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Record W4409629085 · doi:10.1158/1538-7445.am2025-6127

Abstract 6127: Genomic instability regulates STING mediated anti-tumor immunity through distinctive cytosolic DNA structures

2025· article· en· W4409629085 on OpenAlexaff
Shayla R. Mosley, Natalie Lapa, Courtney Mowat, Kristi Baker

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStingGenome instabilityImmunityDNABiologyCancer researchCell biologyDNA damageGeneticsImmune system

Abstract

fetched live from OpenAlex

Abstract Background. Cancer genomes are characterized by instability, with significant levels of DNA damage and mutation due to DNA repair defects. In colorectal cancer (CRC), defects in mismatch repair define the microsatellite instable (MSI) subtype, with stronger immunogenicity and better prognosis than the more common chromosomally instable (CIN) subtype. The mechanisms behind these differences are unknown, but their understanding could identify strategies to improve CIN CRC prognosis. The STING pathway detects foreign DNA in the cytosol, leading to induction of innate and adaptive immune responses. In cancer cells, STING also recognizes self cytosolic DNA (cyDNA) in the form of micronuclei or diffuse fragments generated by endogenous or treatment induced DNA damage. Our lab previously identified this pathway as a key player in the increased cytotoxic T cell infiltration characteristic of MSI CRCs. As MSI CRCs do not contain more cyDNA than CIN, we hypothesize that specific sequence or structural patterns exist within cyDNA from different CRC subtypes that lead to differential STING activation and thereby induction of overall anti-tumor immunity. Methodology. We first aimed to examine whether cyDNA produced in MSI vs CIN CRC cells differentially induce STING and thereby anti-tumor immunity. CyDNA isolated from MC38 CRC cells with mutations in Mlh1 (modeling MSI) or Kras (CIN) were used to stimulate dendritic cells (DCs), key mediators of anti-tumor immunity. We found equal concentrations of MSI cyDNA more strongly activates STING, and thereby cytotoxic T cells, than CIN cyDNA. CyDNA from MSI CRC patient organoids showed similar results. Next, we aimed to characterize specific changes in cyDNA composition in MSI vs CIN CRC cells and examine how these alterations affect STING signalling. Sequencing identified patterns prevalent in highly stimulatory cyDNAs, including microsatellites. Stimulation with oligos and cyDNA enriched for microsatellites indicate enhanced STING and cytotoxic T cell activation through improved cGAS binding. Likewise, adoptive transfer of DCs activated by microsatellite rich DNAs induced stronger DC and T cell activation in orthotopic CIN tumors. Preliminary data suggests secondary DNA structures may influence this process. Finally, we aim to evaluate the contribution of micronuclei on STING activation in MSI vs CIN CRCs. DC stimulations with micronuclei isolated from MSI and CIN cells indicate MSI micronuclei also lead to enhanced STING activation over CIN micronuclei. We will evaluate micronuclei composition to identify underlying mechanisms. Significance. CRC is the second most deadly cancer worldwide, and immune recognition is crucial to treatment efficacy. This project will further our understanding of immune differences between MSI and CIN CRCs that may be used to develop therapeutic strategies, such as STING agonists, to improve CIN patient prognosis. Citation Format: Shayla Mosley, Natalie Lapa, Courtney Mowat, Kristi Baker. Genomic instability regulates STING mediated anti-tumor immunity through distinctive cytosolic DNA structures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6127.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.380
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), 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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