Abstract 560: The use of molecular biomarkers to quantify drug distribution in solid tumors
Bibliographic record
Abstract
Abstract The tumor microenvironment plays a critical role in the efficacy of chemotherapy. The disorganized vasculature within solid tumors leads to decreased drug delivery to the tumor and poor penetration of drugs from blood vessels to the tumor cells. Our laboratory has shown limited distribution of the auto-fluorescent drugs doxorubicin and mitoxantrone using quantitative immunohistochemistry. However, most anti-cancer drugs are not fluorescent and do not have antibodies that recognize them. The aim of the present study is to characterize the spatial distribution within solid tumors of biomarkers of drug effect: cleaved caspase 3 (a marker of apoptosis), γH2aX (a marker of DNA damage) and Ki67 (a marker of cell proliferation) in relation to blood vessels (recognized by an antibody to CD31). We have quantified the time-dependent distribution of these biomarkers in two models: human breast cancer MDA-MB-231 xenografts and murine mammary EMT6 syngeneic tumors following treatment with doxorubicin and melphalan respectively. Biomarker distributions have been compared to distributions of doxorubicin fluorescence. Melphalan's distribution within a solid tumor has been assessed for the first time with the use of a melphalan-DNA adduct recognizing monoclonal antibody. These studies are designed to provide a basis for selecting biomarkers to reflect the distribution of other non-fluorescent agents. The distribution of doxorubicin decreases exponentially with increasing distance from blood vessels, and is similar to the distribution of γH2aX at 10 minutes after drug injection. The activation of cleaved caspase 3 (indicating apoptosis) at 24 and 48 hours following treatment also mirrors the distribution of doxorubicin. The analysis of biomarker distributions in EMT6 tumors following treatment with melphalan in relation to tumor blood vessels is in progress. The results of these studies will be applied to quantify the intratumoral distribution of other non-fluorescent anticancer drugs (hypoxia-activated pro-drugs). 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 560. doi:10.1158/1538-7445.AM2011-560
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".