Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe an androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naïve, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harbors BRCA2 and CHD1 somatic mutations, shows an SPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modeled in vivo. Comparison of the treatment-naïve PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds.
Patient-derived organoids (PDOs) represent promising preclinical models in various tumor types. In the context of prostate cancer (PCa), however, their establishment has been hampered by poor success rates, which impedes their broad use for translational research applications. Along with the necessity to improve culture conditions, there is a need to identify factors influencing outcomes and to determine how to assess success versus failure in organoid generation. In the present study, we report our unbiased efforts to generate PDOs from a cohort of 81 PCa specimens with diverse pathological and clinical features. We comprehensively analyzed histological features of each enrolled sample (Gleason score, tumor content, proliferation index) and correlated them with organoid growth patterns. We identified improved culture conditions favoring the generation of PCa organoids, yet no specific intrinsic tumor feature was broadly associated with sustained organoid growth. In addition, we performed phenotypic and molecular characterization of tumor-organoid pairs using immunohistochemistry, immunofluorescence, fluorescence in situ hybridization, and targeted sequencing. Morphological and immunohistochemical profiles of whole organoids altogether provided a fast readout to identify the most promising ones. Notably, primary samples were associated with an initial take-rate of 83% (n = 60/72) in culture, with maintenance of cancer cells displaying common PCa alterations, such as PTEN loss and ERG overexpression. These cancer organoids were, however, progressively overgrown by organoids with a benign-like phenotype. Finally, out of nine metastasis samples, we generated a novel organoid model derived from a hormone-naïve lung metastasis, which displays alterations in the PI3K/Akt and Wnt/β-catenin pathways and responds to androgen deprivation. Taken together, our comprehensive study explores determinants of outcome and highlights the opportunities and challenges associated with the establishment of stable tumor organoid lines derived from PCa patients.
Commercially available targeted panels miss genomic regions frequently altered in hepatocellular carcinoma (HCC). We sought to design and benchmark a sequencing assay for genomic screening of HCC. We designed an AmpliSeq custom panel targeting all exons of 33 protein-coding and two long noncoding RNA genes frequently mutated in HCC, TERT promoter, and nine genes with frequent copy number alterations. By using this panel, the profiling of DNA from fresh-frozen (n = 10, 1495×) and/or formalin-fixed, paraffin-embedded (FFPE) tumors with low-input DNA (n = 36, 530×) from 39 HCCs identified at least one somatic mutation in 90% of the cases. Median of 2.5 (range, 0 to 74) and 3 (range, 0 to 76) mutations were identified in fresh-frozen and FFPE tumors, respectively. