Abstract 5313: The potential role of cellular iron in head and neck squamous cell carcinoma.
Bibliographic record
Abstract
Abstract Introduction. Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Half of the patients present with advanced disease, which despite aggressive treatments, achieves five-year survival rates of only 50%, underscoring a need to better understand the biology of this disease. One approach would be to examine the role of cellular iron in HNSCC. We are interested in the role of iron as a result of: (1) A previous study in our lab in which uroporphyrinogen decarboxylase was identified as a radiosensitizing target for HNSCC. The radiosentization was due to alterations in iron homeostasis which elevated reactive oxygen species (ROS) and enhance tumor oxidative stress and cytotoxicity. (2) The requirement of iron in a rate limiting step with ribonucleotide reductase for DNA synthesis, and hence cell proliferation. (3) The deregulation of iron in many cancers. Experimental design. A list of proteins involved in iron homeostasis was generate from the literature and evaluated using qRT-PCR in 3 HNSCC cells (FaDu, UTSCC 42a, UTSCC 8) compare to a Normal Oral Epithelial (NOE) cell line. The most highly over expressed iron protein across all cell lines compared to the NOE was hemochromatosis (HFE), thus was selected for further evaluation. Knockdown of HFE was achieved using a siRNA based approach and cellular effects were determined using MTS, clonogenic, BRDU and flow cytometry assays with or without 4 Gy of radiation. Iron rescue experiments where preformed using Ferric ammonium citrate (FACs). Iron chelation was accomplished in HNSCC cells lines using ciclopirox olamine (CPX), a clinical approved iron chelating chemotherapeutic. Results. HFE was selected for further evaluation based on the expression in HNSCC cell lines versus the NOE cell line. Mutations in HFE are linked to the genetic condition hemochromatosis, which is characterized by elevated hepcidin levels and iron accumulation in peripheral tissues. Cell proliferation assays (MTS, clonogenic, BRDU assay) after HFE knockdown with or without RT in HNSCC cells demonstrated a significant decrease in proliferation across all cancer cells with negligible effects on NOE cells. Furthermore, we observed a significant decrease in the Labile iron pool and cellular ROS levels, following HFE knockdown. Re-introduction of iron into the cell after HFE knockdown rescued our phenotype, suggesting that this process is indeed mediated by cellular iron levels. Next, we treated HNSCC cell lines CPX and observed a significant decrease in cell viability compared to control treated cells. Conclusion. HFE appears to be an important protein in controlling cellular iron. HFE knockdown resulted in a reduction in cellular iron which decreases the amount of iron available for DNA synthesis and hence cell proliferation. Therefore, elevated cellular iron appears to be an important factor for the progression of HNSCC, thus iron chelation strategies may valuable in the context of this disease. Citation Format: Michelle Lenarduzzi, Angela Hui, Winnie Yue, Justin Williams, Fei Fei Liu. The potential role of cellular iron in head and neck squamous cell carcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5313. doi:10.1158/1538-7445.AM2013-5313
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".