Stanniocalcin 2 induces oxaliplatin resistance in colorectal cancer cells by upregulating P-glycoprotein
Bibliographic record
Abstract
Multidrug resistance (MDR) limits the anticancer effects of chemotherapy in patients with metastatic colorectal cancer (CRC). Oxaliplatin is a common component of combinational therapeutic regimens administered to patients with metastatic CRC; however, it is also used as a constituent of adjuvant therapy for patients at a risk of recurrent disease. In the present study, we investigated the role of stanniocalcin 2 (STC2) in chemoresistance. STC2 knockdown sensitized chemoresistant CRC cells to oxaliplatin. Moreover, the expression of exogenous STC2 in chemonaïve CRC cells induced oxaliplatin resistance. We confirmed that STC2 upregulated P-glycoprotein (P-gp) expression in CRC cells. Furthermore, shRNA against phosphoinositide 3-kinase (PI3K) or Akt inhibited the action of STC2 on P-gp upregulation and MDR in CRC. To our knowledge, this is the first report to demonstrate the induction of oxaliplatin resistance in CRC cells in response to STC2 stimulation of P-gp via the PI3K/Akt signaling pathway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".