Why haven't biologists cured cancer?

Cancer is among the stickiest of medical wickets, for several reasons:

* 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!

Lovely article. The part that resonates most with me is towards the end: What some software developers would refer to as "friction". Medical tests are high friction for reasons the author hinted at. I'm optimistic some of the cfDNA or fragmentome cancer screenings will be useful for catching cancer early. If you try to dig on the topics, you'll find that the projects (GRAIL etc) are proud their methods and datasets are proprietary. The ones that play the political and business game best are getting funding for trials.

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.

This idea of "curing cancer" as if cancer was a monolithic disease really needs to die.

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?

Saying we can never cure cancer because it's not a single disease doesn't quite strike me as accurate.

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.

As an aside, it's interesting to note that there is a hypothesis that one reason why humans, and most other species, do not regrow limbs is precisely as a means of protecting against cancer. The few species that are able to regenerate limbs usually have to activate the regeneration, and that activation involves turning on an immune surveillance system that seeks out potentially cancerous cells and kill them efficiently.