Cell Line Picker

Heavey Lab

Prostate cancer cell line picker

Based on Ahmed et al., Communications Medicine (2026); categories follow the paper’s selection framework (Fig 5) · doi:10.1038/s43856-026-01886-y

Choose your cell lines like you mean it. In vitro biology can only take us so far in mimicking the human, and we all live with that. We can do better though: 3D culture, co-culture, and thinking carefully about the supplements and hormones in our media all help to close the gap. But none of it matters if the cell line you start with is the wrong one. Pick badly at the outset and your external validity has already left the building, no matter how fancy the culture system is. So before you grab the line your lab mate has stashed in the freezer, filter below for the line that best mirrors the clinical cohort your experiments are actually about. One honest caveat: the data to do this properly is patchy. As we noted in our paper, some fields (ancestry in particular) are hard to come by for many cell lines, but that is exactly why we should use what we do have to match our cohorts as closely as we can.

Matching cell lines

click a category above to see its filters

Provenance: every field traces to Ahmed et al. (2026), Communications Medicine, doi:10.1038/s43856-026-01886-y: Table 1 (age, sampling site, ethnicity, cancer type, androgen status); Supplementary Tables 1–10 (roster, laboratory sources, treatment percentages); Supplementary Data 1 (availability and access); Fig 5 (Gleason, stage, alterations); Fig 6 (transcriptomic patient-likeness). Derived fields (age bands, site groups, metastatic inference) are marked as derived in the workbook’s data_notes sheet.

Picker v1.01 (data version 4) · built 12 November 2026 · Heavey Lab, University College London. Categories follow the paper’s Fig 5 selection framework; the paper’s three-step presentation is offered here as categories rather than steps so researchers can filter in any order.

Ahmed Z, Mosabbir W, Tandon D, Pinto Pereira S, Cheema U, Loizidou M, Withington J, Moore C, Okoli U, Heavey S. Multiomics comparison between prostate cell lines and patient-derived tissue to evaluate cell line clinical relevance. Communications Medicine 2026. doi:10.1038/s43856-026-01886-y