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Record W4412646762 · doi:10.3389/fimmu.2025.1639853

Transglutaminase 2 regulates ovarian cancer metastasis by modulating the immune microenvironment

2025· article· en· W4412646762 on OpenAlexafffund
Dalia Ibrahim, Mélanie Grondin, Kristianne J.C. Galpin, Sara Asif, Emily A. Thompson, Sarah Nersesian, John Abou‐Hamad, Maryam Echaibi, Galaxia M. Rodriguez, Pauline Navals, Elizabeth A. Macdonald, B. P. K. Ryan, David P. Cook, Jeffrey W. Keillor, Barbara C. Vanderhyden

Bibliographic record

VenueFrontiers in Immunology · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsOvarian cancerTumor microenvironmentCancer researchMetastasisTissue transglutaminaseCancerImmune systemBiologyCancer cellMedicineImmunologyInternal medicineEnzyme

Abstract

fetched live from OpenAlex

Introduction Ovarian cancer is the most lethal gynecological malignancy. Deepening our knowledge of the interactions within the tumor microenvironment (TME) is important for discovering new targeted treatment strategies. Transglutaminase 2 (TG2) is a protein implicated in many biological and pathophysiological processes, including promoting tumor progression in ovarian cancer. Its role in disease progression has been studied in ovarian cancer cells; however, its role in the ovarian TME is less understood. Methods In this study, for the first time, we assessed the therapeutic potential of novel covalent irreversible small molecule TG2 inhibitors in xenograft models of ovarian cancer. We further elucidated the role of TG2 in ovarian cancer cells and syngeneic tumors by immune phenotyping using flow cytometry, RNA sequencing, and immunohistochemistry to characterize the contribution of TG2 in the TME to the metastatic process of ovarian cancer. Results To investigate the transamidation catalytic and GTP binding activities of TG2 in cancer cells, we used several TG2 inhibitors, some of which decreased invasiveness of human ovarian cancer cell lines in vitro and lengthened survival of the SKOV3 xenograft model. Using the ID8 Trp53 -/- Brca1 -/- and KPCA.B syngeneic mouse models of ovarian cancer, we defined the contribution of TG2 in the TME to the metastatic process. Lack of TG2 in the TME prolonged survival in the ID8 Trp53 -/- Brca1 -/- metastatic model, but it did not affect survival in the non-metastatic KPCA.B model. Through extensive analysis of the immune composition in both the primary tumor and metastatic ascites in the ID8 Trp53 -/- Brca1 -/- model, we discovered that the lack of host TG2 resulted in decreased frequency of immunosuppressive tumor-associated macrophages, and increased frequency of T cells, NK cells, and B cells. RNA sequencing of the primary tumors with or without TG2 present in the TME, revealed an enrichment of pathways related to B cell activation and regulation. Discussion These findings highlight the importance of TG2 in the TME for ovarian cancer metastasis, potentially by activation of humoral immunity and specifically highlight a crucial role for TG2 in modulating B cells to prolong survival in mouse models of ovarian cancer.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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