Cancer DNA is detectable in blood years before diagnosis
sciencenews.org
sciencenews.org
- Sure, cancer can develop years before diagnosis. Pre-cancerous clones harboring somatic mutations can exist for decades before transformation into malignant disease.
- The eternal challenge in ctDNA is achieving a "useful" sensitivity and specificity. For example, imagine you take some of your blood, extract the DNA floating in the plasma, hybrid-capture enrich for DNA in cancer driver genes, sequence super deep, call variants, do some filtering to remove noise and whatnot, and then you find some low allelic fraction mutations in TP53. What can you do about this? I don't know. Many of us have background somatic mutations speckled throughout our body as we age. Over age ~50, most of us are liable to have some kind of pre-cancerous clones in the esophagus, prostate, or blood (due to CHIP). Many of the popular MCED tests (e.g. Grail's Galleri) use signals other than mutations (e.g. methylation status) to improve this sensitivity / specificity profile, but I'm not convinced its actually good enough to be useful at the population level.
- The cost-effectiveness of most follow on screening is not viable for the given sensitivity-specificity profile of MCED assays (Grail would disagree). To achieve this, we would need things like downstream screening to be drastically cheaper, or possibly a tiered non-invasive screening strategy with increasing specificity to be viable (e.g. Harbinger Health).
It COULD be used to craft a pipeline that dramatically improved everyone's health. It would take probably a decade or two of testing (an annual MRI, an annual sequencing effort, an annual very wide blood panel) in a longitudinal study with >10^6 people to start to show significant reductions in overall cancer mortality and improvements in diagnostics of serious illnesses. The diagnostic merit is almost certainly hiding in the data at high N.
The odds are that most of the useful things we would find from this are serendipitous - we wouldn't even know what we were looking at right now, first we need tons of training data thrown into a machine learning algorithm. We need to watch somebody who's going to be diagnosed with cancer 14 years from now, and see what their markers and imaging are like right now, and form a predictive model that differentiates between them and other people who don't end up with cancer 14 years from now. We [now] have the technology for picking through complex multidimensional data looking for signals exactly like this.
In the meantime, though, you have to deal with the fact that the system is set up exclusively for profitable care of well-progressed illnesses. It would be very expensive to run such a trial, over a long period of time, and the administrators would feel ethically bound to unblind and then report on every tiny incidentaloma, which completely fucks the training process.
This US is institutionally unable to run this study. The UK or China might, though.
The child of a friend of mine has PTEN-Hamartom-Tumor-Syndrom, a tendency to develop tumors throughout life due to a mutation in the PTEN gene. The poor child gets whole body MRIs and other check-ups every half year. As someone in biological data science, I always tell the parents how difficult it will be to prevent false positives, because we don't have a lot of data on routine full body check-ups on healty people. We just know the huge spectrum on how healthy/ok tissue looks like.
>CRISPR/Cas9 can be directed to cut DNA in targeted areas, enabling the ability to accurately edit (remove, add, or replace) DNA where it was cut. The modified blood stem cells are transplanted back into the patient where they engraft (attach and multiply) within the bone marrow...
https://www.fda.gov/news-events/press-announcements/fda-appr...
I wonder if our current research product is only considered the gold standard because doing things in a probabilistic way is the only way we can manage the complexity of the human body to date.
It’s like me running an application many, many times with many different configurations and datasets, while scanning some memory addresses at runtime before and after the test runs, to figure out whether a specific bug exists in a specific feature.
Wouldn’t it be a lot easier if I could look at the relevant function in the source code and understand its implementation to determine whether it was logically possible based on the implementation?
We currently don’t have the ability to decompile the human body, or understand the way it’s “implemented”, but that is something that tech is rapidly developing tools that could be used for such a thing. Either a way to corroborate enough information aggregated about the human body “in mind” than any person can in one lifetime and reason about it, or a way to simulate it with enough granularity to be meaningful.
Alternatively, the double-blindedness of a study might not be as necessary if you can continually objectively quantify the agreement of the results with the hypothesis.
Ie if your AI model is reporting low agreement while the researchers are reporting high agreement, that could be a signal that external investigation is warranted, or prompt the researchers to question their own biases where they would’ve previously succumbed to confidence bias.
