Membrane Hsp70—A Novel Target for the Isolation of Circulating Tumor Cells After Epithelial-to-Mesenchymal Transition
Bibliographic record
Abstract
The presence of circulating tumor cells (CTCs) in the peripheral blood is a pre-requisite for progression, invasion, and metastatic spread of cancer. Consequently, the enumeration and molecular characterization of CTCs from the peripheral blood of patients with solid tumors before, during and after treatment serves as a valuable tool for categorizing disease, evaluating prognosis and for predicting and monitoring therapeutic responsiveness. Many of the techniques for isolating CTCs are based on the expression of epithelial cell surface adhesion molecule (EpCAM, CD326) on tumor cells. However, the transition of adherent epithelial cells to migratory mesenchymal cells (epithelial-to-mesenchymal transition, EMT)-an essential element of the metastatic process-is frequently associated with a loss of expression of epithelial cell markers, including EpCAM. A highly relevant proportion of mesenchymal CTCs cannot therefore be isolated using techniques that are based on the "capture" of cells expressing EpCAM. Herein, we provide evidence that a monoclonal antibody (mAb) directed against a membrane-bound form of Hsp70 (mHsp70)-cmHsp70.1-can be used for the isolation of viable CTCs from peripheral blood of tumor patients of different entities in a more quantitative manner. In contrast to EpCAM, the expression of mHsp70 remains stably upregulated on migratory, mesenchymal CTCs, metastases and cells that have been triggered to undergo EMT. Therefore, we propose that approaches for isolating CTCs based on the capture of cells that express mHsp70 using the cmHsp70.1 mAb are superior to those based on EpCAM expression.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".