Lung cancer-derived exosomes are a kind of valuable and clinically-predictable biomarkers for lung cancer, but they have the limitations in individual differences when being applied in liquid biopsy. To improve their ...Lung cancer-derived exosomes are a kind of valuable and clinically-predictable biomarkers for lung cancer, but they have the limitations in individual differences when being applied in liquid biopsy. To improve their application value and accuracy in clinical diagnosis, a dual-labelled electrochemical method is herein reported for precise assessment of lung cancer-derived exosomes. To do so, two probes are prepared for the dual labeling of exosome membrane to run DNA assembly reactions: One is modified with cholesterol and can insert into exosome membrane through hydrophobic interaction;another one is linked with programmed death ligand-1(PD-L1) antibody and can bind to exosome surface-expressing PD-L1 via specific immunoreaction. Quantum dots-tagged signal strands are used to collect respective DNA products, and produce stripping signals corresponding to the amounts of total exosome and surfaceexpressing PD-L1, respectively. A wide linear relationship is established for the quantitative determination of lung cancer-derived exosomes in the range from 103to 1010particles/m L, whereas the ratiometric value of the two stripping signals is proven to have a better diagnostic use in screening and staging of lung cancer when being applied to clinical samples. Therefore, our method might provide a new insight into precise diagnosis of lung cancer, and offer sufficient information to refiect the biomarker level and guide the personalized treatment level even at an early stage in clinic.展开更多
The cancer stem cell hypothesis provides a basis for prediction of the recurrence and risk of metastasis in breast cancer.However,the unique expression pattern of stemness markers and the presence of nonstem-like canc...The cancer stem cell hypothesis provides a basis for prediction of the recurrence and risk of metastasis in breast cancer.However,the unique expression pattern of stemness markers and the presence of nonstem-like cancer cells with varied phenotypes have brought great challenges to the characterization of breast cancer stem cells.To address these challenges,a phenotype-directed DNA nanomachine has been designed for high-accuracy labeling and in situ analysis of the stem cell-like subpopulation in breast cancer.The key for the design is to use cell surfaceanchored inputs to activate the nanomachine,which undergoes different branch migration pathways such that the signal strand can only be brought onto the cancer cells having the stem cell-like phenotype.Highly sensitive determination and single-step isolation of the stem cell-like subpopulation were achieved by incorporating functional groups into the signal strand such that the nanomachine was successfully applied in a tumor-bearing mouse model.Overall,the approach provides for a substantial improvement in capability for the analysis of the breast cancer stem cell-like subpopulation,and it is expected that the new approach will advance the use of DNA nanomachines in cancer-related studies.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 81972799, 82202834, and 81871449)。
文摘Lung cancer-derived exosomes are a kind of valuable and clinically-predictable biomarkers for lung cancer, but they have the limitations in individual differences when being applied in liquid biopsy. To improve their application value and accuracy in clinical diagnosis, a dual-labelled electrochemical method is herein reported for precise assessment of lung cancer-derived exosomes. To do so, two probes are prepared for the dual labeling of exosome membrane to run DNA assembly reactions: One is modified with cholesterol and can insert into exosome membrane through hydrophobic interaction;another one is linked with programmed death ligand-1(PD-L1) antibody and can bind to exosome surface-expressing PD-L1 via specific immunoreaction. Quantum dots-tagged signal strands are used to collect respective DNA products, and produce stripping signals corresponding to the amounts of total exosome and surfaceexpressing PD-L1, respectively. A wide linear relationship is established for the quantitative determination of lung cancer-derived exosomes in the range from 103to 1010particles/m L, whereas the ratiometric value of the two stripping signals is proven to have a better diagnostic use in screening and staging of lung cancer when being applied to clinical samples. Therefore, our method might provide a new insight into precise diagnosis of lung cancer, and offer sufficient information to refiect the biomarker level and guide the personalized treatment level even at an early stage in clinic.
基金the National Natural Science Foundation of China(grant nos.81972799 and 81871449)the Natural Science Foundation of Shanghai(grant no.23ZR1421400).
文摘The cancer stem cell hypothesis provides a basis for prediction of the recurrence and risk of metastasis in breast cancer.However,the unique expression pattern of stemness markers and the presence of nonstem-like cancer cells with varied phenotypes have brought great challenges to the characterization of breast cancer stem cells.To address these challenges,a phenotype-directed DNA nanomachine has been designed for high-accuracy labeling and in situ analysis of the stem cell-like subpopulation in breast cancer.The key for the design is to use cell surfaceanchored inputs to activate the nanomachine,which undergoes different branch migration pathways such that the signal strand can only be brought onto the cancer cells having the stem cell-like phenotype.Highly sensitive determination and single-step isolation of the stem cell-like subpopulation were achieved by incorporating functional groups into the signal strand such that the nanomachine was successfully applied in a tumor-bearing mouse model.Overall,the approach provides for a substantial improvement in capability for the analysis of the breast cancer stem cell-like subpopulation,and it is expected that the new approach will advance the use of DNA nanomachines in cancer-related studies.
