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How accurate is in vitro prediction of carcinogenicity?

ABSTRACT: Positive genetic toxicity data suggest carcinogenic hazard, and this can stop a candidate pharmaceutical reaching the clinic. However, during the last decade, it has become clear that many non-carcinogens produce misleading positive results in one or other of the regulatory genotoxicity assays. These doubtful conclusions cost a lot of time and money, as they trigger additional testing of apparently genotoxic candidates, both in vitro and in animals, to discover whether the suggested hazard is genuine. This in turn means that clinical trials can be put on hold. This review describes the current approaches to the 'misleading positive' problem as well as efforts to reduce the use of animals in genotoxicity assessment. The following issues are then addressed: the application of genotoxicity testing screens earlier in development; the search for new or improved in vitro genotoxicity tests; proposed changes to the International Committee on Harmonisation guidance on genotoxicity testing [S2(R1)]. Together, developments in all these areas offer good prospects of a more rapid and cost-effective way to understand genetic toxicity concerns.

SUBMITTER: Walmsley RM

PROVIDER: S-EPMC3058158 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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How accurate is in vitro prediction of carcinogenicity?

Walmsley Richard Maurice RM Billinton Nicholas N

British journal of pharmacology 20110301 6

Positive genetic toxicity data suggest carcinogenic hazard, and this can stop a candidate pharmaceutical reaching the clinic. However, during the last decade, it has become clear that many non-carcinogens produce misleading positive results in one or other of the regulatory genotoxicity assays. These doubtful conclusions cost a lot of time and money, as they trigger additional testing of apparently genotoxic candidates, both in vitro and in animals, to discover whether the suggested hazard is ge ...[more]

PMID: 21091657

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Project description:Purpose Aromatase inhibitors (AIs) have an established role in breast cancer treatment. Response rates are only 50-70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Participants and Methods Pre- and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 post-menopausal women with ER+ breast cancer receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed by three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterised and a four gene classifier of clinical response was established (accuracy of 96%) based upon the level of two genes prior to treatment (one associated with immune signalling, IL6ST and the other with apoptosis, NGFRAP1) and two proliferation genes (ASPM, MCM4) at 2 weeks of therapy. The four gene signature was found to be 91% accurate in a blinded, completely independent validation dataset of patients treated with anastrozole. Matched 2 week on-treatment biopsies improved predictive power over pre-treatment biopsies alone. This signature also significantly predicted recurrence free survival (p=0.029) and breast cancer specific survival (p=0.009). We demonstrate that the test can also be performed using quantitative PCR or immunohistochemistry. Conclusion A four gene predictive model of clinical response to AIs by two weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and a failure to reduce proliferation by 2 weeks are functional characteristics of breast tumours that do not respond to AIs. 25 Pre treatment, 25 two week and 25 three month on-treatment primary breast tumour samples from the same patients. Data was analysed with two previously generated datasets, GSE55374 which was also processed on Illumina HT-12v4 BeadChips (GPL10558) and GSE20181 on Affymetrix U133A GeneChips (GPL96)

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How accurate is in vitro prediction of carcinogenicity?

Publications

How accurate is in vitro prediction of carcinogenicity?

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