A variety of biophysical forces are altered in the tumor microenvironment (TME) and these forces can influence cancer progression. One such force is interstitial fluid flow (IFF)-the movement of fluid through the tissue matrix. IFF was previously shown to induce invasion of cancer cells, but the activated signaling cascades remain poorly understood. Here, it is demonstrated that IFF induces invasion of ERBB2/HER2-expressing breast cancer cells via activation of phosphoinositide-3-kinase (PI3K). In constitutively activate ERBB2-expressing cells that have undergone epithelial-to-mesenchymal transition (EMT), IFF-mediated invasion requires the chemokine receptor CXCR4, a gradient of its ligand CXCL12, and activity of the PI3K catalytic subunits p110a and b. In wild-type ERBB2-expressing cells, IFF-mediated invasion is chemokine receptorindependent and requires only p110a activation. To test whether cells undergoing EMT alter their signaling response to IFF, TGFb1 was used to induce EMT in wild-type ERBB2-expressing cells, resulting in IFF-induced invasion dependent on CXCR4 and p110b.Implications: This study identifies a novel signaling mechanism for interstitial flow-induced invasion of ERBB2-expressing breast cancer cells, one that depends on EMT and acts through a CXCR4-PI3K pathway. These findings suggest that the response of cancer cells to interstitial flow depends on EMT status and malignancy.

The growth and progression of most solid tumors depend on the initial transformation of the cancer cells and their response to stroma-associated signaling in the tumor microenvironment 1 . Previously, research on the tumor microenvironment has focused primarily on tumor-stromal interactions 1-2 . However, the tumor microenvironment also includes a variety of biophysical forces, whose effects remain poorly understood. These forces are biomechanical consequences of tumor growth that lead to changes in gene expression, cell division, differentiation and invasion 3 . Matrix density 4 , stiffness [5][6] , and structure 6-7 , interstitial fluid pressure 8 , and interstitial fluid flow 8 are all altered during cancer progression.Interstitial fluid flow in particular is higher in tumors compared to normal tissues [8][9][10] . The estimated interstitial fluid flow velocities were measured and found to be in the range of 0.1-3 μm s -1 , depending on tumor size and differentiation 9, 11 . This is due to elevated interstitial fluid pressure caused by tumor-induced angiogenesis and increased vascular permeability 12 . Interstitial fluid flow has been shown to increase invasion of cancer cells [13][14] The technique presented here imposes interstitial fluid flow on cells in vitro and quantifies its effects on invasion (Figure 1). This method has been published in multiple studies to measure the effects of fluid flow on stromal and cancer cell invasion [13][14][15]17 . By changing the matrix composition, cell type, and cell concentration, this method can be applied to other diseases and physiological systems to study the effects of interstitial flow on cellular processes such as invasion, differentiation, proliferation, and gene expression. Video LinkThe 3. Mix components of the gel on ice in the same sequence as above and incubate final solution for 1 hr at 4°C. In our experience, a 1 hr incubation prior to cell seeding results in a more uniform gelation of the collagen. Make sure to keep Matrigel and collagen on ice at all times and to work as fast as possible to prevent gelation.

patients did not receive NCCN-recommended therapies, and 8,888 (73%) patients received at least first-line treatment. Of the total, 5,111(42%) received second-line treatment, and 3,163 (26%) received third-line treatment. Patients in the 66-70 years category had a greater proportion receiving treatment (80%) as compared with older age categories (76% and 65%). Patients diagnosed between 2000-2004 had a higher proportion receiving Chemo-only (18%) as compared to later periods (5% and 4%). Among patients receiving first-line treatment, 44.5% received R-chemo and 21.3% received R-alone. In the second-line setting, the proportions receiving R-chemo (35%) and R-alone (33%) were similar, but in the third-line setting, a larger proportion received R-alone (41.5%) compared to R-Chemo (28.8%). The median time to initiation was earlier for R-chemo (57 days) and Chemo-alone (51 days), as compared to R-alone (77 days) and Other (73 days) therapies. The median follow-up times were shortest for patients receiving no treatment (876 days) compared to all other treatment types (> 1600 days). ConCluSionS: In Medicare patients ≥ 66 years with FL diagnosed between 2000-2013, slightly under one-third did not receive recommended treatment. Among those that received treatment, R-Chemo and R-alone therapies saw higher utilizations compared to all other therapy types. Patient characteristics were associated with different treatment patterns and sequencing of therapies.

Progression of invasive carcinoma involves the deregulation of molecular signaling pathways that results in the acquisition of oncogenic phenotypes. Functional enrichment analysis allows for the identification of deregulated pathways from omics scale expression data. Given the importance of post-transcriptional regulatory mechanisms on protein expression and function, identification of deregulated pathways on the basis of protein expression data is likely to provide new insights. In this study, we have developed methods for label-based mass spectrometry in a large number of samples and applied these methods toward identification and quantification of protein expression in samples of infiltrating ductal carcinoma, benign breast growths, and normal adjacent tissue. We identified 265 proteins with differential expression patterns in infiltrating ductal carcinoma relative to benign growths or normal breast tissue. Analysis of the differentially expressed proteins indicated the deregulation of signaling pathways related to proliferation, invasion and metastasis, and immune response. Our approach provides complementary information to gene expression microarray data and identifies a number of deregulated molecular signaling pathways indicative of breast cancer progression that may enable more accurate, biologically relevant diagnoses and provide a stepping stone to personalized treatment.