Difference between revisions of "Team:CLSB-UK"

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About 90% of lung cancers are caused by smoking and as smoking rates have declined, there has been a corresponding reduction in incidence of lung cancers.<ref> (n.d.). Lung cancer: diagnosis and management - NICE. Retrieved October 7, 2017, from https://www.nice.org.uk/guidance/cg121/chapter/introduction</ref> However, nearly 30% of the global  population are still estimated to smoke.<ref name="gopal">Gopal, M., Abdullah, S. E., Grady, J. J., & Goodwin, J. S. (2010). Screening for lung cancer with low-dose computed tomography: a systematic review and meta-analysis of the baseline findings of randomized controlled trials. Journal of thoracic oncology, 5(8), 1233-1239.</ref>
 
About 90% of lung cancers are caused by smoking and as smoking rates have declined, there has been a corresponding reduction in incidence of lung cancers.<ref> (n.d.). Lung cancer: diagnosis and management - NICE. Retrieved October 7, 2017, from https://www.nice.org.uk/guidance/cg121/chapter/introduction</ref> However, nearly 30% of the global  population are still estimated to smoke.<ref name="gopal">Gopal, M., Abdullah, S. E., Grady, J. J., & Goodwin, J. S. (2010). Screening for lung cancer with low-dose computed tomography: a systematic review and meta-analysis of the baseline findings of randomized controlled trials. Journal of thoracic oncology, 5(8), 1233-1239.</ref>
  
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Revision as of 22:27, 15 October 2017

Project BATMAN

a new way to detect cancer using toehold switches

Late presentation and non-specific symptoms are the main
reasons 1.6 million people worldwide die from lung cancer every year

Dr Sujal Desai, Consultant Chest Radiologist

We have developed a new way to detect cancer at an early stage by measuring micro-RNAs (miRNAs), biomarkers found in blood. We use toehold switches to regulate expression of GFP in response to specific miRNAs. This method could be applied to a myriad of diseases, but we have chosen to use non-small cell lung cancer (NSCLC) as a proof of concept. We hope our work in NSCLC detection demonstrates the potential that toehold switches have to offer as a cheap and effective diagnostic tool.

Biomarkers in the blood

Abnormal levels of miRNAs mir-15b-5p and mir-27b-3p in blood serum are indicative of NSCLC[1]. We have designed two sequence-specific sensors that utilise synthetic riboregulators called toehold switches. These toehold switches detect mir-15b-5p and mir-27b-3p and produce fluorescent reporter proteins in their presence. We designed our sensors to work in a cell-free system, allowing them to be used safely and in a low-tech environment.

Non-small cell lung cancer

Lung cancer is the most common cause of cancer-related mortality, with 1.6million deaths in 2012. That’s 20% of all reported deaths due to cancer. Non-small cell lung cancer (NSCLC) makes up ~80% of all incidences of lung cancer.[2] 58% of all cases in 2012 were reported in less developed countries.[3]

NSCLC is characteristically aggressive and pathologically diverse.[4] Common subtypes include pulmonary adenocarcinoma (~50%) and squamous cell carcinoma (~40%). The classification of the original tumour will impact prognosis and treatment. Treatment still centres around cytotoxic chemotherapy, although new treatments show promise including immunotherapies.[5][2]

NSCLC’s high mortality rate is, in large part, down to the late stage at which the disease is normally diagnosed.[6] This often renders surgery, which can curative in early stages, pointless as the tumour has metastasised.[7][8]

About 90% of lung cancers are caused by smoking and as smoking rates have declined, there has been a corresponding reduction in incidence of lung cancers.[9] However, nearly 30% of the global population are still estimated to smoke.[10]

Late diagnosis kills

Non-small cell lung cancer 5 year survival rates by stage

Stage IA IB IIA IIB IIIA IIIB IV
Survival 49% 45% 30% 31% 14% 5% 1%

Non-small cell lung cancer (NSCLC) has low 5-year survival rates due to late presentation of symptoms, quick tumour progression and high probability of metastasis.[11] Late diagnosis renders surgery, which can curative in early stages, pointless as the tumour has metastasised.[12][13]

Micro-RNA (miRNA)

Micro-RNAs (miRNAs) can act as potent biomarkers for a myriad of diseases.

