Team:CSMU Taiwan/Poster

Poster: CSMU_Taiwan



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miRNA.DOC: A novel detection method for Oral Cancer

Presented by team CSMU_Taiwan 2020


Cheng-Yang, Ma1, Yi-Ching, Chen1, Hung-Yu, Chen1, Huan-Jui, Chang1, Dai-Rou, Lee1, Hung-Liang, Pai1, Tzu-Hsuan, Hsiao1, Matilda, Key1, Cheng-Ruei, Yang1, Hsin-Jung, Lee2, Kuan-Lin, Chen2, Ting-Yu, Lin2, Ting-Yu, Lin2, Shao-Chi, Lo2, Ho-Lo, Huang2, Shen-Lin, Chen2, Kuo-Chen, Huang2, Dr. Yu-Fan, Liu3


1iGEM Student Team Member, 2iGEM Team Advisor, 3iGEM Team PI


Abstract

Inspection and palpation are the two main ways for doctors to determine whether they would take a biopsy test or not when doctors suspect that their patients get oral cancer.1 Inspection and palpation may have detection bias and largely depends on the experience and judgment of the doctor. Therefore, iGEM CSMU_Taiwan developed a new oral cancer detection method, miRNA.DOC, to deal with this problem. We adapted the "Toehold Switch" technique and a glucometer to create a novel detection device.2 Those toehold switches we designed would detect miRNAs in human saliva and it will allow the reporter protein, invertase, to be translated. Invertase would break down sucrose into glucose and fructose. After that, the glucometer would be used to measure the concentration of glucose and present quantitative data for the patients' oral condition. We successfully found the best two toehold switches, zr31 and zr146_A, from all the 21 toehold switches we design after testing their ON/OFF ratios, sensitivities, and specificities. Then we measured the glucose concentration under different amounts of the miRNA triggers and verified the positive correlation between the glucose concentration and the amount of those triggers. With the regression curve formulas, we can measure the amount of the miRNA from the glucometer readouts. With miRNA.DOC, we hope to provide a quantitative, non-invasive, and accessible method for oral cancer detection. By using this product, patients can be diagnosed earlier, recover sooner, and move one step closer to good health.

Introduction

Oral Cancer

According to WHO, oral cancer is all malignancies arising in the soft tissues of the lip, tongue and elsewhere in the oral mucous membranes. It's the eighth most common cancers of the world. The global incidence rate is about 1.5 per 100,000 people. While in Taiwan, it is 33.6, which is about 22 times higher. The relatively high prevalence of oral cancer is mainly because a high-risk group of the community exists, who exhibit habits of betel nut chewing.

The average death age is 56 years old, which is 10 years less than other kinds of cancer. On top of that, oral cancer often has a diagnostic delay. An even more concerning issue is the increasing amount of cases each year. The yearly confirmed cases have doubled over the past ten years in Taiwan. Therefore, we can see that oral cancer is a local and serious problem in Taiwan.

The Problem

According to the research of WHO, oral cancer is having high cure rates when detected early and treated with best practices. However, the current detection method and diagnosis process are biased and have some problems. As Dr Yu-Feng Huang in CSMU said," There exist problems in current detection method due to the detection bias."

The current detection method for oral cancer is mainly dependent on visual examinations. Dentist or ENT doctor can utilize visual examination and palpation to observe if there is any prodrome of oral cancer, such as white and red patch and long-term ulcers. When those oral potentially malignant disorders (OPMD) lesions are observed, those patients will be referred for a biopsy to confirm its malignancy. But, on average, there is only one OSCC case confirmed out of nine biopsies. These indicate that the current detection method is biased and relies heavily on experience. In other words, the results may vary a lot according to different people conducting the process.

Toehold Mechanism

Toehold switch is a lock that can repress the expression of the reporter protein. Correspondingly, our targeted RNA sequence serves as a key to open the lock.

Toehold switch is mainly composed of three parts, the trigger binding site (TBS) that is complementary to a target RNA sequence, a hairpin loop containing the ribosomal binding site (RBS), and a linker sequence that connects the toehold structure with the protein-coding sequence. [2]

When the targeted RNA sequence binds to the trigger binding sites, it unwinds the lower and upper stem. The RBS and start codon are exposed. Thus, the ribosome can attach to the start codon and translate the reporter protein sequence.

Biomarker

Our Goal - Choice of Biomarkers for Detecting OSCC


Among several potential biomarkers for detection of OSCC, we chose to examine salivary miRNA 21, 31, and 146 due to their relative ease of collection, validated diagnostic accuracy, and prospects of detecting OSCC early on.

