Abstract 6417: Deciphering aberrant STING pathway and exploring oncolytic viruses therapy in low grade serous ovarian carcinoma
Bibliographic record
Abstract
Abstract There are two serous ovarian cancer histotypes, low and high grade (LGSOC and HGSOC), which are distinct clinical and biological entities. LGSOC is a rare histotype with a relatively stable genome, while HGSC is more common and genomically unstable. Somewhat surprisingly LGSOC expresses high levels of the stimulator of the interferon genes (STING). The STING pathway recognizes cytoplasmic double-stranded DNA and mounts innate cellular immunity through interferon-beta type I production. Our objective is to investigate the aberrant STING signaling in LGSOC and test the effectiveness of oncolytic viruses against LGSOC. We used immunohistochemistry on tissue microarrays (TMAs) to assess STING protein expression in different ovarian cancer histotypes. Whole proteome analysis was applied to identify differentially expressed proteins in LGSOC and HGSOC patient samples (both n=9). Further, a semi-targeted proteomics approach was used to evaluate the expression levels of the STING pathway-related proteins in LGSOC, HGSOC, and LGSOC precursor tumors (each subtype, n=20). To evaluate the key transcription, phosphorylation, and translocation events in STING signaling, we treated LGSOC cell lines with an agonist (dsDNA90) and performed qPCR, immunoblotting, and immunofluorescence experiments, respectively. We tested the viability of the LGSOC cell lines in response to Vaccinia Virus (VV), and Vesicular Stomatitis Virus (VSV) based oncolytic vectors with or without immunostimulatory transgenes. Our results show that STING protein levels were consistently higher in LGSOC TMAs relative to other histotypes. Proteomics analysis showed that the half of the 16 most differentially expressed proteins were the effectors of STING signaling with unexpectedly lower expression in LGSOC, suggesting that despite the robust levels of STING in LGSOC tumors, the pathway is not fully active. Attenuated STING translocation and expression of IFNB1 and other cytokines in LGSOC cell lines confirm the aberrancy in the STING pathway. Semi-targeted proteomics revealed the considerable overexpression of STIM1 in LGSOC patient tumors, which has previously been shown to sequester STING in the endoplasmic reticulum. The treatment with VV and VSV oncolytic viruses significantly reduced the proliferation of LGSOC cell lines. In summary, we find attenuated STING signaling in LGSOC, possibly due to overexpression of STIM1 preventing STING translocation. Although oncolytic viruses show promising results in LGSOC cell lines, more research is needed to determine the optimal treatment strategy, testing oncolytic viruses expressing various transgenes and combination therapies. Citation Format: Almira Zhantuyakova, Dawn Cochrane, Gian Negri, Sandra E. Spencer Miko, Taha Azad, Jutta Huvila, Marta Llaurado Fernandez, Mark Carey, Gregg B. Morin, John Bell, David Huntsman. Deciphering aberrant STING pathway and exploring oncolytic viruses therapy in low grade serous ovarian carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6417.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".