MiRNAs are short non-coding RNAs of 19-24 nucleotides in length. They are involved in regulating the post-transcriptional silencing of protein-coding genes in eukaryotes[14][15][16]. MiRNAs can be found extracellularly in various body fluids, including serum[17][1], plasma[18], saliva[19], urine[20] and breast milk[21]. It has been hypothesised that cells actively secrete miRNAs via two pathways: in microvesicles and bound to RNA binding proteins.[22]

RNA binding proteins and microvesicles shield circulating miRNAs from ribonuclease degradation in body fluids.[22] Furthermore, they’re capable of delivering the miRNAs to recipient cells.[23][24][21] These miRNAs can then trigger downstream signalling events, indicating that circulating miRNAs play a role in cell-to-cell communication.[24][21][25]

Recent studies have also shown that differential levels of miRNAs in body fluids are indicative of specific diseases, including many forms of cancer[1][18][20][26]. MiRNA stability, accessibility by non-invasive methods (liquid biopsy) and their ability to diagnose diseases in early stages provides strong evidence that circulating miRNAs are potent biomarkers[27]. Microarrays and qPCR are typically used to quantify circulating miRNAs. However, primer design for qPCR is difficult and microarrays are complicated and expensive to prepare.


Toehold switches

Toehold switches are synthetic riboregulators that control gene expression post transcriptionally. They are hairpin loops found in the 5’ region of mRNA that can switch between two configurations - one which promotes and one which represses translation based on the presence or absence of a cognate RNA.

Initially the start codon is surrounded by a strong secondary structure. This significantly reduces translational efficiency,[28][29] so translation is repressed. Activation of translation occurs upon the binding of a trigger RNA to a region of the toehold switch called the trigger binding site. Trigger RNA binding begins at the toehold region, which is a linear sequence at the 5’ end of the toehold switch. The trigger RNA then completes a branch migration with the stem of the hairpin loop, thus relieving the secondary structure around the start codon and activating translation.

Initially the start codon is surrounded by a strong secondary structure - the hairpin stem. As the ribosome cannot melt the stem, translation of a fluorescent reporter protein coding sequence is repressed.


Play animation

When a trigger RNA binds to the toehold region (a linear sequence at the 5’ end of the switch) it undergoes a branch migration with the lower part of the stem. This relieves the secondary structure around the start codon. The ribosome bound to the RBS can then melt the remaining stem


Next

This activates translation and fluorescence from the reporter protein can be observed.


Reset

Previous riboregulators have relied on base pairing to the RBS to prevent ribosome binding.[30][31][32] For these the trigger RNA must contain the RBS sequence to displace the sequence bound to the RBS, dramatically reducing programmability of the trigger RNA. However, the trigger RNA for a toehold switch has very few sequence constraints due to the lack of base pairing to the RBS and start codon (as strand displacement does not occur in the regions which have fixed sequences).

Furthermore, in previous riboregulators trigger RNA binding is initiated in the short loop domain of the hairpin module.[30][31][33] Subsequently, the binding thermodynamics in previous riboregulators are not as favourable as the toehold switch’s because toehold switches have longer linear trigger binding regions. This increases the probability of spontaneous trigger RNA dissociation and reduces the likelihood of successful strand displacement of the RBS from the incumbent sequence bound to it in previous riboregulators in previous riboregulators.[34] The dynamic range of previous riboregulators has therefore been limited to a maximum of 55 fold[30], whereas toehold switches display a mean dynamic range of over 400 fold[35]. The large dynamic range that toehold switches offer allows for low concentrations of miRNAs to be detected.

We used toehold switches to detect miRNAs, as they have few sequence constraints so an arbitrary RNA sequence can act as the trigger RNA. As such, toehold switch mediated miRNA detection could act as a ubiquitous mechanism, capable of detecting any miRNA sequence for any disease.

Following miRNA extraction from a body fluid, the miRNA is added to a cell free system containing an excess of toehold switches that detect a specific target miRNA. These toehold switches regulate translation of GFP. The intensity of fluorescence produced by our circuits is therefore indicative of the number of toehold switches activated and consequently, the miRNA levels in the body fluid.

