The Role of Erythropoietin and Erythropoiesis-Stimulating Agents in Tumor Progression
Bibliographic record
Abstract
Over the past few decades, understanding of the physiologic function of erythropoietin (EPO) has evolved significantly. EPO binds to erythropoietin receptors (EPOR), initiating signaling that stimulates growth, inhibits apoptosis, and induces the differentiation of erythroid progenitors to increase red blood cell mass. EPO has additionally been shown to exert tissue-protective effects on multiple tissues, suggesting a pleiotropic mechanism of action. Erythropoiesis-stimulating agents (ESA) are used clinically for treating cancer-related anemia [chemotherapy-induced anemia (CIA)]. Recent clinical trials have reported increased adverse events and/or reduced survival in ESA-treated cancer patients receiving chemotherapy, potentially related to EPO-induced cancer progression. Signaling pathways downstream of EPO/EPOR have been shown to influence numerous cellular functions in both normal and tumor cells, including proliferation, apoptosis, and drug resistance. Some studies have reported effects on proliferation, reduced chemotherapy efficacy, reduction of apoptosis, and resistance to selective therapies on cancer cell lines, whereas others have shown null effects. In addition, newer targeted cancer therapies that are directed toward specific signaling pathways may be antagonized by ESAs. This molecular interplay between anticancer agents and potential survival signals triggered by ESAs may have been underestimated and may contribute toward decreased survival seen in certain trials. As more targeted anticancer therapies become available, these types of interactions may mitigate therapeutic efficacy by allowing tumor cells to acquire drug resistance. Therefore, a more complete understanding of the complex pathways involved will allow for the rational use of ESAs for the safe treatment of CIA in oncology patients.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".