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Predictive pharmacogenetic biomarkers for breast cancer recurrence prevention by simvastatin.

ABSTRACT: Background: Statins treat hyperlipidemia and prevent cardiovascular morbidity and mortality. Evidence suggests that they also have anti-neoplastic activity. Several studies show a reduced rate of breast cancer recurrence among lipophilic statin users (e.g., simvastatin), motivating calls for clinical trials of statins in breast cancer patients. We measured the impact of genetic variation in statin-metabolizing enzymes and drug transporters on the recurrence rate in simvastatin-treated breast cancer patients.Methods: We conducted a nested case-control study among Danish women diagnosed with non-metastatic, invasive breast cancer between 2004-2010 who had filled ?1 prescription for simvastatin after diagnosis. Cases were all breast cancer recurrences from the source population; one control was matched to each case on cancer stage, estrogen receptor and hormone therapy status, calendar period of diagnosis, and duration of simvastatin exposure. We genotyped variants in simvastatin-metabolizing enzymes (CYP3A4/rs35599367 and CYP3A5/rs776746) and drug transporters (ABCB1/rs2032582 and SLCO1B1/rs4149056), and estimated their association with recurrence with logistic regression models.Results: We observed protective (though imprecisely-measured) associations between variants in genes encoding drug transporters (ABCB1 and SLCO1B1) and simvastatin-metabolizing enzymes (CYP3A4 and CYP3A5) and breast cancer recurrence in simvastatin-treated women. For example, carrying two variant alleles in ABCB1 was associated with a 31% lower rate of recurrence (multivariable OR = 0.69, 95% CI: 0.31, 1.5).Conclusion: Our study provides weak evidence to support the use of genetic variation in ABCB1, SLCO1B1, CYP3A4, and CYP3A5 as biomarkers of breast tumor response to simvastatin. Validation of these findings within adjuvant clinical trials is encouraged.

SUBMITTER: Ahern TP

PROVIDER: S-EPMC7483991 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Predictive pharmacogenetic biomarkers for breast cancer recurrence prevention by simvastatin.

Ahern Thomas P TP Damkier Per P Feddersen Søren S Kjærsgaard Anders A Lash Timothy L TL Hamilton-Dutoit Stephen S Lythjohan Cathrine Bredal CB Ejlertsen Bent B Christiansen Peer M PM Cronin-Fenton Deirdre P DP

Acta oncologica (Stockholm, Sweden) 20200430 9

<b>Background:</b> Statins treat hyperlipidemia and prevent cardiovascular morbidity and mortality. Evidence suggests that they also have anti-neoplastic activity. Several studies show a reduced rate of breast cancer recurrence among lipophilic statin users (<i>e.g.</i>, simvastatin), motivating calls for clinical trials of statins in breast cancer patients. We measured the impact of genetic variation in statin-metabolizing enzymes and drug transporters on the recurrence rate in simvastatin-trea ...[more]

PMID: 32351149

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Project description:Heterogeneity of the tumor microenvironment (TME) is one of the major causes of treatment resistance in breast cancer. Among TME components, nervous system role in clinical outcome has been underestimated. Identifying neuronal signatures associated with treatment response will help to characterize neuronal influence on tumor progression and identify new treatment targets. The search for hormonotherapy-predictive biomarkers was implemented by supervised machine learning (ML) analysis on merged transcriptomics datasets from public databases. ML-derived genes were investigated by pathway enrichment analysis, and potential gene signatures were curated by removing the variables that were not strictly nervous system specific. The predictive and prognostic abilities of the generated signatures were examined by Cox models, in the initial cohort and seven external cohorts. Generated signature performances were compared with 14 other published signatures, in both the initial and external cohorts. Underlying biological mechanisms were explored using deconvolution tools (CIBERSORTx and xCell). Our pipeline generated two nervous system-related signatures of 24 genes and 97 genes (NervSign24 and NervSign97). These signatures were prognostic and hormonotherapy-predictive, but not chemotherapy-predictive. When comparing their predictive performance with 14 published risk signatures in six hormonotherapy-treated cohorts, NervSign97 and NervSign24 were the two best performers. Pathway enrichment score and deconvolution analysis identified brain neural progenitor presence and perineural invasion as nervous system-related mechanisms positively associated with NervSign97 and poor clinical prognosis in hormonotherapy-treated patients. Transcriptomic profiling has identified two nervous system-related signatures that were validated in clinical samples as hormonotherapy-predictive signatures, meriting further exploration of neuronal component involvement in tumor progression.SignificanceThe development of personalized and precision medicine is the future of cancer therapy. With only two gene expression signatures approved by FDA for breast cancer, we are in need of new ones that can reliably stratify patients for optimal treatment. This study provides two hormonotherapy-predictive and prognostic signatures that are related to nervous system in TME. It highlights tumor neuronal components as potential new targets for breast cancer therapy.

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Predictive pharmacogenetic biomarkers for breast cancer recurrence prevention by simvastatin.

Publications

Predictive pharmacogenetic biomarkers for breast cancer recurrence prevention by simvastatin.

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