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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Decoding Breast Cancer: Emerging Molecular Biomarkers and Novel Therapeutic Targets for Precision Medicine
Dámaris P Intriago-Baldeón1, Eduarda Sofía Pérez-Coral1, Martina Isabella Armas Samaniego2
1Grupo de Investigación en Biomedicina Experimental y Aplicada, Facultad de Ciencias de la Salud, Universidad Internacional SEK (UISEK), Quito 170120, Ecuador.
Abstract:
Breast cancer is the most frequent gynecological malignancy and the main cause of cancer death in the female population worldwide. One of the most significant challenges in its clinical management is the molecular heterogeneity of malignant breast tumors, which is reflected in the current molecular classification of these entities. In each of these tumor molecular subtypes, distinct genetic alterations are involved, and several intracellular signaling pathways contribute to defining their biological identity and clinical response. This literature review summarized the main classic and emerging biomarkers in breast cancer, along with the therapies associated with them. There are several classic biomarkers associated with this disease, such as estrogen and progesterone receptors, the HER2 receptor, and the Ki-67 cell proliferation marker. Given the limitations of these biomarkers, new biomarkers have been identified, including the TP53 tumor suppressor gene, the EGFR, different types of RNAs, plus epigenetic and immunological biomarkers. The integration of classic and emerging biomarkers along with new therapeutic targets in the clinical practice has promoted a thorough understanding of the high molecular complexity of breast cancer and the development of precision medicine strategies which increase the chances of therapeutic success.
Insights
This review covers classic and emerging biomarkers for breast cancer, including estrogen/progesterone receptors, HER2, Ki-67, TP53, and EGFR. Understanding these biomarkers aids precision medicine and improves therapeutic success.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Breast cancer is a leading cause of cancer death globally, characterized by significant molecular heterogeneity.
- This heterogeneity complicates clinical management and treatment response prediction.
- Current molecular classifications reflect distinct genetic alterations and signaling pathways within tumor subtypes.
Purpose of the Study:
- To review classic and emerging biomarkers in breast cancer.
- To discuss associated therapies and their clinical implications.
- To highlight the role of biomarkers in advancing precision medicine.
Main Methods:
- Literature review of classic and emerging breast cancer biomarkers.
- Analysis of established markers like estrogen and progesterone receptors, HER2, and Ki-67.
- Identification and discussion of novel biomarkers including TP53, EGFR, RNAs, and epigenetic/immunological markers.
Main Results:
- Classic biomarkers (ER, PR, HER2, Ki-67) have limitations in fully characterizing breast cancer.
- Emerging biomarkers such as TP53, EGFR, various RNAs, and epigenetic/immunological markers offer deeper insights.
- Integration of these biomarkers enhances understanding of molecular complexity.
Conclusions:
- Novel biomarkers complement traditional ones, improving the characterization of breast cancer subtypes.
- Precision medicine strategies, informed by comprehensive biomarker analysis, enhance therapeutic success rates.
- Continued research into biomarkers is crucial for personalized breast cancer treatment.
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