Additionally, image acquisition with conventional AFM is too slow to capture fast cellular morphology changes. Researchers have extensively modified the AFM system for imaging eukaryotic cells and neurons with high spatial and temporal resolution. While progress has been made over the past decades in the pursuit to optimize atomic force microscopy AFM for imaging living cells, there were still a number of limitations and technological issues that needed to be addressed before fundamental questions in cell biology could be address in living cells.
The system differs in many ways from a conventional AFM: it uses an extremely long and sharp needle attached to a highly flexible plate. The system is also optimized for fast scanning to capture dynamic cellular events.
Application of atomic force microscopy in cancer research
These modifications have enabled researchers to image living cells, such as mammalian cell lines or mature hippocampal neurons, without any sign of cellular damage. In particular, this study demonstrates the capability to track structural dynamics and remodeling of the cell surface, such as morphogenesis of filopodia, membrane ruffles, pit formation or endocytosis, in response to environmental stimulants.
An example of this capability can be visualized in movie 1, where a fibroblast is imaged before and after treatment with insulin hormone, which intensely enhances the ruffling at the leading edge of the cell. Another example is seen in movie 2, where the morphological changes of a finger-like neuronal protrusion in the mature hippocampal neuron are observed. However, studies have shown that the DSF-Cu complex has an anti-tumor effect [ ]. The stiffness and adhesion of nasopharyngeal carcinoma cells treated with DSF-Cu have been shown to be increased [ ], which suggested that DSF-Cu reduces the deformability and enhances the adhesion of these cells.
DSF-Cu may, therefore, inhibit the malignant growth and metastasis of nasopharyngeal carcinoma cells. Changes in the deformability and adhesion of cancer cells may be due to major changes in the morphology and structure of the cell surface following drug treatment. After treatment of colon cancer cells with AEE and Celecoxib, their cell surfaces became rough and severely contracted, with pseudopodia and filopodia disappearing completely [ ].
A beginner's guide to atomic force microscopy probing for cell mechanics
The morphology and ultrastructure of Hela and HepG2 cells were also changed after being treated by colchicine and cytidine, and the degree of damage to cancer cells varied with the concentration of the drugs, and the timing of their administration [ ]. These findings suggested that the surface morphology of cells can change dramatically after stimulation by drugs or bioactive compounds.
In addition, the efficacy of drugs can be judged by their effects on cell surface roughness and hardness. Prostate cancer is a malignant tumor that occurs in the prostate gland of men. Ren et al. These studies suggested that AFM can be effectively used in the screening and evaluation of anticancer drugs. The development of new anti-cancer drugs is essential for the treatment of cancer. Most of the anti-tumor drugs are cytotoxic substances.
Due to their poor specificity, they can also cause damage to human normal cells, and may cause strong adverse reactions while providing only low anti-cancer efficiency. Traditional liposomes and nanomaterials have been shown to have good biocompatibility, sustained release, and targeting after being modified and improved, and are the most attractive drug carriers.
In evaluating the physical properties and stability of liposomes, AFM is one of the most effective detection technologies [ ]. Lapatinib is a dual inhibitor that is used to treat advanced breast cancer and some other cancers [ , , ]. Carbon nanomaterials are widely used in biomedical devices and biosensors, including carbon nanoparticles CNP , carbon nanotubes CNT , and graphene, etc. One study found that carbon nanoparticles CB which were covered using BSA and surface-coupled to methotrexate methotrexate to form complexes CBM were better than methotrexate alone for inhibiting tumor cells [ ].
Surface morphological changes were found on functionalized CB and CBM, which was mainly reflected in the significant change in roughness [ ].
This indicated that CNP could be used as a nano-carrier to connect anticancer drugs with their corresponding target cells. The surface structure of these nanoparticles or nanocomposites can be quickly determined by AFM [ ], allowing for the possible function and work scope of the nano-composites to be predicted. AFM can assist in the evaluation, screening, and development of anti-cancer drugs. Therapeutic methods that can cause changes in the morphology and mechanical properties of cancer cells can be detected by AFM, which provides an aid for the diagnosis and treatment of cancer.
The distal metastasis of cancer is the cause of death in most cancer patients. Understand the differences between primary cancer cells and metastatic cancer cells is therefore critical for the diagnosis and treatment of cancer. At present, it is known that the original cancer cells and metastatic cells have different genetic maps [ , ], which can be used in clinical diagnosis. It has been shown that Raman spectroscopy can successfully distinguish between cancer and healthy cells, primitive and metastatic cancer cells, and cancerous and healthy tissues [ , , , ].
The prominent advantage of Raman spectroscopy is that it is possible to know the chemical composition of the substance [ ], which is impossible for AFM. AFM may be combined with a confocal laser scanning microscope CLSM to study the mechanical properties of individual cancer cells [ ]. In the early stage of cancer development, the mechanical properties and morphology of cells change. Researchers can detect changes in the elasticity of cancer cells using AFM and elucidate its relationship to malignancy in the early transformation process.
Alpha-enolase ENO1 is a multifunctional protein [ , ] that is not only one of the enzymes involved in glycolysis, but also a fibrinogen receptor that promotes cancer metastasis [ , , , ]. Combined use of AFM and CLSM revealed that ENO1 gene silencing made pancreatic cancer cells coarser, damaging the adhesion between cancer cells, and between cancer cells and stroma, resulting in the invasion and metastasis of pancreatic cancer cells [ ].
Cervical cancer is the second most common cancer in women [ ]. Accurate and early diagnosis can reduce costs, greatly benefiting patients. It also provides advantages over scanning electron microscopy SEM imaging, allowing for high-resolution 3D imaging, with faster sample preparation, and determining the unique mechanical properties of cells. Multiple forms of detection are more accurate than those provided by a single format test. The imaging diagnosis of cervical carcinoma cells with AFM and SEM has the advantages of fast detection, easy operation, low cost, and so on [ ].
However, with AFM, work area selection is very blind, and the work area itself is very limited. Scanning can only be done on the micrometer scale, and it is very difficult to scan larger sample surfaces. Utilizing the large-scale search capabilities of SEM to find and target features or areas of interest that need to be studied by AFM can greatly improve the efficiency of analyses. This system can also be used to detect and diagnose other cancers. The World Health Organization classifies astrocytomas based on the microscopic appearance of tumors [ ].
However, the details of the complex morphology vary according to the specific tumor and patient, and the final classification has to be determined by an experienced pathologist. Therefore, in order to make the classification more accurate, more objective criteria need to be determined.
The combined use of AFM imaging and Data Mining Techniques to classify brain tumors is a recently-developed method, achieving Patients with stage II tumors can quickly be diagnosed using this method, reducing their risk of cancer metastasis. AFM imaging and mechanical measurement techniques have been widely used in the biomedical field, and allows for the determination of cell structure and function from level of single molecules to that of individual cells. These methods can be used to differentiate between cancer and normal cells at the single-cell level, and enables visual drug research.
No technology lacks drawbacks, and AFM technology does have limitations, but its use in combination with other complimentary technologies is a developing trend and is expanding the use of AFM. The mechanical properties of cells can be used as a new diagnostic physical biomarker to supplement traditional tissue detection [ ]. However, there are still many problems to be solved before the application of AFM technology can be fully realized in practice for example, in the diagnosis of cancer. The usage efficiency and the temporal resolution should be improved.
At present, AFM measurement of cells mainly depends on manual operation, including manual control of the probes to target cells, manual parameter setting to obtain cell force curves, and manual offline processing of experimental data. This leads to very low experimental efficiency, and it takes several minutes to take a measurement of a cell [ 8 ]. In particular, in order to obtain statistically significant conclusions, many cells need to be measured, which results in a large workload, and limits the practical application of AFM at the single cell level.
This has made it difficult to monitor changes in the mechanical properties of cells in real time. High-speed AFM can also be used for imaging of mammalian cells [ ]. The standardization of AFM measurements is another requirement. The results of different studies can only be compared when the conditions are in full agreement, and it is difficult for researchers to maintain identical experimental conditions.
Therefore, in order to make the measurement results of different research groups comparable, the measurement process needs to be standardized, as does sample treatment. For clinical and practical applications, multiple clinical cases are needed to verify the reliability of mechanical property detection. Sample preparation and AFM measurements need to be standardized, and the relative values characteristic of cancer cells and normal cells need to be determined.
Some studies directly measure the mechanical properties of the original cancer tissue, which allows for detection of the different stages of tumor metastasis [ , ]. However, tumor tissue includes cancerous cells, normal cells, blood vessels, and extracellular matrix [ ], which means that such measurements describe the mechanical properties of the local tissue, and not of isolated cancer cells. The most difficult part of the measurement is to determine the contribution of each component to the mechanical properties of cancerous tissue.
Studies have shown that other non-tumor cells in tumor tissues also affect the development and metastasis of tumors [ ]. In addition, tumor tissue is highly heterogeneous, with differences manifesting in different tumor tissues as well as in different parts of the same tissue [ ]. Therefore, tumor tissues in different locations may have different mechanical properties, and different parts of the tissue need to be extracted for comparative detection.
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