All of this is fuzzy anyway - we likely will not ever understand everything at 100% or have perfect outcomes, but if you can cut the overhead of each study down by an order of magnitude, you can run more studies to fine-tune the results.
Alternatively, you can have an AI passively running studies to verify reproducibility and flag cases where it fails, whereas now the way the system values contributions makes it far less useful for a human author to invest the time, effort, and money. Ie improve recovery from a bad study a lot quicker rather than improve the accuracy.
EDIT: These are probably all ideas other people have had before, so sorry to anyone who reaches the end of my brainstorming and didn’t come out with anything new. :)
Do a detailed enough study of an entire population and you get very strong hypothesis testing for all sorts of diseases & treatments simultaneously. You don't have to spend tens of millions of dollars and multiple PHD generations running a blinded study to replicate a specific untested first-principles part of modern medicine's treatment for a rare disease, you get that shit for free and call it up in a SQL query.
Like if we had some kind of prophylactic cancer treatment that was easy/cheap/safe enough to recommend to people even on mild suspicion of cancer with false positives, we could offer it to positive tests. Maybe even just lifestyle interventions if those are proven to work. That's probably very difficult though, just dreaming out loud.
It gives people the agency to alter their lifestyle trajectory.
I personally suspect that people get and cure cancer all the time.
I wonder if cancer is just damage to your body - either a lot of direct damage or interfering with the body's ability to manage/heal itself.
if someone was pre-cancer, would it help to exercise, cut out sugar, use the sauna, stop overeating? I'll bet it might make a difference
the problem is you do the test for 7 billion people, say, 30 times over their life... 210000000000 tests. imagine how many false negatives and false positives, the cost of follow up testing only to find... false positive. the cost of telling someone they have cancer when they don't. the anger of telling someone they are free of cancer, only to find out they had it all along
this tech isn't that good, nowhere near it, more like a 1 in 100 or 10 in 100 rate of "being wrong". those numbers can get cheesed towards more false positives or false negatives.
as for grail, they tried to achieve this and printed OK numbers... ... .. but their test set was their training set. so the performance metrics went to shit when they rolled it out to production
So, more like — did the tumor come back? And if that does happen, with ctDNA, can you detect that there is a relapse before you would otherwise find it with standard imaging. Most studies I’ve seen have shown that this happens and ctDNA is a good biomarker for early detection of relapse.
The case for proactively looking for circulating tumor DNA without an initial diagnosis or underlying genetic condition is a bit dicier IMHO. For example, what if really like to know (I haven’t read this article, but I’m pretty familiar with the field) is how many people had a detectable cancer in their plasma (ctDNA), but didn’t receive a cancer diagnosis. It’s been known for a while that you can detect precancerous lesions well before a formal cancer diagnosis. But, what’s still an open question AFAIK, is how many people have precancerous lesions or positive ctDNA hits that don’t form a tumor?
(I’ve done a little work in this area)
And the question would be “do I believe the test when it tells me the cancer is gone?” When you know it’s not 100% accurate?
Or do you always do the adjuvant treatment considering the very small chance the test is wrong has a very high cost (death)?
I lost my wife to melanoma that metastasized to her brain after cancerous mole and margin was removed 4 years earlier. They did due diligence and by all signs there was no evidence of recurrence, until there was. They think that the tumor appeared 2-3 months before symptoms (headaches) appeared, so it was unlikely that you’d discover it otherwise.
With something like this, maybe you could get lower dose immunotherapy that would help your body eradicate the cancer?
Literally anything that reduces cancer deaths is a win. I'm certainly not campaigning against early detection tests like this! Just talking about a challenge that comes up operationalizing them.
What is CHIP?
It’s when bone marrow cells acquire mutations and expand to take up a noticeable proportion of all your bone marrow cells, but they’re not fully malignant, expanding out of control.
There are a lot of companies right now trying to apply AI to health, but what they are ignoring is that there are orders of magnitude less health data per person than there are cat pictures. (My phone probably contains 10^10 bits of cat pictures and my health record probably 10^3 bits, if that). But it's not wrong to try to apply AI, because we know that all processes leak information, including biological ones; and ML is a generic tool for extracting signal from noise, given sufficient data.
