Cancer’s resistance may be written years before treatment begins, new hypothesis argues

Treatment resistance remains the leading cause of cancer mortality, and for decades oncologists have modeled it as an adaptive response: tumors evolve under the pressure of chemotherapy or targeted drugs, and hardy survivors emerge. A new hypothesis and theory article published in Frontiers in Oncology by Cesar A. Perez of the Sarah Cannon Research Institute at Florida Cancer Specialists & Research Institute and Annette R. Khaled of the Burnett School of Biomedical Sciences at the University of Central Florida argues that this framing captures only half the story. Writing in the journal’s Cancer Metabolism section, the authors propose that a substantial component of resistance is established before any therapeutic exposure, forged by the chronic metabolic environment of the tissue in which the malignancy arises. By the time an oncologist sees the patient, they contend, the Darwinian competition that selects for survival may already be largely complete.

The core of the argument is that metabolic dysregulation acts as a selective pressure on premalignant tissue, not merely as a passive risk factor in the conventional epidemiologic sense. Chronic hyperinsulinemia increases bioavailable insulin-like growth factor 1 (IGF-1) and sustains activation of the PI3K–AKT–mTOR and RAS–MAPK signaling cascades, the two master growth pathways that drive proliferation and survival. Paradoxically, in tissues where insulin resistance has developed, mitogenic sensitivity is preserved even as glucose disposal falters, creating an environment highly permissive to clonal selection. Elevated inflammatory mediators, including interleukin-6, leptin, and other adipokines, further amplify proliferative signaling while dampening apoptotic responses. A systematic review using the hyperinsulinemic–euglycemic clamp confirmed that severe insulin resistance is present in patients with cancer relative to matched controls, with a mean glucose disposal rate of 4.7 versus 7.5 mg/kg/min, and limited evidence suggests this metabolic adaptation may precede clinical diagnosis rather than follow it.

The mechanism by which metabolic state becomes inscribed into cellular behavior runs through the epigenome. Metabolic intermediates—S-adenosylmethionine (SAM), acetyl-CoA, α-ketoglutarate, and NAD+—serve as obligate substrates for chromatin-modifying enzymes, continuously coupling a cell’s metabolic condition to its epigenetic landscape. Shifts in one-carbon metabolism can directly alter histone methylation and downstream transcription across every cell division that occurs during the years of subclinical dysregulation preceding diagnosis. Among the relevant modifications, the authors focus on histone H3 lysine 9 (H3K9) methylation, catalyzed by the methyltransferases EHMT1 and EHMT2—known as GLP and G9a—which deposit mono- and dimethyl marks using SAM as the methyl donor. H3K9me2 at apoptotic and differentiation loci has been linked to drug resistance in prior studies, making this mark a candidate bridge between metabolism and treatment failure.

Two distinct inputs shape this chromatin landscape, and the authors are careful to separate them. Hypoxia is the driver of H3K9me2 gain: low oxygen stabilizes the G9a protein and increases H3K9me2 at tumor-suppressor and apoptotic loci, effectively silencing the genes that would otherwise command damaged or abnormal cells to die. SAM availability works separately. When SAM is limiting, EHMT1/2 preferentially preserve H3K9me1 while higher-order di- and trimethylation decline, so SAM depletion does not itself add to H3K9me2. One-carbon and SAM status is therefore best understood as setting the available H3K9me1 substrate pool, whereas hypoxia-stabilized G9a generates the resistance-associated H3K9me2. The consequence of both processes is an elevated apoptotic threshold and an enrichment of epigenetically primed, apoptosis-resistant cells before a tumor is histologically apparent or clinically detected. The authors note an unresolved gap: whether G9a regulation in premalignant epithelial compartments mirrors the dynamics seen in metabolic tissues such as liver and adipose, where G9a expression drops under high-fat conditions, has not been systematically characterized.

A compelling precedent for the idea that metabolic intervention can undo epigenetic hardening comes from pancreatic cancer, where pharmacologic inhibition of the metabolic pathway driving epigenomic reprogramming reversed both the chromatin state and the malignant phenotype. Against this mechanistic backdrop, the clinical prediction converges: tumors arising in metabolically dysregulated tissue should harbor larger fractions of pre-existing resistant subclones. Parallel mechanisms, not competing ones, produce a cell population more likely to progress, survive dormancy, and resist treatment. In this framing, resistance is less a response to therapy than the clinical unveiling of a cellular architecture established years earlier.

The population-scale data that speak to this hypothesis have arrived, perhaps unexpectedly, through the GLP-1 receptor agonists, the drug class behind the current obesity-treatment revolution. These agents reduce hyperinsulinemia, attenuate IGF-1 bioavailability, and suppress systemic inflammatory markers, making them the most informative pharmacologic probe of the metabolic hypothesis—though the authors stress they are not its therapeutic endpoint. The emerging observational signal is provocative. A 2026 meta-analysis of 24 observational studies enrolling nearly 4 million patients found a 30 percent reduction in obesity-related cancer risk, and a large retrospective cohort confirmed reduced overall cancer incidence in adults with obesity, with a hazard ratio of 0.83. Body mass index–independent reductions in acute myeloid leukemia and breast cancer incidence, persisting after adjustment for metabolic covariates, hint at a mechanism operating through metabolic signaling rather than adiposity reduction alone, though these data remain preliminary conference abstracts. In a preclinical colitis-associated carcinogenesis model, the dual agonist tirzepatide reduced tumor burden by suppressing metabolic pathways without inducing weight loss.

