Cancer kills only the confused.
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Cancer kills only the confused.

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DEEPWAVE

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Made with 💙 by me (how to).

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Status: Draft Epistemic status: Hypothesis

I was very surprised when reading Alberts Molecular Biology of the Cell that we basically don’t know how metastasis (cancer spreading through the body) works. This is my theory, plus some thoughts on what cancer even is.

Metastasis can only happen at Phase Boundaries

To understand cancer, I think you have to ask: why do young people get less of it? Why is cancer something that occurs at all times in most species, but is effectively only lethal to aged animals?

There are two standard answers to this: either because cancer is caused by combining certain mutations, and that just gets more likely with time, or because our immune system gets weaker as we age. These certainly play a role, but I want to propose a more fundamental theory: for cancer to spread (metastasize, which ultimately kills you) it needs to find areas where new cancer can form. Animals that don’t die from cancer (young people, naked mole rats, plants, etc.) don’t control the arising of cancer, but they effectively make it impossible for cancer to spread. The way they do this is by minimizing the phase boundaries between separate cellular communication collectives, where the goal state of the local environment (the “phase identity”) is less clearly defined. As we age, these areas increase, as intercellular signaling degrades, and we get lethal forms of cancer.

An Antropomorphized Intro to Cancer

Let's unpack this hypothesis. First, what IS cancer? In the simplest worldview, cancer is just "a change in the level at which evolutionary pressure dominates". (For more on this, see the interview with Athena Aktipis on why cancer is a fundamental phenomena in our universe or her book) When I'm healthy, evolution works on me, all my cells sacrifice each other (literally. There are immune cells which throw out their DNA as nets to trap invaders, the most badass seppuku imaginable), for the greater good (me). But sometimes, cells stop sharing that goal and become rogue, selfish, individuals. Cancer is rebellion.

Now this usually doesn't pose a problem, our internal military (immune system) squashes down rebellions all the time. But more importantly, our cells talk to each other constantly, indoctrinating, controlling, checking in with their neighbors, and justifying each and every action to the collective. If any cell notices they are stepping out of the line, they rather commit suicide (apoptosis) than harm the great overlords (the germline, me). This explains why, in my opinion, the most important oncogenes (a mutation that makes cancer more likely) are all related to gap junctions, see Bioelectric signaling: Reprogrammable circuits underlying embryogenesis, regeneration, and cancer: Cell. Gap junctions are connections between cells that allow them to exchange their cell plasma, their internals, and therefore all their inputs, beliefs, decisions, and outputs. They exchange their selves. Now if you and your partner both had perfect, constant, involuntary mind-reading, would it even make sense to talk about two different you's?

This mechanism - of sharing goals between large collections of cells through gap junctions - is what keeps you alive, and rebellions at bay. But sometimes, though unfortunate accidents, cells not only acquire mutations that make them dangerous (want to spread their ideas, acquire resources, don't want to die, etc. all the classical convergent instrumental goals of misaligned optimizers), they also lose their gap junctions, their safety mechanism. You have cancer.

What do I mean with Phase Boundaries

On Cancer:

On Misalignment:

Why Would AI Want to do Bad Things? Instrumental Convergence

How can we predict that AGI with unknown goals would behave badly by default? The Orthogonality Thesis video: https://www.youtube.com/watch?v=hEUO6pjwFOo Instrumental Convergence: https://arbital.com/p/instrumental_convergence/ Omohundro 2008, Basic AI Drives: https://selfawaresystems.files.wordpress.com/2008/01/ai_drives_final.pdf With thanks to my excellent Patrons at https://www.patreon.com/robertskmiles : Jason Hise Steef Jason Strack Chad Jones Stefan Skiles Jordan Medina Manuel Weichselbaum 1RV34 Scott Worley JJ Hepboin Alex Flint James McCuen Richárd Nagyfi Ville Ahlgren Alec Johnson Simon Strandgaard Joshua Richardson Jonatan R Michael Greve The Guru Of Vision Fabrizio Pisani Alexander Hartvig Nielsen Volodymyr David Tjäder Paul Mason Ben Scanlon Julius Brash Mike Bird Tom O'Connor Gunnar Guðvarðarson Shevis Johnson Erik de Bruijn Robin Green Alexei Vasilkov Maksym Taran Laura Olds Jon Halliday Robert Werner Paul Hobbs Jeroen De Dauw Konsta William Hendley DGJono robertvanduursen Scott Stevens Michael Ore Dmitri Afanasjev Brian Sandberg Einar Ueland Marcel Ward Andrew Weir Taylor Smith Ben Archer Scott McCarthy Kabs Kabs Phil Tendayi Mawushe Gabriel Behm Anne Kohlbrenner Jake Fish Bjorn Nyblad Jussi Männistö Mr Fantastic Matanya Loewenthal Wr4thon Dave Tapley Archy de Berker Kevin Vincent Sanders Marc Pauly Andy Kobre Brian Gillespie Martin Wind Peggy Youell Poker Chen Kees Darko Sperac Paul Moffat Noel Kocheril Jelle Langen Lars Scholz

