Carbon‐ion radiation enhances migration ability and invasiveness of the pancreatic cancer cell, PANC‐1, <i>in vitro</i>
Bibliographic record
Abstract
Pancreatic cancer is an aggressive disease that responds poorly to conventional photon radiotherapy. Carbon-ion (C-ion) radiation has advantages compared with conventional radiotherapy, because it enables more accurate dose distribution and more efficient tumor cell killing. To elucidate the effects of local radiotherapy on the characteristics of metastatic tumors, it is necessary to understand the nature of motility in irradiated tumor cells; this will, in turn, facilitate the development of effective strategies to counter tumor cell motility, which can be used in combination with radiotherapy. The aim of the present study was to examine the invasiveness of pancreatic cancer cells exposed to C-ion irradiation. We found that C-ion irradiation suppressed the migration of MIAPaCa-2, BxPC-3 and AsPC-1; diminished the invasiveness of MIAPaCa-2; and tended to reduce the invasion of BxPC-3 and AsPC-1. However, C-ion irradiation increased the invasiveness of PANC-1 through the activation of plasmin and urokinase-type plasiminogen activator. Administration of serine protease inhibitor (SerPI) alone failed to reduce C-ion-induced PANC-1 invasiveness, whereas the combination of SerPI and Rho-associated coiled-coil forming protein kinase (ROCK) inhibitor suppressed it. Furthermore, PANC-1 showed mesenchymal-amoeboid transition when we treated with SerPI alone. In conclusion, C-ion irradiation is effective in suppressing the invasive potential of several pancreatic tumor cell lines, but not PANC-1; this is the first study showing that C-ion irradiation induces the invasive potential of a tumor cell line. Further in vivo studies are required to examine the therapeutic effectiveness of radiotherapy combined with inhibitors of both mesenchymal and amoeboid modes of tumor cell motility.
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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) | 0.001 | 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".