Cancer is just a catch-all term for somatic cell mutations that become unmanageable. There are as many ways to get "cancer" as there are ways to mutate cells into these sort of uncontrollable states. And there are cures for multiple cancers today (Imantinib, Herceptin, etc). There actually have been enormous recent strides in drugs like PD-1 inhibitors that do have a broad spectrum affect against cancers, but I think outside of this one particular example, the real math problem is how do you expect to contain a mutational state of a cell with 10000x ways to reach that state with a single, or even handful of drugs?

Im not sure who the target audience is for the article, but it strikes me as one where if the author were more knowledgeable on the subject, they would have many of the answers to what they are asking. It reads to me like someone writing "why are there still bugs in programming? Is it because of too many buttons on the screens?"

Im in agreement with you that most people don't grasp just how medicine as an area of study is unfathomably complex. It mimics a fractal in the sense that the deeper we go in trying to understand things it just opens up a wider scope of investigation.

If you've written any code at all, you know that a non-orthogonal system is incredibly complex. It isn't just a matter of complexity scaling linearly with the count of the individual parts. Complexity scales with the interactions between each component, and between the assemblages of those components that have emergent interactions. Change one line of code, and you get wildly different behavior in another part of the system, or seemingly nothing for a long time until the system deletes its own database suddenly one day.

Curing cancer is a dramatically broad statement, because each kind is different, interacts with a different part of the body, and has different ways of growing and sustaining itself. Each intervention causes a cluster of unintended side-effects, again, because the body is a non-orthogonal system. Even your simple statements fall flat. Most cancer cells disguise themselves as normal cells from the perspective of the body's immune system. It's why the cancer can grow at all. The other factor is that most things that would kill cancer cells would kill cells... in general. Pull one thread wrong, fix one bug the wrong way... you end up doing more harm than good.

Maybe we'll get to a point where we have combinations of nanotech and gene therapies that eliminate most cancers. But it won't be simple. Getting there in an ethical fashion makes it even harder. How do we experiment with this kind of nanotech (which is not even off the ground yet). How do we experiment with this kind of gene therapy (we have more traditional paths to tread here, but there are still some quandaries).

We're just not there yet, and I doubt it will ever be something as reductive as your two items.

[1] https://www.science.org/content/article/scientists-say-they-... (2018)

Yep. It's like modifying an undocumented API where there are tens of thousands of endpoints and you know there are a few dozen services that rely on each endpoint, and probably a few dozen more that nobody knows about. You are only allowed test runs that are expected to succeed, since test failures = death. Your dev environment is a mouse. Every change gets pushed to prod with no option to revert.

1. Draw some circles.

2. Draw the rest of the owl.

> 1. Identify rogue cells 2. Destroy the rogue cells.

Oh, is that all?:D And which of those do we have the tech to do?

4. Reinforce control of the chemical polluters

Push to assure that as much people as possible are supplied with food and water that are clean of cancer triggering chemicals. Educate people about sunburns is useful also, but people will rarely get leukemia or pancreatic cancer by sun exposure alone.

The sad truth is that most people will not be grateful for --not having-- cancer or --not going-- into a fat accumulation spiral by chemicals breaking the body fat system. People just take this for granted, or expect somebody volunteering to do this work for free.

Is not a lack of will, is a lack of resources. Banners are still one of the most powerful tools against cancer and the most underrated one.

Cancer is not a simple anomaly detection problem. I mean, there's that, but so much more. These cells, each one of them, by their very nature, looks exactly like your normal healthy cells, on the outside. It's what's inside the cell that's going to kill you. The uncontrolled replication. There are 36 trillion cells in the human body. How are you going to monitor them all? Well, turns out we have several methods built in, collectively called the immune system. But again, they're mainly looking for "not self". Because if they were looking for "self" you'd have another problem, called auto-immunity.

The uncertainty is real. It's not a hypothetical uncertainty. Combinatorics is a bitch.

