Paraffin-embedding lithography and micro-dissected tissue micro-arrays: tools for biological and pharmacological analysis of <i>ex vivo</i> solid tumors
Bibliographic record
Abstract
There is an urgent need and strong clinical and pharmaceutical interest in developing assays that allow for the direct testing of therapeutic agents on primary tissues. Current technologies fail to provide the required sample longevity, throughput, and integration with standard clinically proven assays to make the approach viable. Here we report a microfluidic micro-histological platform that enables ex vivo culture of a large array of prostate and ovarian cancer micro-dissected tissue (MDT) followed by direct on-chip fixation and paraffination, a process we term paraffin-embedding lithography (PEL). The result is a high density MDT-Micro Array (MDTMA) compatible with standard clinical histopathology that can be used to analyse ex vivo tumor response or resistance to therapeutic agents. The cellular morphology and tissue architecture are preserved in MDTs throughout the 15 day culture period. We also demonstrate how this methodology can be used to study molecular pathways involved in cancer by performing in-depth characterization of biological and pharmacological mechanisms such as p65 nuclear translocation via TNF stimuli, and to predict the treatment outcome in the clinic via MDT response to taxane-based 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 | 0.001 |
| 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) | 0.000 | 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".