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Record W4414491666 · doi:10.1158/2326-6074.cimm25-a021

Abstract A021: Sumoylation blockade exposes the dark epigenome to drive ZBP1 viral mimicry for cancer immunotherapy

2025· article· en· W4414491666 on OpenAlexaboutno aff
Maria Goicoechea, Nathalia Moraes de Vasconcelos, Tencho Tenev, Pascal Meier

Bibliographic record

VenueCancer Immunology Research · 2025
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsnot available
Fundersnot available
KeywordsNecroptosisInnate immune systemCancer immunotherapyEpigenomeEffectorCancer cellSUMO proteinChromatin

Abstract

fetched live from OpenAlex

Abstract Viral mimicry strategies are emerging as powerful tools in cancer therapy by leveraging the reactivation of endogenous elements that remain dormant in the 'dark epigenome'. Re-expression of transposable elements (TEs) from these latent chromatin regions can generate potent immunostimulatory RNAs that trigger innate immune responses against tumors. A key effector in this context is the innate immune sensor ZBP1, which triggers necroptotic cell death and immune activation in response to viral or endogenous Z-form nucleic acids. Our data reveal that ZBP1 activity is tightly suppressed in cancer cells through two converging and sequential mechanisms: SUMOylation and inhibitor of apoptosis proteins (IAPs). First, SUMOylation represses TEs, thereby preventing their transcription into immunogenic nucleic acids that can accumulate in the cytoplasm, trigger nucleic acid stress, and activate an interferon response. The resulting IFN-rich environment not only reinforces TE expression and contributes to further RNA buildup, but also upregulates ZBP1, priming cells for ZBP1-mediated necroptosis. Execution of this death pathway is facilitated when Z-RNA species within the TE-derived transcripts engage ZBP1 and trigger downstream necroptotic signaling. At this stage, IAPs impose a secondary brake, restraining necroptotic cell death despite ZBP1 activation. This model was mechanistically dissected using a series of gene-specific knockout models alongside the SUMO inhibitor subasumstat and SMAC mimetics, both of which are currently being evaluated in separate clinical trials. We demonstrate that the proposed regulatory axis operates in murine primary stromal and cancer cell lines and in human cancer cells across distinct tumor types. Based on these findings, we propose a combinatorial treatment strategy that employs these clinically available agents to simultaneously target SUMOylation and IAPs, thereby reactivating ZBP1 and unleashing a powerful, intrinsic viral-mimicry circuit that drives robust antitumor immunity. This dual-targeting approach offers a novel therapeutic avenue - turning epigenetically silenced viral elements into cancer’s Achilles’ heel. Citation Format: Maria Goicoechea, Nathalia M. Vasconcelos, Tencho Tenev, Pascal Meier. Sumoylation blockade exposes the dark epigenome to drive ZBP1 viral mimicry for cancer immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr A021.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.360
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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