There are 3 billion base pairs per normal human cell. The difference between a normal cell and a cancer cell can be on a similar order (a cancer cell may have many billions or less than a billion base pairs). There are similar problems for the number of proteins, lipids, polysaccharides, metal ions etc, per cell.

Three billion times 36 trillion, oh, and many generations of many of those 36 trillion over time. So, let's casually say a billion billion cells in a human life time. Times 3 billion base pairs. If one of those cells gets out of control, you've got a problem. Shockingly, only one in six people die of cancer.

Only under the most austere circumstances can we partially characterize a single cancer cell, and even then we waste many, many other cancer cells to surface that one cell (e.g. single cell transcriptomics).

Other methods allow us to examine many cells, but we can't examine them as closely (histology, histochemistry, immunochemistry, in situ hybridization, flow cytometry, targeted genomics, shotgun sequencing, karyotyping, etc), and we still never see most of the cells.

To get a basic understanding, it's advisable to take the ground up approach used in statistical mechanics: in cancer, from the ground up, a single cell is the source of the initial problem. That cell and its progeny divide many times, let's say 30-40 times. Now you have a billion cells, maybe 10-100 billion cells. Every one of which is starting from an unmanaged state, highly vulnerable to additional mutations. And probably the cell of origin died 20 generations before you find the tumor. Even in a basic science research setting, it would be exceedingly challenging to demonstrate you had found "the cell of origin".

This is very similar to physics: there are things we can know at one energy level that we can't know at another energy level. You can't explore Bose-Einstein condensates with the LHC. You're off by 20 orders of magnitude. You can't do single cell transcriptomics on a 1 kg en bloc cancer resection specimen, you're off by 20 orders of magnitude.

Complicating matters, fission is actually pretty straight forward compared to biology. In fission, you've got a very small number of elements involved, at very high, specified purity. In biology, you can barely guess most of what the organism consumed in the last 24 hours, let alone what they've been exposed to over a lifetime.

Cancer, nuclear physics, internet-scale computation, most of the really interesting problems: you can't just "take pictures" of the whole thing. It would be like assuming you can "just understand" what's happening in an actual nuclear explosion using some cameras and a sound understanding of math. Or the proposal that we could just understand the global economy by examining the ledger of all transactions. It's ridiculously beyond the realm of possible.

Even in the Trinity explosion, a highly controlled, intensively studied nuclear explosion, we can't even be sure how many neutrons the beryllium-polonium initiator produced. 8? 10? Not really sure which atoms produced them, for sure. And how many got produced in each succeeding fission generation? Meh? I mean, we can do some statistics, but that's it. That's roughly the scale of the problem we're dealing with in cancer research: where'd the thing come from? And where's it going? Statistically, we can make some guesses, but no one understands the whole thing.

Today I learned cancer is basically Cotton Eyed Joe.

Seriously, though, excellent write up!

Appealing to the authority of a pathologist is safe in my book given the subject matter and the education of the counterparty. There is a lower bound of requisite knowledge beneath which it's not worth even trying to entertain your claims about just "find and destroy rogue cells". You can't even begin to respond with logic and refutation if you haven't achieved anything close to the level of expertise required to be certified as a pathologist. Coming in here trying to play the angle of "well just model with supercomputers" isn't the winning ticket. Contrary to stereotypes of computer-illiterate doctors, there are some wicked smart people working in medicine (I've met and befriended many) and I guarantee your genius approach was considered and abandoned decades ago.

My ignorance has a model like: If you keep putting sugar in the gas tank, how do you fix the car? How do I stay healthy if I eat only crap? How do I stay fit if I never get out of my chair?

Shit, would it be one of those cause and effect things?

I am literally saying that avoiding the hard problem is going to work in the general case. I would argue that radiation therapy is in this vein.

Why?

Which feels like it should be true for a sufficiently targetable "laser" right?

Metastatic cancer is defined by essentially there being too many things to hit though, but therein lies the entire detail: you can't treat someone faster than they die of either the cancer or the treatment.

*Laser is being used metaphorically

Google paraneoplastic syndromes. Cancer is rarely a problem of just tumors.

> just "laser" all the tumours out and problem solved right?

