Multifaceted Interplay between Hormones, Growth Factors and Hypoxia in the Tumor Microenvironment
Bibliographic record
Abstract
Hormones and growth factors (GFs) are signaling molecules implicated in the regulation of a variety of cellular processes. They play important roles in both healthy and tumor cells, where they function by binding to specific receptors on target cells and activating downstream signaling cascades. The stages of tumor progression are influenced by hormones and GF signaling. Hypoxia, a hallmark of cancer progression, contributes to tumor plasticity and heterogeneity. Most solid tumors contain a hypoxic core due to rapid cellular proliferation that outgrows the blood supply. In these circumstances, hypoxia-inducible factors (HIFs) play a central role in the adaptation of tumor cells to their new environment, dramatically reshaping their transcriptional profile. HIF signaling is modulated by a variety of factors including hormones and GFs, which activate signaling pathways that enhance tumor growth and metastatic potential and impair responses to therapy. In this review, we summarize the role of hormones and GFs during cancer onset and progression with a particular focus on hypoxia and the interplay with HIF proteins. We also discuss how hypoxia influences the efficacy of cancer immunotherapy, considering that a hypoxic environment may act as a determinant of the immune-excluded phenotype and a major hindrance to the success of adoptive cell therapies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".