Liver metastasis development in breast cancer patients is common and confers a poor prognosis. So far, the prognostic significance of surgical resection and clinical relevance of biomarker analysis in metastatic tissue have barely been investigated. We previously demonstrated an impact of WNT signaling in breast cancer brain metastasis. This study aimed to investigate the value of established prognostic markers and WNT signaling components in liver metastases. Overall N = 34 breast cancer liver metastases (with matched primaries in 19/34 cases) were included in this retrospective study. Primaries and metastatic samples were analyzed for their expression of the estrogen (ER) and progesterone receptor, HER-2, Ki67, and various WNT signaling-components by immunohistochemistry. Furthermore, β-catenin-dependent and -independent WNT scores were generated and analyzed for their prognostic value. Additionally, the influence of the alternative WNT receptor ROR on signaling and invasiveness was analyzed in vitro. ER positivity (HR 0.09, 95 % CI 0.01–0.56) and high Ki67 (HR 3.68, 95 % CI 1.12–12.06) in the primaries had prognostic impact. However, only Ki67 remained prognostic in the metastatic tissue (HR 2.46, 95 % CI 1.11–5.44). Additionally, the β-catenin-independent WNT score correlated with reduced overall survival only in the metastasized situation (HR 2.19, 95 % CI 1.02–4.69, p = 0.0391). This is in line with the in vitro results of the alternative WNT receptors ROR1 and ROR2, which foster invasion. In breast cancer, the value of prognostic markers established in primary tumors cannot directly be translated to metastases. Our results revealed β-catenin-independent WNT signaling to be associated with poor prognosis in patients with breast cancer liver metastasis.Electronic supplementary materialThe online version of this article (doi:10.1007/s10585-016-9780-3) contains supplementary material, which is available to authorized users.

Transcription factors (TFs) are gene regulatory proteins that are essential for an effective regulation of the transcriptional machinery. Today, it is known that their expression plays an important role in several types of cancer. Computational identification of key players in specific cancer cell lines is still an open challenge in cancer research. In this study, we present a systematic approach which combines colorectal cancer (CRC) cell lines, namely 1638N-T1 and CMT-93, and well-established computational methods in order to compare these cell lines on the level of transcriptional regulation as well as on a pathway level, i.e., the cancer cell-intrinsic pathway repertoire. For this purpose, we firstly applied the Trinity platform to detect signature genes, and then applied analyses of the geneXplain platform to these for detection of upstream transcriptional regulators and their regulatory networks. We created a CRC-specific position weight matrix (PWM) library based on the TRANSFAC database (release 2014.1) to minimize the rate of false predictions in the promoter analyses. Using our proposed workflow, we specifically focused on revealing the similarities and differences in transcriptional regulation between the two CRC cell lines, and report a number of well-known, cancer-associated TFs with significantly enriched binding sites in the promoter regions of the signature genes. We show that, although the signature genes of both cell lines show no overlap, they may still be regulated by common TFs in CRC. Based on our findings, we suggest that canonical Wnt signaling is activated in 1638N-T1, but inhibited in CMT-93 through cross-talks of Wnt signaling with the VDR signaling pathway and/or LXR-related pathways. Furthermore, our findings provide indication of several master regulators being present such as MLK3 and Mapk1 (ERK2) which might be important in cell proliferation, migration, and invasion of 1638N-T1 and CMT-93, respectively. Taken together, we provide new insights into the invasive potential of these cell lines, which can be used for development of effective cancer therapy.

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