MUC1-induced transcriptional programs associated with tumorigenesis predict outcome in breast and lung cancer

Abstract

The Mucin 1 (MUC1) oncoprotein is aberrantly overexpressed in diverse human malignancies including breast and lung cancer. Although MUC1 modulates the activity of several transcription factors, there is no information regarding the effects of MUC1 on global gene expression patterns and the potential role of MUC1-induced genes in predicting outcome for cancer patients. We have developed an experimental model of MUC1-induced transformation that has identified the activation of gene families involved in oncogenesis, angiogenesis, and extracellular matrix remodeling. A set of experimentally derived MUC1-induced genes associated with tumorigenesis was applied to the analysis of breast and lung adenocarcinoma cancer databases. A 35-gene MUC1-induced tumorigenesis signature predicts significant decreases in both disease-free and overall survival in patients with breast (n=295) and lung (n=442) cancers. The data show that the MUC1 oncoprotein contributes to the regulation of genes that are highly predictive of clinical outcome in breast and lung cancer patients.

Figure 1

MUC1-CD induces tumorigenesis that is accompanied by distinct changes in gene expression. A, tumor formation of 3Y1/Vector and 3Y1/MUC1-CD cells. Points, mean; bars, SE. B, significant increases in gene expression in transition of 3Y1/MUC1-CD cells grown in vitro to in vivo.

Figure 2

MUC1-CD–induced tumorigenesis is associated with the activation of genes that functionally contribute to tumor growth. A, expressional clustering of all differentially expressed genes. B, tumorigenesis subset. C, metastasis, cell motility, and angiogenesis subset. Gray, 3Y1/Vector in vitro; black, 3Y1/MUC1-CD in vitro; white, 3Y1/MUC1-CD in vivo. Red, overexpressed. Values are mean-normalized log₂-transformed signals.

Figure 3

A 93-gene subset of MUC1-CD–induced tumorigenesis genes predicts poor outcome in breast and lung cancers. A, expressional clustering of the 93-gene subset in breast cancer (n = 295) partitions patient samples into 2 subgroups (red and blue bars). Vertical axis, patients; colored bars to the right of the cluster diagram correspond to the survival curves in B. For lung cancer, patient subgroups were defined based on differential expression of the 93-gene subset and determined using k-means clustering. Kaplan-Meier survival curves of disease-free and overall survival for breast (B; n = 295) and lung (C; n = 442) cancers show patient subgroups defined by differential expression of the 93-gene subset have significant differences in outcome.

Figure 4

A 35-gene MTS is prognostic in breast and lung cancers. K-means clustering of breast (A) and lung (B) cancers by expression of MTS. Kaplan-Meier curves for overall survival for breast (C) and lung (D) cancers. Kaplan-Meier curves for disease-free survival for breast (E) and lung (F) cancers. For graphs (A–F): red, MTS+; blue, MTS−. See Table 1 for further details.