Beneath cancer’s genetic chaos, tumor cells may be confined to just a handful of recurring states, revealing a simpler path to treatment.
Cancer is often defined by its complexity: countless mutations, shifting cell populations, and tumors that evolve under pressure. But Andrea Califano’s research points to a surprising possibility: that beneath all that variation, cancer cells may be confined to only a handful of stable states.
It is this hidden order that led Califano, a physicist by training and now a cancer researcher, to describe cancer as a “quantum disease.” The comparison is not literal; rather, it reflects the idea that tumor cells may occupy discrete biological states, much as electrons are limited to specific energy levels in an atom.
“We’re really just following the data,” says Califano, the Clyde ’56 and Helen Wu Professor of Chemical Biology at Columbia University Vagelos College of Physicians and Surgeons and head of Biohub New York. “What we’ve seen over and over again is that each type of cancer has a limited number of cellular states. Just as electrons are restricted to a limited number of quantized energy states in an atom, cancer cells can only occupy one of these stable states or be in rapid transit between them. More critically, these states are conserved across virtually all patients with a specific type of cancer.”
Two recent Nature Genetics papers from the Califano lab strengthen this idea. If researchers can identify every state available to a particular cancer and find drugs that eliminate each one, they may be able to design treatments that work across many patients instead of creating a different strategy for every tumor.
A Finite Map of Cancer
“If cancer is quantum, the good news is that we may not need personalized medicine,” Califano says. “A combination of therapies targeting the handful of distinct, detectable states may be all that is needed, and those combinations should be effective for virtually every patient.”
Traditional chemotherapy and radiation attack a defining feature of many tumors: rapid cell division. They do this largely by inflicting overwhelming DNA damage, but healthy tissues containing fast-growing cells can also be harmed.
Targeted therapies take a more selective approach. Herceptin, for example, blocks abnormal HER2 signaling that can cause cancer cells to multiply uncontrollably. Drugs like this helped establish personalized medicine, in which treatment is matched to the mutations found in an individual tumor.
The challenge is scale. Tumors can carry many genetic alterations, and different patients with the same cancer may have very different combinations. Cancer cells can also evolve under treatment, allowing resistant populations to survive and expand.
Looking Beyond Mutations
Califano argues that mutation-focused treatment addresses only part of the disease.
“Going after mutations in cancer genes—so-called oncogenes—is a very powerful concept,” Califano says. “Yet, most often, it only buys patients some extra time. The reality is that cancer is much more complex, because the potential number of mutational patterns in about 2000 oncogenes is larger than the number of atoms in the universe.”
His team is therefore studying what those mutations ultimately make a cell become. Many different genetic routes may converge on the same cellular state, producing cells that depend on a similar set of proteins and may share the same therapeutic vulnerabilities.
“I was trained a physicist, and what physicists like to do is figure out how things work,” Califano says. “Cancer is like a box with a complex set of levers and pulleys and gears that work together. Can we fully reconstruct these mechanisms to make sense of what we observe?”
Finding Cancer’s Master Regulators
To reconstruct that machinery, Califano’s laboratory collects molecular data from living cancer cells and uses it to build what is essentially a mathematical model of the disease. The goal is to determine which proteins control a cell’s identity rather than simply cataloging every mutation it contains.
The analysis highlights proteins known as master regulators, which work together to maintain a malignant state. “These are the generals that control the state of the cell,” Califano says. “If you shut down these proteins—we call them cancer’s master regulators—the cell can’t sustain its malignant state anymore.”
Earlier work from the laboratory suggested that the number of master regulator combinations is unexpectedly small. An analysis of more than 10,000 samples from over 20 cancer cohorts identified only 112 distinct states. Later studies of individual cells found one cancer with a single state, while none examined so far had more than seven.
This limited number could expose a weakness shared across patients. Even when two tumors have different mutations, they may still depend on the same master regulators if their cells occupy the same state.
Six States in Pancreatic Cancer
Identifying those states is only the first step. A tumor can contain several cellular populations at once, and some cells may move from one state to another when conditions change, or treatment removes their competitors.
In a paper published Aug. 26 in Nature Genetics, Pasquale Laise, Mikko Turunen, and Alvaro Curiel Garcia analyzed hundreds of thousands of pancreatic cancer cells one at a time. Every tumor contained cells drawn from the same six states.
“What really differed among patients wasn’t their cancer cells’ states but rather the fraction of cells in one state versus another, which seems to be key effect of mutations,” Califano says.
The finding suggests that mutations may influence the proportions of states within a tumor more than the identities of the states themselves. That could explain how genetically different tumors arrive at similar biological outcomes.
