Cancer has long been the leading cause of death among modern populations. According to statistics from the Ministry of Health and Welfare of the Republic of China (Taiwan), a total of 50,161 people died of cancer in 2020, accounting for 36.6% of all deaths (Figure 1) (Ministry of Health and Welfare, 2020).
▲ Figure 1: The top ten causes of cancer death in Taiwan, 2020
Of the fatalities caused by cancer, 18% were due to lung cancer, more than any other cancer. Therefore, it is a priority issue we aim to resolve. Upon reviewing relevant data on lung cancer, we found that this phenomenon is not unique to Taiwan. Globally, in 2020, lung cancer had the highest mortality rate among all types of cancer (Figure 2).
▲ Figure 2: 2020 Mortality rate of cancer. (World Health Organization, 2020, original data from the International Agency of Research on Cancer)
There might be two primary reasons why lung cancer causes such a severe impact: it is hard to detect in its early stages and prone to metastasize in its later stages, even after surgery.
The difficulty in early detection is mainly due to the nonspecific symptoms of early-stage lung cancer, including coughing, chest pain, and shortness of breath, which are often treated as respiratory symptoms. Thus, many lung cancer patients may only discover they have primary lung cancer when they seek medical attention for symptoms of metastatic cancer. Although the detector may not be able to identify the early stage of lung cancer cells, we can still compensate for it by promoting and educating people about healthy practices.
What's more, the critical factor making treatment difficult is the cancer's propensity for metastasis. Once lung cancer cells have spread to multiple organs, the situation becomes extremely challenging for doctors. Cancer metastasis resulting from inadequate postoperative follow-up also causes serious problems. We believe an improvement can be made by focusing on detecting lung cancer metastasis, especially the unpredictable metastasis after surgery.
An important feature of lung cancer metastasis is the appearance of circulating tumor cells (CTCs) in the blood. CTCs can leave the region where the original cancer occurred, enter the circulatory system, and metastasize to other organs. When ≥ 5 CTCs are detected in the blood, it is recognized as a high risk of cancer metastasis (Cristofanilli, M. et al. 2004).
The major way to detect CTC is to use monoclonal antibodies, which have the advantage of high specificity, and the combination of fluorescent dyes and detection devices (e.g. flow cytometry) can further enhance the sensitivity of the test. However, monoclonal antibodies also have disadvantages: the preparation, storage, and transportation of antibodies are costly, resulting in high prices of detection (Paoletti, C. et al. 2016); and the detection devices are expensive and only affordable in urban hospitals or medical examination centers, reducing the convenience of examination. These two disadvantages hinder the popularization and normalization of CTC detection.
Therefore, we carried out the CTC-FAST project to develop a more accessible and affordable CTC detection technology to closely and rapidly monitor cancer metastasis. Our goal is to detect lung cancer cell metastasis through closely monitoring the appearance of CTCs and initiating immediate treatment to reduce the high mortality rate of lung cancer.
To make CTC detection affordable, we decided to use DNA molecules to capture CTCs from blood samples. The advantages of applying DNA as a capturing platform include:
In the first design, we used four separate single-stranded DNAs (ssDNAs) to assemble a DNA tetrahedron in a complementary manner. The length of each edge is 17 bp, and the turns (endpoints of the tetrahedron) are 2 bp. One of the ssDNA has 14 extra nucleotides at the 5' terminal, which will form an overhang at one endpoint of the tetrahedron. The FA is conjugated on the adapter ssDNA complementary to this extension. This design also enables the exchange of FA with other DNA aptamers, which will allows us to modify our design to detect CTCs of other cancers in the future.
▲ Figure 3: The DNA tetrahedron with one overhang at one endpoint is formed by 4 ssDNAs (colored blue, purple, yellow, and green). The adaptor ssDNA complementary to the 5' overhang in blue ssDNA is colored pink
After assembling the DNA tetrahedron, we found that the success rate was not as expected. The separate ssDNAs have a moderate possibility to form polyhedrons through complementation between tetrahedrons. Therefore, we aim to optimize the assembly method of the DNA tetrahedron.
To minimize the possibility of polyhedron formation from separated ssDNAs, we decided to fuse the separate ssDNAs into one continuous ssDNA. These continuous ssDNAs, namely tetrahedral ssDNA, must pass through each edge of a tetrahedron twice, ultimately ending at one of the tetrahedron's vertices with a short overhang (Youli, J. et al. 2021).
In addition, this tetrahedron must be anchored on the wall of the detection chamber for CTC capture. Therefore, we immobilized the zinc finger protein (ZFP) PBSII and Zif268 onto the wall of the detection chamber and inserted the corresponding recognizing motif into the two edges furthest from the FA-conjugated endpoint to ensure the FA face points to the chamber (Conrado, R. J. et al. 2012) (Figure 4).
To release the captured CTCs from the DNA tetrahedron-folic acid, we introduced a trans-auto-splicing sequence onto the adapter ssDNA conjugated with folic acid and the DNA tetrahedron. Upon the addition of zinc ions, the trans-auto-splicing sequence self-cleaves (Figure 4).
▲ Figure 4: The design of tetrahedron formed by one single tetrahedral ssDNA.
Because it is hard for a company to generate long ssDNA with highly complementary sequences for concept confirmation, we first employed in vitro rolling circle amplification (RCA) (Li, C. et al. 2023) to generate the tetrahedral ssDNA (Please check details in design). To splice the long ssDNA into individual tetrahedral ssDNA, we flanked the tetrahedral ssDNA with a cis-auto splicing sequence (Youli, J. et al. 2021). The cis-auto splicing sequence will self-cleave after adding zinc ions (Figure 5).
