Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction

Abstract

BACKGROUND: For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables -nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER þ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence. METHODS: Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model. RESULTS: Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%.CONCLUSION: The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence.

Sodium valproate inhibits MDA-MB-231 breast cancer cell migration by upregulating NM23H1 expression

“…Although VPA has been shown to reduce cancer proliferation to some extent, data about its effect on breast cancer cells are still insufficient in both animals and humans, and studies have often yielded contrasting results and conflicting conclusions (Dutertre et al, 2010;Adams et al, 2010;Baneshi et al, 2010). The inhibitory effect of VPA may be cancer type-specific in many studies; for example, one study found no difference in invasiveness between treated and untreated bladder cancer cell lines HTB5 and HTB9 (Byun et al, 2009).…”

Justification effectiveness of systemic treatment of breast cancer depending on body mass index

“…Along with this recent literature there is information that women are overweight effectiveness of systemic treatments may be lower than expected. Other data refute this information [3].…”

“…Implicit in this mechanism for resistance is cross-talk activation between the ER and the epidermal growth factor receptor (EGFR/ Her-2/neu) pathways [3]. Treatment with various signal transduction inhibitors has been used in combination with endocrine therapy to overcome resistance, such as gefitinib, which targets the internal tyrosine kinase domain of EGFR, and trastuzumab, which blocks the external domain of Her-2/neu [4].…”

Prognostic and predictive factors of early breast cancer

“…Of them, tumor size and nodal status are clearly among the strongest predictors of overall survival and metastasis and are also strong predictors of postmastectomy chest wall relapse when radiation is not used [1,2] . However, the outcomes of numerous studies correlating clinical and pathologic features of the primary tumor and/or nodal disease with prognosis have not been uniformly reported [3][4][5][6][7][8][9][10][11] . For example, the presence of multicentric disease is strongly associated with other risk factors for local-regional recurrence, such as tumor size and nodal involvement, but in patients with stage II disease with 0-3 positive lymph nodes, multicentric disease does not seem to elevate the risk of local-regional recurrence [12] .…”