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Theranostic Interpolation of Genomic Instability in Breast Cancer
Rabia Rasool1, Inam Ullah1, Bismillah Mubeen1
1Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore 54000, Pakistan.
Abstract:
Breast cancer is a diverse disease caused by mutations in multiple genes accompanying epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance results in genomic instability. Theranostic has the potential to foretell and estimate therapy response, contributing a valuable opportunity to modify the ongoing treatments and has developed new treatment strategies in a personalized manner. "Omics" technologies play a key role while studying genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics, metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many effective results. Several diverse tools are used to investigate genomic instability and underlying mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the implications of computational biology regarding mutational and pathway analyses, identification of prognostic markers, and the development of strategies for precision medicine. We also review different technologies required for the investigation of genomic instability in breast cancer cells, including recent therapeutic and preventive advances in breast cancer.
Insights
Genomic instability drives breast cancer diversity. "Omics" technologies and computational biology offer new avenues for early diagnosis, personalized therapies, and improved treatment strategies for breast cancer.
Area of Science:
- Oncology
- Genetics
- Computational Biology
Background:
- Breast cancer arises from genetic mutations and epigenetic changes affecting oncogenes and tumor suppressors.
- Genomic instability, caused by disruptions in cell cycle, DNA repair, and telomere maintenance, is a hallmark of breast cancer.
- Theranostics and "Omics" technologies (genomics, proteomics, metabolomics) are crucial for understanding and managing breast cancer.
Purpose of the Study:
- To explore the genomic landscape and tumor heterogeneity in breast cancer.
- To investigate the mechanisms driving genomic instability in breast cancer initiation.
- To review computational biology's role in analyzing mutations, pathways, and developing precision medicine strategies.
Main Methods:
- Review of "Omics" technologies (genomics, proteomics, metabolomics) for studying breast cancer.
- Analysis of computational techniques for early diagnosis and therapy prediction.
- Examination of tools used to investigate genomic instability and its mechanisms.
Main Results:
- Genomic instability is a key factor in breast cancer development and heterogeneity.
- Computational biology aids in identifying prognostic markers and developing personalized treatment strategies.
- "Omics" data provides insights into mutational landscapes and pathway alterations.
Conclusions:
- Understanding genomic instability is vital for advancing breast cancer research and treatment.
- Precision medicine approaches, informed by "Omics" and computational analysis, hold significant promise.
- Technological advancements are crucial for investigating breast cancer and developing novel therapeutic and preventive strategies.
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