Our project

That’s a overview of our system. To learn more about the different aspects of our project check out the links below.

References

  1. ↑ 1.0 1.1 1.2 Hennessey, P. T., Sanford, T., Choudhary, A., Mydlarz, W. W., Brown, D., Adai, A. T., & Califano, J. A. (2012). Serum microRNA biomarkers for detection of non-small cell lung cancer. PloS one, 7(2), e32307.
  2. ↑ 2.0 2.1 Chan, B. A., & Hughes, B. G. (2015). Targeted therapy for non-small cell lung cancer: current standards and the promise of the future. Translational lung cancer research, 4(1), 36.
  3. ↑ Ferlay, J., Soerjomataram, I., & Ervik, M. (2012). GLOBOCAN, cancer incidence and mortality worldwide: IARC cancer base no. 11 [Internet]. Lyon, France: International Agency for Research on Cancer; 2013.
  4. ↑ Board, P. A. T. E. (2017). Non-Small Cell Lung Cancer Treatment (PDQ®).
  5. ↑ Chen, Z., Fillmore, C. M., Hammerman, P. S., Kim, C. F., & Wong, K. K. (2014). Non-small-cell lung cancers: a heterogeneous set of diseases. Nature reviews. Cancer, 14(8), 535.
  6. ↑ Dajac, J., Kamdar, J., Moats, A., & Nguyen, B. (2016). To Screen or not to Screen: Low Dose Computed Tomography in Comparison to Chest Radiography or Usual Care in Reducing Morbidity and Mortality from Lung Cancer. Cureus, 8(4).
  7. ↑ Uramoto, H., & Tanaka, F. (2014). Recurrence after surgery in patients with NSCLC. Translational lung cancer research, 3(4), 242.
  8. ↑ Molina, J. R., Yang, P., Cassivi, S. D., Schild, S. E., & Adjei, A. A. (2008, May). Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship. In Mayo Clinic Proceedings(Vol. 83, No. 5, pp. 584-594). Elsevier.
  9. ↑ (n.d.). Lung cancer: diagnosis and management - NICE. Retrieved October 7, 2017, from https://www.nice.org.uk/guidance/cg121/chapter/introduction
  10. ↑ Gopal, M., Abdullah, S. E., Grady, J. J., & Goodwin, J. S. (2010). Screening for lung cancer with low-dose computed tomography: a systematic review and meta-analysis of the baseline findings of randomized controlled trials. Journal of thoracic oncology, 5(8), 1233-1239.
  11. ↑ Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011). Global cancer statistics. CA: a cancer journal for clinicians, 61(2), 69-90.
  12. ↑ Uramoto, H., & Tanaka, F. (2014). Recurrence after surgery in patients with NSCLC. Translational lung cancer research, 3(4), 242.
  13. ↑ Molina, J. R., Yang, P., Cassivi, S. D., Schild, S. E., & Adjei, A. A. (2008, May). Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship. In Mayo Clinic Proceedings(Vol. 83, No. 5, pp. 584-594). Elsevier.
  14. ↑ Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. cell, 116(2), 281-297.
  15. ↑ Ambros, V. (2004). The functions of animal microRNAs Nature 431: 350–355. Proceedings of the National Academy of Sciences of the United States of America, 103, 3687-3692.
  16. ↑ Kim, V. N., Han, J., & Siomi, M. C. (2009). Biogenesis of small RNAs in animals. Nature reviews Molecular cell biology, 10(2), 126-139.
  17. ↑ Zen, K., & Zhang, C. Y. (2012). Circulating microRNAs: a novel class of biomarkers to diagnose and monitor human cancers. Medicinal research reviews, 32(2), 326-348.
  18. ↑ 18.0 18.1 Mitchell, P. S., Parkin, R. K., Kroh, E. M., Fritz, B. R., Wyman, S. K., Pogosova-Agadjanyan, E. L., ... & Lin, D. W. (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences, 105(30), 10513-10518.
