Data For: The Precision Oncology Approach to Molecular Cancer Therapeutics Targeting Oncogenic Signaling Pathways is a Means to an End

Published: 28 May 2024| Version 1 | DOI: 10.17632/p3txj3rfj2.1
Manish Kumar


Cancer is a fatal genetic disease with different aspects of complexity, including cancer immune evasion, treatment resistance and recurrence, requiring optimized treatment for proper cure. Molecular studies have revealed that tumors are hugely heterogeneous in nature, leading to the complexity of cancer progression that is ultimately linked to its genetic machinery. In recent decades, there has been a deluge in the large-scale production of anticancer agents, primarily due to advances in genomic technologies enabling precise targeting of oncogenic pathways involved in disease development. It is important to note that patients with the same types of cancer respond differently to cancer treatments, indicating the need for patient-specific treatment options. An in-depth genomic study of tumors will be needed to fully understand the driving factors of cancer initiation and progression for effective targeted therapy. Precision oncology has evolved as a form of cancer therapy focused on genetic profiling of patients’ tumors to identify molecular alterations involved in cancer manifestation for tailored individualized treatment of the disease. This article aims to briefly explain the foundations and frontiers of precision oncology and review the tools and techniques involved in the process to assess its scope and importance in achieving effective cures against cancer.


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Cancer genomics and precision oncology: The TCGA Research Network started in 2005 has profiled and analyzed a large number of human tumors to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels and thereby provided reliable diagnostic and prognostic biomarkers for different cancer types since then.The presence of mutated genes is strongly correlated with cancer incidence, very specific causative genes or a small set of genes for most cancers have not been confirmed after decades of genomic studies. Nobel laureate James D. Watson spoke at Cancer World 2013: "We can go ahead and sequence every piece of DNA that has ever existed, but I don't think we'll find the Achilles heel of cancer. Importantly,, it is not only necessary to associate genetic mutations with different cancers but also to work on the mechanism of action of mutagens by focusing on enzymes which could invariably mediate oncogenic transformations. For example, overexpression of the ribonucleotide reductase (RnR) enzyme which catalyzes the formation of deoxyribonucleotides from ribonucleotides necessary for cell division, is implicated in many forms of cancer and the genes for the components of the enzyme are often mutated, leading to hyperactivity of the enzyme. But there are instances indicating that cytoplasmic material rather than the karyoplast would be responsible for cellular transformation that might be better explained as a consequence of certain epigenetic modulation than purely genetic changes. .RnR active site inhibitors have been developed accordingly to biophysically deactivate the enzyme when necessary, with positive results A comprehensive analysis of tumors based on their genomic studies must reveal the alterations in signaling pathways indicating patterns of vulnerabilities and the means to identify prospective targets for the development of personalized treatments and new combination therapies.Nobel laureate James D. In this regard, the Cancer Cell Map Initiative (CCMI), launched in 2015 by researchers at the University of California, San Francisco and the University of California, San Diego, allowed researchers to determine how hundreds of genetic mutations involved in a few types of cancer affect the activity of certain crucial proteins which ultimately lead to the manifestation of cancer. As there is a large amount of sequence data from many different cancer types, efforts are being made to extract mechanistic insights from the available information, requiring an integrated computational and experimental strategy that will help place these alterations in the higher order contexts of signaling mechanisms in cancer cells. This is the defined goal of the CCMI and has the potential to create a resource that can be used for cancer genome interpretation, enabling the identification of key complexes and pathways to better understand the biology underlying different cancer types and conditions for precise treatment of the disease.


Oncology, Cell Signaling, Immunotherapy, Targeted Therapeutic Agent