Dataset Information

A computational model to predict bone metastasis in breast cancer by integrating the dysregulated pathways.

ABSTRACT: BACKGROUND: Although there are a lot of researches focusing on cancer prognosis or prediction of cancer metastases, it is still a big challenge to predict the risks of cancer metastasizing to a specific organ such as bone. In fact, little work has been published for such a purpose nowadays. METHODS: In this work, we propose a Dysregulated Pathway Based prediction Model (DPBM) built on a merged data set with 855 samples. First, we use bootstrapping strategy to select bone metastasis related genes. Based on the selected genes, we then detect out the dysregulated pathways involved in the process of bone metastasis via enrichment analysis. And then we use the discriminative genes in each dysregulated pathway, called as dysregulated genes, to construct a sub-model to forecast the risk of bone metastasis. Finally we combine all sub-models as an ensemble model (DPBM) to predict the risk of bone metastasis. RESULTS: We have validated DPBM on the training, test and independent sets separately, and the results show that DPBM can significantly distinguish the bone metastases risks of patients (with p-values of 3.82E-10, 0.00007 and 0.0003 on three sets respectively). Moreover, the dysregulated genes are generally with higher topological coefficients (degree and betweenness centrality) in the PPI network, which means that they may play critical roles in the biological functions. Further functional analysis of these genes demonstrates that the immune system seems to play an important role in bone-specific metastasis of breast cancer. CONCLUSIONS: Each of the dysregulated pathways that are enriched with bone metastasis related genes may uncover one critical aspect of influencing the bone metastasis of breast cancer, thus the ensemble strategy can help to describe the comprehensive view of bone metastasis mechanism. Therefore, the constructed DPBM is robust and able to significantly distinguish the bone metastases risks of patients in both test set and independent set. Moreover, the dysregulated genes in the dysregulated pathways tend to play critical roles in the biological process of bone metastasis of breast cancer.

SUBMITTER: Zhou X

PROVIDER: S-EPMC4161863 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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A computational model to predict bone metastasis in breast cancer by integrating the dysregulated pathways.

Zhou Xionghui X Liu Juan J

BMC cancer 20140827

<h4>Background</h4>Although there are a lot of researches focusing on cancer prognosis or prediction of cancer metastases, it is still a big challenge to predict the risks of cancer metastasizing to a specific organ such as bone. In fact, little work has been published for such a purpose nowadays.<h4>Methods</h4>In this work, we propose a Dysregulated Pathway Based prediction Model (DPBM) built on a merged data set with 855 samples. First, we use bootstrapping strategy to select bone metastasis ...[more]

PMID: 25163697

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Project description:BACKGROUND: Bone metastasis is a main cause of morbidity in breast cancer. Since breast cancer is a heterogeneous disease, the interactions of cancer cells with the skeletal host cells might also be diverse. We hypothesized that gene expression signatures induced by heterotypic interaction of breast cancer cells and osteoblasts might be of clinical relevance. METHODOLOGY/PRINCIPAL FINDINGS: We established an ex vivo co-culture model using benign breast epithelial cells or a panel of 5 malignant breast epithelial cells in combination with primary human osteoblasts and determined associated gene expression changes with HEEBO microarrays. Pretreatment gene expression profiles of 295 early stage breast cancers published from the Netherlands Cancer Institute with a median follow up of 12.6 years allowed evaluating in vitro effects in the in vivo situation.The effects of the interaction between osteoblasts and breast cancer cell lines of different origin were very heterogeneous. Hs578T cells started to proliferate in co-culture with osteoblasts, SKBR-3 induced a TGF-? response and MDA-MB231 cells showed two distinct sets of up-regulated genes: A set of interferon response genes associated with an up-regulation of STAT1 was in vivo remarkably coherent providing a basis for segregation of tumors into two groups. In a uni-variate analysis, early stage tumors with high expression levels (n?=?136) of this gene set had a significantly lower overall survival rate (p?=?0.005) (63% at 10 years) than tumors with low expression levels (n?=?159) (overall survival: 77% at 10 years). The second gene set was associated with IL-6 and did not significantly change the overall survival rate (p?=?0.165), but was significantly associated with a shorter time to bone metastasis (p?=?0.049; 74% vs. 83% at 10 years). CONCLUSION/SIGNIFICANCE: An IL-6 gene expression pattern induced by heterotypic interaction of breast cancer cells with osteoblasts in vitro is associated with a higher rate of bone metastasis in vivo.

Project description:The establishment of bone metastasis remains one of the most frequent complications of patients suffering from advanced breast cancer. Patients with bone metastases experience high morbidity and mortality caused by excessive, tumor-induced and osteoclast-mediated bone resorption. Anti-resorptive treatments, such as bisphosphonates, are available to ease skeletal related events including pain, increased fracture risk, and hypercalcemia. However, the disease remains incurable and 5-year survival rates for these patients are below 25%. Within the bone, disseminated breast cancer cells localize in "metastatic niches," special microenvironments that are thought to regulate cancer cell colonization and dormancy as well as tumor progression and subsequent development into overt metastases. Precise location and composition of this "metastatic niche" remain poorly defined. However, it is thought to include an "endosteal niche" that is composed of key bone cells that are derived from both, hematopoietic stem cells (osteoclasts), and mesenchymal stromal cells (osteoblasts, fibroblasts, adipocytes). Our knowledge of how osteoclasts drive the late stage of the disease is well-established. In contrast, much less is known about the interaction between osteogenic cells and disseminated tumor cells prior to the initiation of the osteolytic phase. Recent studies suggest that mesenchymal-derived cells, including osteoblasts and fibroblasts, play a key role during the early stages of breast cancer bone metastasis such as tumor cell homing, bone marrow colonization, and tumor cell dormancy. Hence, elucidating the interactions between breast cancer cells and mesenchymal-derived cells that drive metastasis progression could provide novel therapeutic approaches and targets to treat breast cancer bone metastasis. In this review we discuss evidences reporting the interaction between tumor cells and endosteal niche cells during the early stages of breast cancer bone metastasis, with a particular focus on mesenchymal-derived osteoblasts and fibroblasts.

Dataset Information

A computational model to predict bone metastasis in breast cancer by integrating the dysregulated pathways.

Publications

A computational model to predict bone metastasis in breast cancer by integrating the dysregulated pathways.

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