No. The tumors don't just evaporate. The treatment causes tissue necrosis. Your laser causes inflammation. Even the high tech IMRT you're picturing has those problems.

>Metastatic cancer is defined by essentially there being too many things to hit though,

Metastasis as a concept is fairly meaningless in how you're using it. There are so many more factors in treatment of various cancers that have nothing to do with the distribution. There's a lot that clinpath looks at and frankly I care much more about what's on those reports than playing where's Waldo with nodules. Frequently we assume micrometastasis just based on the cell line or other characteristics.

> therein lies the entire detail

So no.

> you can't treat someone faster than they die of either the cancer or the treatment.

Again far more consideration goes into it but I'm losing my desire to debate these contrived simplistic takes.

I am aware of necrosis. You need to either completely break down the cell or remove the material. Radiation of course does not do this but surgery of course does.

My appeal to you would be to allow more disruption in this space. Software and Hardware are (mostly) unregulated which allowed for the explosion of progress.

> My appeal to you would be to allow more disruption in this space

No. There is far too much disruption that we don't want/need. If you want to help, go put yourself through medical school first, and then bring your CS knowledge to supplement it.

Jumping in when you haven't learned the basics wastes everyone's time like you have here.

The fact of the matter is that I think any kind of refutation is actually pretty difficult for you (perhaps due to the medical training). It likely would have been easier had you just agreed and said "Yes if you can destroy the cancer cells you can treat >90% of all cancer."

https://www.ncbi.nlm.nih.gov/books/NBK507890/

On the other hand, maybe it would be enough to filter out every cell that is not identified as a blood cell. This should be an easier task.

Probably we could direct only a small part of blood into this filtering machine at a time. Sounds like it would be still more like a machine detecting if there are cancer cells present in the bloodsteam rather than a machine eliminating metastasization.

I think the "cure cancer without biology" approach makes somewhat sense (I assume you would still need some biology :) ). Don't many surgeries already fall into this category? Let's say we made an automated colonoscopic machine that scanned the whole intestine and destroyed all abnormal colonic crypts. Now if this machine worked well, you would essentially cure at least those colon cancers that go through some aberrant crypt stage.

According to Craig Venter, early detection is what we need to eliminate cancer(s): https://youtu.be/iUqgTYbkHP8?t=15m37s

You can actually compare the sensitivity/specificity for PSA prostate screens versus something like ResNet for image recognition. The latter is in the high 90s for both metrics. The former can be as low as 0.06 for specificity if you want to actually achieve high sensitivity (detect prostate cancer with extremely extremely high false positives)

I respectfully disagree. Maybe our problem is that of attitude, which you also exhibit when saying "with a single, or even handful of drugs". Drugs as such may be a dead end.

Once upon a time, we decided to study cancer from a biochemical and genetic point of view and look for drugs, which may actually be suboptimal. To give an analogy, what if you tried to debug a faulty program using a beeper instead of a debugger with screen. It would be a nasty work and it would take long. This is not an intrinsic problem of software ("fundamental undebuggability of 10 thousand errors"), it is "just" a wrong approach to debugging.

We are not the only mammals, we can look around nature and learn from it. What do we see when we study cancer in other species? Mammalian species that are highly resistant to cancer (whales, bats, naked mole rats etc.) seem not to rely on drugs or their biochemical equivalents, but rather kill cancerous cells biologically, with help of their immune systems.

Notably, if a species is highly resistant to cancer, it tends to be highly resistant to all sorts of cancer at once, or, at the very least, to many sorts of cancer at once, which indicates that a common suppressive mechanism for cancer ("cure" or "preventive cure") is well within the realm of possibility and that for all their biochemical diversity, cancer cells can be universally recognized and whacked in an efficient way.

The same actually holds about young people. Our own species is highly resistant to almost all cancers at once when young, and incidence of most cancers tends to grow with age along a very similar curve, which, again, indicates some commonalities under that extreme biochemical diversity.

Most of the progress in fight against cancer in the 21st century comes from biological approaches, not from better chemicals. The chemical approach may be fundamentally flawed.

