A decade of pharmacogenomics research on tyrosine kinase inhibitors in metastatic renal cell cancer: a systematic review

Dose Optimization in Oncology Drug Development: The Emerging Role of Pharmacogenomics, Pharmacokinetics, and Pharmacodynamics

Drugs' safety and effectiveness are evaluated in randomized, dose-ranging trials in most therapeutic areas. However, this is only sometimes feasible in oncology, and dose-ranging studies are mainly limited to Phase 1 clinical trials. Moreover, although new treatment modalities (e.g., small molecule targeted therapies, biologics, and antibody-drug conjugates) present different characteristics compared to cytotoxic agents (e.g., target saturation limits, wider therapeutic index, fewer off-target side effects), in most cases, the design of Phase 1 studies and the dose selection is still based on the Maximum Tolerated Dose (MTD) approach used for the development of cytotoxic agents. Therefore, the dose was not optimized in some cases and was modified post-marketing (e.g., ceritinib, dasatinib, niraparib, ponatinib, cabazitaxel, and gemtuzumab-ozogamicin). The FDA recognized the drawbacks of this approach and, in 2021, launched Project Optimus, which provides the framework and guidance for dose optimization during the clinical development stages of anticancer agents. Since dose optimization is crucial in clinical development, especially of targeted therapies, it is necessary to identify the role of pharmacological tools such as pharmacogenomics, therapeutic drug monitoring, and pharmacodynamics, which could be integrated into all phases of drug development and support dose optimization, as well as the chances of positive clinical outcomes.

Optimization of blood pressure measurement practices for pharmacodynamic analyses of tyrosine-kinase inhibitors

Blood pressure measurements form a critical component of adverse event monitoring for tyrosine kinase inhibitors, but might also serve as a biomarker for dose titrations. This study explored the impact of various sources of within-individual variation on blood pressure readings to improve measurement practices and evaluated the utility for individual- and population-level dose selection. A pharmacokinetic-pharmacodynamic modeling framework was created to describe circadian blood pressure changes, inter- and intra-day variability, changes from dipper to non-dipper profiles, and the relationship between drug exposure and blood pressure changes over time. The framework was used to quantitatively evaluate the influence of physiological and pharmacological aspects on blood pressure measurements, as well as to compare measurement techniques, including office-based, home-based, and ambulatory 24-h blood pressure readings. Circadian changes, as well as random intra-day and inter-day variability, were found to be the largest sources of within-individual variation in blood pressure. Office-based and ambulatory 24-h measurements gave rise to potential bias (>5 mmHg), which was mitigated by model-based estimations. Our findings suggest that 5-8 consecutive, home-based, measurements taken at a consistent time around noon, or alternatively within a limited time frame (e.g., 8.00 a.m. to 12.00 p.m. or 12.00 p.m. to 5.00 p.m.), will give rise to the most consistent blood pressure estimates. Blood pressure measurements likely do not represent a sufficiently accurate method for individual-level dose selection, but may be valuable for population-level dose identification. A user-friendly tool has been made available to allow for interactive blood pressure simulations and estimations for the investigated scenarios.

Genome-Wide Meta-Analysis Identifies Variants in DSCAM and PDLIM3 That Correlate with Efficacy Outcomes in Metastatic Renal Cell Carcinoma Patients Treated with Sunitinib

Individual response to sunitinib in metastatic renal cell carcinoma (mRCC) patients is highly variable. Earlier, sunitinib outcome was related to single nucleotide polymorphisms (SNPs) in CYP3A5 and ABCB1. Our aim is to provide novel insights into biological mechanisms underlying sunitinib action. We included mRCC patients from the European EuroTARGET consortium (n = 550) and the RIKEN cohort in Japan (n = 204) which were analysed separately and in a meta-analysis of genome-wide association studies (GWAS). SNPs were tested for association with progression-free survival (PFS) and overall survival (OS) using Cox regression. Summary statistics were combined using a fixed effect meta-analysis. SNP rs28520013 in PDLIM3 and the correlated SNPs rs2205096 and rs111356738 both in DSCAM, showed genome-wide significance (p < 5 × 10−8) with PFS and OS in the meta-analysis. The variant T-allele of rs28520013 associated with an inferior PFS of 5.1 months compared to 12.5 months in non-carriers (p = 4.02 × 10−10, HR = 7.26). T-allele carriers of rs28520013 showed an inferior OS of 6.9 months versus 30.2 months in non-carriers (p = 1.62 × 10−8, HR = 5.96). In this GWAS we identified novel genetic variants in PDLIM3 and DSCAM that impact PFS and OS in mRCC patients receiving sunitinib. The underlying link between the identified genes and the molecular mechanisms of sunitinib action needs to be elucidated.

