Most gastrointestinal stromal tumor (GIST) patients develop clinical resistance to approved tyrosine kinase inhibitors (TKI). The development of effective treatment strategies for refractory GIST requires identification of novel targets for investigational agents and well-characterized preclinical models, like patient-derived xenograft (PDX) models, to evaluate them. While GIST PDX models have been shown to mirror patient tumors in cell morphology and driver mutation status, studies across tumor types indicate that PDX models may undergo limited genomic changes during engraftment and passaging. We performed a comprehensive genomic analysis of six KIT-mutant GIST PDX models derived from TKI-refractory patients. Pairwise comparison of copy number variation (CNV) profiles indicated strong correlation between PDX and matched primary tumors. Four models exhibited changes in the number of CNV events relative to the primary tumors, suggesting clonal selection and tumor heterogeneity during engraftment and passaging. Analysis of cancer-associated gene aberrations showed stability of primary KIT driver mutations, with minor fluctuations in the allelic frequencies of acquired mutations, suggesting initial heterogeneity of GIST tumors and potential enrichment of sub-clonal populations through passaging. To functionally assess model fidelity in vivo, three PDX models were treated with the approved second-line TKI sunitinib. The models exhibited differential responses that could not be fully explained by driver mutation status alone, highlighting the need for further investigation in larger cohorts.These findings highlight the importance of comprehensive genomic characterization of PDX models prior to their use in preclinical studies, supporting more accurate interpretation of experimental results and preserving their value as research tools.

Recent pan-cancer analyses have identified Complement Factor H (CFH) expression as an immune-related and prognostic biomarker. However, interpretation of CFH transcriptional data requires consideration of isoform specificity. The CFH gene encodes both full-length factor H (FH) and the biologically active splice isoform factor H-like 1 (FHL-1), which differ in structure and tissue localization. Common transcriptional and knockdown approaches do not distinguish between these isoforms, potentially introducing biological heterogeneity into diagnostic and prognostic assessments. Isoform-resolved analyses may therefore enhance the specificity and clinical utility of CFH-based biomarkers in oncology.