engleski

Is cancer self-seeding linked to IHC similarities between primary & metastatic tumors?

Larry Norton and Joan Massagué recently proposed a provocative model of cancer growth (1, 2) that is based on a unified process of growth and metastasis including self-seeding of the primary tumor by circulating tumor cells. As pointed out in the first paper (1), new insights in cancer growth can focus our therapies to mechanisms involved in metastasis, including metastasis to self. Clinicians usually require some testable prediction before accepting new interpretation of the previously defined phenomenon and cancer growth is no exception. An obvious candidate for testing is the model’ s prediction that continuous exchange of malignant cells between metastatic sites and the primary tumor would make all tumor sites similar in malignant cells subpopulations. Based on this prediction, we have tried to statistically compare immunohistochemical (IHC) features of breast cancers and their metastasis on data of 60 ductal invasive breast cancer patients, as presented elsewhere (3). IHC profiles of six parameters (ER, PR, Ki-67, bcl-2, p53, and cathepsin D) for primary tumors and their node metastasis were done. Observed values were compared by the Wilcoxon matched pairs test and a p-value was calculated for the each patient. Wilcoxon p-values ranged in our patients from 0.0431 to 0.999 with median of 0.593 (eight cases), mean value of 0.571 and standard deviation of 0.297. Six cases had p-values below 0.10 and 10 cases above 0.90. If we can use the Wilcoxon p-value as a measure of similarity in IHC profiles of primary and metastatic breast cancer sites, higher values might suggest higher rates of self seeding that prevent any site-specific evolution of malignant subclones. On the contrary, the low values can be expected in patients with low rates of self seeding, thus allowing separate tumor sites to take separate routes of development. According to the described distribution of p-values, it seems that our group of patients involved both expected types. To check out whether p-values are dependent on tumor size, or on the share of the axillary node involvement (number of positive nodes divided by the number of extirpated nodes), we have performed an EM clustering of our cases based on tumor size and their node involvement (StatSoft, Inc. (2004). STATISTICA (data analysis software system), version 7 ; www.statsoft.com). Two clusters were identified: the first one with 39 cases and the second with 21 cases, as shown in Figure 1. The first cluster is characterized by smaller tumors and lower axillary involvement, while the contrary can be said for the second one. It turned out that the Wilcoxon p-values were significantly higher in the first cluster, tested with the Mann-Whitney U test (Z=2.378, p=0.0173). This result suggests that higher similarity in IHC profiles of breast cancer and its axillary metastasis can be expected in small aggressive tumors that, despite their small size, have already produced a regional metastasis. Larger tumors might be less continuous in self-feeding, so local evolution of subclones can take place in primary and secondary sites and this can explain the lower Wilcoxon p-values.

tumor growth models; tumor architecture; metastatic breast cancer

Radi se o e-pismu izašlom kao prilog komentiranog rada u The Oncologistu 2005 ; 10(6) 370-381