Yeah, a "cure" in form of a chemical drug is likely impossible. But a "cure" in a form of a genetic treatment etc. may well be possible.

Anyone down for adding some whale genome to theirs? :)

So it turns out Richard Feynman, after working in Los Alamos on the first nuclear bomb, and before going on to win a Nobel in Physics, actually did a stint as a biologist at CalTech. In fact he was doing some of the earliest work on ribosomes... so fundamental that he could have been the first person to discover that most all ribosomes were functionally equivalent:

"It would have been a fantastic and vital discovery if I had been a good biologist. But I wasn't a good biologist. We had a good idea, a good experiment, the right equipment, but I screwed it up: I gave her infected ribosomes ­­ the grossest possible error that you could make in an experiment like that. My ribosomes had been in the refrigerator for almost a month, and had become contaminated with some other living things. Had I prepared those ribosomes promptly over again and given them to her in a serious and careful way, with everything under control, that experiment would have worked, and we would have been the first to demonstrate the uniformity of life: the machinery of making proteins, the ribosomes, is the same in every creature. We were there at the right place, we were doing the right things, but I was doing things as an amateur -- stupid and sloppy."

So one of the world's best physicists almost became one of the world's most prominent molecular biologists, but actually fucked up the experiment for practical reasons.

I think this really underscores how not every problem is fundamentally a math problem... In the real world, especially with biology there's a shit ton of practical tedious things to deal with that can hamstring even the most brilliant experiments.

1. Funding. Drugs have a low probability of success and a long lag time. Investors think in discount rates. A high-risk venture like biology is less appealing than an advertising-based tech platform with zero marginal costs.

2. Costs. Biology uses a LOT of proprietary instruments, kits, and chemical reagents. A lot. It also needs a lot of manual labor that would be difficult to roboticize.

3. Time. Biological experiments operate on biological timescales. Code takes seconds to run. Cell cultures take a day to grow. Even fancy new multiplexed sequencing assays take a while. You have the library prep time, the sequencing, and the downstream analysis. Its a long process. Now imagine waiting years and years to see if a drug in clinical trial prevents Alzheimer's.

4. Complexity. How do you make an equation for a giant network of weakly-interacting parts? Biology is a very "data-driven" field for this reason. The introduction of new microscopy, chemical conjugation techniques, and high-throughput assays has only made things worse. I genuinely hope some black box AI will be able to help us make sense of this mess and cure cancer. But medicine is full of interventions and incomplete prior histories, which will make naive association models hard to use.

As Michael Levin said it, "reductionism is aptly named, it reduces what you can do". Do check out his research btw, it's some seriously impressive stuff. According to him, cancer, in particular, is simply a result of a group of cells electrically disconnecting from the surrounding tissue. He was able to force them to reconnect in one of his experiments, curing the tumor without killing anything.

And it's also just as reductionist, trying to represent everything as electrical interactions.

That's not true. We know a lot of molecular-level details about morphogenesis. The classic Sonic Hedgehog signalling is a good example: https://en.wikipedia.org/wiki/Sonic_hedgehog_protein

Is it possible that electric potentials might play some role in some organisms? Certainly. However, we know for sure that they don't act alone. Chemical signalling definitely happens.

> And it does make sense for cancer to be a morphogenesis defect

It doesn't, really. Even assuming Levin's models are correct, most cancers have nothing to do with morphogenesis. Cancers are caused by internal genetic cell malfunctions, that stop them from reacting to external signals properly. It doesn't really matter if signals are electric or molecular ones.

The default state for normal human cells is "dead". If you take a random cell and put it in a Petri dish, it'll likely die. Most cells need to receive constant molecular signals from nearby cells to _not_ die. Once this mechanism is broken, you get cancer.

The "skilled", "famous" and "influential" scientists in cancer research spend almost all their time fighting for grants, undermining each other, jockeying for influence, exaggerating their own importance, publishing phony papers etc.

Underpaid novices, trainees, grad students, and postdocs with little prior experience do the actual work in the lab.

