A Novel Primary Cell Line Model of Localized Prostate Cancer and Radioresistance—A Role for Nicotinamide N-Methyltransferase
Bibliographic record
Abstract
Prostate cancer cell lines are particularly clinically homogenous, mostly representing metastatic states rather than localized disease. While there has been significant work in the development of additional models, few have been created without oncogenic transformation. We derived a primary prostate cancer cell line from a patient with localized Gleason 7 prostate cancer-designated CaB34-which spontaneously immortalized. We leveraged CaB34 to generate a paired radioresistant subline, CaB34-CF, using a clinically relevant fractionated radiotherapy schedule. These two paired cell lines were investigated extensively to determine their molecular characteristics and therapy responses. Both CaB34 and CaB34-CF express prostate-specific markers, including KRT18, NKX3.1, and AMACR. Multi-omic analyses using RNAseq and shotgun proteomics identified NNMT as the most significantly dysregulated component in CaB34-CF. A bioinformatic analysis determined that NNMT was more abundant within prostate tumors compared to benign prostate, suggesting a role in tumor progression. Knockdown studies of NNMT demonstrated significant radiosensitization of CaB34-CF cells, which was largely a result of increased radiation-induced cellular senescence. Growth as 3D organoids was significantly higher in the CaB34-CF line, and demonstrated a less structured pattern of expression of cytokeratin markers. Radiosensitization with NNMT siRNA was recapitulated in a 3D organoid clonogenic assay in CaB34-CF cells. Our research provides a paired primary model of treatment-naïve and radioresistant disease to address mechanisms of therapy resistance, while expanding the repertoire of localized prostate cancer cell lines for the research community. In addition, our findings present NNMT as a potential therapeutic target for sensitization of radioresistant disease.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".