Finding our Biomarkers - miRNAs


In our search of suitable biomarkers for detecting OSCC, we consulted professor Cheng-Chia, Yu, an expert in the field of OSCC rapid screening, and gained valuable insight on our considerations on selecting biomarkers. Professor Yu told us: "It's important to consider whether your biomarkers can distinguish between different stages of oral cancer and their convenience for detection." He further suggested us to choose upregulated miRNAs due to their detection convenience, and select biomarkers that can distinguish patients at different stages. Therefore, we focused our attention on selecting miRNAs which are upregulated in OSCC patients.

Salivary miRNAs - Diagnostic advantages on OSCC


miRNAs play an important role in the post-transcriptional regulation of tumour development, and the alteration of miRNAs in cancer cell illustrates its possibility to become biomarkers for detecting cancer [3]. In the context of OSCC, the dysregulated cell-free miRNAs may be released from the apoptosis or necrosis of cancerous tissue in the oral cavity [3]. Saliva can preserve this dysregulated profile of miRNAs due to the encapsulation of miRNAs in extracellular bodies and the direct contact of salivary miRNAs with oral cancer tissue [4]. Furthermore, the collection and analysis of saliva represent a cost-effective way for cancer screening [4]. As a result, salivary miRNAs encompass the diagnostics potential of miRNAs and the accessibility of saliva, making it a compelling biological sample for detecting OSCC.

Three Selected miRNAs - Improve the Efficacy of Detecting OSCC


Between multiple candidates of salivary miRNAs, we picked miRNA 21, 31, and 146 for their validated properties and diagnostic accuracy on early detection of OSCC. Specifically saying, miRNA 21 and 31 are capable of detecting OPMD (Oral Potentially Malignant Disease) which acts as a predictor of developing OSCC [5,6]. On the improvement of diagnostic accuracy, miRNA 146 possesses high sensitivity and specificity on detecting OSCC [7]. Additionally, with 9.84 fold of upregulation, miRNA 31 can discriminate OSCC patients from healthy individuals with significant differential expression [6]. Consequently, we hope that the incorporation of 3 different miRNAs can effectively improve the robustness for our OSCC detection system.

Toehold Design

Initially, we designed our toehold switches based off of Wang et al.'s (2019)[8]. They have designed a toehold switch for miRNA 21 which is also one of the miRNAs that we plan to detect. However, we were still having trouble with designing our own version of the toehold switch as the analysis with NUPACK showed unoptimal results. Therefore, we consulted with Alexander Green from Arizona State University and he advised us to design the toehold switch based off of one of his more recent studies on toehold switch for ZIKA virus (2016)[9].
We split the design of toehold switches into three sections:
  1. Trigger binding site
    The trigger binding site (TBS) was solely designed upon reverse translating the sequence.
  2. Loop
    We looked at one of Green’s[9] and Wang’s paper for our choice of design. In the paper, he designed two seperate loop structures and tested their effects on the ON/OFF ratio.
  3. Linker
    We adapted linkers from Green, Wang, and our randomization.
After they were put together, we ran NUPACK to ensure the spontaneous formation of the secondary structure at 37 degrees Celsius and Vienna RNA Package to predict the interaction between our trigger and the toehold switch. Figure 1. This is the result from NUPACK for one of our designs, it shows spontaneous formation and proper secondary structure for the loop.
Figure 2. This is the result from Vienna RNA package for the same design as the figure above. The black line in the figure indicates the amount of energy required to open the secondary structures of the TBS. The line red indicates the amount of energy required to open the secondary structure after the binding of the trigger.

Reporter

Reporter protein selection


Invertase, also called β-D-fructofuranosidase, is an enzyme for the hydrolysis of sucrose into glucose and fructose. It is commonly used as reporter proteins since its product, glucose, can be easily detected with a personal glucose meter (PGM)[10], which has a high utilization rate in the public. According to the previous research, Thermotoga maritima Invertase (invertase from Thermotoga maritima) (TmINV) has been proven to have high activity and thermo-stability compared to the commonly used commercial yeast invertase.[11] Thus, we chose it to be our reporter protein.

Invertase activity test


We used both models and experiments to test the activity of invertase. For the modeling, we used MATLAB to create a model for kinetic investigations of the enzymatic reactions. As for the wet lab experiments, we produced the invertase with the PURExpress protein synthesis kit. Then we measured its reaction velocity under different sucrose concentrations. The result of the model and the experiment is shown below.

Figurex. The initial velocity of the invertase enzymatic reaction under different sucrose concentrations. The green line refers to the regression curve of experimental data, and the blue line refers to the invertase activity model.

The initial velocity of the reaction increases as the concentration of the substrate, sucrose, rises. The trend of experimental data fitted our model.