It is much, much worse than a reasonable person would imagine!

You'd be surprised. One of their larger challenges has been that the regulatory environment is very murky. It's definitely not anything goes, but it's not as well roadmapped as it is for human drugs.

It seems there is a steady stream of progress in biology and its medical tie-ins, but it is slow and cumbersome. Unrelated: It seems like a lot of the techniques in biology are discovered partly by chance (ie dedicated work in an area that bears fruit, perhaps not in an expected form). Ways to leverage various bacteria, phages, proteins etc to provide insight, or perform a manipulation. The molecular biology techniques we have available seem like a tiny fraction of what we could discover. And in a way, it seems as much engineering or tool-making as science.

[0]: https://www.youtube.com/watch?v=Q7iWB6xbkwQ

* Cancer is not a disease, it's a family of diseases, with a wide spectrum of causes, symptoms, and treatments.

* Cancer is, fundamentally, a mutiny of your own cells against the rest of your body. Because cancer is fundamentally a part of you, it can shanghai some of the resources your body normally uses for itself, like blood vessel infrastructure. It can also masquerade as a healthy part of you, for example to your immune system. Hell, part of your immune system can become cancer (as in leukemia)!

* Cancer metastasizes, which means that even if you get rid of the main tumor, a few of those rebellious cancer cells can use your circulatory or lymphatic systems to start new rebel colonies elsewhere in your body, which means you could be fucked all over again. Treating this form of cancer can be an arduous, painful, sickness-inducing process of chemo- and/or radiotherapy.

We are closer than ever to "a cure for cancer" with things like immunotherapy treatments which can program your immune system to target the specific kind of cancer you have. Unfortunately, most of these need to be tailored per patient, which procedure is neither cheap nor routine. And it still doesn't always work for all cancers!

Biology especially human biology is a lot harder simply because experiments have bigger ethical issues.

Even if you have desperate cancer patients there are limits how and what you can test.

And we have others fields where all these brilliant people according to him are working and all the money goes and the problems are also not solved.

A human body belonging to a lucky person might live the better part of a century, all the time which it grows, heals itself when injured, processes food into new resources, hosts an example of the best known thinking machine in the world (the human brain), and literally has the machinery to produce one or more additional human beings. These are capabilities which are incredibly difficult to replicate artificially, so much so that producing a robot that could do even half of these things remains firmly in the realm of science fiction. And it wasn't designed, it was evolved, so it's about the worst mess of spaghetti code you could imagine. It's simply a hard problem.

In physics you can totally shatter your test object to get to the inner functions.

You can't do that with living creatures especially humans.

- The preclinical drug discovery phase was not mentioned much. This phase involves discovering/designing/creating an actual drug against a potential biological mechanism/target uncovered by biology/genomics. Although this is generally seen as a more tractable element of the drug development path, it can still be very difficult and requires many years of additional research. Even so, some targets are well known to have great potential in disease, but it has been very difficult to generate a selective and potent drug against it. This phase typically does involve more "theoretically defined" research (although it is still messy) with chemists, biophysicists and pharmacologists, which fit more into the article's mention of the "mathematician". Yet, in line with the article, these often-talented people cannot always create a suitable drug for a given target. Providing further evidence that it is not "just" a lack of mathematically talented individuals.

- The reasons for drug failures in the clinic can be more numerous than alluded to in the article. Some drugs are very toxic, not only because of off-target side effects, but potentially also due to on-target side effects. In deadly cancers, this might not be so much of a problem, but it can still be a limiting element when we combine drugs to limit the surfacing of drug resistant cancer cells.

- As mentioned by others, cancer cells are cells from our own body, and they utilize our body's functions in excessive or highly altered manners to grow. However, blocking these functions selectively in cancer cells can be difficult (especially if non-genetically) as these functions often are still present in all other cells.

