Defining Clinical Utility of Germline Indicators of Toxicity Risk: A Perspective

Potential association of SULT2A1 and ABCG2 variant alleles with increased risk for palbociclib toxicity

Aim: This study evaluated associations between CYP3A4*22 and variants in other pharmacogenes (CYP3A5, SULT2A1, ABCB1, ABCG2, ERCC1) and the risk for palbociclib-associated toxicities.Materials & methods: Two hundred cancer patients who received standard-of-care palbociclib were genotyped and associations with toxicity were evaluated retrospectively.Results: No significant associations were found for CYP3A4*22, CYP3A5*3, ABCB1_rs1045642, ABCG2_rs2231142, ERCC1_rs3212986 and ERCC1_rs11615. Homozygous variant carriers of SULT2A1_rs182420 had higher incidence of dose modifications due to palbociclib toxicity (odds ratio [OR]: 4.334, 95% CI: 1.057-17.767, p = 0.042). ABCG2_rs2231137 variant carriers had borderline higher incidence of grade 3-4 neutropenia (OR: 4.14, 95% CI: 0.99-17.37, p = 0.052).Conclusion: Once validated, SULT2A1 and ABCG2 variants may be useful to individualize palbociclib dosing to minimize toxicities and improve treatment outcomes.

Attempted replication of pharmacogenetic association of variants in PPP1R14C and CCDC148 with aromatase inhibitor-induced musculoskeletal symptoms

Third-generation aromatase inhibitors (AI) are the standard treatment for patients with hormone receptor positive (HR+) breast cancer. While effective, AI can lead to severe adverse events, including AI-induced musculoskeletal syndrome (AIMSS). Genetic predictors of AIMSS have the potential to personalize AI treatment and improve outcomes. We attempted to replicate results from a previous genome-wide association study that found a lower risk of AIMSS in patients carrying PPP1R14C rs912571 and a higher risk in patients carrying CCDC148 rs79048288. AIMSS data were collected prospectively from patients with HR+ breast cancer prior to starting and after 3 and 6 months of adjuvant AI via the Patient-Reported Outcome Measurement Information System and Functional Assessment of Cancer Therapy-Endocrine Symptom. Germline genotypes for PPP1R14C rs912571 and CCDC148 rs79048288 were tested for a similar association with AIMSS as previously reported via $2 tests. Of the 143 patients with AIMSS and genetics data were included in the analysis. There was no association identified between PPP1R14C rs912571 and AIMSS risk ( P  > 0.05). Patients carrying CCDC148 rs79048288 variant alleles had lower AIMSS incidence in a secondary analysis ( P  = 0.04); however, this was in the opposite direction of the previous finding. The study did not replicate previously reported associations with AIMSS risk for genetic variants in PPP1R14C and CCDC148 and AIMSS risk. Further research is needed to discover and validate genetic predictors of AIMSS that can be used to personalize treatment in patients with HR+ breast cancer.

Cost-utility analysis and cross-country comparison of pharmacogenomics-guided treatment in colorectal cancer patients participating in the U-PGx PREPARE study

OBJECTIVES

A cost-utility analysis was conducted to evaluate pharmacogenomic (PGx)-guided treatment compared to the standard-of-care intervention among patients diagnosed with colorectal cancer (CRC) in Italy.

METHODS

Data derived from a prospective, open-label, block randomized clinical trial, as a part of the largest PGx study worldwide (355 patients in both arms) were used. Mortality was used as the primary health outcome to estimate life years (LYs) gained in treatment arms within a survival analysis context. PGx-guided treatment was based on established drug-gene interactions between capecitabine, 5-fluorouracil and irinotecan with DPYD and/or UGT1A1 genomic variants. Utility values for the calculation of Quality Adjusted Life Year (QALY) was based on Visual Analog Scale (VAS) score. Missing data were imputed via the Multiple Imputation method and linear interpolation, when possible, while censored cost data were corrected via the Replace-From-The-Right algorithm. The Incremental Cost-Effectiveness Ratio (ICER) was calculated for QALYs. Raw data were bootstrapped 5000 times in order to produce 95% Confidence Intervals based on non-parametric percentile method and to construct a cost-effectiveness acceptability curve. Cost differences for study groups were investigated via a generalized linear regression model analysis. Total therapy cost per patient reflected all resources expended in the management of any adverse events, including medications, diagnostics tests, devices, surgeries, the utilization of intensive care units, and wards.

RESULTS

The total cost of the study arm was estimated at €380 (∼ US$416; 95%CI: 195-596) compared to €565 (∼ US$655; 95%CI: 340-724) of control arm while the mean survival in study arm was estimated at 1.58 (+0.25) LYs vs 1.50 (+0.26) (Log Rank test, X2 = 4.219, df=1, p-value=0.04). No statistically significant difference was found in QALYs. ICER was estimated at €13418 (∼ US$14695) per QALY, while the acceptability curve indicated that when the willingness-to-pay was under €5000 (∼ US$5476), the probability of PGx being cost-effective overcame 70%. The most frequent adverse drug event in both groups was neutropenia of severity grade 3 and 4, accounting for 82.6% of total events in the study arm and 65.0% in the control arm. Apart from study arm, smoking status, Body-Mass-Index and Cumulative Actionability were also significant predictors of total cost. Subgroup analysis conducted in actionable patients (7.9% of total patients) indicated that PGx-guided treatment was a dominant option over its comparator with a probability greater than 92%. In addition, a critical literature review was conducted, and these findings are in line with those reported in other European countries.

CONCLUSION

PGx-guided treatment strategy may represent a cost-saving option compared to the existing conventional therapeutic approach for colorectal cancer patient management in the National Health Service of Italy.

