Unveiling stem-like traits and chemoresistance mechanisms in ovarian cancer cells through the TGFβ1-PITX2A/B signaling axis
Bibliographic record
Abstract
Ovarian cancer (OC) is the deadliest gynecological malignancy, having a high mortality rate due to its asymptomatic nature, chemoresistance, and recurrence. However, the proper mechanistic knowledge behind these phenomena is still inadequate. Cancer recurrence is commonly observed due to cancer stem cells which also show chemoresistance. We aimed to decipher the molecular mechanism behind chemoresistance and stemness in OC. Earlier studies suggested that PITX2, a homeobox transcription factor and, its different isoforms are associated with OC progression upon regulating different signaling pathways. Moreover, they regulate the expression of drug efflux transporters in kidney and colon cancer, rendering chemoresistance properties in the tumor cell. Considering these backgrounds, we decided to look for the role of PITX2 isoforms in promoting stemness and chemoresistance in OC cells. In this study, PITX2A/B has been shown to promote stemness and to enhance the transcription of ABCB1. PITX2 has been discovered to augment ABCB1 gene expression by directly binding to its promoter. To further investigate the regulatory mechanism of PITX2 gene expression, we found that TGFβ signaling could augment the PITX2A/B expression through both SMAD and non-SMAD signaling pathways. Collectively, we conclude that TGFβ1-activated PITX2A/B induces stem-like features and chemoresistance properties in the OC cells.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".