Cells in the living microenvironment are constantly subjected to physical forces such as tensile forces, hydrostatic pressure, and shear forces. Cell perception and response to external signals is an important mechanical property of the cell's self-regulation to adapt to and respond to changes in the mechanical forces of the external environment. For example, in the tumor microenvironment, when the spatial structure, tension intensity, elastic coefficient, etc. change, cancer cells will make corresponding adjustments to change their own mechanical properties, on the one hand, by driving and adjusting the cell shape, skeleton structure and adhesion affinity, to produce specific adaptive behaviors, such as invasion, migration, etc.; on the other hand, by activating specific gene programs, changing DNA transcription in the cell nucleus, activating the corresponding signaling pathways, and ultimately triggering drug resistance mechanisms.
Understanding and studying the mechanical properties of cells is essential for cell isolation, disease diagnosis, immune status analysis, and drug screening. At present, the most commonly used methods of measuring the mechanical properties of single cells are mainly divided into two categories: 1) by manipulating a beam or cantilever to apply mechanical stimulation to cells, measuring the relevant force curves to obtain mechanical feedback from cells, including atomic force microscopy, optical tweezers, and magnetic tweezers. 2) The mechanical distribution of large cells is mapped using the substrate deformation of randomly distributed fluorescent particles, including traction force microscopy and micro-column array detection sensors. However, complex calculations and the throughput of a "1 cell/trial" determine their limited ability in large cell-based clinical analysis.
Recently, the Chang Lingqian Research Group of Beijing University of Aeronautics and Astronautics published a research paper in the Journal of Small entitled: High-throughput DNA tensioner platform for interrogating mechanical heterogeneity of single living cell.
This work ensures high-throughput cell orientation manipulation (up to 10E6 cells/chip) by accurately designing arrayed and graphical single-cell microporous array chips, which meets the requirements of population cell behavior research from the cell number and meets statistical significance. At the same time, single cells can be addressed and precisely controlled and traced, which is not achievable by conventional techniques. The bottom of the microwell is modified with a DNA tension sensor for fluorescence imaging for high-resolution imaging of cellular mechanical forces.
The DNA tension sensor can be spontaneously embedded in the cell membrane by modified cholesterol, and under the stimulation of the external environment, changes in the mechanical properties of cells are induced by the DNA tension sensor to change the hairpin structure, resulting in the separation of fluorophores and quenching groups, thereby generating a fluorescent signal. The DNA tension sensor can adjust the measured threshold value by adjusting the length and sequence of the hairpin structure, and its measurement accuracy can reach the pN level.
Figure 1 Schematic of a high-throughput DNA tension sensor platform used to study the mechanical heterogeneity of single cells
The results show that there is a clear mechanical heterogeneity between drug-resistant tumor cells and non-drug-resistant tumor cells. Compared with non-resistant tumor cells, the hardness of resistant tumor cells with certain resistance to the chemotherapy drug paclitaxel is reduced, and the fluorescence signal caused by cell mechanical force is increased. To further analyze the causes of single-cell mechanistic heterogeneity, we confirmed the underlying genetic heterogeneity between the two cell populations by single-cell RNA sequencing techniques, and the results showed a general increase in expression of VEGFA and MINK1, two genes associated with cytoskeletal remodeling in drug-resistant cells.
Subsequently, the research team downgraded the expression levels of these two genes by transfecting siVEGFA and siMINK1 into drug-resistant tumor cells. Finally, the platform detection results showed that with the downregulation of the relevant gene expression, the fluorescence signal of drug-resistant tumor cells decreased significantly, confirming that VEGFA and MINK1 were positively correlated with the mechanism of increased mechanical force of drug-resistant cells, suggesting that VEGFA and MINK1 may be involved in the mechanical regulation of tumor cells in the process of drug resistance formation.
Figure 2:Imaging and analysis of mechanical forces of drug-resistant and non-drug-resistant tumor cells
To assess the clinical application value of the platform, we collected 10 primary tumor cell samples of lung cancer tissue and 5 tumor cell samples in lung cancer pleural effusion. Tumor cells are screened for immunofluorescence staining based on tumor cell biomarker epithelial cell adhesion molecules. Subsequently, the mechanism was used to detect the mechanical properties of the screened tumor cells. By comparing the fluorescence signals of each single cell, the statistical results showed that the mechanical force of primary cells in lung cancer tissue was significantly lower than that of pleural effusion tumor cells, which is consistent with other reported results of metastatic tumor cells having higher mechanical force than non-metastatic tumor cells.
In addition, the research team used qPCR to measure the expression of VEGFA and MINK1 in 10 lung cancer tissue samples and 5 pleural effusion samples, and the expression of VEGFA and MINK1 in metastatic lung cancer cells was relatively high compared with non-metastatic tumor cells. This result confirms that the platform can effectively distinguish between non-metastatic tumor cells and metastatic tumor cells based on mechanical heterogeneity, supporting the potential of the platform in the clinical study of tumor metastasis from the perspective of cell mechanical properties.
Figure 3. Mechanical force characteristics of metastatic tumor cells versus non-metastatic tumor cells in clinical tumor cell samples
The first author of the study was Hang Xinxin, a doctoral student of Beihang Airlines, and Dr. He Shiqi and Dong Zaizai, a master's student. The first units are Beijing Biomedical Engineering High-tech Innovation Center and Beihang College of Biological and Medical Engineering. Jiang Lan, a researcher at the Beijing Institute of Genomics of the Chinese Academy of Sciences, is a co-corresponding author of the paper, who provided important assistance in identifying two key genes, VEGFA and MINK1; the patient samples in the study were provided by Peking University Cancer Hospital; and other key co-authors of the paper include Professor Ren Tianling of Tsinghua University, Professor Fan Yubo of Beihang University, and Lou Jizhong, researcher of the Institute of Biophysics of the Chinese Academy of Sciences.
Thesis Link:
https://doi.org/10.1002/smll.202106196