The most striking clinical evidence comes from a retrospective cohort of 841,831 patients with breast cancer drawn from the TriNetX network, in which propensity-matched GLP-1RA users demonstrated approximately 60 percent lower all-cause mortality at both 5 and 10 years compared with non-users, alongside a large relative improvement in recurrence-free survival. A finding of this magnitude in a dataset of this size commands attention and scrutiny, all the more so given its retrospective design. Intriguingly, when GLP-1RA users were compared not with untreated controls but with users of sodium-glucose cotransporter 2 inhibitors—another drug class that corrects insulin resistance through a distinct mechanism—the survival difference was attenuated, leaving only modest residual benefit after covariate adjustment. The implication is subtle but potentially transformative: if two mechanistically distinct agents that share the common property of metabolic normalization produce convergent oncologic signals, then the operative variable may not be either drug, but the metabolic environment that both drugs correct.

The counterweight is substantial, and the authors confront it directly. A meta-analysis of 48 randomized controlled trials enrolling 94,245 participants found no effect of GLP-1RAs on obesity-related cancer incidence, and a separate RCT-based meta-analysis reported increased thyroid and colorectal cancer risk, with Mantel–Haenszel odds ratios of 1.55 and 1.27 respectively. The authors attribute these discrepancies to trial design rather than failure of the mechanism: the trials were not designed with cancer endpoints, had inadequate follow-up durations for solid tumor latency, and lacked metabolically enriched patient selection. But they are careful not to treat these as exculpations of the null result. The metformin precedent is instructive: the MA.32 trial and a subsequent meta-analysis of 22 randomized trials confirmed no benefit on disease-free or overall survival, despite a compelling mechanistic rationale. The intervention was simply not potent enough. By that logic, meaningfully reversing the metabolic selective pressure may require a more potent, broader-acting intervention deployed in a metabolically high-risk population.

What elevates the hypothesis above speculation is its alignment with the somatic evolution literature, which indicates that resistance predominantly pre-exists. Multiple orthogonal approaches—cell-free DNA analysis, high-complexity barcode tracing, and single-cell sequencing—have collectively demonstrated that acquired resistance frequently arises from pre-existing subclones selected by therapeutic pressure. The same single-cell analyses that identify pre-existing resistant genotypes also document treatment-associated transcriptional reprogramming, indicating that selection and adaptation operate together. What has been missing is a specific account of how the resistant architecture becomes established in the first place, and the metabolic framework supplies one: chronic metabolic stress creates conditions in which EHMT1/2 gain the upper hand in premalignant tissue, concentrating repressive marks at genes governing cell death and differentiation, yielding a subpopulation already primed to resist apoptosis before any treatment is given. These clones, the authors argue, might not be generated by treatment but revealed by it. The framework explicitly does not claim to account for reversible drug-tolerant persister states or to exclude resistance genuinely acquired during treatment.

The authors specify the experiment that would directly test the hypothesis, and it has not been performed: correlating pretreatment fasting insulin, HOMA-IR, and IGF-1/IGF-binding protein 3 ratio with baseline subclonal architecture, H3K9me2 state, circulating tumor DNA heterogeneity, and treatment outcome in metabolically unselected patients initiating systemic therapy. Reverse causation predicts metabolic abnormality follows neoplastic change; this model requires the opposite ordering. Treatment-induced plasticity predicts resistant chromatin states emerge only after exposure; this model predicts they are demonstrable in treatment-naive tissue. Each prediction is testable, and none has yet been tested directly. The urgency is sharpened by young adults with early-onset colorectal cancer who are neither obese nor diabetic, a cohort for whom conventional risk factors do not suffice as explanation, and by the CHALLENGE trial, which provided the first level I evidence in stage III and high-risk stage II colon cancer that structured post-chemotherapy exercise—an intervention known to reduce fasting insulin, IGF-1 bioavailability, and inflammatory markers—improves disease-free survival. A cautionary note comes from the neoadjuvant setting, where concurrent GLP-1RA use during chemoimmunotherapy for early-stage triple-negative breast cancer was associated with reduced pathologic complete response in one retrospective cohort, though a subsequent multi-institution study found diabetes mellitus, not GLP-1RA use, independently associated with reduced response. The authors are explicit that the evidence does not yet establish that GLP-1 receptor agonists prevent recurrence or resistance, and that patients with established metabolic indications should be treated for those indications on their own merits. But the central untested prediction—that pretreatment metabolic state correlates with baseline subclonal architecture, chromatin state, and treatment outcome—is tractable, fundable, and immediately actionable, and the answers will matter whatever they turn out to be.

Subject of Research: How chronic metabolic dysregulation epigenetically primes pre-existing cancer treatment resistance before therapy

Article Title: Metabolic oncology: clonal selection and the pre-existing origins of cancer resistance

Article References: Metabolic oncology: clonal selection and the pre-existing origins of cancer resistance. (n.d.). https://doi.org/10.3389/fonc.2026.1951576

Image Credits: AI Generated

DOI: 10.3389/fonc.2026.1951576

Keywords: cancer metabolism, treatment resistance, clonal selection, epigenetics, H3K9 methylation, EHMT1/EHMT2, GLP-1 receptor agonists, hyperinsulinemia, IGF-1, tumor evolution, metformin, early-onset colorectal cancer