In the future, a paper strip reminiscent of a pregnancy test could be used to quickly diagnose the flu and other infectious diseases.
Trying to get a handle on CRISPR news in 2019 can be daunting if you haven't been avidly reading up on it for the last five years.
CRISPR as a diagnostic tool would be a major game changer for medicine and agriculture.
On top of trying to grasp how the science works, and keeping track of its ever expanding applications, you may also have seen coverage of an ongoing legal battle about who owns the intellectual property behind the gene-editing technology CRISPR-Cas9. And then there's the infamous controversy surrounding a scientist who claimed to have used the tool to edit the genomes of two babies in China last year.
But gene editing is not the only application of CRISPR-based biotechnologies. In the future, it may also be used as a tool to diagnose infectious diseases, which could be a major game changer for medicine and agriculture.
How It Works
CRISPR is an acronym for a naturally occurring DNA sequence that normally protects microbes from viruses. It's been compared to a Swiss army knife that can recognize an invader's DNA and precisely destroy it. Repurposed for humans, CRISPR can be paired with a protein called Cas9 that can detect a person's own DNA sequence (usually a problematic one), cut it out, and replace it with a different sequence. Used this way, CRISPR-Cas9 has become a valuable gene-editing tool that is currently being tested to treat numerous genetic diseases, from cancer to blood disorders to blindness.
CRISPR can also be paired with other proteins, like Cas13, which target RNA, the single-stranded twin of DNA that viruses rely on to infect their hosts and cause disease. In a future clinical setting, CRISPR-Cas13 might be used to diagnose whether you have the flu by cutting a target RNA sequence from the virus. That spliced sequence could stick to a paper test strip, causing a band to show up, like on a pregnancy test strip. If the influenza virus and its RNA are not present, no band would show up.
To understand how close to reality this diagnostic scenario is right now, leapsmag chatted with CRISPR pioneer Dr. Feng Zhang, a molecular biologist at the Broad Institute of MIT and Harvard.
What do you think might be the first point of contact that a regular person or patient would have with a CRISPR diagnostic tool?
FZ: I think in the long run it will be great to see this for, say, at-home disease testing, for influenza and other sorts of important public health [concerns]. To be able to get a readout at home, people can potentially quarantine themselves rather than traveling to a hospital and then carrying the risk of spreading that disease to other people as they get to the clinic.
"You could conceivably get a readout during the same office visit, and then the doctor will be able to prescribe the right treatment right away."
Is this just something that people will use at home, or do you also foresee clinical labs at hospitals applying CRISPR-Cas13 to samples that come through?
FZ: I think we'll see applications in both settings, and I think there are advantages to both. One of the nice things about SHERLOCK [a playful acronym for CRISPR-Cas13's longer name, Specific High-sensitivity Enzymatic Reporter unLOCKing] is that it's rapid; you can get a readout fairly quickly. So, right now, what people do in hospitals is they will collect your sample and then they'll send it out to a clinical testing lab, so you wouldn't get a result back until many hours if not several days later. With SHERLOCK, you could conceivably get a readout during the same office visit, and then the doctor will be able to prescribe the right treatment right away.
I just want to clarify that when you say a doctor would take a sample, that's referring to urine, blood, or saliva, correct?
FZ: Right. Yeah, exactly.
Thinking more long term, are there any Holy Grail applications that you hope CRISPR reaches as a diagnostic tool?
FZ: I think in the developed world we'll hopefully see this being used for influenza testing, and many other viral and pathogen-based diseases—both at home and also in the hospital—but I think the even more exciting direction is that this could be used and deployed in parts of the developing world where there isn't a fancy laboratory with elaborate instrumentation. SHERLOCK is relatively inexpensive to develop, and you can turn it into a paper strip test.
Can you quantify what you mean by relatively inexpensive? What range of prices are we talking about here?
FZ: So without accounting for economies of scale, we estimate that it can cost less than a dollar per test. With economy of scale that cost can go even lower.
