Tissue microarrays for rapid linking of molecular changes to clinical endpoints

Abstract

Advances in genomics and proteomics are dramatically increasing the need to evaluate large numbers of molecular targets for their diagnostic, predictive or prognostic value in clinical oncology. Conventional molecular pathology techniques are often tedious, time-consuming, and require a lot of tissue, thereby limiting both the number of tissues and the number of targets that can be evaluated. Here, we demonstrate the power of our recently described tissue microarray (TMA) technology in analyzing prognostic markers in a series of 553 breast carcinomas. Four independent TMAs were constructed by acquiring 0.6 mm biopsies from one central and from three peripheral regions of each of the formalin-fixed paraffin embedded tumors. Immunostaining of TMA sections and conventional "large" sections were performed for two well- established prognostic markers, estrogen receptor (ER) and progesterone receptor (PR), as well as for p53, another frequently examined protein for which the data on prognostic utility in breast cancer are less unequivocal. Compared with conventional large section analysis, a single sample from each tumor identified about 95% of the information for ER, 75 to 81% for PR, and 70 to 74% for p53. However, all 12 TMA analyses (three antibodies on four different arrays) yielded as significant or more significant associations with tumor-specific survival than large section analyses (p < 0.0015 for each of the 12 comparisons). A single sample from each tumor was sufficient to identify associations between molecular alterations and clinical outcome. It is concluded that, contrary to expectations, tissue heterogeneity did not negatively influence the predictive power of the TMA results. TMA technology will be of substantial value in rapidly translating genomic and proteomics information to clinical applications.

Figure 1.

Breast cancer prognosis tissue microarray (TMA). Overview of an H&E stained TMA section containing samples of the tumor center.

Figure 2.

Examples of positive and negative tumors. Single punches (0.6 mm diameter) positive for ER (A), PR (B), and positive and negative for p53 respectively (C and D).

Figure 3.

Immunohistochemical analyses of ER, PR, and p53 on TMAs and on large sections. Only tumors that were interpretable on all four TMAs and on large sections were included in this analysis. The bars on the left of each group reflect the positivity found in the individual TMA from the tumor center (C) and the three peripheric areas (P1, P2, P3). The bars marked as 2A, 3A, and 4A give the frequency of positivity that was obtained by combining the data from 2 TMAs (2A: center + periphery 1), 3 TMAs (3A: center + peripery 1 + periphery 2), or from all four TMAs (4A). Tumors are considered positive in this calculation if at least one sample was considered positive. The bar on the right gives the frequency detected on large sections (LS).

Figure 4.

ER immunostaining and prognosis. The association with tumor-specific survival is shown for ER data obtained on the TMA containing tissue from the tumor center (A), the three TMAs containing different samples from the tumor periphery (B–D), the combination of the data from all four TMAs counting every tumor as positive if at least one sample was scored positive (E), and on large sections (F).

Figure 5.

PR immunostaining and prognosis. The association with tumor-specific survival is shown for PR data obtained on the TMA containing tissue from the tumor center (A), the three TMAs containing different samples from the tumor periphery (B–D), the combination of the data from all four TMAs counting every tumor as positive if at least one sample was scored positive (E) and on large sections (F).

Figure 6.

p53 immunostaining and prognosis. The association with tumor-specific survival is shown for p53 data obtained on the TMA containing tissue from the tumor center (A), the three TMAs containing different samples from the tumor periphery (B–D), the combination of the data from all four TMAs counting every tumor as positive if at least one sample was scored positive (E), and on large sections (F). G and H: Results of a quantitative analysis of the large sections. The percentage of positive cells (G) and the staining intensity (H) were linked to prognosis.

Figure 7.

Heterogeneity of results in individual tumors. Only tumors that were interpretable in all four TMAs were included in these analyses. A shows the percentage of individual tumors with 0 to 4 positive TMA results. The survival rates for tumors with homogenous and heterogeneous IHC results are shown for ER (B), PR (C), and p53 (D).