Why Would AI Want to do Bad Things? Instrumental Convergence

On Phase Boundaries:

Brain Criticality - Optimizing Neural Computations

To try everything Brilliant has to offer—free—for a full 30 days, visit http://brilliant.org/ArtemKirsanov/. The first 200 of you will get 20% off Brilliant’s annual premium subscription. My name is Artem, I'm a computational neuroscience student and researcher. In this video we talk about the concept of critical point – how the brain might optimize information processing by hovering near a phase transition. Patreon: https://www.patreon.com/artemkirsanov Twitter: https://twitter.com/ArtemKRSV OUTLINE: 00:00 Introduction 01:11 - Phase transitions in nature 05:05 - The Ising Model 09:33 - Correlation length and long-range communication 13:14 - Scale-free properties and power laws 20:20 - Neuronal avalanches 25:00 - The branching model 31:05 - Optimizing information transmission 34:06 - Brilliant.org 35:41 - Recap and outro The book: https://mitpress.mit.edu/9780262544030/the-cortex-and-the-critical-point/ REFERENCES (in no particular order): 1. Zimmern, V. Why Brain Criticality Is Clinically Relevant: A Scoping Review. Front. Neural Circuits 14, 54 (2020). 2. Beggs, J. M. The criticality hypothesis: how local cortical networks might optimize information processing. Phil. Trans. R. Soc. A. 366, 329–343 (2008). 3. Beggs, J. M. The cortex and the critical point: understanding the power of emergence. (The MIT Press, 2022). 4. Heffern, E. F. W., Huelskamp, H., Bahar, S. & Inglis, R. F. Phase transitions in biology: from bird flocks to population dynamics. Proc. R. Soc. B. 288, 20211111 (2021). 5. Beggs, J. M. & Plenz, D. Neuronal Avalanches in Neocortical Circuits. J. Neurosci. 23, 11167–11177 (2003). 6. Avramiea, A.-E., Masood, A., Mansvelder, H. D. & Linkenkaer-Hansen, K. Long-Range Amplitude Coupling Is Optimized for Brain Networks That Function at Criticality. J. Neurosci. 42, 2221–2233 (2022). 7. O’Byrne, J. & Jerbi, K. How critical is brain criticality? Trends in Neurosciences 45, 820–837 (2022). 8. Haldeman, C. & Beggs, J. M. Critical Branching Captures Activity in Living Neural Networks and Maximizes the Number of Metastable States. Phys. Rev. Lett. 94, 058101 (2005). 9. Beggs, J. M. Being critical of criticality in the brain. Frontiers in Physiology. Derivation that only power laws are scale-free: https://youtu.be/m6FQqXAHNT8 CREDITS: Icons by https://biorender.com Brain 3D models were modeled with Blender software using publicly available BrainGlobe atlases (https://brainglobe.info/atlas-api) Ising model zooming animations: https://youtu.be/MxRddFrEnPc This video was sponsored by Brilliant

Brain Criticality - Optimizing Neural Computations

Citation

In academic work, please cite this essay as:

Groß, Heye, “Metastasis can only happen at Phase Boundaries”, heye.earth (2023-11-15), available at https://heye.earth/telomeres/.