Abstract 6002: Increased ferroptosis sensitivity and epithelial to mesenchymal transition of breast cancer cells overcoming chemotherapeutic mediated apoptotic caspase activation
Bibliographic record
Abstract
Abstract The survival of cancer cells post chemotherapeutic treatment can lead to the presence of recurrent tumors and continues to be a barrier to effective cancer treatment. The majority of chemotherapeutics kill cells through the induction of executioner caspases and subsequent apoptotic death, and resistance to apoptosis can lead to the presence of anastatic cancer cells. Executioner caspase release was previously thought to be the point of no return from apoptotic cell death, however, it has been shown that removal of the reagent causing caspase release can lead to recovery of cells from apoptotic signaling, a phenomenon which has been termed ``Anastasis``. This presents a need for a better understanding of the underlying mechanisms behind cancer cell survival and the mechanisms that lead to cell recovery and recurrent tumors. We have hypothesized that when treated with chemotherapeutics, some cells will evade cell death even when executioner caspases have been activated. By identifying surviving anastatic cells and the pathways involved in their evasion of cell death, we hope to propose novel therapeutic strategies to prevent their survival. The novel CasExpress system, developed by the Denise Montell lab group, was used to identify and isolate a population of cells surviving caspase-3 activation as a result of chemotherapeutic treatment in Triple Negative Breast Cancer (TNBC) cell lines. The CasExpress system permanently labels these cells with GFP post caspase-3 activation. Analysis of this population of SUM159 anastatic cells, identified by their GFP expression, demonstrates that these cells have an increased resistance to further chemotherapeutic treatment, a decrease in levels of active caspase-3, an up-regulation of Cancer Stem Cell marker CD44, and a more mesenchymal phenotype. Furthermore, these “anastatic cells” express decreased levels of GPX-4, an enzyme that mitigates ferroptosis via lipid peroxide reduction, and are more sensitive to GPX-4 and xCT inhibitor mediated ferroptosis cell death.To investigate the link between Epithelial to Mesenchymal Transition (EMT) and ferroptosis mediated cell death, we used TGF-b to stimulate EMT in NMe mouse epithelial cells. We found that TGF-b induced EMT is associated with increased sensitivity to ferroptosis mediated by GPX-4 inhibition. Furthermore, the TGF-b induced EMT cells have a marked decrease in the expression of GPX4, similar to what was observed in the TNBC anastatic cells. These results indicate a potential link between EMT and an increased sensitivity to ferroptosis, and provide novel strategies for identifying and targeting chemotherapeutic resistant tumor cells. Citation Format: Rachel Hausman, Wells Brown, Paul McDonald, Shannon Awrey, Gongping Sun, Denise Montell, Shoukat Dedhar. Increased ferroptosis sensitivity and epithelial to mesenchymal transition of breast cancer cells overcoming chemotherapeutic mediated apoptotic caspase activation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6002.
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".