DMET™ (Drug-Metabolizing Enzymes and Transporters) microarray analysis of colorectal cancer patients with severe 5-fluorouracil-induced toxicity

Tools in Pharmacogenomics Biomarker Identification for Cancer Patients

The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.

Pharmacogenomics and functional imaging to predict irinotecan pharmacokinetics and pharmacodynamics: the predict IR study

PURPOSE

Irinotecan (IR) displays significant PK/PD variability. This study evaluated functional hepatic imaging (HNI) and extensive pharmacogenomics (PGs) to explore associations with IR PK and PD (toxicity and response).

METHODS

Eligible patients (pts) suitable for Irinotecan-based therapy. At baseline: (i) PGs: blood analyzed by the Affymetrix-DMET™-Plus-Array (1936 variants: 1931 single nucleotide polymorphisms [SNPs] and 5 copy number variants in 225 genes, including 47 phase I, 80 phase II enzymes, and membrane transporters) and Sanger sequencing (variants in HNF1A, Topo-1, XRCC1, PARP1, TDP, CDC45L, NKFB1, and MTHFR), (ii) HNI: pts given IV 250 MBq-^99mTc-IDA, data derived for hepatic extraction/excretion parameters (CL_HNI, T_1/2-HNI, 1hRET, HEF, T_d1/2). In cycle 1, blood was taken for IR analysis and PK parameters were derived by non-compartmental methods. Associations were evaluated between HNI and PGs, with IR PK, toxicity, objective response rate (ORR) and progression-free survival (PFS).

RESULTS

N = 31 pts. The two most significant associations between PK and PD with gene variants or HNI parameters (P < 0.05) included: (1) PK: SN38-Metabolic Ratio with CL_HNI, 1hRET, (2) Grade 3+ diarrhea with SLC22A2 (rs 316019), GSTM5 (rs 1296954), (3) Grade 3+ neutropenia with CL_HNI, 1hRET, SLC22A2 (rs 316019), CYP4F2 (rs2074900) (4) ORR with ALDH2 (rs 886205), MTHFR (rs 1801133). (5) PFS with T_1/2-HNI, XDH (rs 207440), and ABCB11 (rs 4148777).

CONCLUSIONS

Exploratory associations were observed between Irinotecan PK/PD with hepatic functional imaging and extensive pharmacogenomics. Further work is required to confirm and validate these findings in a larger cohort of patients.

AUSTRALIAN NEW ZEALAND CLINICAL TRIALS REGISTRY (ANZCTR) NUMBER

ACTRN12610000897066, Date registered: 21/10/2010.

Glutathione S-transferases genes variants and chemotherapy efficacy in gastrointestinal cancer patients: a meta-analysis based on 50 pharmacogenetic studies

Background: The role of glutathione s-transferase genes (GSTP1, GSTM1 and GSTT1) variants and the GSTP1 expression level on chemotherapy efficacy of gastrointestinal cancer (GIC) patients were inconsistent. Methods: A meta-analysis about GSTP1, GSTM1 and GSTT1 variants and the GSTP1 expression level on chemotherapy efficacy of GIC patients was performed using data from PubMed, PMC, EMBASE, Web of Science, and Wanfang database. Results: Our meta-analysis enrolled 50 publications including 6518 patients. We found that patients with GIC harboring GSTP1 (IIe105Val) Val locus had higher objective response rates (ORR) than the IIe/IIe genotypic patients (odds ratio (OR) = 1.580, 95% confidence interval (CI) = 1.159-2.154, P = 0.004). Significant associations were found between the Ile105Val variant and overall survival of Caucasian GIC patients (IIe/Val vs. IIe/IIe: OR = 0.797 (0.674-0.944), P = 0.009). Caucasian GIC patients and gastric cancer patients with GSTT1 null genotype had worse response rates compared to GSTT1 present patients (OR = 0.530 (0.356-0.789), P = 0.002; OR = 0.643 (0.463-0.895), P = 0.009, respectively). Conclusion: This meta-analysis illustrates that GSTP1 IIe105Val and GSTT1 null/present variants could be useful predictors of chemotherapy efficacy in patients with gastrointestinal cancer.

Association between SLCO1B1 rs4149056 and tegafur-uracil-induced hepatic dysfunction in breast cancer

Aim: The aim of this study was to identify pharmacogenomic biomarkers to predict tegafur-uracil (UFT)-induced liver dysfunction. Patients & methods: A total of 68 patients, who were administered UFT, were evaluated using a two-step pharmacogenomics analysis. Results: The first screening revealed the association between five SNPs and UFT-induced hepatic dysfunction. In the second step, SLCO1B1 (rs4149056) was found to be the only SNP associated with UFT treatment-related elevation of aspartate aminotransferase (odds ratio: C/C vs T/T = 7.8, C/T vs T/T = 5.7; p = 0.037) and alanine transaminase (odds ratio: C/C vs T/T = 12.2, C/T vs T/T = 4.1; p = 0.034) levels. Conclusion: The SLCO1B1 polymorphisms are possible predictors of UFT treatment-related hepatic dysfunction.

