Project Description
Cancer early detection is pivotal for increasing survival rates among patients, but tests can be inaccessible and costly, leading to a scenario where patients typically do not receive care for their cancer until it becomes apparent that they may have cancer, which by then it would be too late for effective treatment interventions. It is common knowledge that early detection for a disease or condition, like cancer, allows for early clinical interventions, which would lead to a more likely chance of optimal patient outcomes. Currently, there are five available cancer screening tests: prostate, lung, breast, colorectal, and cervical cancer, which can be invasive, inaccurate, and limited to these five cancers. One multi-cancer early detection (MCED) test was developed, which detects cancerous cell-free DNA (cfDNA) in plasma (Klein et al, 2021). However, this MCED test relies on PCR or next-generation sequencing, which are expensive, time-consuming, and require equipment inaccessible to a typical clinician’s office (Mandal et al., 2021).
The inception of our project starts with the development from Collins et al. (2021) of conditionally active guide RNA (switch gRNA), which is only active in the presence of a “trigger” RNA sequence. Part of our project’s inception also uses methods from Hmelo et al. (2015) in order to help guide the design of our E. coli. Normally, gRNA is always active and guides a CRISPR enzyme to cut a specific plasmid or piece of DNA. However, switch gRNA is only active in the presence of a specific sequence of mRNA, which allows us to set a cancerous mRNA sequence as a condition for CRISPR activation. The target sequence in our project is a section of c-Myc mRNA, a biomarker for over 70% of cancers (Madden et al, 2021). This, combined with the fact we can identify this section of c-Myc mRNA in plasma (Oloomi et al., 2012), makes it the perfect candidate for developing a noninvasive MCED test.
To distribute and organize the work load of this project, we decided to divide responsibilities into three separate aims. The first aim focused on detecting exogenous synthetic RNA. This aim is primarily trying to figure out how to get strands of RNA into the E. coli cell membrane so that the plasmids, synthesized in other aims, can get to work. The second aim is to detect cancerous endogenous RNA. Endogenous detection of cancerous RNA pertains to cloning a new plasmid that will detect cancerous RNA, specifically c-Myc transcripts, and new conditionally active gRNA to activate with it. The third and final aim is trying to negatively select and detect RNA through growth-no-growth screening. This is the final stage and will improve the sensitivity of the system and allow the readily detection of cancer RNA strands when completed.
Plasmids provided by Collins et. al expressing various gRNA and trigger RNA strands are transformed into E. coli DH5a with pCB705 (GFP) and pCB482 (dFnCas12a). (A) Plasmid pCB1227; GFP always expressed, Non-targeting gRNA. (B) Plasmid pCB1228; GFP never expressed. Targeting gRNA . (C) Plasmid pCB1229; GFP expressed. Correct switch/random gRNA trigger. (D) Plasmid pCB1230; GFP not expressed. Correct switch/correct gRNA trigger.
This was the recreation of the Collins et. al. paper (referenced in background). This was to demonstrate that the plasmids provided by Collins et al functioned as expected- essentially a proof of concept. If this were to be implemented in the real world, a proper proof of concept protocol would need to be in place before human practice.
One option would be to continue the negative selection methods that we have implemented using Aim 3 (See "Aims"). This would be to use the sacB gene and a toxin such as LacI and observe through an overnight culture if the cells are resistant or die when the E. coli cell comes into contact with a c-Myc or another cancerous gene. Then if this is successful, we can further test using human blood and/or human samples with a target gene.
Our goal is to produce an accessible, cost-effective, and noninvasive MCED test by detecting overexpressed c-Myc mRNA in patients' plasma. To do this, we aim to transform E. coli with three plasmids that respectively produce switch gRNA, CRISPR enzymes, and toxins in the presence of sucrose. Additionally, we need the ability to transform exogenous mRNA into our bacteria. By default, when grown on an agar plate with sucrose, our bacteria will produce a toxin that will kill all colonies.
However, if our targeted, exogenous c-Myc transcript is transformed into our bacteria, the gRNA will activate and direct CRISPR to cut the toxin-producing plasmid, resulting in the growth of colonies. If successful, this system would create a growth-no-growth diagnostic tool available to most standard diagnostic laboratories or clinician's offices. Currently, two-thirds of our project has been completed, with the sensitivity of a toxin-producing plasmid as the final barrier.
Collins, S. P.; Rostain, W.; Liao, C.; Beisel, C. L. Sequence-Independent RNA Sensing and DNA Targeting by a Split Domain CRISPR–Cas12a gRNA Switch. Nucleic acids research 2021, 49 (5), 2985–2999. https://doi.org/10.1093/nar/gkab100.
Hmelo L. R.; Borlee B. R.; Almblad H.; Love M. E.; Randall T. E.; Tseng B. S.; Lin C.; Irie Y.; Storek K. M.; Yang J. J.; Siehne R. J.; Howell P. L.; Singh P. K.; Tolker-Nielsen T.; Parsek M. R.; Schweizer H. P.; Harrison J. J. Precision-Engineering the Pseudomonas Aeruginosa Genome with Two-Step Allelic Exchange. Nature Protocols [Online] 2015, 10:1820–1841. https://doi.org/10.1038/nprot.2015.115.
Klein E. A.; Richards D.; Cohn A.; Tummala M.; Lapham R.; Cosgrove D.; Chung G.; Clement J.; Gao J.; Hunkapiller N.; Jamshidi A.; Kurtzman K. N.; Seiden M. V.; Swanton C.; Liu M. C. Clinical Validation of A Targeted Methylation-Based Multi-Cancer Early Detection Test Using An Independent Validation Set. Annals of Oncology [Online] 2021, 32 (9), 1167–1177.
Madden S. K.; Dantas de Araujo A.; Gerhardt M.; Fairlie D. P.; Mason J. M. Taking the Myc Out of Cancer: Toward Therapeutic Strategies to Directly Inhibit c-Myc. Molecular Cancer [Online] 2021, 20 (3), https://doi.org/10.1186/s12943-020-01291-6.
Mandal, S.; Li, Z.; Chatterjee, T.; Khanna, K.; Montoya, K.; Dai, L.; Petersen, C.; Li, L.; Tewari, M.; Johnson-Buck, A.; Walter, N. G. Direct Kinetic Fingerprinting for High-Accuracy Single-Molecule Counting of Diverse Disease Biomarkers. Accounts of chemical research [Online] 2021, 54 (2), 388–402. https://doi.org/10.1021/acs.accounts.0c00621.
Oloomi, M.; Bouzari, S.; Mohagheghi, M. A.; Khodayaran-Tehrani, H. Molecular Markers in Peripheral Blood of Iranian Women with Breast Cancer. Cancer microenvironment [Online] 2012, 6 (1), 109–116. https://doi.org/10.1007/s12307-012-0118-7.
Taketo, A. RNA Transfection of Escherichia Coli by Electroporation. Biochimica et Biophysica Acta (BBA) - Gene Structure and Expression [Online] 1989, 1007:127–129. https://doi.org/10.1016/0167-4781(89)90142-5.