The pharmacogenomics of drug resistance to protein kinase inhibitors

Dysregulation of growth factor cell signaling is a major driver of most human cancers. This has led to development of numerous drugs targeting protein kinases, with demonstrated efficacy in the treatment of a wide spectrum of cancers. Despite their high initial response rates and survival benefits, the majority of patients eventually develop resistance to these targeted therapies. This review article discusses examples of established mechanisms of drug resistance to anticancer therapies, including drug target mutations or gene amplifications, emergence of alternate signaling pathways, and pharmacokinetic variation. This reveals a role for pharmacogenomic analysis to identify and monitor for resistance, with possible therapeutic strategies to combat chemoresistance

RNA expression of the molecular signature genes for metastasis in colorectal cancer

Colorectal cancer is an endemic disease in the Western world. Search for molecular signatures present in primary tumors that predict tumor metastasis potential has been proposed and in particular, a 17-gene molecular signature is associated with poor survival in breast cancer, prostate cancer, meduloblastoma and lymphoma in a recent study. Using quantitative real-time PCR assay (qPCR), our study observed tumor-normal differential RNA expression in 15 of these 17 genes in a cohort of 52 stage III colorectal cancer patients (all P0.05), two distinct groups among these genes were observed with Spearman correlation scores >0.6 (P0.05), but the recurrence group had more patients with mucinous tumors (9/12 vs. 7/25, P<0.05) and more lymph node involvement (median 7.2 vs. 2.5, P<0.05) compared to the non-recurrence group. Moreover, survival analysis revealed a significant difference in patient overall survival time between low and high tumor RNA levels for 1 of the 17 genes (PTTG1, P=0.024). Our qPCR validation study confirms the importance of most 17-gene molecular signature genes with differential RNA expression and suggests the relevance of PTTG1 for survival in colorectal cancers

Carbamazepine, HLA-B*1502 and risk of Stevens–Johnson syndrome and toxic epidermal necrolysis: US FDA recommendations

Recently, the USA FDA has made a labeling change to the drug information contained in carbamazepine. Owing to recent data implicating the HLA allele B*1502 as a marker for carbamazepine-induced Stevens–Johnson syndrome and toxic epidermal necrolysis in Han Chinese, the FDA recommends genotyping all Asians for the allele. This allele is seen in high frequency in many Asian populations other than Han Chinese, but there are few data on whether the allele is a marker for this severe outcome in anyone other than Han Chinese. In fact, the association has not been found in Caucasian patients. We review the data that prompted this recommendation, list data for other ethnic groups, both Asian and non-Asian, and briefly discuss the implication of this recommendation for clinical practice

Pharmacogenetics, enzyme probes and therapeutic drug monitoring as potential tools for individualizing taxane therapy

The taxanes are a class of chemotherapeutic agents that are widely used in the treatment of various solid tumors. Although taxanes are highly effective in cancer treatment, their use is associated with serious complications attributable to large interindividual variability in pharmacokinetics and a narrow therapeutic window. Unpredictable toxicity occurrence necessitates close patient monitoring while on therapy and adverse effects frequently require decreasing, delaying or even discontinuing taxane treatment. Currently, taxane dosing is based primarily on body surface area, ignoring other factors that are known to dictate variability in pharmacokinetics or outcome. This article discusses three potential strategies for individualizing taxane treatment based on patient information that can be collected before or during care. The clinical implementation of pharmacogenetics, enzyme probes or therapeutic drug monitoring could enable clinicians to personalize taxane treatment to enhance efficacy and/or limit toxicity

Analysis of innate and acquired resistance to anti-CD20 antibodies in malignant and nonmalignant B cells

The anti-CD20 monoclonal antibody, rituximab, provides a significant therapeutic benefit for patients with B-cell disorders. However, response to therapy varies and relapses are common, so an understanding of both inherited and acquired rituximab resistance is needed. In order to identify mechanisms of inherited resistance, sensitive versus resistant individuals were selected from a survey of 92 immortalized lymphoblastoid B-cell lines from normal individuals. Levels of CD20 protein and surface expression were lower in the resistant group. In contrast, CD20 mRNA levels were not correlated with susceptibility, suggesting regulation at a post-transcriptional level. To examine acquired resistance, resistant sublines were selected from both lymphoblastoid as well as lymphoma cell lines. Confirming previous findings, there was significant down-regulation of CD20 protein expression in all the resistant sublines. CD20 mRNA splice variants are reported to be associated with development of resistance. Three splice variants were observed in our cell lines, each lacking the binding epitope for rituximab, but none were associated with rituximab resistance. The second generation anti-CD20 mAb, ofatumumab, was more active compared with rituximab in vitro in the survey of all B-cell lines, mirroring results that have been reported previously with malignant B-cells. These studies show that normal B-lymphoblastoid cell lines can be used to model both innate and acquired mechanisms of resistance. They validate the important role of CD20 expression and enable future genetic studies to identify additional mediators of anti-CD20 mAb resistance