Is there value in developing what is actually quite an innovative tool in a way that visually doesn't seem innovative because it's reminiscent of a pregnancy test? And I don't mean that as an insult.
FZ: [Laughs] Ultimately, we want the technology to be as accessible as possible, and pregnancy test strips have such a convenient and easy-to-use form. I think modeling after something that people are already familiar with and just changing what's under the hood makes a lot of sense.
Feng Zhang
(Photo credit: Justin Knight, McGovern Institute)
It's probably one of the most accessible at-home diagnostic tools at this point that people are familiar with.
FZ: Yeah, so if people know how to use that, then using something that's very similar to it should make the option very easy.
You've been quite vocal in calling for some pauses in CRISPR-Cas9 research to make sure it doesn't outpace the ethics of establishing pregnancies with that version of the tool. Do you have any concerns about using CRISPR-Cas13 as a diagnostic tool?
I think overall, the reception for CRISPR-based diagnostics has been overwhelmingly positive. People are very excited about the prospect of using this—for human health and also in agriculture [for] detection of plant infections and plant pathogens, so that farmers will be able to react quickly to infection in the field. If we're looking at contamination of foods by certain bacteria, [food safety] would also be a really exciting application.
Do you feel like the controversies surrounding using CRISPR as a gene-editing tool have overshadowed its potential as a diagnostics tool?
FZ: I don't think so. I think the potential for using CRISPR-Cas9 or CRISPR-Cas12 for gene therapy, and treating disease, has captured people's imaginations, but at the same time, every time I talk with someone about the ability to use CRISPR-Cas13 as a diagnostic tool, people are equally excited. Especially when people see the very simple paper strip that we developed for detecting diseases.
Are CRISPR as a gene-editing tool and CRISPR as a diagnostics tool on different timelines, as far as when the general public might encounter them in their real lives?
FZ: I think they are all moving forward quite quickly. CRISPR as a gene-editing tool is already being deployed in human health and agriculture. We've already seen the approval for the development of growing genome-edited mushrooms, soybeans, and other crop species. So I think people will encounter those in their daily lives in that manner.
Then, of course, for disease treatment, that's progressing rapidly as well. For patients who are affected by sickle cell disease, and also by a degenerative eye disease, clinical trials are already starting in those two areas. Diagnostic tests are also developing quickly, and I think in the coming couple of years, we'll begin to see some of these reaching into the public realm.
"There are probably 7,000 genetic diseases identified today, and most of them don't have any way of being treated."
As far its limits, will it be hard to use CRISPR as a diagnostic tool in situations where we don't necessarily understand the biological underpinnings of a disease?
FZ: CRISPR-Cas13, as a diagnostic tool, at least in the current way that it's implemented, is a detection tool—it's not a discovery tool. So if we don't know what we're looking for, then it's going to be hard to develop Cas13 to detect it. But even in the case of a new infectious disease, if DNA sequencing or RNA sequencing information is available for that new virus, then we can very rapidly program a Cas13-based system to detect it, based on that sequence.
What's something you think the public misunderstands about CRISPR, either in general, or specifically as a diagnostic tool, that you wish were better understood?
FZ: That's a good question. CRISPR-Cas9 and CRISPR-Cas12 as gene editing tools, and also CRISPR-Cas13 as a diagnostic tool, are able to do some things, but there are still a lot of capabilities that need to be further developed. So I think the potential for the technology will unfold over the next decade or so, but it will take some time for the full impact of the technology to really get realized in real life.
What do you think that full impact is?
FZ: There are probably 7,000 genetic diseases identified today, and most of them don't have any way of being treated. It will take some time for CRISPR-Cas9 and Cas12 to be really developed for addressing a larger number of those diseases. And then for CRISPR-based diagnostics, I think you'll see the technology being applied in a couple of initial cases, and it will take some time to develop that more broadly for many other applications.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.