But our health information gathering systems are engineered to deal with individual very specific hypotheses generated by experts, which require high quality measurements of specific individual metrics that some expert, such as yourself, have figured may be relevant. So we get high quality data, in very small quantities -a few bits per measurement.
Suppose you invent a new cheap sensor for extracting large (10^7+ bits/day) quantities of information about human biochemistry, perhaps from excretions, or blood. You run a longitudinal study collecting this information from a cohort and start training a model to predict every health outcome.
What are the properties of the bits collected by such a sensor, that would make such a process likely to work out? The bits need to be "sufficiently heterogeneous" (but not necessarily independent) and their indexes need to be sufficiently stable (in some sense). What is not required if for specific individual data items to be measured with high quality. Because some information about the original that we're interested in (even though we don't know exactly what it is) will leak into the other measurements.
I predict that designs for such sensors, which cheaply perform large numbers of low quality measurements are would result in breakthroughs what in detection and treatment, by allowing ML to be applied to the problem effectively.
A chemosensor also sounds like a useful thing it should give concentration by time. Minimally invasive option would be to monitor breath, better signal in blood.
I'd be really curious to see how longitudinal results of sequencing + data banking, plus other routine bloodwork, could lead to early detection and better health outcomes.
There are nevertheless privacy issues, which I did not address as my first comment was already very long, especially for a tangent. Most obviously, people would be consenting to the collection of data whose significance they cannot reasonably forsee.
I do agree that most current AI companies are unlikely to be a good steward of such data, and the current rush to give away health records needs to stop. In a way it's a good thing that health records are currently so limited, since the costs will so obviously outweigh the benefits.
It's kind of why I'm favor of universal option to align financial incentives. Like given how sick the US population is, it probably makes sense to put a lot more people of GPL-1s and invest in improving their efficacy and permanence. Like nationalize-the-patent COVID-operational-warp-speed level urgency. There are over 100M Americans that are pre-diabetic, the cost of treating a diabetic is about 20k/yr. So $4 trillion in new costs, on top of the misery and human suffering.
Sounds like either there are complicating factors or an absence of standard protocol adherence.
US health insurance is a mess, but that doesn’t sound like the entire story. I suspect urologists see a fair amount of friction for routine procedures related to prostrate health.
Like I said, there is more to this story.
Searching the web shows that Cigna forces some patients to use this program in order to receive coverage for certain conditions. They're likely saving all the info collected through it in order to use it to deny you coverage if they can at all make an argument that something was caused by your lifestyle, was pre-existing for a certain amount of time, etc-- at least, that's the vibe I got from researching it.
Oh God, that is so sad and infuriating. :(
COVID was different because being a transmissible disease, there was a strong motivation to try to maximise the percent of the population immunised. With GLP-1 agonists, if you made them freely available, likely over >50% of eligible patients would take them voluntarily, which would result in massive long-term cost savings from lifestyle diseases, even considering the continued costs from the other 50% who will refuse. And insurers may even give discounts to those who take GLP-1s (if permitted by regulators)
GLP-1s are probably going to have the unintended side effect of increasing weight stigma - already obesity skews poor, once most of the well-off obese people cure their obesity with GLP-1s it is going to skew even more poor. I can foresee a cycle in which GLP-1s increase weight stigma which pushes more people into taking them which then increases weight stigma even more, which could drive up their adoption even further
The U.S. is a different kind of mess. It’s a patchwork of heavy government restrictions, large public programs like Medicare, and for-profit corporations, all thrown together without a coherent design. It’s no surprise it’s expensive. In 2023, healthcare spending was nearly 18% of GDP. Another factor could simply be wealth: higher per capita GDP tends to correlate with higher healthcare spending. To be fair to the U.S. healthcare system, it is highly capitalized, with much higher concentrations of diagnostic equipment like MRI machines than other OECD countries, and it does have some of the highest five-year survival rates for cancer and heart disease.
Even so, all of these healthcare systems are heavily dysfunctional in many ways.
