Abstract 283: Vascular ageing as a modulator of tumor angiogenesis, antiangiogenesis and metastasis
Bibliographic record
Abstract
Abstract Ageing profoundly influences vascular homeostasis and impacts angiogenesis, including in cancer. This is rarely considered in preclinical studies, as mouse tumor models usually rely on animals between 1-6 months of age (5-25% of life expectancy), while the majority of adult cancer patients are diagnosed in later decades of life. Thus a better characterization of a pediatric, adult and geriatric state of the vascular system is badly needed to properly design age-appropriate antiangiogenic anticancer therapies. Using aged (over 12 months old), aged and atherosclerotic (ApoE-/-) and aged and diet induced obese (DIO) C57BL/6 mice we have demonstrated that model tumors (Lewis Lung Carcinoma) exhibit profoundly different angiogenic and metastatic patterns in those settings then in conventional syngeneic recipients. We documented age-related molecular differences in tumor blood vessels and have shown that the antitumor effects of several therapeutic agents (L-NAME, Sutent, AG28262, metronomic cyclophosphamide) are affected by vascular age and comorbidities. Age also changes the pattern of metastasis as aged mice tend to exhibit less aggressive metastatic growth. On the other hand metastasis following treatment with antiangiogenic agents (Sutent without chemotherapy) is more accentuated in young mice then in their aged counterparts. Finally, we report age-related changes in vascular characteristics of human kidney tumours, including a significantly higher expression of eNOS in tumours of younger patients. Overall, these observations suggest that age may play a significant role in modulation of angiogenesis, antiangiogenesis and metastasis in various tumor settings and agents more effective in adult patients may not have the same impact in the pediatric population. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 283. doi:10.1158/1538-7445.AM2011-283
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".