About this Research Topic
In cancer pharmacotherapy, many issues faced preclude achieving the desired clinical outcomes. Poor response to treatment, ineffectiveness of the drugs, multidrug resistance, cancer recurrence, and cytotoxic drugs-related problems (DRPS) represent major obstacles in clinical practice. The heterogeneity and complexity of cancer coupled with the microenvironment lead to no or only partial response in some patients. The response for antineoplastic treatments approved by Food and Drug Administration (FDA) ranges from 20% to 60%, with an average of only 40 %. The prevalence of DRPs in medical practice accounts for 25 % of hospitalized patients. Given their narrow therapeutic window and complex pharmacologic profile, the percentage is much higher for chemotherapeutic agents. The intense need for combination therapy exacerbates such issues. Furthermore, the disease alters the pharmacokinetic parameters due to reduced levels of serum-binding proteins, malnutrition, edema, or hepatic and/or renal dysfunction.
Pharmacogenomics (PGx) is an emerging field that covers applying genetic information to tailor the selection and utilization of medicines to individual patients to amplify drug efficacy, mitigate adverse drug reactions, and improve therapeutic outcomes. In cancer pharmacotherapy, the PGx approach has gained considerable attractiveness due to the aforementioned issues associated with the tumor and its therapies. It has a considerable capability to individualize cancer therapy, limiting the frequency and severity of toxicity while enhancing efficiency. It is a powerful tool to identify individuals at high risk of adverse effects or who are most likely to benefit from a certain medication, advancing us toward the ultimate goal of personalized neoplasm pharmacotherapy. In cancer, genomics is distinguished significantly compared to other diseases in the way the patient's germline genome and the tumor's somatic genome are implicated in the sickness. The patient's genome causes interindividual variations in inherited genes, while the latter's responsibility is the accumulation of acquired somatic mutations that result in variable responses.
Predicting clinical outcomes in cancer patients based on their genetic factors has increasingly become of researchers' interest. To date, there are multiple genetic biomarkers whose impact has been identified. Consequently, genetic testing for some drugs has been recommended by FDA. To cite relevant examples, breast cancer patients who are HER2 gene positive are good candidates for trastuzumab and ado-trastuzumab. In contrast, those whose cancers do not produce this gene must not receive these medications since they do not respond to them.
Concerning toxicity, DPD is crucial for the metabolism and degradation of fluorouracil. Patients who have DPD*2A polymorphism are poor or intermediate metabolizers and are borne for higher risk of severe, life-threatening, or fatal toxicities. Similarly, FDA recommends dose reductions for mercaptopurine in patients with genetic variations related to TPM and/or NUDT15 to minimize the risk of myelosuppression. Other targeted drugs, chemotherapeutic drugs, and immune checkpoint inhibitors are affected by genomic profiling and require clinically actionable measures of PGx information.
The vital role of genomics analysis, supported by robust evidence, for advancing the pharmacological treatment of cancer urges the active progress of genomic research in the field along with further regulatory guidance and support for optimizing the treatment in the oncological field. It also prompts the advancement of genomics technologies, including developing high throughput technologies, genome-wide scans, gene expression arrays, and SNP chips to discover candidate genes and SNPs that had not yet been identified and validate their PGx associations which can finally be evaluated for their clinical implementations.
In light of the foregoing, this Research Topic aims to collect the most recent progress in the oncology PGx for confronting the major challenges in cancer pharmacotherapy. This includes but is not limited to the updates on the impact of genetic variations on drug efficacy and safety, drug metabolism, drug-receptors binding, drug uptake, and targeted drug development. It welcomes submissions of original research, reviews articles, protocols, case reports, etc. Original research based solely on in silico techniques will not be considered for review.
Please note that:
- If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities, and additional clinical information and assessment of clinical response/effects should be included.
- If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for selecting the specific data studied should be provided.
- Studies related to natural compounds, herbal extracts, or traditional medicine products, will not be included in this Research Topic.
Pharmacogenomics (PGx) is an emerging field that covers applying genetic information to tailor the selection and utilization of medicines to individual patients to amplify drug efficacy, mitigate adverse drug reactions, and improve therapeutic outcomes. In cancer pharmacotherapy, the PGx approach has gained considerable attractiveness due to the aforementioned issues associated with the tumor and its therapies. It has a considerable capability to individualize cancer therapy, limiting the frequency and severity of toxicity while enhancing efficiency. It is a powerful tool to identify individuals at high risk of adverse effects or who are most likely to benefit from a certain medication, advancing us toward the ultimate goal of personalized neoplasm pharmacotherapy. In cancer, genomics is distinguished significantly compared to other diseases in the way the patient's germline genome and the tumor's somatic genome are implicated in the sickness. The patient's genome causes interindividual variations in inherited genes, while the latter's responsibility is the accumulation of acquired somatic mutations that result in variable responses.
Predicting clinical outcomes in cancer patients based on their genetic factors has increasingly become of researchers' interest. To date, there are multiple genetic biomarkers whose impact has been identified. Consequently, genetic testing for some drugs has been recommended by FDA. To cite relevant examples, breast cancer patients who are HER2 gene positive are good candidates for trastuzumab and ado-trastuzumab. In contrast, those whose cancers do not produce this gene must not receive these medications since they do not respond to them.
Concerning toxicity, DPD is crucial for the metabolism and degradation of fluorouracil. Patients who have DPD*2A polymorphism are poor or intermediate metabolizers and are borne for higher risk of severe, life-threatening, or fatal toxicities. Similarly, FDA recommends dose reductions for mercaptopurine in patients with genetic variations related to TPM and/or NUDT15 to minimize the risk of myelosuppression. Other targeted drugs, chemotherapeutic drugs, and immune checkpoint inhibitors are affected by genomic profiling and require clinically actionable measures of PGx information.
The vital role of genomics analysis, supported by robust evidence, for advancing the pharmacological treatment of cancer urges the active progress of genomic research in the field along with further regulatory guidance and support for optimizing the treatment in the oncological field. It also prompts the advancement of genomics technologies, including developing high throughput technologies, genome-wide scans, gene expression arrays, and SNP chips to discover candidate genes and SNPs that had not yet been identified and validate their PGx associations which can finally be evaluated for their clinical implementations.
In light of the foregoing, this Research Topic aims to collect the most recent progress in the oncology PGx for confronting the major challenges in cancer pharmacotherapy. This includes but is not limited to the updates on the impact of genetic variations on drug efficacy and safety, drug metabolism, drug-receptors binding, drug uptake, and targeted drug development. It welcomes submissions of original research, reviews articles, protocols, case reports, etc. Original research based solely on in silico techniques will not be considered for review.
Please note that:
- If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities, and additional clinical information and assessment of clinical response/effects should be included.
- If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for selecting the specific data studied should be provided.
- Studies related to natural compounds, herbal extracts, or traditional medicine products, will not be included in this Research Topic.
Keywords: Pharmacogenomics, Cancer, Drug-Related Problems, Genetic Variations, Drug Development, Drug Efficacy, Drug Safety
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