|Richard Iggo graduated in physiology and medicine from the University of Bristol in 1984. He trained in Internal Medicine at the John Radcliffe Hospital, Oxford and the Hammersmith Hospital, London. In 1987 he became a clinical fellow in David Lane's lab and received his PhD from the University of London in 1991. He was then appointed as a junior group leader at the Swiss Institute for Experimental Cancer Research, Lausanne, where he was promoted to senior scientist in 1997. He was appointed to the chair of Molecular Medicine at the University of St Andrews in 2005 and to a chair of Cell Biology at the University of Bordeaux in 2008.|
Understanding breast cancer to develop new treatments :
The Iggo lab has two main goals: to understand the function of genes defective in breast cancer, and to improve the treatment of breast cancer. To achieve the former, the lab tests potential oncogenes for their ability to convert normal breast cells into tumour cells. To achieve the latter, the lab studies gene signatures of breast tumours treated with chemotherapy at the Bergonié Cancer Institute.
Many drugs currently used to treat breast cancer have major side effects. By limiting more toxic drugs to patients unlikely to respond to simpler treatments, substantial morbidity could be avoided without compromising the outcome for individual patients. Microarrays provide an unbiased means to identify markers that predict response to treatment. We have performed microarray analysis of breast cancer biopsies taken in the context of a multicentre academic clinical trial (EORTC 10994) organised by Hervé Bonnefoi at the Bergonié Cancer Institute.
To predict the response of individual tumours to the drugs used in the study, we first developed a new approach to disentangle the known biological factors that dominate the expression profiles of breast tumours. The only factor that survived rigorous testing in other datasets was stroma (Farmer et al 2009). There are many possible explanations for this result, but the simplest is that stromal fibroblasts secrete proteins that help the tumour cells to survive in the presence of chemotherapy. Whatever the mechanism, it is a weak effect that requires confirmation in an experimental model before attempting to exploit it in the clinic. Future work will address this issue by comparing the response to chemotherapy of xenografts in mice.
Analysis of the underlying patterns of gene expression in tumours from the EORTC 10994 trial showed that the tumours fall naturally into three major groups. These correspond to three cell types: ER+/AR+ luminal cells, ER‑/AR‑ basal cells and ER‑/AR+ molecular apocrine cells. The molecular apocrine group is closely related to the ERBB2+ tumour class identified by scientists at Stanford. The pattern of steroid receptor expression suggests that tumours in the apocrine group are distinguished by unopposed androgen signalling (Farmer et al 2005). To understand how normal breast cells develop into these three different types of tumour, we have established cell culture models that allow us to convert mammary epithelial cells into tumour cells. To do this we use lentiviral vectors to introduce cDNAs and microRNAs into normal human mammary epithelial cells derived from reduction mammoplasty tissue (Duss et al 2007).
Farmer, P., H. Bonnefoi, P. Anderle, D. Cameron, P. Wirapati, V. Becette, S. Andre, M. Piccart, M. Campone, E. Brain, G. Macgrogan, T. Petit, J. Jassem, F. Bibeau, E. Blot, J. Bogaerts, M. Aguet, J. Bergh, R. Iggo and M. Delorenzi (2009). "A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer." Nat Med 15: 68-74.
Duss, S., S. Andre, A. L. Nicoulaz, M. Fiche, H. Bonnefoi, C. Brisken and R. D. Iggo (2007). "An oestrogen-dependent model of breast cancer created by transformation of normal human mammary epithelial cells." Breast Cancer Res 9: R38.
Farmer, P., H. Bonnefoi, V. Becette, M. Tubiana-Hulin, P. Fumoleau, D. Larsimont, G. Macgrogan, J. Bergh, D. Cameron, D. Goldstein, S. Duss, A. L. Nicoulaz, C. Brisken, M. Fiche, M. Delorenzi and R. Iggo (2005). "Identification of molecular apocrine breast tumours by microarray analysis." Oncogene 24: 4660-71.