The question
Do some established cancers remain dependent on one dominant cancer-driving gene?
This is the specific idea being tested.
The Hypothesis Critic · A guide for everyone
Oncogene Addiction Hypothesis
Do some established cancers remain dependent on one dominant cancer-driving gene?
What you need to knowSome defined cancers remain strongly dependent on a dominant driver, despite other genetic changes.Relative explanatory fit: Leading among models compared
Why the evidence supports this: Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer.
Review summary
Claim assessed: Cancers with prospectively defined driver–tumor pairs depend on continuous dominant oncogene signaling for maintenance, so selective signaling withdrawal produces tumor regression.
Finding: The preregistered scope-matched rule reports SC1 at Η: endogenous conditional-driver and common-conduit interventions, genetic withdrawal, mechanistic resistance/rescue and baseline molecularly defined clinical trials converge on tumor-maintenance dependence across named pairs. Significant primary nonresponse, host/apoptosis dependence and persistence prevent Θ or Ω. SC2 pan-cancer one-driver generalization and SC3 residual-cell eradication remain Γ as broader mechanistic claims without matching general causal validation.
Key points
- SC1: Selective withdrawal of dominant oncogene signaling regresses tumors in defined driver–cancer pairs. — HSEF Η, Moderate confidence.
- SC2: Most cancers depend on a single dominant oncogene in the same way. — HSEF Γ, Moderate confidence.
- SC3: Driver withdrawal eliminates residual populations and gives durable treatment-free control. — HSEF Γ, Moderate confidence.
Verdict and review details
- Evidence grade
- HSEF Η — Strong convergent causal evidence, intervention-sensitive
- Confidence
- Moderate
- Framework
- HSEF v5.3
- Review date
- Literature cutoff
- Published
- Review attribution (recorded)
- Codex
Evidence scope: 66 primary reports; literature cutoff 2026-10-08; source examination UTC date 2026-10-09; bounded critical review, not exhaustive systematic review.
The grade applies to the stated claim. Model rankings and individual subclaim grades remain separate from the overall causal-evidence grade.
Full scientific assessment and references · Scorecard (JSON) · Review source (Markdown)
The result at a glance
Some defined cancers remain strongly dependent on a dominant driver, despite other genetic changes.
Read the labels in this illustration
THE MAIN FINDING Some defined cancers remain strongly dependent on a dominant driver, despite other genetic changes. The idea Do some established cancers remain dependent on one dominant cancer-driving gene? Dominant driver active Driver stays essential Tumour maintained Proposed chain — plausible, not established What the evidence supports A continuing dependence in defined cancers Best fit in this review Dominant driver Cancer cells Dominant driver In tested settings, turning the driver off limits tumour survival. What remains uncertain Which cancers depend on one driver and which do not How resistance routes emerge when the driver is blocked How long dependence persists as cancers evolve Evidence comes from cells, animals, and people — each setting carries different weight. Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer. Conceptual illustration
Supported explanation
A continuing dependence in defined cancers
Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer.
Evidence for the stated claim
Strong causal evidence
This conclusion applies to the people, conditions and outcomes covered by the review.
Which explanation fits?
This explanation fits best in the reviewed comparison.
A separate question from the causal evidence grade
How does this explanation compare with alternatives?
Leading among models comparedThe reviewed hypothesis ranks first among 5 models compared for this stated claim.
Claim under review: rank 1 among 5 compared models.
Leading explanation: Scoped dominant-oncogene maintenance dependence.
Position in this comparison: First rank.
The causal grade asks how well the stated causal claim is established. This comparison asks which of the assessed explanations fits the reviewed findings better. A leading explanation can remain unproven. Models can overlap or include the tested mechanism; an alternative ahead does not make that mechanism irrelevant. These ordinal ranks apply within this review; they do not measure the size of a difference or rank scientific strength across topics.
Read the labels in this illustration
TWO EXPLANATIONS, COMPARED A · The idea under review Do some established cancers remain dependent on one dominant cancer-driving gene? Proposed chain Dominant driver Stays essential Tumour maintained Each arrow is a proposal, not a proven step. Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer. B · Leading explanation A continuing dependence in defined cancers This explanation fits best in this comparison Dominant driver Dependence holds in defined cancers A better fit is not proof of every part of the explanation. These explanations can overlap. Conceptual illustration
Idea being tested · rank 1
Do some established cancers remain dependent on one dominant cancer-driving gene?
Strong causal evidence for the stated claim.
Supported explanation · rank 1
A continuing dependence in defined cancers
Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer.
