from patients with colorectal cancer (CRC) and non-malignant colorectal diseases (CRD). And to assess the potential of MAGE-A3 as a diagnostic biomarker for distinguishing malignant from benign colorectal conditions.   Study Design and Blood Sample Collection A case-control study was conducted from 1st of November 2024 to 31 January 2025 at the Department of Microbiology, College of Medicine, Al-Iraqia University.   Two groups were categorised from 60 patients suffering from GIT problems: The first one, the CRC group (n = 30), patients who are diagnosed with confirmed colorectal cancer and didn’t start therapy, the second one, the CRD group (n=30), patients who suffer from other Colorectal diseases. Healthy control samples (n = 30) were used as the calibrator group to normalise gene expression data from CRC (n = 30) and CRD (n = 30) samples. All groups were with ages ranging between (16-81) years old, of both sexes. Blood samples were collected from participants selected from major hospitals in Baghdad, including the Medical City Directory hospitals (GIT and Liver Diseases Teaching Hospital, Baghdad Teaching Hospital and Oncology Hospital), representing the typical patient population for colorectal diseases.   Exclusion Criteria Excluded from the study were patients who stopped participating because they underwent chemotherapy, passed away or decided not to continue and hemolysis samples.   Sample Collection and RNA Extraction RNA Extraction: Total RNA was extracted using TRIzol™ Reagent (Invitrogen, USA; Cat. No. 15596026) following the manufacturer’s instructions. Briefly, 600 µL of TRIzol™ was added to 0.5 mL of blood in a 1.5 mL microcentrifuge tube, followed by 0.15 mL chloroform for cell lysis. Samples were incubated at 25°C for 20 min and then centrifuged at 12,000×g for 15 min. The mixture separated into a lower red phenol-chloroform phase, an interphase and a colorless upper aqueous phase. The aqueous phase containing RNA was carefully transferred to a new tube. RNA was precipitated by adding 0.45 mL isopropanol, incubated at 25°C for 20 min and centrifuged at 12,000×g for 10 min. The RNA pellet was washed with 0.75 mL of 75% ethanol, vortexed and centrifuged at 7,500×g for 5 min. The supernatant was discarded and the pellet was air-dried for 15 min, then resuspended in 50 µL RNase-free water and incubated at 60°C for 15 min using a thermomixer. RNA quantity and purity were measured using a Nanodrop spectrophotometer and integrity was confirmed by agarose gel electrophoresis.   Quantitative Real-Time (RT-PCR) Following the manufacturer’s instructions, total RNA was converted into cDNA using the EasyScript® First-Strand cDNA Synthesis SuperMix Kit (TransGen Biotech, Beijing, China; Cat. No. AE301-02). The cDNA synthesis process involved incubating the mixture at 25°C for 10 minutes to allow random primers to anneal, followed by 42°C for 15 minutes to activate reverse transcriptase and enable binding of Oligo(dT) primers and finally at 85°C for 5 seconds to terminate enzyme activity.The resulting of cDNA was stored at -20°C until use.   Real-time PCR was done using SYBR Green detection with a special kit on a Rotor-Gene Q Real-Time PCR System. The PCR reaction mixture (20 µL) contained SYBR Green Master Mix, forward and reverse primers, cDNA template and nuclease-free water. Each sample was duplicate for both the target and reference genes.   The thermal cycling conditions included enzyme activation at 95°C for 60 seconds (1 cycle), denaturation at 95ºC for 15 seconds, extension at 60ºC for 30 seconds for 45 cycles, followed by melt curve analysis from 60 to 95ºC.   The 2^(-ΔΔCt) method [16] was used for relative quantification, with GAPDH serving as the internal reference gene to normalise threshold cycle (Ct) values. ΔCT was calculated by subtracting the Ct of GAPDH from the Ct of MAGE-A3 and ΔΔCT was obtained by subtracting the ΔCT of the control samples from the ΔCT of the experimental samples. Relative expression levels were expressed as 2^(-ΔΔCT) to ensure accurate quantification of MAGE-A3 expression.   Specific primers for MAGE-A3 and the housekeeping gene GAPDH were designed and obtained from Macrogen® (Korea) (Table 1).   Table 1: Primers Used and Designed in this Study Gene/Primer Sequence (5′ → 3′) Source MAGE-A3 Forward (MAGE-A3_F) 5-GTTTCCACTGCCTCCTGTGAC-3 macrogen® (Korea) MAGE-A3 Reverse (MAGE-A3_R) 5-GACGCTCATTCAACCATCCGT-3 macrogen® (Korea) GAPDH Forward (GAPDH-F) 5-GTCTCCTCTGACTTCAA-3 macrogen® (Korea) GAPDH Reverse (GAPDH-R) 5-ACCACCCTGTTGCTGTA-3 macrogen® (Korea)   Ethical Approval The study protocol was approved by the Ethics Committee of Al-Iraqia University (Approval ID: FM.SA/150 2025/4/27). Written informed consent was obtained from all participants prior to sample collection.   Statical Analysis Data were entered, verified and analysed using computer software programs of Statistical Package of Social Science (SPSS) version 26 and STATISTICA version 9. Descriptive statistics including frequency, distribution tables, number and percentages for qualitative data as well as mean, standard deviation and range for quantitative data were employed, Comparisons of MAGE-A3 expression among the study groups (CRC, CRD and healthy controls) were performed using one-way ANOVA, assuming normal distribution and homogeneity of variance. Chi-square tests were applied to assess differences in categorical variables, such as sex distribution and expression positivity, while the Likelihood ratio test was used as an alternative when Chi-square assumptions were not fully met. A p-value of <0.05 was used for determining statistical significance throughout study.

data

This study highlights the significant upregulation of MAGE-A3 mRNA in patients with colorectal cancer (CRC) compared to CRD. Age was significantly associated with colorectal cancer and disease (P = 0.000), while sex differences were not significant. Among CRC cases, adenocarcinoma was the predominant type, with most tumors moderately differentiated. Gene expression above one was significantly higher in the CRC group than the CRD group, suggesting its potential as a diagnostic biomarker for CRC.   Future Recommendations Future studies should include larger, multicenter cohorts, validate findings at the protein level, incorporate longitudinal follow-up and explore potential therapeutic implications.   Limitations This study is limited by a small sample size, case-control design, single-country setting and lack of protein-level validation or long-term follow-up.