In contrast to all of this, cosmetic surgery and laser eye surgery are the only fields of medicine where prices have actually fallen in inflation-adjusted terms, which is extraordinary, as prices in healthcare in general have increased much faster than inflation. The superior performance of these fields is because of basic market dynamics. People pay out of pocket, so they’re price conscious, and providers compete. There are also fewer regulatory restrictions since these fields aren’t tied up in government programs like Medicare.
Innovation is the only thing that reliably drives prices down. But in most of healthcare, it moves slowly. Devices often take 10-30 years to cycle out. Compare that to consumer electronics, where turnover happens every 1-2 years.
If it were up to me, I’d make restrictions on medical providers much lighter. Anyone could offer medical procedures as long as they disclose they’re uncertified and include a government-mandated warning. That kind of freedom is necessary to solve hard problems. You can’t regiment innovation and industry development. Gatekeeping in the name of consumer safety is the worst thing that can be done to any industry, and unfortunately, there is heavy gatekeeping in healthcare.
That is not to say that I am opposed to government intervention in general. I think it can play a critical role in advancing healthcare. Where government intervention creates the most value is in funding research for the public domain: drug designs, medical procedures, and open datasets. These investments have enormous returns and are best handled by governments. If the private sector focused on delivery and innovation, with governments making strategic contributions in foundational research, healthcare would see revolutionary improvements generation after generation.
It's all private in the Netherlands, just with non-discriminatory mandatory private insurance, so that makes sense.
EDIT:
Adding these caveats:
1. There is a ton of nuance in the diagnosis, since most people have a small amount of cancer in their blood at all times
2. The screenings are 5-10k + follow up appointments to actually see if its real cancer
3. All in cost then could be much higher per person
4. These tests arent something that are currently produced to be used at mass scale
This is not to downplay the potential benefit of early cancer detection... which is huge. And in the US/UK anyway, there are ongoing large trials to try to figure some of this stuff out in the space of blood-based cancer screening, as part of the path to convincing regulatory bodies and eventual reimbursement for certain tests. As mentioned, you can currently at least get the Galleri test out of pocket (<$1k, not cheap, but not exorbitant either), as well as whole body MRIs (a bit more expensive, ~$2-5k).
Many prostate cancers, for instance, are slow growing and won't kill you before something else does. If you try to take that kind of cancer out surgically or zap it with radiation or chemo the side effects could be severe.
We do a lot of CT imaging in the emergency department and it sucks if we incidentally find an abnormal growth in a young patient's CT head. These are usually benign and often not worth performing brain surgery to get a biopsy.
The internet is a powerful tool of communication, but turns out some people don't have anything worthwhile to communicate.
People talk about the “immune system” but they are really referring to a number of systems the body uses to regulate itself, more or less successfully, around environmental pressures. The body is a system under tension, sometimes extreme tension leads to extreme success (success here being growth of power), sometimes it breaks the body, and sometimes the systems have been slowly failing for a while, and most treatments will not help. Medicine is only useful in the specific case where the power of the body would be promoted if not for one thing, that the body would be healthy, at least manageably so, without that issue.
Incorrect.
There are tons of cancers that hide and mask with symptoms common to other symptoms. Kidney cancer, for example, presents pretty similarly to both kidney stones and UTIs. Even blood in the urine isn't proof positive that anything is wrong beyond either of those conditions. And, by the time blood is in the urine, it's often too late.
Liver cancer is even worse. The first symptoms you get can be thought of as a simple pulled muscle, just a little ache in the back. By the time you have appreciable problems, like turning yellow, it's quite advanced and too late to really do much.
There are common cancers like colon, skin, breast, and prostate that more fit your description of being mostly harmless so long as you get regular screenings and eat healthy. But, for every part of the body, a cancer can form and the symptoms are very often invisible.
I'm unfortunately all too familiar with how cancer looks. My wife currently has stage 4 cancer that started as kidney cancer. She does not drink or smoke, gets enough rest, and is very active.
Thus, in young people cancer presents rapidly as they develop, these screenings are expensive and unnecessary. For old/sick/unhealthy people, or people who are predisposed to certain cancers, they will probably get something else anyway, so its an expensive workup to help treat a disease that won’t actually benefit much in the long term.
