Afadin cooperates with Claudin-2 to promote breast cancer metastasis.

Claudin-2 promotes breast cancer liver metastasis by enabling seeding and early cancer cell survival. We now demonstrate that the PDZ-binding motif of Claudin-2 is necessary for anchorage-independent growth of cancer cells and is required for liver metastasis. Several PDZ domain-containing proteins were identified that interact with the PDZ-binding motif of Claudin-2 in liver metastatic breast cancer cells, including Afadin, Arhgap21, Pdlim2, Pdlim7, Rims2, Scrib, and ZO-1. We specifically examined the role of Afadin as a potential Claudin-2-interacting partner that promotes breast cancer liver metastasis. Afadin associates with Claudin-2, an interaction that requires the PDZ-binding motif of Claudin-2. Loss of Afadin also impairs the ability of breast cancer cells to form colonies in soft agar and metastasize to the lungs or liver. Immunohistochemical analysis of Claudin-2 and/or Afadin expression in 206 metastatic breast cancer tumors revealed that high levels of both Claudin-2 and Afadin in primary tumors were associated with poor disease-specific survival, relapse-free survival, lung-specific relapse, and liver-specific relapse. Our findings indicate that signaling downstream from a Claudin-2/Afadin complex enables the efficient formation of breast cancer metastases. Moreover, combining Claudin-2 and Afadin as prognostic markers better predicts the potential of breast cancer to metastasize to soft tissues.

Multiview 3-D Echocardiography Fusion with Breath-Hold Position Tracking Using an Optical Tracking System.

Recent advances in echocardiography allow real-time 3-D dynamic image acquisition of the heart. However, one of the major limitations of 3-D echocardiography is the limited field of view, which results in an acquisition insufficient to cover the whole geometry of the heart. This study proposes the novel approach of fusing multiple 3-D echocardiography images using an optical tracking system that incorporates breath-hold position tracking to infer that the heart remains at the same position during different acquisitions. In six healthy male volunteers, 18 pairs of apical/parasternal 3-D ultrasound data sets were acquired during a single breath-hold as well as in subsequent breath-holds. The proposed method yielded a field of view improvement of 35.4 ± 12.5%. To improve the quality of the fused image, a wavelet-based fusion algorithm was developed that computes pixelwise likelihood values for overlapping voxels from multiple image views. The proposed wavelet-based fusion approach yielded significant improvement in contrast (66.46 ± 21.68%), contrast-to-noise ratio (49.92 ± 28.71%), signal-to-noise ratio (57.59 ± 47.85%) and feature count (13.06 ± 7.44%) in comparison to individual views.