Unlocking Precision Medicine: The Role of Biomarkers in Oncology
Diagnosis, prognosis and treatment planning in oncology has revolutionized by biomarkers. Key biomarkers like Tumor Mutational Burden (TMB), Microsatellite Instability (MSI), Homologous Recombination Deficiency (HRD), and Loss of Heterozygosity (LOH) score play critical roles in personalized medicine, helping oncologists decide treatments to patients and improve outcomes.
Tumor Mutational Burden (TMB) measures the number of mutations within a tumor's DNA. High TMB can indicate better responses to immunotherapy. For instance, patients with non-small cell lung cancer (NSCLC) and melanoma have shown improved outcomes with immune checkpoint inhibitors like pembrolizumab and nivolumab when TMB is high [1,2].
Microsatellite Instability (MSI) shows defects in the DNA mismatch repair system. MSI-high status, common in colorectal and endometrial cancers, predicts better responses to immunotherapies like pembrolizumab and nivolumab. MSI testing examines tumor tissue for instability in microsatellite regions [3,4].
Homologous Recombination Deficiency (HRD) and Loss of Heterozygosity (LOH) Score assess a tumor's DNA repair capabilities. HRD makes tumors more susceptible to treatments like PARP inhibitors. For example, ovarian and breast cancer patients with BRCA mutations (indicating HRD) benefit from PARP inhibitors such as olaparib. The FDA has approved olaparib, rucaparib, and niraparib for HRD-positive ovarian cancer, highlighting HRD's importance as a biomarker [5].
Next-Generation Sequencing (NGS) plays a crucial role in identifying and analyzing these biomarkers. NGS provides comprehensive genetic profiling, enabling precision medicine, early detection, and monitoring of treatment responses. It supports clinical trials and research by identifying novel genetic mutations and pathways involved in cancer.
In conclusion, TMB, MSI, HRD, and LOH score have pivotal role in oncology, guiding personalized treatment decisions. NGS technology has been instrumental in their identification and analysis, paving the way for more effective and tailored cancer therapies. Real-world examples, like pembrolizumab in MSI-high colorectal cancer and olaparib in HRD-positive ovarian cancer, demonstrate their transformative impact on clinical practice [1,5].
Reference:
1. Ricciuti, Biagio et al. “Association of High Tumor Mutation Burden in Non-Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 Expression Levels.” JAMA oncology vol. 8,8 (2022): 1160-1168. doi:10.1001/jamaoncol.2022.1981
2. Ning, Biao et al. “The Predictive Value of Tumor Mutation Burden on Clinical Efficacy of Immune Checkpoint Inhibitors in Melanoma: A Systematic Review and Meta-Analysis.” Frontiers in pharmacology vol. 13 748674. 9 Mar. 2022, doi:10.3389/fphar.2022.748674
3. Gatalica, Zoran et al. “High microsatellite instability (MSI-H) colorectal carcinoma: a brief review of predictive biomarkers in the era of personalized medicine.” Familial cancer vol. 15,3 (2016): 405-12. doi:10.1007/s10689-016-9884-6
4. Tinker, Anna V et al. “A rapidly evolving landscape: immune checkpoint inhibitors in pretreated metastatic endometrial cancer.” Therapeutic advances in medical oncology vol. 15 17588359231157633. 18 Mar. 2023, doi:10.1177/17588359231157633
5. Valabrega, Giorgio et al. “Differences in PARP Inhibitors for the Treatment of Ovarian Cancer: Mechanisms of Action, Pharmacology, Safety, and Efficacy.” International journal of molecular sciences vol. 22,8 4203. 19 Apr. 2021, doi:10.3390/ijms22084203
