Inhibition of Heme Oxygenase-1 Increases Responsiveness of Pancreatic Cancer Cells to Anticancer Treatment
Bibliographic record
Abstract
Heme oxygenase-1 (HO-1) is believed to represent a key enzyme for the protection of cells against "stress." Its overexpression in different types of human cancers supports the notion that HO-1 provides a growth advantage and contributes to cellular resistance against chemotherapy and radiotherapy. Given the poor survival rates of patients with pancreatic cancer due to its aggressive growth behavior and its exceptional resistance to all known forms of anticancer treatment, we have investigated the expression of HO-1 in human pancreatic cancer cells growth behavior and prognosis. Expression of HO-1 was analyzed in human pancreatic cancer samples in comparison with normal pancreas by quantitative PCR, Western blot, and confocal microscopy. The influence of radiotherapy and chemotherapy on HO-1 expression in pancreatic cancer cell lines was evaluated. Furthermore, HO-1 expression was specifically suppressed by small interfering RNA transfection and subsequently the alterations of growth behavior and resistance to anticancer treatment were tested. Human pancreatic cancer showed a 6-fold and 3.5-fold HO-1 up-regulation in comparison to normal pancreas based on mRNA and protein level, respectively (P < 0.05). Cancer tissues revealed marked HO-1 immunoreactivity in tumor cells and in tumor associated immunocytes. Treatment of the pancreatic cancer cell lines with gemcitabine or radiation strongly induced HO-1 expression. Targeted knockdown of HO-1 expression led to pronounced growth inhibition of the pancreatic cancer cells and made tumor cells significantly more sensitive to radiotherapy and chemotherapy. Therefore, specific inhibition of HO-1 expression may be a new option in pancreatic cancer therapy and may be used as sensitizer to chemotherapy and radiotherapy.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".