Clinical significance of radiation-induced CD133 expression in residual rectal cancer cells after chemoradiotherapy
Bibliographic record
Abstract
CD133 and CD44 have been considered as markers for colorectal cancer stem cells (CSCs). The association of CD133 and CD44 expression with radiation has not been fully examined in rectal cancer. Both CD133 (PROM) and CD44 mRNA levels were measured in post-chemoradiotherapy (CRT) specimens of 52 rectal cancer patients using real-time RT-PCR and compared to clinicopathological variables and clinical outcome. Their protein levels were examined in the radiation-treated HT29 human colon cancer cell line. Post-CRT CD133 in residual cancer cells was significantly higher than matched pre-CRT CD133 in biopsy specimens (n=30). By contrast, CD44 was significantly lower in post-CRT specimens (P<0.01). CD133 was associated with distant recurrence after CRT followed by surgery (P<0.05). Patients with elevated CD133 in residual cancer cells showed poor disease-free survival (P<0.05). No significant association between post-CRT CD44 and clinical outcome was found. The in vitro study showed that CD133 protein was increased in a radiation dose-dependent manner, despite of the decreased number of clonogenic radiation-surviving cells. CD44 protein was decreased after irradiation. CD133, but not CD44, was increased in radiation-resistant surviving colon cancer cells. Post-CRT CD133 in residual cancer cells may predict metachronous distant recurrence and poor survival of rectal cancer patients after CRT.
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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".