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Liquid biopsy has shown significant research and clinical implications in cancer. Particularly, the isolation of circulating tumor cells (CTCs) in preclinical studies can provide crucial information about disease progression and therefore may guide treatment decisions. Microfluidic isolation systems have played a considerable role in CTC isolation for cancer studies, disease diagnosis, and prognosis. CTCs are often studied using preclinical animal models such as xenografts or syngeneic models. However, most isolation systems are tested on human cell lines and human blood, whereas less validation studies are done on preclinical samples such as CTCs from mouse models. Here, we demonstrate and evaluate a complete workflow of a sized‐based inertial microfluidic device to isolate CTCs from blood using exclusively mouse blood and mouse cancer cell lines. We then incorporate the cytospin, a commonly used method for enumeration of small number of cells in a glass slide to quantify the total cell yield of our workflow.
Liquid biopsy has shown significant research and clinical implications in cancer. Particularly, the isolation of circulating tumor cells (CTCs) in preclinical studies can provide crucial information about disease progression and therefore may guide treatment decisions. Microfluidic isolation systems have played a considerable role in CTC isolation for cancer studies, disease diagnosis, and prognosis. CTCs are often studied using preclinical animal models such as xenografts or syngeneic models. However, most isolation systems are tested on human cell lines and human blood, whereas less validation studies are done on preclinical samples such as CTCs from mouse models. Here, we demonstrate and evaluate a complete workflow of a sized‐based inertial microfluidic device to isolate CTCs from blood using exclusively mouse blood and mouse cancer cell lines. We then incorporate the cytospin, a commonly used method for enumeration of small number of cells in a glass slide to quantify the total cell yield of our workflow.
Although significant progress in the treatment of breast cancer has been achieved, toxic therapies would not be required if breast cancer could be prevented from developing in the first place. While breast cancer prevention is difficult to study in humans due to long disease latency and stochastic cancer development, transgenic mouse models with 100% incidence and defined mammary tumor onset, provide excellent models for tumor prevention studies. In this study, we used Neu/Erbb2 transgenic mice (MTB‐TAN) as a model of human HER2+ breast cancer to investigate whether a family of microRNAs, known as the miR‐200 family, can prevent mammary tumor development. Overexpression of Neu induced palpable mammary tumors in 100% of the mice within 38 days of Neu overexpression. When the miR‐200b/200a/429 cluster was co‐overexpressed with Neu in the same mammary epithelial cells (MTB‐TANba429 mice), the miR‐200b/200a/429 cluster prevented Neu from inducing mammary epithelial hyperplasia and mammary tumor development. RNA sequencing revealed alterations in the extracellular matrix of the mammary gland and a decrease in stromal cells including myoepithelial cells in Neu transgenic mice. Immunohistochemistry for smooth muscle actin confirmed that mammary epithelial cells in control and MTB‐TANba429 mice were surrounded by a layer of myoepithelial cells and these myoepithelial cells were lost in MTB‐TAN mice with hyperplasia. Thus, we have shown for the first time that elevated expression of miR‐200 family members in mammary epithelial cells can completely prevent mammary tumor development in Neu transgenic mice possibly through regulating myoepithelial cells.
Breast cancer detection and differentiation of breast tissues are critical for accurate diagnosis and treatment planning. This study addresses the challenge of distinguishing between invasive ductal carcinoma (IDC), normal glandular breast tissues (nGBT), and adipose tissue using electrical impedance spectroscopy combined with Gaussian relaxation-time distribution (EIS-GRTD). The primary objective is to investigate the relaxation-time characteristics of these tissues and their potential to differentiate between normal and abnormal breast tissues. We applied a single-point EIS-GRTD measurement to ten mastectomy specimens across a frequency range f = 4 Hz to 5 MHz. The method calculates the differential ratio of the relaxation-time distribution function Δ γ between IDC and nGBT, which is denoted by Δ γ IDC − nGBT , and Δ γ between IDC and adipose tissues, which is denoted by Δ γ IDC − adipose . As a result, the differential ratio of Δ γ between IDC and nGBT Δ γ IDC − nGBT is 0.36, and between IDC and adipose Δ γ IDC − adipose is 0.27, which included in the α -dispersion at τ peak 1 = 0.033 ± 0.001 s . In all specimens, the relaxation-time distribution function γ of IDC γ IDC is higher, and there is no intersection with γ of nGBT γ nGBT and adipose γ adipose . The difference in γ suggests potential variations in relaxation properties at the molecular or structural level within each breast tissue that contribute to the overall relaxation response. The average mean percentage error δ for IDC, nGBT, and adipose tissues are 5.90%, 6.33%, and 8.07%, respectively, demonstrating the model’s accuracy and reliability. This study provides novel insights into the use of relaxation-time characteristic for differentiating breast tissue types, offering potential advancements in diagnosis methods. Future research will focus on correlating EIS-GRTD finding with pathological results from the same test sites to further validate the method’s efficacy.
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