INTERNATIONAL CONGRESS OF
CancerGenetics
Exploring the Correlation of Key Breast Cancer Biomarkers with BCL2, GRB7, and BIRC5 Gene Expression: Advancing Personalized Treatment Strategies
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Mohammadreza Haji Jafari,1 Rita Arabsolghar,2 Nazanin Aghaiee,3 Samin Davatgar,4 Jamileh Saberzadeh,5,*
1. Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences
2. Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences/ Diagnostic Laboratory Sciences and Technology Research Center, Paramedical School, Shiraz University of Medical Science
3. Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences
4. Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences
5. Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences/ Diagnostic Laboratory Sciences and Technology Research Center, Paramedical School, Shiraz University of Medical Science
- Introduction: Breast cancer is a heterogeneous disease characterized by a diverse range of molecular alterations. The assessment of key biomarkers such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 at the primary stage, using molecular techniques like immunohistochemistry and reverse transcriptase quantitative PCR (RT-qPCR), plays a crucial role in determining intrinsic tumor subtypes. Furthermore, the expression levels of these essential biomarkers in individual patients can enable personalized treatment approaches, mitigate the likelihood of inappropriate therapy, and provide insights into the potential risk of tumor recurrence post-surgery. Certain multigene RT-qPCR assays focused on pretreatment tissue samples evaluate a specific set of hormone receptor genes linked to breast tumor invasion and proliferation, alongside traditional biomarkers. These assays are vital for selecting appropriate therapies and predicting the likelihood of tumor recurrence. Among these important biomarkers are BCL2, GRB7, and BIRC5 (Survivin), which exhibit a strong correlation with primary biomarkers such as ER, PR, HER2, and Ki67. Investigating BCL2 expression is critical in cases of ER-positive tumors that are resistant to hormone therapy, as it can guide the implementation of supplementary hormonal treatments aimed at reducing tumor size. Additionally, elevated GRB7 expression in HER2-positive tumors is associated with an increased risk of tumor recurrence; hence, GRB7 antagonist peptides in HER2+/GRB7+ cases may enhance survival rates. Furthermore, a high co-expression of Ki67 and BIRC5 is indicative of a greater likelihood of tumor recurrence and metastasis, suggesting that more aggressive treatment strategies may be necessary to extend patient survival. In this study, we aimed to evaluate the correlation between BCL2, GRB7, and BIRC5 biomarkers and major breast cancer biomarkers, with the goal of optimizing personalized treatment strategies for breast cancer patients.
- Methods: Firstly, RNA of formalin-fixed paraffin-embedded (FFPE) tumor tissues from 100 patients with infiltrative, primary stage, and untreated breast cancer and 12 normal margin samples were extracted. In addition, immunohistochemistry (IHC) results of key biomarkers for breast tumor tissues were available. After that, RNA-extracted samples were examined by TaqMan probe RT-qPCR for quantification of BCL2, GRB7, and BIRC5 expression. Then, the relative fold change (RFC) of each sample was calculated by the Livak formula. Next, the qualitative expression of biomarkers BCL2, GRB7, and BIRC5, obtained from RT-qPCR testing, was evaluated in relation to the qualitative expression of the four main biomarkers, ER, PR, HER2, and Ki67, obtained from IHC testing, using the Chi-square statistical test. Finally, using the non-parametric Spearman statistical test, the correlation of expression between the three biomarkers BCL2, GRB7, and BIRC5 was examined across the entire study population.
- Results: The statistical analysis revealed significant correlation between the expression of BCL2 with ER (p-value = 0.025) and PR (p-value = 0.008). GRB7 was significantly correlated with HER2 (p-value = 0.000), and BIRC5 with Ki67 (p-value = 0.001). There was a significant inverse correlation between the relative expression of BCL2 and BIRC5 (p-value = 0.000). Conversely, there was a significant direct correlation between BCL2 and GRB7 (p-value = 0.000). However, the analysis did not reveal a significant correlation between BIRC5 and GRB7 (p-value = 0.054)
- Conclusion: A significant correlation was identified between the expression levels of BCL2 with ER and PR, GRB7 with HER2, and BIRC5 with Ki67. This interrelationship is crucial not only for guiding treatment decisions tailored to specific breast cancer subtypes but also for offering reliable prognostic insights. Such insights can aid in predicting the duration of tumor recurrence post-treatment, assessing survival probabilities, and evaluating the risk of metastasis. The correlation between BCL2 and GRB7 supports the hypothesis that increased expression of these biomarkers may lead to the inhibition of apoptotic pathways across various breast cancer subtypes. In contrast, the negative correlation observed between BCL2 and BIRC5 indicates that, in advanced stages of the disease, high levels of BCL2 expression may be viewed as a negative prognostic factor. This interplay among the biomarkers highlights the complexity of breast cancer biology and underscores the importance of tailored therapeutic approaches based on biomarker profiles.
- Keywords: Breast cancer; Biomarkers; Personalized medicine; BCL2; GRB7; BIRC5
