Metabolic characterization of locally advanced breast cancer in response to NAC treatment based on HR MAS MRS
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Breast cancer is the most frequent cancer disease among women globally. Locally advanced breast cancer (LABC) consists of different groups of breast cancer patients with variable prognosis. Today’s treatment decision is mostly based on clinical assessment, histopathologocal evaluation, and hormone receptor and lymph node status. So far, these data are not sufficient for designing more effective personalized medicine or accurately predicting the prognosis of the disease. Metabolic characterization of tumors may assist clinicians to classify patients for more personalized treatment, and moreover, improving the prognosis. Magnetic resonance (MR) metabolomics assess the downstream product of gene and protein expression and provide predictive and prognostic information for several types of cancer. Proton high resolution magic angle spinning (1H HR MAS) MR spectroscopy is a nondestructive technique which was developed to improve the spectral resolution of MR spectra from intact tissue. The ERETIC method for accurate quantification was used to quantify metabolites. Recently, the metabolic changes have been suggested as a new emerging hallmark of cancer. Choline phospholipid metabolism is involved in cell signaling, lipid metabolism and participating in cell membrane structure. Several studies have suggested total choline containing metabolites (tCho) level as a biomarker for treatment evaluation of breast cancer. Moreover, it has become increasingly clear that high level of GPC is associated with poor prognosis in breast cancer. In this study, nonparametric tests on quantified metabolite data (acquired from 1H HR MAS MRS spectra) were performed to investigate potential biomarkers for prediction of prognosis in LABC patients receiving NAC treatment. The metabolite changes were also studied in order to find a pattern of metabolic changes in LABC patients pre- and post NAC treatment. In addition, the protocols of homogenization and RNA/DNA isolation from tissue samples were optimized. All patients had a metabolic response to NAC. This thesis demonstrates that MR metabolomics profile contains information that is associated with survival status response to treatment in LABC patients. Based on results by both paired and unpaired tests, survivors showed significant decrease in GPC level while non-survivors showed significant decrease in PG/GPC. Moreover, It is become increasingly clear that high level of GPC is associated with poor prognosis in breast cancer. It is also reported that the decreasing in GPC level in response to treatment is related to long-term survivors breast cancer. In normal mammary cell cultures, PC/GPC ratio increases during malignant transformation. The discrepancy between acquired result in this study and previous findings might be as a result of differences in microenvironment of mammary cell cultures and tumor biopsies. In the current study, responders showed significant increase in m-Ino while non-responders showed significant decrease in Cho and tCho. As reported by several studies, m-Ino has demonstrated anti-cancer functions in some of the cancers like breast and colon cancer. However, the molecular mechanisms underlying this anticancer action are not fully understood. In addition, the group with stable disease (non-responders) can obtain <50% decrease in tumor volume based on their definition. This might be the reason for having decrease in Cho and tCho levels in non-responders, which were not expected based on previous findings. After metabolic profiling of LABC patients, the gene and protein expression study on samples could be valuable to introduce over-expressed or down-regulated gene and proteins in patients. Optimization the RNA/DNA and protein isolation would be the first step on this research process. DNA samples concentrations showed to have high linear correlation with tumor cell content. DNA and RNA concentrations were also strongly correlated. The Mann Whitney test between different groups of patients based on their tumor cell content showed significant differences in DNA and RNA concentrations between groups with larger differences in their cell content. This would suggest that the most extracted DNA and RNA are from cancer cells not from normal cells present in the samples. In conclusion, the metabolite response to the NAC treatment in LABC patients may have the potential to assist the prediction of survival and help to identify new targets for LABC breast cancer treatment. Furthermore, high quality RNA and DNA samples would be valuable for further analyses in order to identify new targets for LABC treatment.