Bridging angiogenesis and immune evasion in the hypoxic tumor microenvironment
Bibliographic record
Abstract
) is a ubiquitous microenvironmental factor promoting cancer progression, metastasis, and mortality, owing to the ability of cancer cells to co-opt physiological angiogenic responses. Notwithstanding, the pathophysiological induction of angiogenesis results in an abnormal tumor vasculature, further aggravating hypoxia in a feedforward loop that limits the efficacy of molecular targeted therapies. Recent studies suggest that, besides their canonical roles, angiogenic factors promote a panoply of immunosuppressive effects in the tumor microenvironment. Therefore, intratumoral hypoxia emerges as a hitherto unrecognized mechanism evolutionarily repurposing angiogenic molecules as (patho)physiological immunomodulators. On the other hand, antiangiogenic therapies could be aimed at impeding both tumor growth and immunotolerance toward cancer cells, a beneficial effect that can be countered if hypoxia signaling pathways are left unchecked, leading to therapeutic failure. This review summarizes evidence supporting the hypothesis that hypoxia acts as a common pathophysiological mechanism of resistance to immunotherapeutic and antiangiogenic agents while proposing potential strategies to curtail resistance and mortality in patients bearing solid malignancies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".