Table 1.

Overview of commonly used bioinformatics and high-throughput analytical approaches towards assessing the molecular landscape, as well as donor fidelity, of PDX and PDO models across different cancer types.

Technology Used	Bioinformatics Analysis & Outcomes	Representative Examples and Organ type(s)
Whole Exome Sequencing (WES)	–Match tumour-model mutational profiles and genetic events for tumour suppressor and oncogenes (ex: identification of a frameshift deletion in the same gene, across donors and matching models) –Assess allelic fractions of somatic mutations (distribution of MAF) –Compare trinucleotide alterations and mutation patterns (C → A, C → G, C → T, T → A, T → C, T → G) –Phylogenetic analysis	[19], [20], [25] Gastric Pancreas Oral Cavity
Whole Genome Sequencing (WGS)	–Similar investigations to WES (see above) –Deeper exploration of structural variation events (insertions, deletions, duplications, translocations) that are retained when tumours are transplanted into PDX or PDO –Investigation into copy number changes due to model transplantation, including identification of clones and subclones.	[20], [21], [22], [23] Esophagus Breast Pancreas Oral Cavity
Single-cell RNA sequencing (scRNA)	–investigation of tumour heterogeneity (ex: intra-tumour diversification) –Deeper probe into clonal evolution as well as progression of somatic mutations	[26], [27], [28], [29] Brain Colorectal Lung Breast
Proteomic profiling	–assess overlap of the transcriptome and proteome for given models –identify patient-specific, distinct proteomic signatures for PDX and PDO (ex: microsatellite stability)	[30] Colorectal
Metabolomics	–examine metabolite abundance in preclinical models –identify enriched pathways across patients and PDX or PDO –assess metabolic reprogramming in tumourigenesis and tumour progression –correlate metabolite enrichment against transcriptomic and proteomic profiles to obtain a system-wide understanding of tumourigenesis	[31], [32] Breast Intestine