Experimental methods for single cell intracellular delivery are essential for probing cell signaling dynamics within complex cellular networks, such as those making up the tumor microenvironment. Here, we show a quantitative and general method of interrogation of signaling pathways. We applied highly focused near-infrared laser light to optically inject gold-coated liposomes encapsulating bioactive molecules into single cells for focal activation of cell signaling. For this demonstration, we encapsulated either inositol trisphosphate (IP3), an endogenous cell signaling second messenger, or adenophostin A (AdA), a potent analogue of IP, within 100 nm gold-coated liposomes, and injected these gold-coated liposomes and their contents into the cytosol of single ovarian carcinoma cells to initiate calcium (Ca2+) release from intracellular stores. Upon optical injection of IP3 or AdA at doses above the activation threshold, we observed increases in cytosolic Ca2+ concentration within the injected cell initiating the propagation of a Ca2+ wave throughout nearby cells. As confirmed by octanol-induced inhibition, the intercellular Ca2+ wave traveled via gap junctions. Optical injection of gold-coated liposomes represents a quantitative method of focal activation of signaling cascades of broad interest in biomedical research.
With early detection, 5-year survival rates for ovarian cancer exceed 90%, yet no effective early screening method exists. Emerging consensus suggests over 50% of the most lethal form of the disease originates in the fallopian tube. Twenty-eight women undergoing oophorectomy or debulking surgery provided informed consent for the use of surgical discard tissue samples for multispectral fluorescence imaging. Using multiple ultraviolet and visible excitation wavelengths and emissions bands, 12 fluorescence and 6 reflectance images of 47 ovarian and 31 fallopian tube tissue samples were recorded. After imaging, each sample was fixed, sectioned, and stained for pathological evaluation. Univariate logistic regression showed cancerous tissue samples had significantly lower intensity than noncancerous tissue for 17 image types. The predictive power of multiple image types was evaluated using multivariate logistic regression (MLR) and quadratic discriminant analysis (QDA). Two MLR models each using two image types had receiver operating characteristic curves with area under the curve exceeding 0.9. QDA determined 56 image type combinations with perfect resubstituting using as few as five image types. Adaption of the system for future in vivo fallopian tube and ovary endoscopic imaging is possible, which may enable sensitive detection of ovarian cancer with no exogenous contrast agents.
With early detection, five year survival rates for ovarian cancer are over 90%, yet no effective early screening method exists. Emerging consensus suggests that perhaps over 50% of the most lethal form of the disease, high grade serous ovarian cancer, originates in the Fallopian tube. Cancer changes molecular concentrations of various endogenous fluorophores. Using specific excitation wavelengths and emissions bands on a Multispectral Fluorescence Imaging (MFI) system, spatial and spectral data over a wide field of view can be collected from endogenous fluorophores. Wavelength specific reflectance images provide additional information to normalize for tissue geometry and blood absorption. Ratiometric combination of the images may create high contrast between neighboring normal and abnormal tissue. Twenty-six women undergoing oophorectomy or debulking surgery consented the use of surgical discard tissue samples for MFI imaging. Forty-nine pieces of ovarian tissue and thirty-two pieces of Fallopian tube tissue were collected and imaged with excitation wavelengths between 280 nm and 550 nm. After imaging, each tissue sample was fixed, sectioned and H&E stained for pathological evaluation. Comparison of mean intensity values between normal, benign, and cancerous tissue demonstrate a general trend of increased fluorescence of benign tissue and decreased fluorescence of cancerous tissue when compared to normal tissue. The predictive capabilities of the mean intensity measurements are tested using multinomial logistic regression and quadratic discriminant analysis. Adaption of the system for in vivo Fallopian tube and ovary endoscopic imaging is possible and is briefly described.
Abstract. Ovarian cancer is the most deadly gynecologic cancer, a fact which is attributable to poor early detection and survival once the disease has reached advanced stages. Intraoperative laparoscopic volume holographic imaging has the potential to provide simultaneous visualization of surface and subsurface structures in ovarian tissues for improved assessment of developing ovarian cancer. In this ex vivo ovarian tissue study, we assembled a benchtop volume holographic imaging system (VHIS) to characterize the microarchitecture of 78 normal and 40 abnormal tissue specimens derived from ovarian, fallopian tube, uterine, and peritoneal tissues, collected from 26 patients aged 22 to 73 undergoing bilateral salpingo-oophorectomy, hysterectomy with bilateral salpingo-oophorectomy, or abdominal cytoreductive surgery. All tissues were successfully imaged with the VHIS in both reflectance-and fluorescence-modes revealing morphological features which can be used to distinguish between normal, benign abnormalities, and cancerous tissues. We present the development and successful application of VHIS for imaging human ovarian tissue. Comparison of VHIS images with corresponding histopathology allowed for qualitatively distinguishing microstructural features unique to the studied tissue type and disease state. These results motivate the development of a laparoscopic VHIS for evaluating the surface and subsurface morphological alterations in ovarian cancer pathogenesis. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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