The International Journal of Biochemistry & Cell Biology
Age-associated biomarker profiles of human breast cancer
Introduction
The association between human cancer and aging remains poorly understood [1]. The conventional wisdom among physicians is that “old people get old tumors” [2]; and the fact that most human cancers increase in frequency with aging has long dominated their descriptive epidemiology but received little basic research attention [3], [4]. The incidence of thyroid cancers, for example, increases with aging; but poorly recognized is the fact that its biological aggressiveness (controlled for disease stage and presence of activated oncogenes and loss of tumor suppressor genes) increases even more dramatically with patient age [5]. Yet this age-associated pattern of a worsening biological tumor profile is not universally observed with other age-dependent epithelial cancers [6]; prostate cancer, for example, shows a markedly increasing incidence with age but no age association with any biomarker of prognostic significance. Of all human epithelial cancers, breast cancer is the best studied to date with regard to clinical features distinguishing old versus young tumors; without controlling for tumor stage or biological markers, it appears that advancing age is associated with a more favorable breast tumor biology including a higher proportion of estrogen receptor (ER)-positive cases [7], [8], [9]. These breast cancer studies, however, have evaluated few of the many tumor biomarkers known to associate with patient prognosis and were seldom powered for decade-by-decade analyses across all patient age groups.
Scientists studying the biology of aging across various mammalian species have offered several theories for the observed increase in human cancer with aging [10], [11], [12], [13], [14], [15]: (i) longer exposure interval to carcinogen or tumor promoter (e.g. endogenous estrogen exposure and breast tumorigenesis) (ii) increased transformation susceptibility due to impaired intracellular repair (e.g. DNA) and detoxification (e.g. antioxidant defense) mechanisms and (iii) diminished immune surveillance and/or stromal tissue defense due to an age-associated increase in senescent cell populations. As has been long proposed [14] and recently elaborated upon in more mechanistic detail [15], the above theories all support a general paradigm that age-associated cancers possess an accumulated mutational load with loss of p53-dependent DNA damage checkpoints, acquisition of telomerase activity and a “mutator” phenotype resulting in progressive genetic instability. As well, the escape of transformed cells from an aging tissue population of senescent cells requires loss of cell cycle checkpoints and other biological changes typically found in tumors showing rapid growth and proliferation and a more invasive (i.e. metastatic) phenotype [13]. Unfortunately, clinical studies and direct evidence in support of predictions emerging from these theories are lacking for virtually all age-associated human malignancies including breast cancer [1], [6].
To explore the hypothesis that aging not only increases breast cancer incidence but also alters breast cancer biology, we correlated patient age at diagnosis with tumor histology, stage, and various biomarkers independently determined on two different tumor archives: an American collection of ∼800 paraffin-embedded and immunohistochemically analyzed primary breast cancers, and a European collection of ∼3000 cryobanked primary breast cancers analyzed by ligand-binding and EIA. Within the constraints of their assay methodologies, the multiple biomarkers assayed herein represent validated surrogate measures of tumor growth, invasive potential, genetic instability, endocrine and growth factor receptor dependence.
Section snippets
European tumor collective and biomarker analyses
The European (STB, Basel) collective of 3208 cryopreserved (−70 °C) primary breast tumors and its associated database of patient characteristics including age at diagnosis and survival with/without therapy, as well as tumor characteristics including histology, nuclear grade, stage (TNM with tumor size and number of positive nodes) and selected tumor biomarkers has been previously described [16], [17]. Tissue homogenates were prepared for biomarker measurement by validated radioligand-binding
Statistical methods
Associations between the continuous variable biomarker values from the European database (untransformed or transformed values, as indicated) for each patient age category, displayed as boxplots, were tested for significance using non-parametric Wilcoxon (compares median values of one age group to those of another age group) or Kruskal-Wallis rank-sum (compares median values of all different age groups) statistical tests. Tumor characteristics and IHC scores from the American database
Results
No significant association between breast tumor histology (proportion of invasive ductal versus lobular breast cancers) and patient age at diagnosis was observed in either the European or American tumor collectives. As well, neither collective observed any strong correlations (|r|>0.1; P≤0.05) between age and tumor stage at diagnosis, measured by tumor size (T, with median T values ranging from 2.0 to 2.5 cm across all age groups in both collectives) and nodal involvement (N, with all age groups
Discussion
In addition to the standard characterization of breast cancers by histology, grade and stage, this study evaluated two large European and American breast tumor collectives for prognostic markers that might correlate with increasing patient age at the time of diagnosis. Included in this retrospective analysis were previously validated biomarkers that represented surrogate measures of breast tumor: (i) proliferation, growth and genetic instability (mitotic and apoptotic indices,
Acknowledgements
We thank C. Wullschleger, K. Paris and A. Takahashi for technical assistance, data management and tumor banking in the analysis of the European collective. We thank S. Liu for technical assistance in the analysis of the American collective. This work was supported in part by NIH sponsored Grants R01-CA71468 and R01-CA36773 and DOD sponsored grant DAMD17-99-1-9111, the Hazel P. Munroe (Buck Institute) and Janet Landfear (Mt. Zion Health Systems) memorial funds, as well as funding from the
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