Severe adverse events due to dihydropyrimidine dehydrogenase deficiency in a Japanese patient with colon cancer taking capecitabine: a case report

Fluoropyrimidine has been commonly used not only in unresectable cases of metastatic colorectal cancer, but also in adjuvant therapy. Dihydropyrimidine dehydrogenase (DPD) is an enzyme encoded by the DPYD gene, which is responsible for the rate-limiting step in pyrimidine catabolism and breaks down more than 80% of standard doses of 5-fluorouracil (5-FU) and capecitabine, an oral prodrug of 5-FU. The lack of enzymatic activity increases the half-life of the drug, resulting in excess drug accumulation and toxicity which may lead to life-threatening side effects. There have been several published case reports about DPD deficiency in patients with colorectal cancer in Western countries. However, case reports of DPD deficiency in Japanese patients with colorectal cancer are rare because measuring DPD activity is not covered by public medical insurance in Japan, and it is not examined in our daily clinical practice currently. Therefore, we think that it is important to accumulate such case reports for further understanding. This report describes the case of a Japanese patient with colon cancer who experienced severe side effects while taking capecitabine, due to DPD deficiency. A 68-year-old man with ascending colon cancer underwent curative laparoscopic right hemicolectomy. Because final pathologic staging was Stage IIIa, standard adjuvant chemotherapy with capecitabine (3600 mg/body/day, days 1-14, every 3 weeks) was started on postoperative day 50. After 2 weeks, he started to experience Grade 3 diarrhea and was admitted to the hospital on postoperative day 66. On day 70, the patient had Grade 4 febrile neutropenia. Antibiotics and granulocyte-colony-stimulating factor were administered until his blood tests recovered to the normal degree. After 1 week of diarrhea, antidiarrheal agents were administered, and the patient gradually recovered. During the occurrence of diarrhea, specimen cultures were negative for infection. He was discharged on day 21 of the hospital stay. DPD deficiency was suspected, and 2 weeks later the DPD activity of the peripheral blood mononucleocytes was examined. The result was 10.3 U/mg protein which was remarkedly low (reference range 22.6-183.6 U/mg protein), and DPD deficiency was diagnosed. We always must consider the possibility of DPD deficiency in patients who experience severe side effects while taking capecitabine.

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine

In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.

Pre-treatment assay of 5-fluorouracil degradation rate (5-FUDR) to improve prediction of 5-fluorouracil toxicity in gastro-esophageal cancer

Background

5-fluorouracil (5-FU) based chemotherapy is the most common first line regimen used in gastric and gastroesophageal junction cancer, but development of severe toxicity is a main concern in the treatment. The present study is aimed to evaluate a novel pre-treatment assay, known as the 5-FU degradation rate (5-FUDR), as a predictive factor for 5-FU toxicity.

Methods

Pre-treatment 5-FUDR and gene polymorphisms related to 5-FU metabolism (DPYDIVS14+1G>A, MTHFRA1298T or C677T, TMYS TSER) were characterized in gastro-esophageal cancer patients. Association with toxicities was retrospectively evaluated, using multivariate logistic regression analysis.

Results

107 gastro-esophageal cancer patients were retrospectively analyzed. No relation between gene polymorphisms and toxicity were detected, while low (< 5^th centile) and high (> 95^th centile) 5-FUDRs were associated with development of grade 3-4 toxicity (OR 11.14, 95% CI 1.09-113.77 and OR 9.63, 95% CI 1.70-54.55, p = 0.002).

Conclusions

Compared to currently used genetic tests, the pre-treatment 5-FUDR seems useful in identifying patients at risk of developing toxicity.

5-Fluorouracil toxicity and dihydropyrimidine dehydrogenase enzyme: implications for practice

5-fluorouracil (5-FU) is a fluorinated pyrimidine analog, which is commonly used in combination chemotherapy for treating solid tumors. Dihydropyrimidine dehydrogenase plays an important role in catabolism and clearance of 5-FU. Any alteration in that sequence of enzymatic activity can lead to toxicity and even death in some patients. The most common loss of a functional allele of the dihydropyrimidine gene is the splice-site mutation c.1905+1G>A, which leads to deficiency of the enzyme. However, because of the small percentage of the population in which the deficiency occurs, routine screening is not recommended, and commercial testing is costly. Treatment measures for 5-FU toxicity are mainly supportive, including palliation of symptoms. Good patient assessment and education are imperative to early treatment of 5-FU-induced toxicity. Advanced oncology practitioners and oncology nurses should thoroughly educate patients and their caregivers on both the common and adverse side effects of 5-FU-based therapy and when it may be necessary to immediately contact their healthcare provider.

