Loss of PARP7 Increases Type I Interferon Signaling in EO771 Breast Cancer Cells and Prevents Mammary Tumor Growth by Increasing Antitumor Immunity
Bibliographic record
Abstract
PARP7 is a member of the ADP-ribosyltransferase diphtheria toxin-like (ARTD) family and acts as a repressor of type I interferon (IFN) signaling. PARP7 inhibition causes tumor regression by enhancing antitumor immunity, which is dependent on the stimulator of interferon genes (STING) pathway, TANK-binding kinase 1 (TBK1) activity, and cytotoxic CD8+ T cells. To better understand PARP7′s role in cancer, we generated and characterized PARP7 knockout (Parp7KO) EO771 mouse mammary cancer cells in vitro and in a preclinical syngeneic tumor model using catalytic mutant Parp7H532A mice. Loss of PARP7 expression or inhibition of its activity increased type I IFN signaling, as well as the levels of interferon-stimulated gene factor 3 (ISGF3) and specifically unphosphorylated-ISGF3 regulated target genes. This was partly because PARP7′s modification of the RelA subunit of nuclear factor κ-B (NF-κB). PARP7 loss had no effect on tumor growth in immunodeficient mice. In contrast, injection of wildtype cells into Parp7H532A mice resulted in smaller tumors compared with cells injected into Parp7+/+ mice. Parp7H532A mice injected with Parp7KO cells failed to develop tumors and those that developed regressed. Our data highlight the importance of PARP7 in the immune cells and further support targeting PARP7 for anticancer therapy.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".