- Cancer metastasizes, cancer cells can spread across the body and generate new tumors elsewhere in the body. This can be almost anywhere, and it can be very difficult to detect early metastases in a patient. Hence, stopping treatment too early, even though the doctors might not see any cancer cells and the treatment has strong side effects, means you could redevelop cancer. Moreover, some metastatic sites might be in locations that are hard to reach for a given drug, hence they might not be fully targeted by a given drug.

- Full-blown cancers typically do not develop solely because of a single driving genetic alteration. Instead, a series of 2~5 genetic/biological alterations from a potential pool of dozens of genetic factors in combination leads to an aggressive tumor. Note though that it can be true that a single genetic alteration is dominant and drives a large part of cancer growth. Even in a single cancer type (e.g. colon cancer) the combination of 2-5 alterations leading to aggressive cancer can be different. Moreover, even within a single patient, different metastatic sites might evolve on their own and acquire different combinations of these driving factors. Hence, to truly treat some cancers targeting multiple drivers would be ideal, and each patient might require a relatively unique approach.

- Cancer cells are genetically unstable and can rapidly alter their genetic makeup. The DNA of normal human cells consists of two sets of 23 chromosomes that are well-organized and add up to ~3 billion DNA base pairs (the code of life). Cancers show very variable chromosome numbers and some advanced cancers can have more than 100 chromosomes. Moreover, cancer chromosomes can be heavily altered, where pieces of other chromosomes integrate into others, translocate, bridge, reconnect. It can be a total soup of >10 billion DNA base pairs. Moreover, these changes are different for each cancer, so every cancer patient will be more or less unique. This genetic instability also allows cancer cells to rapidly mutate and adapt/develop resistance to a given drug treatment.

Edit: I've thought of something worth adding. I've been told that certain datasets related to biology and chemistry are normally paywalled. I wonder if restricted access to information due to copyright is also hampering the field's ability to iterate more quickly. It seems like a field that's serious about rapid iteration could make as much data and information available to the public to encourage increased collaboration and propagation of knowledge. Is Nature still considered the most prestigious journal?

A lot of that "slow progress" is due to the FDA's intransigence and conservatism, even in the face of patients like me who are dying already anyway: https://jakeseliger.com/2023/07/22/i-am-dying-of-squamous-ce...

See also "The dead and dying at the gates of oncology clinical trials" https://jakeseliger.com/2024/01/29/the-dead-and-dying-at-the... and my wife on what trying to enroll in clinical trials is like from the patient's perspective: "Please be dying, but not too quickly: a clinical trial story" https://bessstillman.substack.com/p/please-be-dying-but-not-...

We could and should be moving faster. I'm dying anyway, so if a treatment doesn't work or even harms me, I'm not much worse off than I was before the treatment.

We've made tremendous progress in the last 20-30 years. There are some cancers that *are* effectively curable. And others still vex us just as much as they always have.

I'm not an expert so feel free to correct me, but my understanding is that there are plenty of other animals, such as the naked mole rat, that are effectively immune to all forms of cancer because while it might not technically be one disease, all forms of cancer share enough characteristics that there exist a small group of genes that are able to suppress it or develop an immune response that effectively prevents a tumor from growing.

In Vinge's novel "Rainbow's End" there is a particular fragment about how they had automated biological research, with robots at big connected research factories making all the experiments. Such factories would go a long way to shorten the "long cycles" the article mentions, and they perhaps would democratize bio-sciences research. I don't think there are any technological obstacles to building those factories; robots have been employed at factories for a long time and there many robots already used in expensive biological labs. But note the word "expensive". In cultural terms, "expensive" means "big commitment that has to be more important than anything else that can be bought with that money.". This is the cultural part I refer to. As a society, we discuss many things, but biological research is very, very low in that awareness list. In Europe, for example, putting spyware on people's phones is way higher in the agenda. And thus, the public would never approve a 20% (or any other number) of the government budget going towards biological research, unless they had material evidence that that money would indeed cure cancer. For the same reason, they wouldn't use use 20% of their savings to invest on biotech. But if, by the right means, those perceptions could be changed, we would see a revolution in biology and really substantial breakthroughs in life-expectancy.

Doesn't exactly sound like a money making scheme.