Why One Drug May Not Be Enough
“The good news is that, because the same states are found in every patient, if you find a few drugs that, together, target all the states, that combination could be potentially curative. The bad news is that in pancreatic cancer each state can spontaneously change into any of the other states, suggesting that we may never be able to treat these tumors with a single drug.”
A drug might destroy cells occupying one state, only for surviving cells to shift into another and restore the tumor. A successful therapy may, therefore, need to attack every available state simultaneously.
Each drug would target a particular cellular state, creating a combined treatment designed to block every possible route of escape.
Targeting a Fatal Childhood Cancer
Diffuse midline glioma may offer an opportunity to test this strategy. This rare pediatric brain cancer is universally fatal and is difficult to treat because it develops in sensitive structures that control essential functions.
Ester Calvo Fernandez, a graduate student in Califano’s laboratory, used the clinical-grade algorithms OncoTreat and OncoTarget to search for existing drugs predicted to act against its cellular states. She identified three candidates, avapritinib, ruxolitinib, and larotrectinib, that together could target all seven states detected in the disease.
In a paper published April 22 in Nature Genetics, Calvo Fernandez confirmed in laboratory experiments that each drug attacked its predicted states. All but one of the two drug combinations aimed at complementary states performed dramatically better than the corresponding drugs used alone.
The researchers now hope to evaluate the full three-drug combination in a clinical trial. Although all three medicines already exist, their safety and effectiveness as a combined treatment for diffuse midline glioma would still need to be established in patients.
From Mathematical Models to Treatment
“That’s the ultimate goal. A lot of our work sound theoretical,” Califano says. “But everything we predict gets tested in the lab and, when possible, in the clinics. We’ve already shown that these analyses can predict therapies for patients who had failed multiple lines of therapy.
“Hopefully, the identification of drugs targeting hyperconserved, quantized cancer states will help many more.”
References:
“Systematic design of combination therapy by targeting master regulators of coexisting diffuse midline glioma cell states” by Ester Calvo Fernández, Lorenzo Tomassoni, Xu Zhang, Junqiang Wang, Aleksandar Obradovic, Pasquale Laise, Aaron T. Griffin, Lukas Vlahos, Hanna E. Minns, Diana V. Morales, Christian Simmons, Matthew Gallitto, Hong-Jian Wei, Timothy J. Martins, Pamela S. Becker, John R. Crawford, Theophilos Tzaridis, Robert J. Wechsler-Reya, James Garvin, Robyn D. Gartrell, Luca Szalontay, Stergios Zacharoulis, Cheng-Chia Wu, Zhiguo Zhang, Andrea Califano and Jovana Pavisic, 22 April 2026, Nature Genetics.
DOI: 10.1038/s41588-026-02550-w
“Developmental and MAPK-responsive transcription factors regulate distinct malignant cell states and associated genetic dependencies in pancreatic cancer” by Pasquale Laise, Mikko Turunen, Alvaro Curiel-Garcia, Lorenzo Tomassoni, H. Carlo Maurer, Ela Elyada, Bernhard Schmierer, Jeremy Worley, Jordan Kesner, Xiangtian Tan, Ester Calvo Fernandez, Yuanqing Xue, Yining Chen, Kelly Wong, Urszula N. Wasko, Somnath Tagore, Alexander L. E. Wang, Sabrina Ge, Alina C. Iuga, Aaron T. Griffin, Winston Wong, Gulam A. Manji, Mariano J. Alvarez, Faiyaz Notta, David A. Tuveson, Kenneth P. Olive and Andrea Califano, 26 August 2026, Nature Genetics.
DOI: 10.1038/s41588-026-02714-8
This work was supported by the Lustgarten Foundation for Pancreatic Cancer Research, the Irving Institute for Clinical and Translational Research, the NIH (grants U54 CA209997, S10OD012351, S10OD021764, P30CA013696, R35CA197745542, and 5P30DK026687), the Pancreas Center at Columbia/NY Presbyterian Hospital, the Sigrid Juselius Foundation, the Swedish National Genomics Infrastructure (project SNIC 2017-7-265); Uppsala Multidisciplinary Center for Advanced Computational Science, and a Charles H. Revson Senior Fellowship in Biomedical Science (Grant No. 22-22).
Never miss a breakthrough: Join the SciTechDaily newsletter.
Follow us on Google and Google News.
1 Comment
Using patients with a disease that has no effective treatment before safety and efficacy is established for the drug combination should not be a problem. If the combination isn’t safe, the child may die. If the child isn’t treated, they will die. Many parents would be happy to have their child participate in a trial of that sort, as long as they are assured that the drug will be available the their child as soon as the trial has established efficacy.