Prognostic Role of Krüppel-Like Factors 5, 9, and 11 in Endometrial Endometrioid Cancer.

BACKGROUND AND OBJECTIVE: Krüppel-like factors (KLFs) are transcription factors with the ability to mediate cross-talk with signaling pathways involved in cell proliferation control, apoptosis, migration, and differentiation. They also appear to influence steroid hormone signaling through transcriptional networks involving steroid hormone receptors and members of the nuclear receptor family of transcription factors. Our study aims to evaluate the potential prognostic role of KLF5, KLF9, and KLF11 in endometrial cancer, and their correlation with hormonal receptor status and cellular proliferation. MATERIALS AND METHODS: Retrospective observational study on cases of endometrioid endometrial adenocarcinoma collected in the period January 2000-December 2011 at the University of Udine. Formalin-fixed, paraffin-embedded tissue samples were all submitted to tissue microarray immunohistochemical study. A survival analysis was performed. RESULTS: One hundred forty seven patients were included in the study with a mean age at surgery of 65.6 years (±10.2). 80.3% of endometrial malignancies were classified as stage FIGO I (118/147). Radiation therapy and chemotherapy were administered in 62.3% (91/146) and 6.2% (9/145) of patients respectively. Five-year overall survival and disease-free survival resulted 85.4% (95% CI, 79.8-91.4%) and 79.4% (95% CI, 73.0-86.4%) respectively. A high Ki-67, cytoplasmatic KLF5 (HR 4.72, CI.95 1.61-13.89, p < 0.05), and nuclear KLF11 (HR 3.04, CI.95 0.99-9.36, p = 0.053) scores correlated with a shorter overall survival. In addition, a high nuclear KLF11 (HR 2.59, CI.95 1.13-5.95, p < 0.05) score correlated with a shorter disease-free survival. CONCLUSIONS: In patients affected by endometrioid endometrial carcinoma, higher staining levels of KLF5 and KLF11 correlated with a poorer prognosis. However, further studies are required in order to better clarify the role of KLFs in the natural history of endometrial cancer.

An adaptive positivity thresholding method for automated Ki67 hotspot detection (AKHoD) in breast cancer biopsies.

The proliferative activity of breast cancer tissue can be estimated using the Ki67 biomarker. The percentage of positivity of such biomarker is correlated with proliferation and consequently with the prognosis of a breast tumor. Ki67 marked tissue samples are analyzed by an experienced pathologist who identifies the most active areas of tumor cell proliferation called hotspots, and estimates the positivity of each case. A method for the Automated Ki67 Hotspot Detection (AKHoD) is presented in this work. The main objective of the AKHoD method is to automatically and efficiently provide the pathologist with suggestions about Ki67 hotspot areas as a decision support. The input of AKHoD is a digital slide that is divided in tiles. For each tile, AKHoD provides a rough estimate of positivity and cellularity, summarized in very low resolution positivity and cellularity images. In a second step, an adaptive thresholding is applied to such positivity image to identify the most positive connected and convex areas, within cellularity limits set by current guidelines (that is, 500-2000). The method has been preliminarily validated on 50 digital slides for which three expert pathologists provided gold standard hotspots. 82% of the gold standard hotspots have been successfully recognized by the system, spending an average of 54s per slide. While further validation is needed taking into account also patients follow-up, this first experimentation suggests that the proposed method could be adequate for supporting the pathologist in hotspot detection.