All findings

RNF43 + GNAS

RNF43 and GNAS co-occurrence in pancreatic cancer (MSK-MET)

Inconclusive: not measurable by the current pipelineCo-occurrence · Evidence: pattern across patients, not yet tested within subtypes

DataMSK-MET (2021) · Pancreatic cancer

This cohort pools pancreatic adenocarcinoma with pancreatic neuroendocrine tumours, so a pattern here can reflect the mix of tumour types rather than biology within one of them.

Engine's conclusion

Inconclusive. The current version of the test cannot measure this (the patient group is too small or no longer analysed, or the genes are too rarely altered there), so its earlier numbers are shown for reference only.

A well-studied pair (385 papers): on the map it is known biology, a positive control rather than an overlooked discovery.

Signal (x) is the corrected significance on the map's scale, discounted from 3% to 1% because the cohort-composition confound is not yet controlled. Efficacy (y) is credibility times actionability.

Structure & site3D structure: AlphaFold

These genes are altered together more often than chance would predict.

Primary site

Pancreas

This finding's tumour type arises in the highlighted organ.

No structure profile is curated for this gene.

RNF43Gene

A human gene in this finding. Not in the curated driver set, so no structured profile is shown.

RNF43 mutations in pancreatic cancer →RNF43 co-mutations by tumour type →Other findings with RNF43 →

No structure profile is curated for this gene.

GNASGene

A human gene in this finding. Not in the curated driver set, so no structured profile is shown.

GNAS mutations in pancreatic cancer →GNAS co-mutations by tumour type →Other findings with GNAS →

Anatomical figure from the EBI Expression Atlas anatomogram, and predicted structures from the AlphaFold Protein Structure Database (both CC-BY-4.0). A model shows the protein's healthy fold; a highlighted residue marks a recurrent cancer position, not a prediction of a specific mutation's effect.

Statistical evidence
Sources

Weak evidence. Below the α=0.05 reject threshold (e≥20). Unlike a single-look p, this stays valid under the engine's continuous re-testing.

Why it sits here on the map

Molecular-subtype certification is unresolved. Control scope was not recorded. Molecular-subtype control is unverified. The association remains visible, but does not qualify as a subtype-controlled discovery.

The two axes are variables: signal (x) and efficacy (y = credibility × actionability). A point high on both lands in the frontier (top-right). A strong signal with low credibility sits low and to the right: statistically strong, not worth pursuing.

Same question in other cohorts
Earlier model annotation (set aside)

A model wrote this for an earlier measurement of this record. The engine does not stand behind the current result (not measurable by the current pipeline), so the annotation is not part of the record; it is kept here for reference only.

HypothesisModel-generated hypothesis (not evidence)
Written by gpt-5.6-luna

A language model wrote this from the evidence listed below. It is annotation: the engine's verdict above comes only from the measured statistics, never from this text.

RNF43 and GNAS most likely co-occur across pancreatic tumours because the cohort is enriched for a shared pancreatic molecular or lineage subgroup, potentially including IPMN-associated disease, in which both alterations are selected through related upstream biology; this is more plausible than deterministic co-amplification or demonstrated within-tumour cooperation.

Argument strength (model self-report)24%
After adversarial review24%
The argument
  1. 1The co-occurrence is a reproducible population-level signal rather than a simple consequence of globally unstable tumours: the burden-adjusted DISCOVER test gives p = 1.3e-2, log2 odds ratio = 2.2, with 10 observed versus 4.3 expected double-altered tumours, and the association survives multiple testing at q = 6.6e-2.E1E16
  2. 2The leading explanation is molecular-subtype or lineage composition, ranked slightly above a shared upstream driver: a subgroup enriched for both alterations can generate population-level co-occurrence without implying that the genes cooperate within each tumour. The shared-upstream-driver explanation is a close second because both genes are catalogued as cancer drivers, although those catalogues do not establish a pancreatic relationship between them.E1E10E11
  3. 3Deterministic co-amplification of neighbouring genes is lower-ranked because the supplied evidence reports alteration co-occurrence but gives no genomic-location or copy-number evidence that RNF43 and GNAS reside on, or are driven by, the same amplicon.E1
  4. 4A generic data artifact is also lower-ranked, but remains possible through cohort composition, subtype imbalance, or assay-specific alteration calling; the heterogeneity-aware burden adjustment reduces, but does not eliminate, that concern.E1
  5. 5Genuine within-tumour cooperation ranks last on the current evidence. The provided paper records discuss IPMN as a pancreatic precursor or clinically relevant entity but do not establish that RNF43 and GNAS interact, cooperate, or are co-selected in the same tumour; the broader co-mention record therefore supports an under-explored lead rather than a mechanistic conclusion.E6E7E8
  6. 6This lead CONVERGES with the Cybergenic corpus at the level of interpretation: prior APC–RNF43, KRAS–RNF43, TP53–GNAS, and EGFR–GNAS analyses likewise frame alteration patterns as population-level selection or molecular partitioning rather than automatic within-tumour interaction. It is not direct replication because those findings concern different gene pairs and cancer contexts.E12E13E14E15
  7. 7The RNF43 tumour-expression increase is consistent with biologically relevant disease involvement, but it does not distinguish shared lineage composition from a shared upstream driver or prove that the DNA alterations cooperate.E2E3E10
What would confirm or refute it

In an independent pancreatic cancer cohort, annotate IPMN-associated versus conventional ductal tumours and relevant molecular subtypes, then test RNF43–GNAS co-occurrence with multivariable logistic regression adjusted for subtype, lineage, tumour purity, copy-number burden, and sequencing platform. In parallel, perform single-cell or clonal DNA sequencing on double-positive tumours to determine whether both alterations occur in the same clone; a functional co-dependency screen with individual and combined perturbation would be required before claiming within-tumour cooperation.

Strongest competing explanation (model)

The strongest deflating explanation is unmeasured subtype or lineage composition, which could create the association without a direct shared driver; a shared upstream process remains nearly tied for first place. Co-amplification and technical calling bias cannot be excluded without locus-level copy-number and orthogonal validation. Because no cited paper actually studies the RNF43–GNAS relationship, a within-tumour cooperation mechanism is unearned, and the FDR-adjusted signal is only moderate despite the sizeable odds ratio.

Adversarial review (second model pass)

Weakest link: The central IPMN/lineage explanation is unsupported by the numbered evidence, while the association rests on only 10 co-altered tumours with modest multiple-testing evidence and could reflect cohort composition or other artifacts.

Evidence the argument cites

Model-written annotation, not a finding. The statistics it cites are real and are shown above; the argument connecting them is a hypothesis that needs wet-lab or clinical validation before it means anything.

Cite this finding
Permalink
https://cybergenic.im/findings/9b22e8f9-2f7e-497f-a1b5-1aa356011158
First seen
13 Aug 2026
Prediction registry
Locked 13 Aug 2026, row hash 26dfb1b7cbe0f0e16e93bde3cc7813be (not testable out of sample). How the registry works
BibTeX
@misc{cybergenic_9b22e8f9,
  author       = {{Cybergenic}},
  title        = {{RNF43 and GNAS co-occurrence in pancreatic cancer (MSK-MET)}},
  year         = {2026},
  howpublished = {\url{https://cybergenic.im/findings/9b22e8f9-2f7e-497f-a1b5-1aa356011158}},
  note         = {Research engine finding, first seen 2026-08-13; prediction locked 2026-08-13, registry row hash 26dfb1b7cbe0f0e16e93bde3cc7813be},
  month        = aug
}

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