Effect of UGT, SLCO, ABCB and ABCC polymorphisms on irinotecan toxicity

Microbiota-Host-Irinotecan Axis: A New Insight Toward Irinotecan Chemotherapy

Irinotecan (CPT11) and its active metabolite ethyl-10-hydroxy-camptothecin (SN38) are broad-spectrum cytotoxic anticancer agents. Both cause cell death in rapidly dividing cells (e.g., cancer cells, epithelial cells, hematopoietic cells) and commensal bacteria. Therefore, CPT11 can induce a series of toxic side-effects, of which the most conspicuous is gastrointestinal toxicity (nausea, vomiting, diarrhea). Studies have shown that the gut microbiota modulates the host response to chemotherapeutic drugs. Targeting the gut microbiota influences the efficacy and toxicity of CPT11 chemotherapy through three key mechanisms: microbial ecocline, catalysis of microbial enzymes, and immunoregulation. This review summarizes and explores how the gut microbiota participates in CPT11 metabolism and mediates host immune dynamics to affect the toxicity and efficacy of CPT11 chemotherapy, thus introducing a new concept that is called "microbiota-host-irinotecan axis". Also, we emphasize the utilization of bacterial β-glucuronidase-specific inhibitor, dietary interventions, probiotics and strain-engineered interventions as emergent microbiota-targeting strategies for the purpose of improving CPT11 chemotherapy efficiency and alleviating toxicity.

Evaluation of pharmacogenomics and hepatic nuclear imaging-related covariates by population pharmacokinetic models of irinotecan and its metabolites

BACKGROUND

Body surface area (BSA)-based dosing of irinotecan (IR) does not account for its pharmacokinetic (PK) and pharmacodynamic (PD) variabilities. Functional hepatic nuclear imaging (HNI) and excretory/metabolic/PD pharmacogenomics have shown correlations with IR disposition and toxicity/efficacy. This study reports the development of a nonlinear mixed-effect population model to identify pharmacogenomic and HNI-related covariates that impact on IR disposition to support dosage optimization.

METHODS

Patients had advanced colorectal cancer treated with IR combination therapy. Baseline blood was analysed by Affymetrix DMET™ Plus Array and, for PD, single nucleotide polymorphisms (SNPs) by Sanger sequencing. For HNI, patients underwent ^99mTc-IDA hepatic imaging, and data was analysed for hepatic extraction/excretion parameters. Blood was taken for IR and metabolite (SN38, SN38G) analysis on day 1 cycle 1. Population modelling utilised NONMEM version 7.2.0, with structural PK models developed for each moiety. Covariates include patient demographics, HNI parameters and pharmacogenomic variants.

RESULTS

Analysis included (i) PK data: 32 patients; (ii) pharmacogenomic data: 31 patients: 750 DMET and 22 PD variants; and (iii) HNI data: 32 patients. On initial analysis, overall five SNPs were identified as significant covariates for CL_SN38. Only UGT1A3_c.31 T > C and ABCB1_c.3435C > T were included in the final model, whereby CL_SN38 reduced from 76.8 to 55.1%.

CONCLUSION

The identified UGT1A3_c.31 T > C and ABCB1_c.3435C > T variants, from wild type to homozygous, were included in the final model for SN38 clearance.

A Systematic Review of Phytochemistry, Pharmacology and Pharmacokinetics on Astragali Radix: Implications for Astragali Radix as a Personalized Medicine

Astragali radix (AR) is one of the most widely used traditional Chinese herbal medicines. Modern pharmacological studies and clinical practices indicate that AR possesses various biological functions, including potent immunomodulation, antioxidant, anti-inflammation and antitumor activities. To date, more than 200 chemical constituents have been isolated and identified from AR. Among them, isoflavonoids, saponins and polysaccharides are the three main types of beneficial compounds responsible for its pharmacological activities and therapeutic efficacy. After ingestion of AR, the metabolism and biotransformation of the bioactive compounds were extensive in vivo. The isoflavonoids and saponins and their metabolites are the major type of constituents absorbed in plasma. The bioavailability barrier (BB), which is mainly composed of efflux transporters and conjugating enzymes, is expected to have a significant impact on the bioavailability of AR. This review summarizes studies on the phytochemistry, pharmacology and pharmacokinetics on AR. Additionally, the use of AR as a personalized medicine based on the BB is also discussed, which may provide beneficial information to achieve a better and more accurate therapeutic response of AR in clinical practice.

Clinical utility of ABCB1 genotyping for preventing toxicity in treatment with irinotecan

Preventing severe irinotecan-induced adverse reactions would allow us to offer better treatment and improve patients' quality of life. Transporters, metabolizing enzymes, and genes involved in the folate pathway have been associated with irinotecan-induced toxicity. We analyzed 12 polymorphisms in UGT1A1, ABCB1, ABCG2, ABCC4, ABCC5, and MTHFR in 158 patients with metastatic colorectal cancer treated with irinotecan and studied the association with grade >2 adverse reactions (CTCAE). Among the most frequent ADRs, the SNPs rs1128503, rs2032582, and rs1045642 in ABCB1 and rs1801133 in MTHFR were associated with hematological toxicity and overall toxicity. The SNP rs11568678 in ABCC4 was also associated with overall toxicity. After correction of P values using a false discovery rate, only ABCB1 variants remained statistically significant. Haplotype analysis in ABCB1 showed an 11.3-fold and 4.6-fold increased risk of hematological toxicity (95% CI, 1.459-88.622) and overall toxicity (95% CI, 2.283-9.386), respectively. Consequently, genotyping of the three SNPs in ABCB1 can predict overall toxicity and hematological toxicity with a diagnostic odds ratio of 4.40 and 9.94, respectively. Genotyping of ABCB1 variants can help to prevent severe adverse reactions to irinotecan-based treatments in colorectal cancer.