I’m not against treating cancer, however let’s recognize that cancer treatment is already an expensive and resource/labor intensive process. And 10yr survival rates are not great for most cancers, we’re only slowing the burn, not stopping it. Sometimes you get lucky and die of something else before the cancer can come back, but nobody is ever “cured,” they are all just delaying the inevitable. Which, as we have seen, can sometimes be worth it (who wouldn’t want another 10 years with a loved one?), but that doesn’t mean our goal should be to find a way to “cure” cancer, it should be to find a way to better manage it, and these screenings don’t seem like they really are, or at least the use-cases for them are minimal.
Annual MRI?
I do wonder if a 5 year whole body MRI or CT would be generally beneficial for the population. I don't think it needs to be Annual to have benefits.
The problem is it really isn't uncommon for your body to create random puss fill sacks all over the place. It's one thing our cancer doctor warned us about. My wife is now on a 6 month CT regimen and ultimately, they'll just ignore new lumps.
GP wasn't asking what they should personally do. They were asking how the doctor would screen for it. (The truth is, the doctor can't/won't-- an annual MRI on every otherwise healthy person, for example, would be prohibitively expensive with how MRIs are currently set up-- and as another commenter pointed out, findings from those can be just as easily ignored or put off until it's too late.)
Being beside that hypochondric point is statistically a much healthier place to be.
The current state of medicine is the current state of medicine in the actual world.
The usual story is that you’re just better off not knowing because you’ll end up doing more harm than good chasing every little suspicious diagnosis. Cancer happens all the time, but many times doesn’t lead to anything.
Is it moral for a doctor to give a test they think is going to increase someone's chance of death.
It involves costs of healthcare for all people involved, workload on health professionals, hospital occupancy, etc and so forth.
If the rate of false positives in these tests are too high, people that need treatment for their actual illnesses might be on a waiting list because too many are doing follow-up screening and biopsies for non-issues.
And to address your silly "collectivist" fear-mongering, your hyper-individualist mentality is a societal disease. We could do with some more collectivism, in the sense that people have a better understanding of the constraints and conditions of the society they are inserted in.
thanks for adding the caveats; they suggest that there are good reasons why it isn't clear cut that health care companies should pay.
It's the same reason they pay for annual physicals in the first place.
In my field, we all think that CfDNA testing will eventually become a standard thing that will go along with your annual physical's blood test, because it has predictive/preventative abilities.
Doing this same idea but with inflammation monitoring would be enormously valuable as well.
They assumed their previous cancer had survived and metastasized. Doctors couldn't find the source. It turned into a waiting game, where they lived with a sword of Damocles over their head. They were retested every few months and monitored. Then after a year the tests the levels dropped off. And the end result was nothing came of it so far.
It's normal to have some amount of pre-cancerous cells get naturally removed by your immune system. And this catches those too.
As far as I can tell, they did a wholesale deal with quest diagnostics, and run your results through ChatGPT and give you supplement / diet recs via a pretty web portal 2x a year for $499.
Claim is it’s 100 biomarkers and would cost avg person $15k retail.
I’m a member and love it.
then i remembered a month or so ago seeing this, and not knowing what to make of it.
Ageless also provides many other longevity therapies.
I get it every year. So far, so good!
Question for you, what do you do when it shows you may have cancer? Do you speak to your physician? Surely, this will change your life even if it doesn't need treatment for next 6 years? Does the treatment change? Can the treatment be done based on those results?
So many questions.
I'm hoping we find more stuff for Alzheimer's. My aunt and now mother have it. I fear that I am next and I am too scared of doing the DNA test to check for genes.
The test is not foolproof and the detection rate for some early stage cancers is quite low. And of course early detection is no promise of a cure. Regardless $800 a year isn't an unreasonable cost for me given I get annual health screenings anyway. My insurance doesn't cover that test but you can use your HSA to pay for it if needed.
what about Europe?
Curious to see how these hold up over the long term.
https://aacrjournals.org/cancerdiscovery/article-abstract/do...
Full text is paywalled, and no mention in abstract of false positive rate in control group. Has this test actually been independently verified? No mention of that important fact in the press release.