Invadopodia-Mediated Remodeling of the Lymphatic Endothelium Drives Cancer Cell Lymphatic Dissemination and is Regulated by a CCR7-Vav2-Rac3 Signaling axis
Bibliographic record
Abstract
ABSTRACT Cancer cell invasion across a lymphatic endothelial barrier and subsequent colonization of regional lymph nodes often marks the first stage of metastatic dissemination. Lymphatic vessels facilitate the escape of cancer cells and can support further metastatic dissemination. Although the clinical and experimental evidence supports a role for lymph node metastases in promoting metastatic spread, the mechanism employed by cancer cells to navigate a lymphatic endothelium and enter lymphatic vessels is poorly characterized. To investigate this, we assessed the interactions between cancer cells and lymphatic endothelial cells and found that Tks5-positive structures, termed invadopodia, remodel lymphatic endothelial junctions. Loss of Tks5 impaired cancer cell invasion across a lymphatic endothelium and significantly reduced lymph node and lung metastasis in a mouse model of breast cancer progression. Surgical removal of the axillary and brachial lymph nodes prior to orthotopic cancer cell injection resulted in a significant reduction in lung tumor burden, further demonstrating the significance of lymph node metastases to metastatic tumor burden. Next, using breast cancer patient primary tumors we found that elevated expression of CCR7, a chemokine receptor, significantly associated with lymph node metastasis. CCR7 localized to invadopodia and promoted cancer cell invasion across lymphatic endothelium, both in the presence and absence of its canonical ligand CCL19. Tyrosine phosphorylation of CCR7 directed the recruitment of Vav2 and activation of Rac3. Our findings highlight a role for lymphatic metastases in promoting distant metastasis and establish a mechanism by which cancer cells breach a lymphatic endothelium.
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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 | 0.001 |
| 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".