Experiment

For each kind of oral cancer-related miRNA, we have designed several toehold switches to detect it. With a series of experiments, we could select the best one for each miRNA and further tested its functionality. Here are our selection criteria for toehold switch:
  1. High ON/OFF ratio. The protein expression should be high in the ON state (with trigger) and low in the OFF state (without trigger).
  2. High sensitivity. The ultimate glucose signal should be high enough so that a small number of miRNAs can also be detected.
  3. High specificity. The toehold structure should only be opened by its specific trigger. In other words, the ON/OFF ratio of the non-specific miRNAs should be close to 1.
The plasmids of the toehold switches would be transcribed and translated with the PURExpress® In Vitro Protein Synthesis Kit (New England Biolabs) at 37℃ for 2 hours. Afterward, we would add 5μl of 0.5M sucrose, and measured the glucose concentration with Bionime Rightest™ GM550 glucose meter after 30 minutes of enzymatic reaction time.
In our experiments, the ON state refers to the conditions with the miRNA triggers; while the OFF state means that there was no miRNA in the environment. We calculated the ON/OFF ratio of the toehold switch, which is defined below:
By measuring the ON/OFF ratios and the glucose concentration values in the ON state, we could find out the most sensitive toehold for microRNA detection.
Moreover, we used miR-191 and miR-233 for our negative selection, which are highly expressed in saliva[12], to see whether our toehold switches would be accidentally turned on by the unrelated miRNA. By comparing the ON/OFF ratios of the specific microRNA with which of the non-related ones, we could find out the most specific toehold switch.
With a systematic evaluation with ON/OFF ratio, sensitivity, and specificity, we could select the best toehold switches for detecting miR-21, miR-31, and miR-146.
For the best toehold switches, we further conducted a quantitative examination on them. We measured the glucose concentrations under different amounts of the miRNA trigger. Understanding the correlation between the two, we can measure the amount of miRNA from the glucose meter readouts and further build up a quantitative system for oral cancer detection.

Result

To select the best toehold switches for detecting miR-21, miR-31, and miR-146, we have carried out a functional test for each toehold switch.
The figure shows the glucose productions of the toehold switches in different states. The blue bar refers to the OFF state (not added with miRNA); the green bar refers to the ON state (added with the specific trigger); the yellow bar refers to the state with non-related RNAs (added with miR-191); the pink bar refers to the state with non-related RNAs (added with miR-223). The ON/OFF ratio of each toehold switch with target microRNAs were listed below. As shown, most of the toeholds had high ON/OFF ratios and great sensitivities, as the glucose concentrations in the ON state are much higher than that in the OFF state. However, the results of the toehold switches for miR-21 detection were different from our expectation, thus we abandon them in further experiments. As for the specificity, most of the ON/OFF ratios with the non-related microRNAs were close to 1, which means the toehold switches had great specificity to their own target microRNAs.
After a systematic evaluation with ON/OFF ratio, sensitivity, and specificity, we found that zr31 (BBa_K3431023) and zr146_A (BBa_K3431027) are the best toehold switches for miR-31 and miR-146 detection. Therefore, we further conducted a quantitative examination on them.
The glucose production of zr31 and zr146_A in the environment with different amounts of miRNA. As shown, the glucose concentration rises as the amount of the trigger increases, suggesting a positive correlation.

Future

Experiment


  • Validating freeze-drying
    • We will prove it feasible to freeze-dry the reagents and our designed toehold switches onto the wall of the reaction tube. Also, we need to make comparisons with our current method to modify the required volume of each reagent or reaction time.

  • Salivary Purification and RNA amplification
    • We will design and conduct experiments on salivary purification and RNA amplification to pretreat samples from every patient for quality control and also enable our designed toehold switches to detect miRNAs in saliva.

  • Finding threshold of the expression of miRNAs
    • We need to collect samples from oral cancer patients with different stages of the disease and conduct experiments to find out the threshold of the expression of miRNAs for each stage. These thresholds help doctors know how serious patients' health conditions are and thus enhance current medical practices.

Application


  • Hospital and clinics
    • Doctors in the hospital and clinics can use miRNA.DOC to deduce the amount of miRNA from the data shown on the glucometer and have a more objective screening process for better diagnostics.

  • High-risk group's workplace
    • Doctors can bring miRNA.DOC to high-risk group's workplace and use miRNA.DOC to screen for the workers who fail to go see a doctor due to busy work or fear of being diagnosed with oral cancer.

  • Home screening
    • We should put more effort to simplify the process of miRNA.DOC and establish a more systematic approach for patients, allowing doctors and patients to document the result from every test and strengthen the monitoring and tracking of oral cancer.

Commercialization

Human Practices

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