In-situ cryo-immune engineering of tumor microenvironment with cold-responsive nanotechnology for cancer immunotherapy.

Cancer immunotherapy that deploys the host's immune system to recognize and attack tumors, is a promising strategy for cancer treatment. However, its efficacy is greatly restricted by the immunosuppressive (i.e., immunologically cold) tumor microenvironment (TME). Here, we report an in-situ cryo-immune engineering (ICIE) strategy for turning the TME from immunologically "cold" into "hot". In particular, after the ICIE treatment, the ratio of the CD8+ cytotoxic T cells to the immunosuppressive regulatory T cells is increased by more than 100 times in not only the primary tumors with cryosurgery but also distant tumors without freezing. This is achieved by combining cryosurgery that causes "frostbite" of tumor with cold-responsive nanoparticles that not only target tumor but also rapidly release both anticancer drug and PD-L1 silencing siRNA specifically into the cytosol upon cryosurgery. This ICIE treatment leads to potent immunogenic cell death, which promotes maturation of dendritic cells and activation of CD8+ cytotoxic T cells as well as memory T cells to kill not only primary but also distant/metastatic breast tumors in female mice (i.e., the abscopal effect). Collectively, ICIE may enable an efficient and durable way to leverage the immune system for combating cancer and its metastasis.

Greatly Enhanced CTC Culture Enabled by Capturing CTC Heterogeneity Using a PEGylated PDMS-Titanium-Gold Electromicrofluidic Device with Glutathione-Controlled Gentle Cell Release.

The circulating tumor cells (CTCs, the root cause of cancer metastasis and poor cancer prognosis) are very difficult to culture for scale-up in vitro, which has hampered their use in cancer research/prognosis and patient-specific therapeutic development. Herein, we report a robust electromicrofluidic chip for not only efficient capture of heterogeneous (EpCAM+ and CD44+) CTCs with high purity but also glutathione-controlled gentle release of the CTCs with high efficiency and viability. This is enabled by coating the polydimethylsiloxane (PDMS) surface in the device with a 10 nm gold layer through a 4 nm titanium coupling layer, for convenient PEGylation and linkage of capture antibodies via the thiol-gold chemistry. Surprisingly, the percentage of EpCAM+ mammary CTCs can be as low as ∼35% (∼70% on average), showing that the commonly used approach of capturing CTCs with EpCAM alone may miss many EpCAM- CTCs. Furthermore, the CD44+ CTCs can be cultured to form 3D spheroids efficiently for scale-up. In contrast, the CTCs captured with EpCAM alone are poor in proliferation in vitro, consistent with the literature. By capture of the CTC heterogeneity, the percentage of stage IV patients whose CTCs can be successfully cultured/scaled up is improved from 12.5% to 68.8%. These findings demonstrate that the common practice of CTC capture with EpCAM alone misses the CTC heterogeneity including the critical CD44+ CTCs. This study may be valuable to the procurement and scale-up of heterogeneous CTCs, to facilitate the understanding of cancer metastasis and the development of cancer metastasis-targeted personalized cancer therapies conveniently via the minimally invasive liquid/blood biopsy.

Methods of Generating Dielectrophoretic Force for Microfluidic Manipulation of Bioparticles.

Manipulation of microscale bioparticles including living cells is of great significance to the broad bioengineering and biotechnology fields. Dielectrophoresis (DEP), which is defined as the interactions between dielectric particles and the electric field, is one of the most widely used techniques for the manipulation of bioparticles including cell separation, sorting, and trapping. Bioparticles experience a DEP force if they have a different polarization from the surrounding media in an electric field that is nonuniform in terms of the intensity and/or phase of the electric field. A comprehensive literature survey shows that the DEP-based microfluidic devices for manipulating bioparticles can be categorized according to the methods of creating the nonuniformity via patterned microchannels, electrodes, and media to generate the DEP force. These methods together with the theory of DEP force generation are described in this review, to provide a summary of the methods and materials that have been used to manipulate various bioparticles for various specific biological outcomes. Further developments of DEP-based technologies include identifying materials that better integrate with electrodes than current popular materials (silicone/glass) and improving the performance of DEP manipulation of bioparticles by combining it with other methods of handling bioparticles. Collectively, DEP-based microfluidic manipulation of bioparticles holds great potential for various biomedical applications.

Deep Learning-Enabled Label-Free On-Chip Detection and Selective Extraction of Cell Aggregate-Laden Hydrogel Microcapsules.

Microfluidic encapsulation of cells/tissues in hydrogel microcapsules has attracted tremendous attention in the burgeoning field of cell-based medicine. However, when encapsulating rare cells and tissues (e.g., pancreatic islets and ovarian follicles), the majority of the resultant hydrogel microcapsules are empty and should be excluded from the sample. Furthermore, the cell-laden hydrogel microcapsules are usually suspended in an oil phase after microfluidic generation, while the microencapsulated cells require an aqueous phase for further culture/transplantation and long-term suspension in oil may compromise the cells/tissues. Thus, real-time on-chip selective extraction of cell-laden hydrogel microcapsules from oil into aqueous phase is crucial to the further use of the microencapsulated cells/tissues. Contemporary extraction methods either require labeling of cells for their identification along with an expensive detection system or have a low extraction purity (<≈30%). Here, a deep learning-enabled approach for label-free detection and selective extraction of cell-laden microcapsules with high efficiency of detection (≈100%) and extraction (≈97%), high purity of extraction (≈90%), and high cell viability (>95%) is reported. The utilization of deep learning to dynamically analyze images in real time for label-free detection and on-chip selective extraction of cell-laden hydrogel microcapsules is unique and may be valuable to advance the emerging cell-based medicine.