  19. ↑ Park, N. J., Zhou, H., Elashoff, D., Henson, B. S., Kastratovic, D. A., Abemayor, E., & Wong, D. T. (2009). Salivary microRNA: discovery, characterization, and clinical utility for oral cancer detection. Clinical Cancer Research, 15(17), 5473-5477.
  20. ↑ 20.0 20.1 Hanke, M., Hoefig, K., Merz, H., Feller, A. C., Kausch, I., Jocham, D., ... & Sczakiel, G. (2010, December). A robust methodology to study urine microRNA as tumor marker: microRNA-126 and microRNA-182 are related to urinary bladder cancer. In Urologic Oncology: Seminars and Original Investigations (Vol. 28, No. 6, pp. 655-661). Elsevier.
  21. ↑ 21.0 21.1 21.2 Kosaka, N., Izumi, H., Sekine, K., & Ochiya, T. (2010). microRNA as a new immune-regulatory agent in breast milk. Silence, 1(1), 7.
  22. ↑ 22.0 22.1 Chen, X., Liang, H., Zhang, J., Zen, K., & Zhang, C. Y. (2012). Secreted microRNAs: a new form of intercellular communication. Trends in cell biology, 22(3), 125-132.
  23. ↑ Vickers, K. C., Palmisano, B. T., Shoucri, B. M., Shamburek, R. D., & Remaley, A. T. (2011). MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nature cell biology, 13(4), 423.
  24. ↑ 24.0 24.1 Valadi, H., Ekström, K., Bossios, A., Sjöstrand, M., Lee, J. J., & Lötvall, J. O. (2007). Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nature cell biology, 9(6), 654.
  25. ↑ Turchinovich, A., Samatov, T. R., Tonevitsky, A. G., & Burwinkel, B. (2013). Circulating miRNAs: cell–cell communication function?. Frontiers in genetics, 4.
  26. ↑ Slater, E. P., Strauch, K., Rospleszcz, S., Ramaswamy, A., Esposito, I., Klöppel, G., ... & Bartsch, D. K. (2014). MicroRNA-196a and-196b as potential biomarkers for the early detection of familial pancreatic cancer. Translational oncology, 7(4), 464-471.
  27. ↑ Etheridge, A., Lee, I., Hood, L., Galas, D., & Wang, K. (2011). Extracellular microRNA: a new source of biomarkers. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, 717(1), 85-90.
  28. ↑ Kudla, G., Murray, A. W., Tollervey, D., & Plotkin, J. B. (2009). Coding-sequence determinants of gene expression in Escherichia coli. science, 324(5924), 255-258.
  29. ↑ Bentele, K., Saffert, P., Rauscher, R., Ignatova, Z., & Blüthgen, N. (2013). Efficient translation initiation dictates codon usage at gene start. Molecular systems biology, 9(1), 675.
  30. ↑ 30.0 30.1 30.2 Callura, J. M., Cantor, C. R., & Collins, J. J. (2012). Genetic switchboard for synthetic biology applications. Proceedings of the National Academy of Sciences, 109(15), 5850-5855.
  31. ↑ 31.0 31.1 Isaacs, F. J., Dwyer, D. J., Ding, C., Pervouchine, D. D., Cantor, C. R., & Collins, J. J. (2004). Engineered riboregulators enable post-transcriptional control of gene expression. Nature biotechnology, 22(7), 841.
  32. ↑ Rodrigo, G., Landrain, T. E., & Jaramillo, A. (2012). De novo automated design of small RNA circuits for engineering synthetic riboregulation in living cells. Proceedings of the National Academy of Sciences, 109(38), 15271-15276.
  33. ↑ Takahashi, M. K., & Lucks, J. B. (2013). A modular strategy for engineering orthogonal chimeric RNA transcription regulators. Nucleic acids research, 41(15), 7577-7588.
  34. ↑ Machinek, R. R., Ouldridge, T. E., Haley, N. E., Bath, J., & Turberfield, A. J. (2014). Programmable energy landscapes for kinetic control of DNA strand displacement. Nature communications, 5, 5324.
  35. ↑ Green, A. A., Silver, P. A., Collins, J. J., & Yin, P. (2014). Toehold switches: de-novo-designed regulators of gene expression. Cell, 159(4), 925-939.