Abstract B006: Does TFPI1 drive development of multiple drug resistant cancer and can the anaphase promoting complex prevent it
Bibliographic record
Abstract
Abstract Chemotherapy is often rendered ineffective by the development of multiple drug resistance (MDR). Given time MDR occurs almost universally and once developed applies in a non-specific manner. The lack of MDR specificity means many drugs, including those a patient has no pervious exposure to, are affected which limits treatment options. The goal of this research is to show nuclear localized tissue factor pathway inhibitor 1 (TFPI1) plays a driving role in development of MDR, and that the Anaphase Promoting Complex (APC) is capable of inhibiting MDR by targeting TFPI1 for degradation. A coagulation regulator, TFPI1 normally inhibits the tissue factor pathway to prevent blood clot formation. However, TFPI1 is highly elevated in many types of MDR cancer where we believe it mediates resistance development. Previous work in our lab has shown plasmid overexpression of TFPI1 induces MDR in MCF7 breast cancer cells, in MDR cells TFPI1 does not localize to the cell surface but instead to the nucleus, and a putative TFPI1 nuclear localization sequence (NLS) was identified. To confirm the putative NLS is required for TFPI1’s localization to nucleus, and subsequent MDR development, NLS mutant or wild type TFPI1-GFP were overexpressed in MCF7 cells. Localization of TFPI1-GFP was observed using widefield and confocal microscopy. Wild type TFPI1-GFP localized to the nucleus while the NLS mutant TFPI1 did not. These results help to confirm the putative NLS and its importance to TFPI1s role in MDR development. The APC is a nuclear E3 ubiquitin ligase and highly conserved regulator of cell cycle progression. Defects in APC function are associated with reduced longevity and cancer. Other work in our lab focuses on the APC’s role in longevity using a yeast model. However, we believe the APC also plays a role in TFPI1’s promotion of MDR. Our observations suggest APC dysfunction exists within MDR cancer cells where APC substrates accumulate, as does TFPI1. We hypothesize that nuclear TFPI1 is an APC substrate, and that APC activation will result in TFPI1 degradation slowing MDR development. Our lab has isolated several small peptides we believe bind and activate the APC, and have used these peptides in conjugation with known APC activators such as Mad2 Inhibitor-1 (M2I-1) to show that APC activation is capable of reducing TFPI1 abundance in MCF7 cells treated with the chemotherapeutic Doxorubicin (Dox). These results suggest TFPI1 is an APC substrate. To summarize, we believe TFPI1 drives development of MDR cancer, for which TFPI1’s accumulation within the nucleus is important. We have shown TFPI1’s NLS is required for localization of the protein to the nucleus, and activation of the APC reduces nuclear accumulation of TFPI1. Moving forward our goal is to demonstrate the effect TFPI1 NLS knockout and APC activation have on the development of MDR in MCF7 cells undergoing drug selection with Dox. By exploring TFPI1’s role in MDR we may elucidate means to slow resistance development and extend chemotherapy effectiveness. Citation Format: Mathew Lubachowski, Troy Harkness. Does TFPI1 drive development of multiple drug resistant cancer and can the anaphase promoting complex prevent it [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr B006.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".