Interindividual Variability in Cytochrome P450 3A and 1A Activity Influences Sunitinib Metabolism and Bioactivation

Sunitinib is an orally administered tyrosine kinase inhibitor associated with idiosyncratic hepatotoxicity; however, the mechanisms of this toxicity remain unclear. We have previously shown that cytochromes P450 1A2 and 3A4 catalyze sunitinib metabolic activation via oxidative defluorination leading to a chemically reactive, potentially toxic quinoneimine, trapped as a glutathione (GSH) conjugate (M5). The goals of this study were to determine the impact of interindividual variability in P450 1A and 3A activity on sunitinib bioactivation to the reactive quinoneimine and sunitinib N-dealkylation to the primary active metabolite N-desethylsunitinib (M1). Experiments were conducted in vitro using single-donor human liver microsomes and human hepatocytes. Relative sunitinib metabolite levels were measured by liquid chromatography-tandem mass spectrometry. In human liver microsomes, the P450 3A inhibitor ketoconazole significantly reduced M1 formation compared to the control. The P450 1A2 inhibitor furafylline significantly reduced defluorosunitinib (M3) and M5 formation compared to the control but had minimal effect on M1. In CYP3A5-genotyped human liver microsomes from 12 individual donors, M1 formation was highly correlated with P450 3A activity measured by midazolam 1'-hydroxylation, and M3 and M5 formation was correlated with P450 1A2 activity estimated by phenacetin O-deethylation. M3 and M5 formation was also associated with P450 3A5-selective activity. In sandwich-cultured human hepatocytes, the P450 3A inducer rifampicin significantly increased M1 levels. P450 1A induction by omeprazole markedly increased M3 formation and the generation of a quinoneimine-cysteine conjugate (M6) identified as a downstream metabolite of M5. The nonselective P450 inhibitor 1-aminobenzotriazole reduced each of these metabolites (M1, M3, and M6). Collectively, these findings indicate that P450 3A activity is a key determinant of sunitinib N-dealkylation to the active metabolite M1, and P450 1A (and potentially 3A5) activity influences sunitinib bioactivation to the reactive quinoneimine metabolite. Accordingly, modulation of P450 activity due to genetic and/or nongenetic factors may impact the risk of sunitinib-associated toxicities.

[Biomarkers for renal cell tumours]

During the last three decades, renal tumours have become increasingly well differentiated on the basis of their histopathological and molecular features. This subtyping has increasingly impacted clinical practice because more therapeutic options are available in organ-confined and metastatic renal cell tumours. The knowledge of the underlying molecular alterations is essential to develop molecular targeted therapies and to select the most effective systemic therapy for each patient. This manuscript gives an overview of the molecular differentiation on the one hand, and on diagnostic, prognostic and predictive biomarkers on the other hand.

Determinants of resistance to VEGF-TKI and immune checkpoint inhibitors in metastatic renal cell carcinoma

Vascular endothelial growth factor tyrosine kinase inhibitors (VEGF-TKIs) have been the mainstay of treatment for patients with advanced renal cell carcinoma (RCC). Despite its early promising results in decreasing or delaying the progression of RCC in patients, VEGF-TKIs have provided modest benefits in terms of disease-free progression, as 70% of the patients who initially respond to the treatment later develop drug resistance, with 30% of the patients innately resistant to VEGF-TKIs. In the past decade, several molecular and genetic mechanisms of VEGF-TKI resistance have been reported. One of the mechanisms of VEGF-TKIs is inhibition of the classical angiogenesis pathway. However, recent studies have shown the restoration of an alternative angiogenesis pathway in modulating resistance. Further, in the last 5 years, immune checkpoint inhibitors (ICIs) have revolutionized RCC treatment. Although some patients exhibit potent responses, a non-negligible number of patients are innately resistant or develop resistance within a few months to ICI therapy. Hence, an understanding of the mechanisms of VEGF-TKI and ICI resistance will help in formulating useful knowledge about developing effective treatment strategies for patients with advanced RCC. In this article, we review recent findings on the emerging understanding of RCC pathology, VEGF-TKI and ICI resistance mechanisms, and potential avenues to overcome these resistance mechanisms through rationally designed combination therapies.

