Identification of PADI2 as a potential breast cancer biomarker and therapeutic target
Bibliographic record
Abstract
BACKGROUND: We have recently reported that the expression of peptidylarginine deiminase 2 (PADI2) is regulated by EGF in mammary cancer cells and appears to play a role in the proliferation of normal mammary epithelium; however, the role of PADI2 in the pathogenesis of human breast cancer has yet to be investigated. Thus, the goals of this study were to examine whether PADI2 plays a role in mammary tumor progression, and whether the inhibition of PADI activity has anti-tumor effects. METHODS: RNA-seq data from a collection of 57 breast cancer cell lines was queried for PADI2 levels, and correlations with known subtype and HER2/ERBB2 status were evaluated. To examine PADI2 expression levels during breast cancer progression, the cell lines from the MCF10AT model were used. The efficacy of the PADI inhibitor, Cl-amidine, was tested in vitro using MCF10DCIS cells grown in 2D-monolayers and 3D-spheroids, and in vivo using MCF10DCIS tumor xenografts. Treated MCF10DCIS cells were examined by flow-cytometry to determine the extent of apoptosis and by RT2 Profiler PCR Cell Cycle Array to detect alterations in cell cycle associated genes. RESULTS: We show by RNA-seq that PADI2 mRNA expression is highly correlated with HER2/ERBB2 (p = 2.2 × 106) in luminal breast cancer cell lines. Using the MCF10AT model of breast cancer progression, we then demonstrate that PADI2 expression increases during the transition of normal mammary epithelium to fully malignant breast carcinomas, with a strong peak of PADI2 expression and activity being observed in the MCF10DCIS cell line, which models human comedo-DCIS lesions. Next, we show that a PADI inhibitor, Cl-amidine, strongly suppresses the growth of MCF10DCIS monolayers and tumor spheroids in culture. We then carried out preclinical studies in nude (nu/nu) mice and found that Cl-amidine also suppressed the growth of xenografted MCF10DCIS tumors by more than 3-fold. Lastly, we performed cell cycle array analysis of Cl-amidine treated and control MCF10DCIS cells, and found that the PADI inhibitor strongly affects the expression of several cell cycle genes implicated in tumor progression, including p21, GADD45α, and Ki67. CONCLUSION: Together, these results suggest that PADI2 may function as an important new biomarker for HER2/ERBB2+ tumors and that Cl-amidine represents a new candidate for breast cancer 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".