Abstract P6-14-07: Genetic ablation of ACF7, a member of the +TIP family of microtubule-binding proteins, impairs metastasis of HER2-positive breast cancer
Bibliographic record
Abstract
Abstract Breast cancer is the leading cause of cancer death in women worldwide. Among the different subtypes of this disease, HER2-positive breast cancer is known to be one of the most aggressive and is linked to poor prognosis. This subtype is prone to develop metastases, reflecting a significant cellular plasticity. While the molecular machinery controlling actin dynamics is well implicated in cell invasion, the contribution of the microtubules is ill-defined. We recently conducted a functional screen to identify such regulators, and characterized ACF7, a microtubule plus-end binding protein (+TIP), as a new promoter of invasion. Here, we aim to determine the in vivo contribution of ACF7 to tumor progression and to reveal the cellular and molecular mechanisms allowing this +TIP to promote metastasis. We analyzed the expression of ACF7 at the protein level across a panel of tumor microarrays and found that it is detectable in all breast cancer subtypes with the highest levels seen in HER2-positive. To study the role of ACF7 during tumor progression, we generated an ACF7 genetically engineered mouse model of breast cancer. We exploited a HER2-positive breast cancer mouse model (MMTV-NIC) that we bred with ACF7Flox mice. This approach allows for conditional deletion of ACF7 in mammary glands and represents a powerful model to define the roles of ACF7 in HER2-driven breast cancer. Our results show that ACF7 is not involved in tumor initiation and tumor growth as no difference between number of nodules per mouse, tumor mass or number of mammary intraepithelial neoplastic lesions was shown. However, our results show a significant decrease in lung metastasis in the ACF7cKO mice. To gain mechanistic insights into the roles of ACF7 in this specific process, we derived primary cell lines from tumors isolated from MMTV-NIC-ACF7WT and MMTV-NIC-ACF7cKO mice. We explored if ACF7 contributes to migration and invasion in a HER2 context. By using live-cell imaging, we demonstrated that ACF7-null cells display defects in both random and directed cell migration, as they show a delay in wound closure. We determined that ACF7KO cells show an increase in focal adhesions size, and exhibit defects in reorienting their actin and microtubules cytoskeletons parallel to the direction of migration. ACF7 was also found to promote cell invasion since ACF7KO cells were less efficient to cross a Matrigel membrane. To investigate the metastatic potential of ACF7-null tumors, we performed RNA-sequencing using RNA isolated from MMTV-NIC-ACF7WT and MMTV-NIC-ACF7cKO tumors. We identified a striking change in expression of genes involved in epithelial to mesenchymal transition (EMT), such as for example E-cadherin, Vimentin or the transcription factor Twist. These results suggest that ACF7 promotes metastasis through maintaining an EMT state in HER2 breast cancer cells. Collectively, our work demonstrates ACF7 as an important player in HER2 positive breast cancer progression via its functions in both cell migration and cell invasion. This works also suggests that developing approaches to therapeutically target regulators of microtubule dynamics may reveal new opportunities to decrease tumor progression and metastatic expansion. Citation Format: Rebecca Cusseddu, Jean-François Côté. Genetic ablation of ACF7, a member of the +TIP family of microtubule-binding proteins, impairs metastasis of HER2-positive breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-14-07.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".