The study explores glucose metabolism in breast cancer by examining biomarkers such as c-MYC, CA 27-29, LDH, and others to determine their potential in differentiating between subtypes, their association with metastasis, and their associations with metabolic changes. Other parameters, such as glycated hemoglobin levels, liver function, and lipid levels, were also measured in both the patient and healthy control groups.

The study was conducted from August 2023 to January 2024 in Baghdad, and included 120 women aged 35–66 years: 80 breast cancer patients (20 of each subtype: Luminal A, HER2-enriched, TPBC, and TNBC) and 40 healthy controls matched for age and BMI. Most patients were stage II or III and receiving standard treatments. Patients with diabetes, polycystic ovary syndrome, or hormone-related disorders were excluded. Diagnosis and receptor status were confirmed by biopsy and histological examination. Biomarkers c-MYC and CA 27-29 were measured by ELISA, and LDH, glycated hemoglobin levels, liver function, and lipids were measured by spectrophotometry.

The most important recommendations of the thesis are:

1. Use integrated, multi-biomarker prognostic models to enhance early detection of breast cancer and support the development of personalized surveillance strategies. Particular attention should be paid to the relationship between metabolic markers (such as HbA1c and lipid levels) and tumor biology, which may reveal important insights into cancer behavior and prognosis.
2. Enhance the clinical utility of biomarkers in breast cancer diagnosis, monitoring, and differentiation into subtypes.
3. Study fluctuations in biomarkers in response to treatment—such as changes in liver enzymes due to chemotherapy or hormonal therapy.