DMET-Miner: Efficient discovery of association rules from pharmacogenomic data

Microarray platforms enable the investigation of allelic variants that may be correlated to phenotypes. Among those, the Affymetrix DMET (Drug Metabolism Enzymes and Transporters) platform enables the simultaneous investigation of all the genes that are related to drug absorption, distribution, metabolism and excretion (ADME). Although recent studies demonstrated the effectiveness of the use of DMET data for studying drug response or toxicity in clinical studies, there is a lack of tools for the automatic analysis of DMET data. In a previous work we developed DMET-Analyzer, a methodology and a supporting platform able to automatize the statistical study of allelic variants, that has been validated in several clinical studies. Although DMET-Analyzer is able to correlate a single variant for each probe (related to a portion of a gene) through the use of the Fisher test, it is unable to discover multiple associations among allelic variants, due to its underlying statistic analysis strategy that focuses on a single variant for each time. To overcome those limitations, here we propose a new analysis methodology for DMET data based on Association Rules mining, and an efficient implementation of this methodology, named DMET-Miner. DMET-Miner extends the DMET-Analyzer tool with data mining capabilities and correlates the presence of a set of allelic variants with the conditions of patient's samples by exploiting association rules. To face the high number of frequent itemsets generated when considering large clinical studies based on DMET data, DMET-Miner uses an efficient data structure and implements an optimized search strategy that reduces the search space and the execution time. Preliminary experiments on synthetic DMET datasets, show how DMET-Miner outperforms off-the-shelf data mining suites such as the FP-Growth algorithms available in Weka and RapidMiner. To demonstrate the biological relevance of the extracted association rules and the effectiveness of the proposed approach from a medical point of view, some preliminary studies on a real clinical dataset are currently under medical investigation.

Key factors of susceptibility to anti-tuberculosis drug-induced hepatotoxicity

Anti-tuberculosis drug-induced hepatotoxicity (ATDH) is one of the leading adverse drug reactions during the course of tuberculosis treatment and poses a considerable challenge to clinicians and researchers. Previous studies have revealed the important contribution of drug metabolism and transporter enzymes to the complexity of ATDH. The emerging roles of immune response and oxidative stress resulting from reactive metabolite in the development of ATDH have also gained attention recently. Both non-genetic and genetic factors can have a significant impact on the susceptibility to ATDH, consequently altering the risk of hepatotoxicity in susceptible individuals. Non-genetic risk factors associated with ATDH include host factors, environment factors and drug-related factors. Genetic factors contributing to the susceptibility of ATDH involve genetic variations in bioactivation/toxification pathways via the cytochrome P450 enzymes (phase I), detoxification reactions by N-acetyl transferase 2, glutathione S-transferase and uridine diphosphate glucuronosyltransferase (phase II) and hepatic transport (phase III), together with immunological factors and antioxidant response. Better understanding of these factors may help to predict and prevent the occurrence of ATDH and develop more effective treatments. This review focuses on the mechanisms of ATDH and the key factors of susceptibility associated with drug metabolism, hepatic transport, immune response and oxidative stress.

How drugs get into cells: tested and testable predictions to help discriminate between transporter-mediated uptake and lipoidal bilayer diffusion

One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest. We use this strategy to compare the intellectual status and available evidence for two models or views of mechanisms of transmembrane drug transport into intact biological cells. One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose “natural” biological roles, and substrates are based in intermediary metabolism. Despite a recent review elsewhere, we can find no evidence able to support BDII as we can find no experiments in intact cells in which phospholipid bilayer diffusion was either varied independently or measured directly (although there are many papers where it was inferred by seeing a covariation of other dependent variables). By contrast, we find an abundance of evidence showing cases in which changes in the activities of named and genetically identified transporters led to measurable changes in the rate or extent of drug uptake. PBIN also has considerable predictive power, and accounts readily for the large differences in drug uptake between tissues, cells and species, in accounting for the metabolite-likeness of marketed drugs, in pharmacogenomics, and in providing a straightforward explanation for the late-stage appearance of toxicity and of lack of efficacy during drug discovery programmes despite macroscopically adequate pharmacokinetics. Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.