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Breast cancer prognosis is a subject undergoing intense study due to its high clinical relevance for effective therapeutic management and a great patient interest in disease progression. Prognostic value of fractal and gray level co-occurrence matrix texture analysis algorithms has been previously established on tumour histology images, but without any direct performance comparison. Therefore, this study was designed to compare the prognostic power of the monofractal, multifractal and co-occurrence algorithms on the same set of images. The investigation was retrospective, with 51 patients selected on account of non-metastatic IBC diagnosis, stage IIIB. Image analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Bootstrap-corrected Cox proportional hazards regression P-values indicated a significant association with metastasis outcome of at least one of the features within each group. AUC values were far better for co-occurrence (0.66-0.77) then for fractal features (0.60-0.64). Correction by the split-sample cross-validation likewise indicated the generalizability only for the co-occurrence features, with their classification accuracies ranging between 67 and 72 %, while accuracies of monofractal and multifractal features were reduced to nearly random 52-55 %. These findings indicate for the first time that the prognostic value of texture analysis of tumour histology is less dependent on the morphological complexity of the image as measured by fractal analysis, but predominantly on the spatial distribution of the gray pixel intensities as calculated by the co-occurrence features.

Owing to exceptional heterogeneity in the outcome of invasive breast cancer it is essential to develop highly accurate prognostic tools for effective therapeutic management. Based on this pressing need, we aimed to improve breast cancer prognosis by exploring the prognostic value of tumor histology image analysis. Patient group (n=78) selection was based on invasive breast cancer diagnosis without systemic treatment with a median follow-up of 147 months. Gray-level co-occurrence matrix texture analysis was performed retrospectively on primary tumor tissue section digital images stained either nonspecifically with hematoxylin and eosin or specifically with a pan-cytokeratin antibody cocktail for epithelial malignant cells. Univariate analysis revealed stronger association with metastasis risk by texture analysis when compared with clinicopathological parameters. The combination of individual clinicopathological and texture variables into composite scores resulted in further powerful enhancement of prognostic performance, with an accuracy of up to 90%, discrimination efficiency by the area under the curve [95% confidence interval (CI)] of 0.94 (0.87-0.99) and hazard ratio (95% CI) of 20.1 (7.5-109.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the models are generalizable. Whereas further validation is needed on an external set of patients, this preliminary study indicates the potential use of primary breast tumor histology texture as a highly accurate, simple, and cost-effective prognostic indicator of distant metastasis risk.

C-myc is considered to have an important role in cancerogenesis and tumor progression. The aim of this study was to evaluate a possible significance of c-myc amplification as a clinically useful prognostic/predictive parameter in metastatic breast cancer (MBC). Eighty-seven MBC patients with known clinicopathological parameters were included in the study, at the time of diagnosis of metastatic disease. In metastatic setting, 52% of patients received CMF, 34% received FAC, and 32% received hormonal therapy (tamoxifen). C-myc amplification was analyzed by chromogenic in situ hybridization, according to the manufacturer's instructions. C-myc amplification was detected in 26% cases and showed a strong correlation with ER status, stage of disease (initial) and existence of distance metastasis. There was no statistically significant difference in MBC (post-relapse) survival between c-myc-nonamplified and c-myc-amplified subgroups regardless of or regarding the treatment. However, correlation was found between c-myc status and individual patient's outcomes. Patients with c-myc amplification treated with chemotherapy (CMF and FAC) had clinical benefit (complete remission, partial remission or stable disease) in contrast to patients without amplification. Lack of significant difference in MBC (post-relapse) survival according to c-myc status could be due to a better response of patients to appropriate treatment (chemotherapy). It is possible that negative prognostic impact of c-myc amplification is masked with increased responsiveness to chemotherapy.