Meta-Analysis of ABCG2 and ABCB1 Polymorphisms With Sunitinib-Induced Toxicity and Efficacy in Renal Cell Carcinoma

Background: ABCG2 and ABCB1 are genes related to the pharmacokinetics of sunitinib and have been associated with its toxicity and efficacy. However, the results have been controversial. This study aimed to evaluate the associations of ABCG2 and ABCB1 polymorphisms with sunitinib-induced toxicity and efficacy in renal cell carcinoma (RCC) by meta-analysis. Methods: PubMed, EMBASE, Cochrane Library, and Web of Science were systematically searched for studies investigating the associations of the ABCG2 rs2231142 polymorphism with sunitinib-induced toxicity and the associations of the ABCB1 rs1128503 and ABCB1 rs2032582 polymorphisms with sunitinib-induced toxicity and clinical outcomes. The associations were evaluated by effect size (ES) with 95% confidence intervals (CIs). Results: Eight and five studies were included in the toxicity and efficacy analysis, respectively, including a total of 1081 RCC patients. The ABCG2 rs2231142 A allele was associated with an increased risk of sunitinib-induced thrombocytopenia and hand-foot syndrome (HFS) in Asians (ES = 1.65, 95% CI = 1.15-2.36, p = 0.006; ES = 1.52, 95% CI = 1.02-2.27, p = 0.041). However, the ABCG2 rs2231142 polymorphism was not associated with sunitinib-induced hypertension or neutropenia (ES = 1.09, 95% CI = 0.69-1.73, p = 0.701; ES = 0.87, 95% CI = 0.57-1.31, p = 0.501). Compared with the C allele, the ABCB1 rs1128503 T allele was associated with a decreased risk of sunitinib-induced hypertension but worse progression-free survival (PFS) (ES = 0.44, 95% CI = 0.26-0.77, p = 0.004; ES = 1.36, 95% CI = 1.07-1.73, p = 0.011). There was no significant association between the T allele or C allele of ABCB1 rs1128503 and overall survival (OS) (ES = 0.82, 95% CI = 0.61-1.10, p = 0.184). The ABCB1 rs2032582 T allele was associated with worse PFS than the other alleles (ES = 1.46, 95% CI = 1.14-1.87, p = 0.003), while there was no significant association between the T allele or other alleles and sunitinib-induced hypertension, HFS, or OS (ES = 0.77, 95% CI = 0.46-1.29, p = 0.326; ES = 1.02, 95% CI = 0.65-1.62, p = 0.919; ES = 1.32, 95% CI = 0.85-2.05, p = 0.215). Conclusion: The results indicate that the ABCG2 rs2231142 polymorphism may serve as a predictor of sunitinib-induced thrombocytopenia and HFS in Asians, while the ABCB1 rs1128503 polymorphism may serve as a predictor of sunitinib-induced hypertension, and both the ABCB1 rs1128503 and rs2032582 polymorphisms may serve as predictors of PFS in RCC. These results suggest a possible application of individualized use of sunitinib according to the genetic background of patients.

Severe hyperglycaemia following pazopanib treatment: The role of drug-drug-gene interactions in a patient with metastatic renal cell carcinoma-A case report

WHAT IS KNOWN AND OBJECTIVE

Pazopanib is a tyrosine kinase inhibitor with hyperglycaemia as a known adverse event, but case reports of severe hyperglycaemia are exceptional. We report a case of severe hyperglycaemia following pazopanib administration in a patient with metastatic renal cell carcinoma.

CASE SUMMARY

Severe hyperglycaemia developed in a patient one month following initiation of pazopanib therapy. As drug-drug-gene interactions may lead to hyperglycaemia, pharmacogenetic assessment was requested. The obtained findings indicated intermediate function of both OATP1B1 and P-glycoprotein transporters, which may cause prolonged pazopanib bioavailability and increased toxicity. Pazopanib was discontinued and, following patient recovery, was reintroduced at a lower dose.

WHAT IS NEW AND CONCLUSION

The pharmacogenetic profiling of the patient on polypharmacy enabled better management of pazopanib therapy.

Pharmacogenomic analyses of sunitinib in patients with pancreatic neuroendocrine tumors

Aim: Evaluate associations between clinical outcomes and SNPs in patients with well-differentiated pancreatic neuroendocrine tumors receiving sunitinib. Patients & methods: Kaplan–Meier and Cox proportional hazards models were used to analyze the association between SNPs and survival outcomes using data from a sunitinib Phase IV (genotyped, n = 56) study. Fisher’s exact test was used to analyze objective response rate and genotype associations. Results: After multiplicity adjustment, progression-free and overall survivals were not significantly correlated with SNPs; however, a higher objective response rate was significantly associated with IL1B rs16944 G/A versus G/G (46.4 vs 4.5%; p = 0.001). Conclusion: IL1B SNPs may predict treatment response in patients with pancreatic neuroendocrine tumors. VEGF pathway SNPs are potentially associated with survival outcomes.