Implications of genome-wide association studies in cancer therapeutics

Genome wide association studies (GWAS) provide an agnostic approach to identifying potential genetic variants associated with disease susceptibility, prognosis of survival and/or predictive of drug response. Although these techniques are costly and interpretation of study results is challenging, they do allow for a more unbiased interrogation of the entire genome, resulting in the discovery of novel genes and understanding of novel biological associations. This review will focus on the implications of GWAS in cancer therapy, in particular germ-line mutations, including findings from major GWAS which have identified predictive genetic loci for clinical outcome and/or toxicity. Lessons and challenges in cancer GWAS are also discussed, including the need for functional analysis and replication, as well as future perspectives for biological and clinical utility. Given the large heterogeneity in response to cancer therapeutics, novel methods of identifying mechanisms and biology of variable drug response and ultimately treatment individualization will be indispensable

Copy number variants in pharmacogenetic genes

Variation in drug efficacy and toxicity remains an important clinical concern. Presently, single nucleotide polymorphisms (SNP) only explain a portion of this problem, even in situations where the pharmacological trait is clearly heritable. The Human CNV Project identified copy number variations (CNVs) across approximately 12% of the human genome, and these CNVs were considered causes of diseases. Although the contribution of CNVs to the pathogenesis of many common diseases is questionable, CNVs play a clear role in drug related genes by altering drug metabolizing and drug response. Here we provide a comprehensive review of the clinical relevance of CNVs to drug efficacy, toxicity, disease prevalence in world populations and discuss the implication of using CNVs as diagnosis in clinical intervention

A Phase II Study of Irinotecan and Carboplatin in Advanced Non-small Cell Lung Cancer with Pharmacogenomic Analysis: Final Report

PurposeWe conducted a phase II study of carboplatin and irinotecan in patients with advanced non-small cell lung cancer (NSCLC). In addition, we studied the correlation between certain genotypes of enzymes involved in irinotecan metabolism with efficacy and toxicity.Patients and MethodsPatients with stage IIIB, IV, or recurrent NSCLC received a combination of irinotecan and carboplatin every 3 weeks at a dose of 200 mg/m2 and area under the curve of 5. Pharmacogenomic analysis was performed on several genes of interest (ABCB1, CYP3A4*1B, ERCC2, GSTP1, UGT1A1*28, and XRCC1).ResultsForty-two patients enrolled between December 2001 and January 2004. Six patients achieved partial responses (14%), and 19 (45%) had stable disease. The median progression-free survival was 6.9 months. The median overall survival was 11.7 months, with 1-year overall survival of 42%. The most common toxicities were hematologic; grade 3 or 4 neutropenia was experienced by 26 patients (62%) during treatment, and 15 patients (36%) experienced grade 3 or 4 thrombocytopenia. The homozygous UGT1A1*28 (7/7) genotype was associated with grade 4 neutropenia in three of four patients (75%), but only eight out of 30 (27%) with 6/6 or 6/7 genotypes experienced grade 4 neutropenia (p = 0.09). None of the 14 patients with the GSTP1 I105V A/A genotype had a partial response, as opposed to five out of 19 (26%) of those with the G/A or G/G genotypes (p = 0.057).ConclusionThe combination of carboplatin and irinotecan is an active combination in NSCLC, with response rates comparable with other platinum-containing doublets. Further studies with irinotecan should incorporate prospective pharmacogenomic analysis to identify markers for response and toxicity

Prediction of steady-state plasma concentrations of olanzapine in Chinese Han in patients based on a retrospective population pharmacokinetic model

Purpose: To develop robust methods of establishing a population pharmacokinetics (Pop-PK) model of olanzapine, using existing hospital in-patient information, in order to predict the steady-state plasma concentration of olanzapine tablets in Chinese Han inpatients, thus providing guidance for individualized therapy for mental disorders.Methods: A retrospective study analyzing and predicting the steady-state plasma olanzapineconcentration was performed using nonlinear mixed-effect modeling (Phoenix® NLME8). The effects of ten potential covariates, including age, gender, Body Mass Index, fasting lipid, family history, alcohol and smoking status in 107 Chinese Han patients with steady-state plasma olanzapine concentration were collected from the hospital information system (HIS) in Wuhan Mental Health Center from Feb 2017 to Jul 2019.Results: The final model was validated using bootstrap and visual predictive check (VPC) and was found to fit the one-compartment mixed error model. Smoking status was found to be the only factor affecting olanzapine tablets clearance. The standard Pop-PK parameters apparent volume of distribution (VL/F) and clearance (CL/F) were 223 L and 12.4 Lꞏh-1, respectively.Conclusion: The Pop-PK model for olanzapine established with the data from HIS is effective inpredicting the plasma olanzapine tablets concentration of individual Chinese in-patients. This Pop-PK model approach can now be adapted to optimize other antipsychotic drugs