Gene Editing and Curing Cancer: CRISPR, Immunotherapy, and Quantum Computing
Book: Quantum Supremacy: How the Quantum Computer Revolution Will Change Everything Author: Michio Kaku ISBN: 978-0385548366
Chapter 11 is where Kaku moves from quantum physics into biology. He covers cancer detection, immunotherapy, CRISPR gene editing, and a fascinating paradox about why elephants almost never get cancer. The quantum computing angle is still there, but this chapter is really about biology and what we now understand about cancer at the genetic level.
Cancer Is Not One Disease
Something Kaku explains well early in the chapter. In 1971, Nixon declared the “War on Cancer.” Historians later concluded that cancer won. Nobody actually understood what cancer was.
The answer turned out to be: cancer is a disease of our genes, but triggered by environmental factors or just random mutations. Not one disease. Thousands of different types of mutations. Cancer cells are basically ordinary cells that have forgotten how to die.
Normally, cells are programmed to die (apoptosis) so new cells can replace them. When that programming breaks, cells reproduce without limit. They become immortal. That is exactly why they kill us.
One interesting detail: cancer mainly spreads after our reproductive years, so evolution had little pressure to eliminate cancer genes. Natural selection does not care much about what happens after you have had children.
Detecting Cancer Early: Liquid Biopsies and Sniffing
Kaku covers two interesting approaches to early detection. First, liquid biopsies. Cancer tumors shed cells and molecules into blood, urine, and saliva. We have known this for over 100 years. Only recently has genetic engineering made it possible to detect just a few hundred cancer cells floating around, years before a tumor forms though. Right now liquid biopsies can detect up to fifty different types of cancer.
Kaku even mentions “smart toilets” that could scan your bodily fluids every time you use the bathroom. Sounds like science fiction but the logic is solid.
Second, sniffing cancers. Dogs can detect prostate cancer from urine with 99 percent accuracy. They have 220 million nasal scent receptors versus our 5 million, and can detect concentrations of one part per trillion.
Andreas Mershin at MIT is building a “nano-nose” with microsensors 200 times more sensitive than a dog’s nose. Right now it costs about $1,000 per sample, but Mershin wants this to become as common as the camera in your cell phone. Processing data from millions of such sensors would require quantum computers.
Immunotherapy and the Immune System Paradox
What happens when cancer is already there? Immunotherapy is a newer option that Kaku explains well.
Cancer cells fly under the radar of our immune system. They are our own cells gone bad, so T and B cells do not recognize them. Immunotherapy works by extracting white blood cells, inserting genetic information about the specific cancer using a harmless virus, and injecting the reprogrammed cells back. Some patients with hopeless prognoses have seen their cancers completely disappear.
Only works for some cancers though, and modifying white blood cell genetics is not always perfect. Side effects can be serious, sometimes fatal.
Kaku then explains something I found genuinely fascinating: how the immune system works at all. There are essentially unlimited possible viruses and bacteria. How does the immune system recognize dangerous ones it has never seen before?
The answer is elegant. B cells have Y-shaped receptors with randomly generated genetic codes at their tips. With around 10^12 possible combinations, almost every possible antigen pattern is already represented. Then the body removes receptors that match its own cells. What remains can identify foreign threats, even ones never seen before.
The process is not perfect though. Sometimes “self” codes are not fully removed, and the immune system attacks the body. That is autoimmune diseases: lupus, rheumatoid arthritis, type 1 diabetes. Sometimes the reverse happens: codes for real threats get accidentally removed, and dangerous cells slip through. That might explain some cancers.
CRISPR: Cut and Paste for Genes
Probably the most exciting part of this chapter. Gene therapy goes back to the 1980s, with at least 10,000 known genetic diseases to target. Early attempts used viruses to deliver corrected genes, but the body would attack the virus. In 1999, a patient died during a trial and funding dried up.
The breakthrough came from studying how bacteria defend against viruses. Bacteria release chemicals that cut viral genes at precise points. Emmanuelle Charpentier and Jennifer Doudna isolated this mechanism and got the Nobel Prize in 2020. Kaku compares it to the jump from typewriters to word processors. CRISPR does cut, copy, and paste for DNA.
One key target is the p53 gene, sometimes called “The Guardian of the Genome.” When it works correctly, p53 suppresses tumors. When mutated, it is involved in about half of all common cancers. It is a long gene with many sites where mutations can develop. Smokers often develop cancers at three specific mutation points on p53, which can actually prove that lung cancer came from cigarettes.
CRISPR is already being used on several diseases: cancer (University of Pennsylvania removed three genes that help cancer hide from the immune system), sickle cell anemia, AIDS (editing the CCR5 gene so the virus cannot enter cells), cystic fibrosis, and Huntington’s disease.
Peto’s Paradox: Why Elephants Do Not Get Cancer
My favorite part of the chapter. Biologist Richard Peto noticed something strange: elephants, with their massive bodies and trillions of cells dividing constantly, should have much higher cancer rates than smaller animals. They do not though.
The answer? Elephants have twenty copies of the p53 gene. We humans have only one. These extra copies work with another gene called LIF to suppress cancer.
It gets interesting though. Whales have only one copy of p53 and one version of LIF, yet they also have low cancer rates. Whales must have other, still unknown, anti-cancer genes. Greenland sharks can live for 500 years, probably thanks to some undiscovered genetic protection. Evolution has found different solutions to the same problem in different species.
As researcher Carlo Maley says: “Every organism that evolved large body size has a different solution to Peto’s paradox.” Nature has already solved the cancer problem multiple times. We just need to find out how. Quantum computers might be what we need to analyze the massive genetic datasets and find these anti-cancer genes hiding in the animal kingdom.
The Bottom Line
Kaku’s vision is not necessarily curing cancer completely, but making it manageable. Like the common cold: there are over 300 rhinoviruses that cause colds and they mutate constantly, so we just live with it. Cancer might follow the same path. Detect it early with liquid biopsies, treat it precisely with CRISPR and immunotherapy, and it becomes a nuisance instead of a death sentence.
For engineers reading this book, the chapter is a good reminder that the hardest computing problems are not always about servers and databases. Sometimes they are about simulating molecular interactions that are fundamentally quantum mechanical. That is exactly where quantum computers could make the biggest difference.
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