Phase III Trial of Adjuvant Sunitinib in Patients with High-Risk Renal Cell Carcinoma: Exploratory Pharmacogenomic Analysis

PURPOSE

In the S-TRAC trial, adjuvant sunitinib prolonged disease-free survival (DFS) versus placebo in patients with loco-regional renal cell carcinoma at high risk of recurrence after nephrectomy. An exploratory analysis evaluated associations between SNPs in several angiogenesis- or hypoxia-related genes and clinical outcomes in S-TRAC.

PATIENTS AND METHODS

Blood samples were genotyped for 10 SNPs and one insertion/deletion mutation using TaqMan assays. DFS was compared using log-rank tests for each genotype in sunitinib versus placebo groups and between genotypes within each of three (sunitinib, placebo, and combined sunitinib plus placebo) treatment groups. P values were unadjusted.

RESULTS

In all, 286 patients (sunitinib, n = 142; placebo, n = 144) were genotyped. Longer DFS [HR; 95% confidence interval (CI)] was observed with sunitinib versus placebo for VEGFR1 rs9554320 C/C (HR 0.44; 95% CI, 0.21-0.91; P = 0.023), VEGFR2 rs2071559 T/T (HR 0.46; 95% CI, 0.23-0.90; P = 0.020), and eNOS rs2070744 T/T (HR 0.53; 95% CI, 0.30-0.94; P = 0.028). Shorter DFS was observed for VEGFR1 rs9582036 C/A versus C/C with sunitinib, placebo, and combined therapies (P ≤ 0.05), and A/A versus C/C with sunitinib (P = 0.022). VEGFR1 rs9554320 A/C versus A/A was associated with shorter DFS in the placebo (P = 0.038) and combined (P = 0.006) groups.

CONCLUSIONS

Correlations between VEGFR1 and VEGFR2 SNPs and longer DFS with sunitinib suggest germline SNPs are predictive of improved outcomes with adjuvant sunitinib in patients with renal cell carcinoma. Independent validation studies are needed to confirm these findings.

Cytochromes P450 1A2 and 3A4 Catalyze the Metabolic Activation of Sunitinib

Sunitinib is a multitargeted tyrosine kinase inhibitor associated with idiosyncratic hepatotoxicity. The mechanisms of this toxicity are unknown. We hypothesized that sunitinib undergoes metabolic activation to form chemically reactive, potentially toxic metabolites which may contribute to development of sunitinib-induced hepatotoxicity. The purpose of this study was to define the role of cytochrome P450 (P450) enzymes in sunitinib bioactivation. Metabolic incubations were performed using individual recombinant P450s, human liver microsomal fractions, and P450-selective chemical inhibitors. Glutathione (GSH) and dansylated GSH were used as trapping agents to detect reactive metabolite formation. Sunitinib metabolites were analyzed by liquid chromatography-tandem mass spectrometry. A putative quinoneimine-GSH conjugate (M5) of sunitinib was detected from trapping studies with GSH and dansyl-GSH in human liver microsomal incubations, and M5 was formed in an NADPH-dependent manner. Recombinant P450 1A2 generated the highest levels of defluorinated sunitinib (M3) and M5, with less formation by P450 3A4 and 2D6. P450 3A4 was the major enzyme forming the primary active metabolite N-desethylsunitinib (M1). In human liver microsomal incubations, P450 3A inhibitor ketoconazole reduced formation of M1 by 88%, while P450 1A2 inhibitor furafylline decreased generation of M5 by 62% compared to control levels. P450 2D6 and P450 3A inhibition also decreased M5 by 54 and 52%, respectively, compared to control. In kinetic assays, recombinant P450 1A2 showed greater efficiency for generation of M3 and M5 compared to that of P450 3A4 and 2D6. Moreover, M5 formation was 2.7-fold more efficient in human liver microsomal preparations from an individual donor with high P450 1A2 activity compared to a donor with low P450 1A2 activity. Collectively, these data suggest that P450 1A2 and 3A4 contribute to oxidative defluorination of sunitinib to generate a reactive, potentially toxic quinoneimine. Factors that alter P450 1A2 and 3A activity may affect patient risk for sunitinib toxicity.

