Should we select specific chemotherapy regimens based on tumour molecular subtypes?


Session type:

Herve Bonnefoi

Hospitaux Universitaires de Geneve, Geneva, Switzerland


Should we select specific chemotherapy regimens based on tumour molecular subtypes?

Considering both the clinical and molecular heterogeneity of breast cancers, one can easily hypothesize that all tumours are not equally sensitive to the different chemotherapy agents or regimens used. This is implicit in the well-versed concept of non-cross resistance: a predefined molecular subtype might be resistant to a specific cytostatic agent or regimen whilst remaining sensitive to another treatment. The challenge is to categorize these molecular subtypes. We will present in this lecture three different approaches. The first approach is very classic and consists of identify subgroups of tumours based on the expression of single molecular markers. The most extensively studied markers are hormone receptors, HER2, TOPO2, and p53. Several trials have recently reported provocative but often contradictory results on the predictive value of these markers, and these data will be summarized. The second approach aiming to identify molecular subtypes uses multiple markers or predictive signatures. Individual response to a cytostatic agent or regimen is a very complex phenomena probably involving many genes and signalling pathways. To address this difficult question modern molecular biology methods which permit analysis of thousands of markers from a single biopsy with high throughput technologies seem more appropriate than single markers studies. Several trials have been conducted trying to identify gene expression signatures predicting for clinical or pathological response after neoadjuvant chemotherapy, with many different study designs which might allow prospective validation of this approach in the near future. The third approach, is more provocative and consists of defining each molecular subtype using the Stanford “breast intrinsic gene set” classification, and then considering the evidence for chemosensitivity in each subgroup. To date, there are fewer confirmatory data for this approach, but the potential advantage is that it may not only allow identification of more accurate class-specific predictors than the global approach, but also might help to identify new therapeutic targets.