Abstract 1018: Epithelial-to-mesenchymal transition (EMT) alters vesiculation of cancer cells expressing oncogenic epidermal growth factor receptor (EGFR): Implications for the aggressive, procoagulant and proangiogenic properties
Bibliographic record
Abstract
Abstract Cancer cells release elevated amounts of membrane-derived organelles containing complex molecular cargo, and known as extracellular vesicles (EVs). This process (vesiculation) is implicated in intercellular communication, as well as in cancer invasion, metastasis, angiogenesis and activation of the coagulation system. We have previously demonstrated a link between oncogenic transformation mediated by mutant K-ras, epidermal growth factor receptor (EGFR) as well as other genetic lesions and the intensity of cancer cell vesiculation. In the present study we interrogate vesiculation during the superimposed processes of de-differentiation and epithelial-to-mesenchymal transition (EMT). In the EGFR-driven epidermoid cancer cell line A431, EMT can be induced by stimulation with EGFR ligands coupled with blockade of the E-cadherin. Of note, A431 cells express high levels of the Tissue Factor (TF) receptor which renders them procoagulant, and is required for the efficient tumor initiation and proangiogenic signalling. A431 cells emit heterogeneous population of EVs, including subsets containing TF, and EGFR. We observed that induction of EMT in A431 cells is associated with a global increase in vesiculation, as revealed by nanoparticle tracking analysis (NTA/Nanosight). At the same time, EGFR and TF are relocated from the plasma membrane to distinct subcellular microdomains, and this change is associated with a rearrangement in the proteome of EVs emitted by cancer cells, including a significant increase in TF content. Tumor cell-derived, TF-containing EVs are readily taken up by endothelial cells and trigger their procoagulant conversion and angiogenic responses. While forming tumors in vivo A431 cells spontaneously undergo multilineage differentiation and generate EMT-like subpopulations, which release into the circulation a subset of EVs with a distinct molecular signature. Thus, EMT-like processes not only modulate intrinsic cellular properties (cell shape, differentiation), but also trigger a shift in cellular vesiculation that may be detected in EV preparations isolated from peripheral blood. Moreover, EVs that emanate from cancer cells upon their entry into the EMT pathway may acquire the ability to modify the extracellular and vascular milieu, and possibly facilitate tumor initiation, invasion and metastasis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1018. doi:1538-7445.AM2012-1018
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".