Antiadhesive antibodies targeting E-cadherin sensitize multicellular tumor spheroids to chemotherapy <i>in vitro</i>
Bibliographic record
Abstract
Multicellular resistance, a subtype of therapeutic resistance manifested in cancer cells grown as three-dimensional multicellular masses, such as spheroids in vitro and solid tumors in vivo, occurs with respect to a variety of anticancer treatment strategies including chemotherapy, ionizing radiation, and even host-mediated antibody-dependent cellular cytotoxicity. Previous studies from our laboratory have shown that multicellular resistance to chemotherapy demonstrated by aggregates of EMT-6 murine mammary carcinoma cells can be overcome by using hyaluronidase to disrupt intercellular adhesive interactions and associated patterns of protein expression. In this proof of principle study, we explored the concept of antiadhesive chemosensitization in the context of human cancer cells by using a monoclonal antibody to disrupt E-cadherin-mediated cell-cell interactions in multicellular spheroids of HT29 human colorectal adenocarcinoma. In so doing, we found that disruption of E-cadherin-mediated adhesion sensitizes multicellular spheroids of HT29 in vitro to treatment with 5-fluorouracil, paclitaxel, vinblastine, and etoposide but not cisplatin. Furthermore, we have found that antibody-mediated blockage of E-cadherin function leads to decreased expression and activity of protein kinase C alpha and beta1, both of which have previously been implicated in chemoresistance exhibited by HT29 cells; however, we have found that the chemosensitization effects of the anti-E-cadherin antibody are independent of its influence on protein kinase C beta1.
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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".