On‐chip determination of tissue‐specific metastatic potential of breast cancer cells

Abstract

Metastasis is one of the major obstacles for breast cancer patients. Limitations of current models demand the development of custom platforms to predict metastatic potential and homing choices of cancer cells. Here, two organ‐on‐chip platforms, invasion/chemotaxis (IC‐chip) and extravasation (EX‐chip) were used for the quantitative assessment of invasion and extravasation towards specific tissues. Lung, liver and breast microenvironments were simulated in the chips using tissue‐specific cells embedded in matrigel. In the IC‐chip, invasive MDA‐MB‐231, but not noninvasive MCF‐7 breast cancer cells invaded into lung and liver microenvironments. In the EX‐chip, MDA‐MB‐231 cells extravasated more into the lung compared to the liver and breast microenvironments. In addition, lung‐specific MDA‐MB‐231 clone invaded and extravasated into the lung microenvironment more efficiently than the bone‐specific clone. Both invasion/chemotaxis and extravasation results were in agreement with published clinical data. Collectively, our results show that IC‐chip and EX‐chip, simulating tissue‐specific microenvironments, can distinguish different in vivo metastatic phenotypes, in vitro. Determination of tissue‐specific metastatic potential of breast cancer cells is expected to improve diagnosis and help select the ideal therapy.

FLI1 and FRA1 transcription factors drive the transcriptional regulatory networks characterizing muscle invasive bladder cancer

“…4 ), we investigated the effect of knock-down in invasive characteristics of this MIBC cell line. To test the invasion capability of T24 cells for the knock-downs, we used IC-CHIP assay, which enables the detection of invasion ability through matrigel across different microenvironment 55 – 57 in three conditions: Positive control (10% FBS), negative control (0% FBS) and muscle microenvironment (Fig. 6a ).…”

“…While drawing boxplots, outlier data were excluded from the graphs using “geom_boxplot (outlier.shape = NA)” function in ggplot2 package 98 , source data includes outlier data too. The invasion capacity of the cells was determined through the normalization of datasets to day 0 55 for T24 and day 1 for 5637 cells. Three independent experiments were performed for each dataset.…”

FLI1 and FRA1 transcription factors drive the transcriptional regulatory networks characterizing muscle invasive bladder cancer

“…4), we investigated the effect of knock-down in invasive characteristics of this MIBC cell line. To test the invasion capability of T24 cells for the knock-downs, we used IC-CHIP assay, which enables the detection of invasion ability through matrigel across different microenvironment 36, 37, 86 in three conditions: Positive control (10% FBS), negative control (0% FBS) and muscle microenvironment (Fig. 6a).…”

“…The quantification of images was performed by Python programming and R Studio as previously described 36 . The invasion capacity of the cells was determined through normalization of datasets to day 0 37 for T24 and to day 1 for 5637 cells.…”

Recent advances in lab-on-a-chip systems for breast cancer metastasis research

“…Firatligil-Yildirir et al utilized organ-on-a-chip platforms to investigate the invasion/chemotaxis behavior of TNBC cells (Figure 5i-l). 71 The modular LOC platform allows the generation of different homing sites including lung, liver and breast microenvironments simulated in a matrigel matrix. It was shown that MDA-MB-231 TNBC cells preferred to invade the lung site compared to the liver or breast microenvironments.…”