▲ Figure 5: The rolling circle amplification (RCA) is applied to generate ssDNA containing multiple copies of tetrahedral ssDNA and cis-auto splicing sequence (colored blue).
However, after interviewing with professionals, we learned that RCA will generate high concentration of ssDNA, which tend to form polyhedron. To improve this condition, we decided to apply rolling circle replication (RCR) (Hao, M., et al. 2020) to generate circular tetrahedral ssDNA in the bacteria. Furthermore, to reduce the interaction between tetrahedral ssDNA, we design to co-express the ssDNA binding protein (SSB).
To activate RCR in E. Coli, we expressed the replication initiation proteins (RepA), which recognize the starting motif RCORI105 and stop motif RCORI65 and transcribes the intervening sequence into a circular ssDNA (Figure 6). The circular tetrahedral ssDNAs are protected and purified by SSB. Finally, zinc ions are added to induce the cis-auto splicing of purified circular tetrahedral ssDNAs and the assembly of tetrahedrons.
▲ Figure 6: The gene block for RCR cassette.
After interviewing immunologists, we learned that FA may also capture macrophages through the membranous FRβ (Chandrupatla et al. 2019). To distinguish CTC from macrophage, we labelled the CTC with green fluorescent protein (mGreen lantern; mGL) conjugated with a 12-mer peptide (namely C7) specifically recognizing FRα (Figure 7) (Xing et al. 2018). This mGL-4A-C7 protein could be freeze dried and stored at room temperature without significant loss of fluorescence.
▲ Figure 7: The schematic diagram of mGL-4A-C7 protein for labeling CTCs. The mGL is modified from GFP and the C7 is fused to the C-terminal of mGL by a 4A linker.
Together, we generate tetrahedral ssDNA in vivo for tetrahedron assembly and CTC capture, which makes CTC detection more affordable.
To improve the convenience of CTC detection, we decided to develop an automated device for CTC capture and subsequent quantification. The design of this device will consist of the following components, as shown in Figure 8:
▲ Figure 8: Design of the CTC detection device.
The overall detection process is as follows: First, healthcare professionals collect a 7.5ml blood sample and isolate the PBMC layer containing CTCs using the gradient density centrifugation method (i.e. Ficoll separation). The PBMCs are then injected into the PBMC chamber, and the peristaltic pump drives the isotonic solution to dilute the sample. The diluted PBMC sample is then advanced into the detection chamber by the peristaltic pump. The FA-conjugated DNA tetrahedron on the chamber walls captures CTCs and macrophages present in the blood. Uncaptured cells are washed out with the excess isotonic solution, directing them to the waste solution storage chamber.
Next, the mGL-4A-C7 fluorescent protein, capable of specifically labeling CTCs, is introduced into the detection chamber for staining. After washing away excess mGL-4A-C7 fluorescent protein with isotonic solution, the Trans-auto-splicing ssDNA is injected to degrade the DNA tetrahedron and release the stained CTCs. Finally, the CTC-containing solution is transported from the detection chamber to the CTC quantification instrument for analysis. In the quantification process, the characteristics of the microchannels help control sample flow, enhancing the accuracy and efficiency of the detection (Figure 9).
▲ Figure 9: The capture process of CTCs in our device.
The CTC quantification instrument employs a photodetector principle for detection. A laser with a wavelength of 488 nm is emitted to excite mGL-4A-C7, which then emits light at a wavelength of 503 nm. The photodetector, sensitive to the 503 nm wavelength, converts the emitted light into a specific signal intensity. Ultimately, the presence of mGL-4A-C7-labed CTCs is determined based on the specific signal intensity (Figure 10).
▲ Figure 10: Fluorescence-based based detection by photodiode.
The finished device:
Through developing the CTC-FAST device, we will effectively improve CTC detection, which could help reduce the high mortality rate of lung cancer.
To further decrease the number of deaths caused by lung cancer, we focused on lung cancer prevention. According to our street survey, we found a lack of public awareness about lung cancer, which then became our main goal for education.
We started from the idea "Medicine and food come from the same source", based on traditional Chinese medicine. We collaborated with the school cafeteria and launched the "Healthy Bento for Healthy Lungs" to reach undergraduates in our university, sharing the ingredients good for lung care.
We then decided to expand the scope to the local youth. We organized Open Lab activities, in which we introduced knowledge about the prevention and treatment of lung cancer as well as shared knowledge about synthetic biology.
Next, to reach the elderly, we organized an event titled "Have You Learned About Lungs? ~ International Lung Cancer Day Health Education Promotion.", and invited local elders. Through this event, the knowledge of lung cancer prevention and treatment can be shared with the age group with the highest risk.
Lastly, for the general public of all age groups, we distributed related cancer prevention information on social media. For our international friends, we sent postcards and included cancer prevention knowledge on the back.
We hope to improve technical issues related to lung cancer metastasis detection through CTC-FAST and, at the same time, increase public knowledge about cancer prevention and treatment through the events organized by our team, ultimately aiming to reduce the mortality rate of lung cancer.
Ministry of Health and Welfare (2021). Analysis of Mortality Statistics for the Year 2021 (Including Appendices). Retrieved May 18, 2023, from https://www.mohw.gov.tw/cp-16-70314-1.html
World Health Organization (2020). Estimated number of deaths in 2020, World, both sexes, all ages. Retrieved May 14, 2023, from
https://gco.iarc.fr/today/online-analysis-pie?v=2020&mode=cancer&mode_population=continents&population=900&populations=900&key=total&sex=0&cancer=39&type=1&statistic=5&prevalence=0&population_group=0&ages_group%5B%5D=0&ages_group%5B%5D=17&nb_items=7&group_cancer=1&include_nmsc=1&include_nmsc_other=1&half_pie=0&donut=0
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