High-Throughput Screening for Novel Anti-cancer Radiosensitizers for Head and Neck Cancer
Bibliographic record
Abstract
Despite advances in therapeutic options for head and neck cancer (HNC), treatment-associated toxicities and overall clinical outcomes have remained disappointing. Even with radiation therapy (RT), which remains the primary curative modality for HNC, the most effective regimens achieve local control rates of 45-55%, with disease-free survival rates of only 30-40%. Thus, the development of novel strategies to enhance tumor cell killing, while minimizing damage to the surrounding normal tissues, is critical for improving cure rates with RT. Accordingly, we sought to identify novel radiosensitizing therapies for HNC, exploiting a high-throughput screening (HTS) approach. Initially, a cell-based phenotype-driven HTS of ~2,000 commercially available natural products was conducted, utilizing the short-term MTS cell viability assay. Cetrimonium bromide (CTAB) was identified as a novel anti-cancer agent, exhibiting in vitro and in vivo efficacy against several HNC models, with minimal effects on normal fibroblasts. Two major limitations of our findings, however, were that CTAB did not synergize with radiation, nor was its precise cellular target(s) elucidated. Consequently, an alternative strategy was proposed involving a target-driven RNAi-based HTS. Since the colony formation assay (CFA) is the gold standard for measuring cellular effects of radiation in vitro, an automated high-throughput colony-formation read-out was developed as a more appropriate end-point for radiosensitivity. Although successful as a tool for the discovery of potent anti-cancer cytotoxics, a technical drawback was its limited dynamic range. Thus, the BrdU incorporation assay, which measures replicative DNA synthesis and is a viable CFA alternative, was employed. From an RNAi-based screen of ~7000 human genes, uroporphyrinogen decarboxylase (UROD), a key regulator of heme biosynthesis, was identified as a novel tumor-selective radiosensitizing target against HNC in vitro and in vivo. Radiosensitization appeared to be mediated via tumor-selective enhancement of oxidative stress from perturbation of iron homeostasis and increased ROS production. UROD was significantly over-expressed in HNC patient biopsies, wherein lower pre-RT UROD levels correlated with improved disease-free survival, suggesting that UROD expression could also be a potential predictor for radiation response. Thus, employing a HTS approach, this thesis identified two novel therapeutic strategies with clinical potential in the management of HNC.
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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) | 0.001 | 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 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".