Affiliation:
1. State Key Laboratory of Chemical Resource Engineering College of Chemistry Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing University of Chemical Technology Beijing 100029 China
2. College of Information Science and Technology Beijing University of Chemical Technology Beijing 100029 China
3. State Key Laboratory of High‐efficiency Utilization of Coal and Green Chemical Engineering National Chemical Experimental Teaching Demonstration Center School of Chemistry and Chemical Engineering Ningxia University Yinchuan 750021 China
Abstract
AbstractPancreatic cancer is a highly malignant and metastatic cancer. Pancreatic cancer can lead to liver metastases, gallbladder metastases, and duodenum metastases. The identification of pancreatic cancer cells is essential for the diagnosis of metastatic cancer and exploration of carcinoma in situ. Organelles play an important role in maintaining the function of cells, the various cells show significant differences in organelle microenvironment. Herein, six probes are synthesized for targeting mitochondria, lysosomes, cell membranes, endoplasmic reticulum, Golgi apparatus, and lipid droplets. The six fluorescent probes form an organelles‐targeted sensor array (OT‐SA) to image pancreatic metastatic cancer cells and cell spheroids. The homology of metastatic cancer cells brings the challenge for identification of these cells. The residual network (ResNet) model has been proven to automatically extract and select image features, which can figure out a subtle difference among similar samples. Hence, OT‐SA is developed to identify pancreatic metastasis cells and cell spheroids in combination with ResNet analysis. The identification accuracy for the pancreatic metastasis cells (> 99%) and pancreatic metastasis cell spheroids (> 99%) in the test set is successfully achieved respectively. The organelles‐targeting sensor array provides a method for the identification of pancreatic cancer metastasis in cells and cell spheroids.
Funder
National Key Research and Development Program of China
Natural Science Foundation of Beijing Municipality
National Natural Science Foundation of China