Abstract P1-07-24: Modeling breast cancer metastasis in the mouse via measurement of circulating tumor cells
Bibliographic record
Abstract
Abstract Objectives: Advances in the detection of circulating tumor cells (CTC) in the blood of metastatic breast cancer patients have indicated that patients with greater than 5 CTC/7.5mL of blood have poorer prognosis; however, little is known about the biology of these cells and what characteristics are critical for breast tumor cell dissemination. We are developing and evaluating several mouse models of breast cancer to characterize important markers that distinguish CTCs from other cell types in the blood as well as to assess whether silencing of various metastasis supporting genes leads to reductions in CTC counts and formation of metastatic tumors. Methods: This study involves two separate approaches to characterize CTCs. The first involves xenograft models using human breast cancer cells injected into the fat pad of immunocompromised mice. These cells are tagged with both mCherry, for detection in blood, and luciferase, to track metastatic spread of the primary tumor cells to other sites via intravital imaging. Blood was collected from tumor bearing mice at end point, processed and stained for characterized CTC markers. The second approach involves endogenous mouse models to characterize CTC counts and relevant markers in a variety of metastatic and non-metastatic murine breast cancer models using negative depletion to remove contaminating normal and hematopoietic cells. In both approaches CTCs have been assessed using the Imagestream by Amnis. Results: Initial xenograft experiments with MDA-MB-231 cells injected into the mouse mammary gland fat pad revealed a low concentration of mCherry+/cytokeratin+/Hoechst+/CD45- cells in the blood of mice without confirmed metastatic dissemination. Pilot studies on endogenous tumor models have demonstrated the utility of our negative depletion approach to remove contaminating hematopoietic cells as well as the detection of a population of EpCAM+/Hoechst+/CD45- cells. Conclusions: Initial experiments have provided feasibility for detailed characterization of mouse CTCs, which will be presented. This work complements our study being carried out on characterizing CTCs in metastatic breast cancer patients. Increasing understanding of the biology of circulating tumor cells and relating their characteristics to those of both the primary and metastatic tumors may reveal mediators common and functionally important to all 3 tumor cell populations and may therefore serve as better targets for treatments that are effective against both the primary and metastatic tumors. Citation Format: Jennifer L Gorman, Michael Parsons, Eldad Zacksenhaus, Sean Egan, Martin Chang, Jim R Woodgett. Modeling breast cancer metastasis in the mouse via measurement of circulating tumor cells [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-07-24.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".