| Challenges |
Potential Solutions |
| • In developmental studies, assessment of cell maturity and identity relies too heavily on expression of markers, which can have low specificity |
• Combining marker expression data with spatial information, transcriptomic analysis and organelle characterisation |
| • Adult lung and cancer organoids lack data to determine to what extent they diverge phenotypically from their tissue of origin |
• Proteomic and transcriptomic characterisation of organoids and tissue of origin at the single cell level |
| |
• Systematic identification of the influence of how medium composition and co-culture with non-epithelial (e.g. immune cells) influence organoid phenotype |
| How well do organoid cultures represent patient cohorts? |
| Challenges |
Potential Solutions |
| • Success rates in lung cancer organoid establishment differ widely between laboratories |
• Systematic comparison of different lung cancer organoid derivation protocols |
| • There is poor representation of pre-invasive disease in organoid cancer models |
• Identification of transcriptional or genomic features associated with successful lung cancer organoid establishment through collaborative efforts |
| • Most chronic pulmonary diseases have limited model availability |
• Disease modelling using genetic engineering of stem cell derived or non-diseased lung organoids |
| To what extent does an organoid capture diversity within a patient? |
| Challenges |
Potential Solutions |
| • Intra-patient (spatial) heterogeneity is not considered in the establishment chronic pulmonary disease organoids |
• More detailed reporting on biopsy location when establishing organoids for chronic pulmonary disease |
| • There is potential loss of intratumour heterogeneity in lung cancer organoids |
• Multi-region organoid establishment combined with high coverage sequencing to detect sub-clonal mutations |
