# Test drugs on freshly cut slices of the patient's own tumour

Source: https://onco.cc/ideas/idea-bio1-tumour-slice-cultures/  
OnCo record `idea-bio1-tumour-slice-cultures` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

A thin slice of a tumour, kept alive for a few days, still contains the immune cells and scaffolding that lab-grown cells lose. Drugs can be tested on it directly.

## Summary

Precision-cut tumour slices preserve native architecture, stroma, vasculature remnants and resident immune cells for several days, and have been used to measure responses to chemotherapy, targeted agents and immunotherapy with imaging and single-cell readouts. They avoid the selection and adaptation that occur during organoid derivation, at the cost of a short experimental window.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: Slice-culture drug response measured within 72 hours predicts clinical response with accuracy at least equal to organoids, and does so for the majority of patients rather than only those whose organoids grow.
- Rationale: Organoid derivation succeeds in a variable fraction of samples and takes weeks, which excludes patients who need decisions now; slices work on almost every resection or core.
- Proposed test: Paired study on 100 resections: derive both slices and organoids, treat both with the patient's regimen, and compare success rate, turnaround time and clinical concordance.
- Maturity: preclinical-evidence
- Actor: research

## Sources

- Bottleneck evidence (Lab models that fail to predict what happens in patients): Wong, Siah & Lo, Estimation of clinical trial success rates (Biostatistics 2019): https://doi.org/10.1093/biostatistics/kxx069

## Connected records

- technologies: [Functional (ex vivo) drug testing](https://onco.cc/technologies/functional-drug-testing/), [Patient-derived organoids](https://onco.cc/technologies/organoids/), [Single-cell & spatial profiling](https://onco.cc/technologies/single-cell-spatial/)
- companies: [Curesponse](https://onco.cc/companies/curesponse/)
- bottlenecks: [Lab models that fail to predict what happens in patients](https://onco.cc/bottlenecks/b-preclinical-models/)
- key papers: [Estimation of clinical trial success rates and related parameters](https://onco.cc/key-papers/paper-wong-biostatistics/)

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