Oncogenomics and CYP450 Implications in Personalized Cancer Therapy

Background: The Human Genome Project has unleashed the power of genomics in clinical practice as a choice of individualized therapy, particularly in cancer treatment. Pharmacogenomics is an interdisciplinary field of genomics that deals with drug response, based on individual genetic makeup. Objective: The main genetic events associated with carcinogenesis activate oncogenes or inactivate tumor-suppressor genes. Therefore, drugs should be specific to inactivate or regulate these mutant genes and their protein products for effective cancer treatment. In this review, we summarize how polymedication decisions in cancer treatments based on the evaluation of cytochrome P450 (CYP450) polymorphisms are applied for pharmacogenetic assessment of anticancer therapy outcomes. Results: However, multiple genetic events linked, inactivating a single mutant gene product, may be insufficient to inhibit tumor progress. Thus, genomics and pharmacogenetics directly influence a patient’s response and aid in guiding clinicians to select the safest and most effective combination of medications for a cancer patient from the initial prescription. Conclusion: This review outlines the roles of oncogenes, the importance of cytochrome P450 (CYP450) in cancer susceptibility, and its impact on drug metabolism, proposing combined approaches to achieve precision therapy.

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Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocw009 ◽

2016 ◽

Vol 23 (4) ◽

pp. 750-757 ◽

Cited By ~ 10

Author(s):

Jun Xu ◽

Hee-Jin Lee ◽

Jia Zeng ◽

Yonghui Wu ◽

Yaoyun Zhang ◽

...

Keyword(s):

Clinical Trials ◽

Cancer Therapy ◽

Cancer Treatment ◽

Knowledge Base ◽

Genetic Alterations ◽

Genetic Alteration ◽

Treatment Trials ◽

Personalized Cancer Therapy ◽

Personalized Cancer ◽

Manual Review

Abstract Objective: Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. Methods: We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. Results and Discussion: The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy.

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Targeting Akt in cancer for precision therapy

Journal of Hematology & Oncology ◽

10.1186/s13045-021-01137-8 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Hui Hua ◽

Hongying Zhang ◽

Jingzhu Chen ◽

Jiao Wang ◽

Jieya Liu ◽

...

Keyword(s):

Clinical Trials ◽

Cancer Therapy ◽

Protein Kinases ◽

Anticancer Agents ◽

Phase Iii ◽

Akt Inhibitor ◽

Precision Therapy ◽

And Migration ◽

Personalized Cancer Therapy ◽

Personalized Cancer

AbstractBiomarkers-guided precision therapeutics has revolutionized the clinical development and administration of molecular-targeted anticancer agents. Tailored precision cancer therapy exhibits better response rate compared to unselective treatment. Protein kinases have critical roles in cell signaling, metabolism, proliferation, survival and migration. Aberrant activation of protein kinases is critical for tumor growth and progression. Hence, protein kinases are key targets for molecular targeted cancer therapy. The serine/threonine kinase Akt is frequently activated in various types of cancer. Activation of Akt promotes tumor progression and drug resistance. Since the first Akt inhibitor was reported in 2000, many Akt inhibitors have been developed and evaluated in either early or late stage of clinical trials, which take advantage of liquid biopsy and genomic or molecular profiling to realize personalized cancer therapy. Two inhibitors, capivasertib and ipatasertib, are being tested in phase III clinical trials for cancer therapy. Here, we highlight recent progress of Akt signaling pathway, review the up-to-date data from clinical studies of Akt inhibitors and discuss the potential biomarkers that may help personalized treatment of cancer with Akt inhibitors. In addition, we also discuss how Akt may confer the vulnerability of cancer cells to some kinds of anticancer agents.

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Personalized Cancer Therapy Considering Cytochrome P450 Variability

Cytochrome P450 Function and Pharmacological Roles in Inflammation and Cancer - Advances in Pharmacology ◽

10.1016/bs.apha.2015.03.004 ◽

2015 ◽

pp. 113-130 ◽

Cited By ~ 1

Author(s):

Saskia Preissner ◽

Maurizio Simmaco ◽

Giovanna Gentile ◽

Robert Preissner

Keyword(s):

Cytochrome P450 ◽

Cancer Therapy ◽

Personalized Cancer Therapy ◽

Personalized Cancer

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A closed-loop optimization framework for personalized cancer therapy design

2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) ◽

10.1109/cibcb48159.2020.9277647 ◽

2020 ◽

Author(s):

Fabrizio Angaroni ◽

Mattia Pennati ◽

Lucrezia Patruno ◽

Davide Maspero ◽

Marco Antoniotti ◽

...

Keyword(s):

Cancer Therapy ◽

Closed Loop ◽

Loop Optimization ◽

Optimization Framework ◽

Personalized Cancer Therapy ◽

Personalized Cancer ◽

Therapy Design

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Making the Most of Complexity to Create Opportunities: Comprehensive Genomic Profiling and Molecular Tumor Board for Patients with Non-Small Cell Lung Cancer (NSCLC)

Cancers ◽

10.3390/cancers13040609 ◽

2021 ◽

Vol 13 (4) ◽

pp. 609

Author(s):

Caterina Fumagalli ◽

Elena Guerini-Rocco ◽

Massimo Barberis

Keyword(s):

Lung Cancer ◽

Small Cell ◽

Tumor Board ◽

Genomic Profiling ◽

Small Cell Lung ◽

Molecular Alterations ◽

Comprehensive Genomic Profiling ◽

Molecular Tumor Board ◽

Personalized Cancer Therapy ◽

Personalized Cancer

Personalized cancer therapy matches the plan of treatment with specific molecular alterations [...]

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Smart Nanoparticles for Chemo-Based Combinational Therapy

Pharmaceutics ◽

10.3390/pharmaceutics13060853 ◽

2021 ◽

Vol 13 (6) ◽

pp. 853

Author(s):

Binita Shrestha ◽

Lijun Wang ◽

Eric M. Brey ◽

Gabriela Romero Uribe ◽

Liang Tang

Keyword(s):

Cancer Treatment ◽

Cancer Biology ◽

Complex Disease ◽

Rapid Development ◽

Acquired Resistance ◽

Therapeutic Index ◽

Chemotherapeutic Agents ◽

Combinational Therapy ◽

Precision Therapy ◽

External Stimuli

Cancer is a heterogeneous and complex disease. Traditional cancer therapy is associated with low therapeutic index, acquired resistance, and various adverse effects. With the increasing understanding of cancer biology and technology advancements, more strategies have been exploited to optimize the therapeutic outcomes. The rapid development and application of nanomedicine have motivated this progress. Combinational regimen, for instance, has become an indispensable approach for effective cancer treatment, including the combination of chemotherapeutic agents, chemo-energy, chemo-gene, chemo-small molecules, and chemo-immunology. Additionally, smart nanoplatforms that respond to external stimuli (such as light, temperature, ultrasound, and magnetic field), and/or to internal stimuli (such as changes in pH, enzymes, hypoxia, and redox) have been extensively investigated to improve precision therapy. Smart nanoplatforms for combinational therapy have demonstrated the potential to be the next generation cancer treatment regimen. This review aims to highlight the recent advances in smart combinational therapy.

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