Proliferation: the most prominent predictor of clinical outcome in breast cancer 

With the advent of array-based technology and the sequencing of the human genome, comprehensive analysis of transcriptional variation at the genomic level has become possible. The knowledge derived from these gene expression profiling studies is already impressive in terms of challenging the currently used system for classifying breast cancer and the existing theories about metastatic progression; it is also impressive in terms of improving our understanding of the basic biology of breast cancer.

To further refine prognosis using gene expression profiling, our group undertook a “hypothesis-driven” approach focusing on histological grade, a well-established pathological parameter that is rooted in the cell biology of breast cancer. Applying a supervised analysis, we developed a Gene expression Grade Index (GGI) score based on 97-genes mainly involved in cell cycle regulation and proliferation. Interestingly, this index, which essentially quantifies the degree of similarity between the tumor expression pattern of these 97 genes and tumor grade, was able to reclassify patients with histologic grade 2 tumors into two groups with distinct clinical outcomes similar to those of histological grade 1 and 3 respectively. This observation challenges the existence and clinical relevance of an intermediate grade classification. Interestingly, we also found that proliferation-related genes captured by the genomic grade may encompass a significant portion of the predictive power of many previously published prognostic signatures, including the 70-gene and 76-gene signatures reported previously from other groups (oral presentation, ASCO 2006, manuscript in preparation). We also found that genomic grade was associated with the different molecular subtypes (previously identified by our group and others):  basal-like, erbB2-like and luminal A and B subgroups. While the luminal A subgroup showed lower GGI levels, the basal-like, erbB2-like and luminal B subgroups had the worst clinical outcome, in keeping with higher GGI levels (oral presentation SABCS, manuscript submitted for publication). These results suggest that genomic grade, which essentially captures the degree of differentiation and proliferation, may reflect the origin of the different cell lineages involved in breast cancer development. Finally, when we explored the implications of the joint distribution of ER status and GGI in predicting clinical outcome, we found that almost all ER-negative tumors were associated with a high GGI scores (high grade),  whereas ER-positive tumors were associated with a heterogeneous mixture of gene expression grade index values. Interestingly, and consistent with our results, almost all prognosis gene expression signatures assigned the vast majority of ER-negative patients in the high-risk group, suggesting that prognostic signatures are very useful for determining the risk of recurrence in the ER-positive subgroup, but much less informative for ER-negative disease...

References

Sotiriou C, Wirapati P, Loi S et al. : "Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis". J Natl Cancer Inst. 2006;98:262-272.

Sotiriou C, Wirapati P, Loi S et al.: "Comprehensive analysis integrating both clinicopathological and gene expression data in more than 1500 samples: Proliferation captured by gene expression grade index appears to be the strongest prognostic factor in breast cancer", Proc Am Soc Clin Oncol. 2006;24:abstr 507.

Sotiriou C, Wirapati P, Loi S et al. : "Better Characterization of estrogen receptor (ER) positive luminal Subtypes using genomic grade",. Breast Cancer Res Treat- SABCS. 2006.

Loi S, Haibe-Kains B, Desmedt C et al. : "Definition of clinically distinct molecular subtypes in estrogen receptor positive breast carcinomas through use of genomic grade",  Paper submitted. 2006

Christos Sotiriou

Functional Genomics and Translational Research Unit, Universite Libre de Bruxelles, Brussels, Belgium