The glucose and lipid metabolism reprogramming is grade-dependent in clear cell renal cell carcinoma primary cultures and is targetable to modulate cell viability and proliferation

Clear cell renal cell carcinoma (ccRCC) has a poor prognosis despite novel biological targeted therapies. Tumor aggressiveness and poor survival may correlate with tumor grade at diagnosis and with complex metabolic alterations, also involving glucose and lipid metabolism. However, currently no grade-specific metabolic therapy addresses these alterations. Here we used primary cell cultures from ccRCC of low- and high-grade to investigate the effect on energy state and reduced pyridine nucleotide level, and on viability and proliferation, of specific inhibition of glycolysis with 2-deoxy-D-glucose (2DG), or fatty acid oxidation with Etomoxir. Our primary cultures retained the tissue grade-dependent modulation of lipid and glycogen storage and aerobic glycolysis (Warburg effect). 2DG affected lactate production, energy state and reduced pyridine nucleotide level in high-grade ccRCC cultures, but the energy state only in low-grade. Rather, Etomoxir affected energy state in high-grade and reduced pyridine nucleotide level in low-grade cultures. Energy state and reduced pyridine nucleotide level were evaluated by ATP and reduced 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium (MTT) dye quantification, respectively. 2DG treatment impaired cell proliferation and viability of low-grade ccRCC and normal cortex cultures, whereas Etomoxir showed a cytostatic and cytotoxic effect only in high-grade ccRCC cultures. Our data indicate that in ccRCC the Warburg effect is a grade-dependent feature, and fatty acid oxidation can be activated for different grade-dependent metabolic needs. A possible grade-dependent metabolic therapeutic approach in ccRCC is also highlighted.

Bevacizumab-induced hypertension: Clinical presentation and molecular understanding

Bevacizumab is a vascular endothelial growth factor-A-specific angiogenesis inhibitor indicated as an adjunct to chemotherapy for the treatment of several types of cancer. Hypertension is commonly observed during bevacizumab treatment, and high-grade toxicity can limit therapy and lead to other cardiovascular complications. The factors that contribute to interindividual variability in blood pressure response to bevacizumab treatment are not well understood. In this review, we outline research efforts to understand the mechanisms and pathophysiology of hypertension resulting from bevacizumab treatment. Moreover, we highlight current knowledge of the pharmacogenetics of bevacizumab-induced hypertension, which may be used to develop strategies to prevent or minimize this toxicity.

Renal cell carcinoma: a critical analysis of metabolomic biomarkers emerging from current model systems

Metabolomics, an emerging field of "omics" sciences, has caught wide scientific attention in the area of biomarker research for cancers in which early diagnostic biomarkers have the potential to greatly improve patient outcome, such as renal cell carcinoma (RCC). Metabolomic approaches have been successfully applied to various human RCC model systems, mostly ex vivo neoplastic renal tissues and biofluids (urine and serum) from patients with RCC. Importantly, in contrast to other cancers, only a few studies have addressed the RCC metabolome using cancer cell culture-based in vitro models. Herein, we first carried out a comprehensive review of current metabolomic data in RCC, with emphasis on metabolite disturbances and dysregulated metabolic pathways identified in each of these experimental models. We then critically analyzed the consistency of evidence in this field and whether metabolites found altered in tumor cell and tissue microenvironment are reflected in biofluids, which constitute the rationale underlying the translation of discovered metabolic biomarkers into noninvasive diagnostic tools. Finally, dominant metabolic pathways and promising metabolites as biomarkers for diagnosis and prognosis of RCC are outlined.

Advances in Lipidomics for Cancer Biomarkers Discovery

Lipids play critical functions in cellular survival, proliferation, interaction and death, since they are involved in chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions. These cellular processes are strongly related to carcinogenesis pathways, particularly to transformation, progression, and metastasis, suggesting the bioactive lipids are mediators of a number of oncogenic processes. The current review gives a synopsis of a lipidomic approach in tumor characterization; we provide an overview on potential lipid biomarkers in the oncology field and on the principal lipidomic methodologies applied. The novel lipidomic biomarkers are reviewed in an effort to underline their role in diagnosis, in prognostic characterization and in prediction of therapeutic outcomes. A lipidomic investigation through mass spectrometry highlights new insights on molecular mechanisms underlying cancer disease. This new understanding will promote clinical applications in drug discovery and personalized therapy.