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Abstract

Personalized medicine and targeted therapy have been emerging fields of study for the remediation and inhibition of cancer. Personalized medicine in the treatment of cancer involves using genetic, immune, and proteomic profiling to provide therapeutic options as well as prognostic background for every patient and their tumor’s genetic mutations. Targeted therapies allow researchers and medical personnel alike to determine the appropriate treatment for a patient based on the molecular basis and mechanistic actions of a cancerous tumor. The overall significance of this study was to express how these treatments use biomarkers to pinpoint the location, and severity of the cancer, and to administer the right treatment. Early detection of tumor‐specific biomarkers can allow the use of non‐invasive routine monitoring.

The study aims to provide an elaborate explanation on the various biomarker classification and present the protocol on how they are sorted and validated to be a potential cancer biomarker used in clinical practice. Categorizing biomarkers relies on their characteristics. These classifiers will divide them into one of the following groups: general biomarkers, DNA biomarkers, and DNA tumor biomarker. The expressions of microRNA also play a role in the determination of cancer, as most of these clusters regulate the expression and transcriptional activity of various cancer cell lines. The expression of the ER receptors in mammalian cells classifies breast cancer into one of the following categories: triple negative, estrogen receptor (ER) negative, or (ER) positive. ER positive breast cancer patients can positively benefit from personalized medicine as these patients have to undergo specific hormonal therapy and supplementary adjuvant chemotherapy to eliminate the estrogen-induced proliferation of these mammalian cells. Drugs like tamoxifen function as antagonists to the ER receptor to inhibit the transcriptional activity of the ER receptors. Other cancer types such as colorectal cancer, and lung cancer may also benefit from such approaches.

The limitations of the study include the unique genomic profiling of each patient, challenges in validation and implementation of drug combinations, and the deployment of technologies for DNA sequencing.

Keywords: cancer, biomarkers, personalized medicine, gene therapy, targeted therapy, DNA Biomarker, RNA expressions, ER, colorectal cancer, lung cancer, prostate cancer, leukemia, targeted treatment

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