These explanations can overlap. Ranking their fit to the evidence is separate from deciding how firmly a cause has been established.
See all the explanations compared
Rank 1: Scoped dominant-oncogene maintenance dependence — A defined baseline driver can remain a rate-limiting maintenance node despite other genomic changes.
Rank 2: Clonal bypass and lineage plasticity — Selection restores drug-resistant target signaling or substitutes a different maintenance route.
Rank 3: Reversible drug-tolerant state — A reversibly altered cellular state survives treatment and can seed later resistance.
Rank 4: Non-addicted residual reservoir — A residual compartment can survive strong signaling inhibition while the bulk regresses.
Rank 5: Non-oncogene stress-support dependency — Residual tumor states can acquire requirements for unmutated stress-support functions.
What this means
✓
Strong causal evidence
Some defined cancers remain strongly dependent on a dominant driver, despite other genetic changes.
Evidence rating: Η · Moderate confidence. How the evidence was assessed.
The important distinction
Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer.
Health and treatment
The preregistered scope-matched rule reports SC1 at Η: endogenous conditional-driver and common-conduit interventions, genetic withdrawal, mechanistic resistance/rescue and baseline molecularly defined clinical trials converge on tumor-maintenance dependence across named pairs. Significant primary nonresponse, host/apoptosis dependence and persistence prevent Θ or Ω. SC2 pan-cancer one-driver generalization and SC3 residual-cell eradication remain Γ as broader mechanistic claims without matching general causal validation.
From an idea to an explanation
Seeing two things together does not prove one causes the other.
What is observed?
Look for the proposed factor and the outcome, in the people or systems covered by the claim.
What else explains it?
A continuing dependence in defined cancers. Turning off the driver limits tumour survival in tested settings. This does not apply automatically to every cancer.
What test tells them apart?
Turn off and restore the driver in the same cancer setting, tracking survival and resistance.
What to test next
What evidence would make the answer clearer?
Read the labels in this illustration
WHAT WOULD MAKE THE ANSWER CLEARER A research question Turn off and restore the driver in the same cancer setting, tracking survival and resistance. then then Change the proposed cause Proposed test Driver turned OFF, then RESTORED — same cancer setting driver on driver off restored Driver left on — comparison group Measure the relevant outcome Proposed test Tumour cell survival is tracked Resistance is watched for variant Measured in every group. Check the result independently Proposed test First team measures Second team repeats An independent check of the result. Same measures, fresh eyes — no shared data until the end. This storyboard shows the logic of a test. It does not show a result. The question is whether the same cancer still needs its driver — and what happens when it returns. Conceptual illustration
A useful next question
Turn off and restore the driver in the same cancer setting, tracking survival and resistance.
Change the proposed cause
Check that the intended change really happened.
Measure the relevant outcome
Allow for other factors and compare with suitable controls.
Check whether it holds up
Look for independent confirmation and the limits of the effect.
These are questions for research, not a claim that the proposed studies have already succeeded.
Read the scientific study designs
Proposed tests: 1 test design(s) are registered in the scorecard.
In plain terms, researchers would change the proposed cause, check that it changed as intended, then measure a meaningful outcome while controlling plausible alternatives. The result should be able to support or count against the claim—not only show that a pathway exists.
Experiment 1: Registered boundary experiment
Study design: In baseline molecularly defined driver–tumor cohorts and matched native models, combine allele-specific withdrawal with direct engagement measures, matched driver restoration and longitudinal lineage-resolved residual-cell tracking. Prospectively include nonresponders; perturb candidate bypass and reservoir dependencies separately. Follow sustained control both during treatment and after predefined cessation.
What would be measured: Bulk regression, apoptosis, driver signaling, residual clone fate, lineage transition, relapse and treatment-free survival over a prespecified interval
Important controls: Restoration at native abundance, non-target genotype controls, equal initial tumor burden, host/apoptosis strata, inhibitor-resistant alleles, barcode collision and rare-clone detection controls, matched cessation eligibility
Result that would support the claim: Independent native models and baseline patient strata show driver-specific regression, while identified modifiers explain most initial failures and residual survival; selective residual-dependency correction adds sustained treatment-free control
Result that would count against it: Fully verified selective withdrawal leaves substantial bulk tumors unchanged across baseline-defined pairs, or restored driver cannot reverse a purported withdrawal effect; residual populations recur despite candidate rescue and elimination controls
Explore the evidence
Read the complete scientific review.
Follow the studies, detailed comparisons and evidence ratings behind this guide.
Open the scientific review →