Checkpoint inhibitors and anti-angiogenic agents: a winning combination

The combination of immune checkpoint inhibitors and anti-angiogenic agents is a promising new approach in cancer treatment. Immune checkpoint inhibitors block the signals that help cancer cells evade the immune system, while anti-angiogenic agents target the blood vessels that supply the tumour with nutrients and oxygen, limiting its growth. Importantly, this combination triggers synergistic effects based on molecular and cellular mechanisms, leading to better response rates and longer progression-free survival than treatment alone. However, these combinations can also lead to increased side effects and require close monitoring.

Integrating pharmacogenomic testing into paired germline and somatic genomic testing in patients with cancer

Precision medicine has revolutionized clinical care for patients with cancer through the development of targeted therapy, identification of inherited cancer predisposition syndromes and the use of pharmacogenetics to optimize pharmacotherapy for anticancer drugs and supportive care medications. While germline (patient) and somatic (tumor) genomic testing have evolved separately, recent interest in paired germline/somatic testing has led to an increase in integrated genomic testing workflows. However, paired germline/somatic testing has generally lacked the incorporation of germline pharmacogenomics. Integrating pharmacogenomics into paired germline/somatic genomic testing would be an efficient method for increasing access to pharmacogenomic testing. In this perspective, the authors argue for the benefits of implementing a comprehensive approach integrating somatic and germline testing that is inclusive of pharmacogenomics in clinical practice.

Abigene, a Prospective, Multicentric Study of Abiraterone Acetate Pharmacogenetics in Metastatic Castration-Resistant Prostate Cancer

Abiraterone acetate (AA) is the first-in-class of drugs belonging to the second-generation of agents inhibiting androgen neosynthesis in advanced prostate cancer. A cumulative experience attests that germinal gene polymorphisms may play a role in the prediction of anticancer agent pharmacodynamics variability. In the present prospective, multicentric study, gene polymorphisms of CYP17A1 (AA direct target) and the androgen transporter genes SLCO2B1 and SLCO1B3 (potential modulators of AA activity) were confronted with AA pharmacodynamics (treatment response and toxicity) in a group of 137 advanced prostate cancer patients treated in the first line by AA. The median follow-up was 56.3 months (95% CI [52.5-61]). From multivariate analysis, rs2486758 C/C (CYP17A1) and PSA (≥10 ng/mL) were associated with a shorter 3-year biological PFS (HR = 4.05, IC95% [1.46-11.22]; p = 0.007 and HR = 2.08, IC95% [1.31-3.30]; p = 0.002, respectively). From a multivariate analysis, the rs743572 (CYP17A1) and performance status were independently associated with significant toxicity (OR = 3.78 (IC95% [1.42-9.75]; p = 0.006 and OR = 4.54; IC95% [1.46-13.61]; p = 0.007, respectively). Host genome characteristics may help to predict AA treatment efficacy and identify patients at risk for toxicity.

Assessment of the Clinical Utility of Pretreatment DPYD Testing for Patients Receiving Fluoropyrimidine Chemotherapy

PURPOSE

Patients who carry pathogenic variants in DPYD have higher systemic fluoropyrimidine (FP) concentrations and greater risk of severe and fatal FP toxicity. Pretreatment DPYD testing and DPYD-guided FP dosing to reduce toxicity and health care costs is recommended by European clinical oncology guidelines and has been adopted across Europe, but has not been recommended or adopted in the United States. The cochairs of the National Comprehensive Cancer Network Guidelines for colon cancer treatment explained their concerns with recommending pretreatment DPYD testing, particularly the risk that reduced FP doses in DPYD carriers may reduce treatment efficacy.

METHODS

This special article uses previously published frameworks for assessing the clinical utility of cancer biomarker tests, including for germline indicators of toxicity risk, to assess the clinical utility of pretreatment DPYD testing, with a particular focus on the risk of reducing treatment efficacy.

RESULTS

There is no direct evidence of efficacy reduction, and the available indirect evidence demonstrates that DPYD-guided FP dosing results in similar systemic FP exposure and toxicity compared with standard dosing in noncarriers, and is well calibrated to the maximum tolerated dose, strongly suggesting there is minimal risk of efficacy reduction.

CONCLUSION

This article should serve as a call to action for clinicians and clinical guidelines committees in the United States to re-evaluate the clinical utility of pretreatment DPYD testing. If clinical utility has not been demonstrated, further dialogue is needed to clarify what additional evidence is needed and which of the available study designs, also described within this article, would be appropriate. Clinical guideline recommendations for pretreatment DPYD testing would increase clinical adoption and ensure that all patients receive maximally safe and effective FP treatment.

Using real world data to advance the provision of supportive cancer care: mucositis as a case study

PURPOSE OF REVIEW

For decades, clinical decision making and practice has been largely informed by data generated through randomized clinical trials (RCTs). By design, RCTs are highly restricted in both scope and scale, resulting in narrow indications and iterative advances in clinical practice. With the transition to electronic health records, there are now endless opportunities to utilize these 'real world' data (RWD) to make more substantive advances in our understanding that are, by nature, more applicable to reality. This review discusses the current paradigm of using big data to advance and inform the provision of supportive cancer care, using mucositis as a case study.

RECENT FINDINGS

Global efforts to synthesize RWD in cancer have almost exclusively focused on tumor classification and treatment efficacy, leveraging on routine tumor pathology and binary response outcomes. In contrast, clinical notes and billing codes are not as applicable to treatment side effects which require integration of both clinical and biological data, as well as patient-reported outcomes.

SUMMARY

Cancer treatment-induced toxicities are heterogeneous and complex, and as such, the use of RWD to better understand their etiology and interaction is challenging. Multidisciplinary cooperation and leadership are needed to improve data collection and governance to ensure the right data is accessible and reliable.