Team:UParis BME/Description
Description
Our solution (in a nutshell)
Our Master’s student team is developing a screening method for detecting early-stage miRNA onco-markers as a part of a worldwide synthetic biology competition, iGEM. We aim to employ de novo designed riboswitches, called toehold switches, to detect and quantify onco-miRNAs, and build a microfluidic device for rapid detection of a select exosome RNA library in patient plasma. Our goal is to create an easy-to-use broad screening method for common aggressive cancers to complement routine blood analysis.
Discover more about our journey and the science behind it by exploring our Project, Laboratory work, and Human Practices / Communications. pages. Or you can stay in this section and find out how early tumour diagnosis is crucial to lowering cancer-associated mortality, and why we picked microRNAs as targets for our diagnostic device.
The current gap in cancer diagnosis
Modern standards of medicine keep evolving every day, as hospitals around the globe integrate innovation and facilitate access to treatment. Nevertheless, the leading causes of death do not show any signs of slowing down. Even the global pandemic could not displace the second leading cause of mortality - cancer, in particular in developed countries like the US.1
Seemingly, there is no shortage of breakthroughs in cancer therapy, as highlighted by the 2018 Nobel Prize in Physiology and Medicine.2 Yet, the words “cancer diagnosis” are still associated with terminal disease. This contradiction has motivated our team to explore the factors contributing to cancer mortality and seek for solutions with the help of synthetic biology.
A short conversation with a clinician will easily confirm that beating cancer is not only about developing better treatments. Just like the most potent antibiotics may not save a patient in bacterial sepsis, cancer discovered late is often too advanced to respond to therapy. Conversely, early-stage cancer diagnosis can improve patient survival across a range of aggressive tumours.3 Yet patients are often referred to an oncologist after the disease has already progressed. Most cancers start without any disease-specific symptoms, precluding timely tumour discovery.4
A hint from patients’ biofluids
Screening programs have already shown improved diagnosis rates in breast cancer.5 However, many tissues are not as accessible with these screening strategies. Tissue biopsy, the gold standard of diagnosis for numerous tumour types, is an invasive procedure that requires cancer suspicion. It acts more like a confirmatory tool, making it unsuitable for screening healthy population.6 Recently, researchers have become increasingly interested in liquid biopsies, relying on harvesting patient's biofluids such as blood, urine, or saliva to screen for oncologic biomarkers.
Liquid biopsy offers a novel avenue for cancer screening programs, as it can be used for non-invasive testing without cancer suspicion. It is minimally invasive and can be routinely performed alongside other laboratory tests. Many hospitals have successfully implemented cancer screens testing for protein biomarkers in peripheral blood samples.7 Nevertheless, this solution is not perfect, as these oncomarkers are not specific to cancer, and often provide false positive or false negative results.8
On the contrary, exosome noncoding RNA demonstrates exceptional potential as a dynamic marker of tumour tissue status. Sharp up- or downregulation of biofluid microRNA (miRNA) reflects changes in the regulatory transcriptome of the cancer tissue, shedding light on tumor activity earlier than current protein markers. These signatures are often shared by multiple cancer types, thus allowing a broader screening solution for multiple cancer types at once. In addition to their utility for early cancer diagnosis, miRNAs are promising biomarkers for predicting tumor progression (prognosis).9,10 Current research in oncology focuses on two themes that are tightly connected: (i) improving the techniques for predicting cancer establishment/ evolution in order to (ii) adapt the therapies to the tumor subtype and to the patient.
- Ahmad FB, Anderson RN. The Leading Causes of Death in the US for 2020. JAMA. 2021;325(18):1829-1830. doi:10.1001/jama.2021.5469
- Cronin, P., Ryan, F. and Coughlan, M. 2008. Undertaking a literature review: a step-by-step approach. Br. J. Nurs. 17: 38-43.
- The Nobel Prize in Physiology or Medicine 2018. NobelPrize.org. https://www.nobelprize.org/prizes/medicine/2018/press-release/. Accessed September 26, 2021.
- Weller D, Vedsted P, Rubin G, et al. The Aarhus statement: improving design and reporting of studies on early cancer diagnosis. Br J Cancer. 2012;106(7):1262-1267. doi:10.1038/bjc.2012.68
- Schiffman JD, Fisher PG, Gibbs P. Early Detection of Cancer: Past, Present, and Future. Am Soc Clin Oncol Educ B. 2015;(35):57-65. doi:10.14694/EdBook_AM.2015.35.57
- Milosevic M, Jankovic D, Milenkovic A, Stojanov D. Early diagnosis and detection of breast cancer. Technol Heal Care. 2018;26:729-759. doi:10.3233/THC-181277
- Esagian SM, Grigoriadou GI, Nikas IP, et al. Comparison of liquid-based to tissue-based biopsy analysis by targeted next generation sequencing in advanced non-small cell lung cancer: a comprehensive systematic review. J Cancer Res Clin Oncol. 2020;146(8):2051-2066. doi:10.1007/s00432-020-03267-x
- Bhawal R, Oberg AL, Zhang S, Kohli M. Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer. Cancers (Basel). 2020;12(9):2428. doi:10.3390/cancers12092428
- Yotsukura S, Mamitsuka H. Evaluation of serum-based cancer biomarkers: A brief review from a clinical and computational viewpoint. Crit Rev Oncol Hematol. 2015;93(2):103-115. doi:https://doi.org/10.1016/j.critrevonc.2014.10.002
- Yerukala Sathipati S, Ho S-Y. Identifying a miRNA signature for predicting the stage of breast cancer. Sci Rep. 2018;8(1):16138. doi:10.1038/s41598-018-34604-3
- Zhou X, Lu Z, Wang T, Huang Z, Zhu W, Miao Y. Plasma miRNAs in diagnosis and prognosis of pancreatic cancer: A miRNA expression analysis. Gene. 2018;673:181-193. doi:https://doi.org/10.1016/j.gene.2018.06.037