How can cancer’s quantum-like states revolutionize treatment strategies?

Researchers at Columbia University’s Vagelos College of Physicians and Surgeons have identified exactly 112 distinct cellular states across over 10,000 tumor samples drawn from more than 20 cancer cohorts. The finding emerges from work led by Andrea Califano, the Clyde ’56 and Helen Wu Professor of Chemical Biology and head of Biohub New York.

What “quantum” means in cancer biology

Califano describes cancer as a “quantum disease” — not in a literal physical sense, but to convey that tumor cells occupy discrete, stable biological states, analogous to electrons confined to quantized energy levels in an atom. “We’re really just following the data,” he says. “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.”

From mutations to master regulators

Traditional approaches focus on genetic mutations, but Califano argues this addresses only part of the disease. “Going after mutations in cancer genes—so-called oncogenes—is a very powerful concept,” he 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 lab instead investigates what those mutations cause a cell to become — its functional identity — identifying proteins known as master regulators that jointly sustain malignant states. “These are the generals that control the state of the cell,” he explains. “If you shut down these proteins—we call them cancer’s master regulators—the cell can’t sustain its malignant state anymore.”

Six universal states in pancreatic cancer

A study published August 26 in Nature Genetics analyzed hundreds of thousands of individual pancreatic cancer cells. Every tumor examined contained cells drawn exclusively 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 research suggests mutations influence the proportions of states within a tumor more than the identities of the states themselves — a mechanism that may explain how genetically divergent tumors converge on similar biological behavior.

Why single-drug therapy fails in state-switching cancers

Because pancreatic cancer cells can spontaneously shift from one state to any other, eliminating a single state with one drug may only prompt surviving cells to transition into another, restoring the tumor. “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,” Califano says.

Three-drug combination for diffuse midline glioma

In diffuse midline glioma — a universally fatal pediatric brain cancer — researchers detected seven states. Ester Calvo Fernandez, a graduate student in Califano’s lab, used clinical-grade algorithms OncoTreat and OncoTarget to identify three existing drugs predicted to collectively target all seven: avapritinib, ruxolitinib, and larotrectinib. A paper published April 22 in Nature Genetics 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 monotherapies. The full three-drug regimen is now slated for clinical trial evaluation, though its safety and efficacy in patients remain to be established.

From mathematical models to clinical testing

“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.”

“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).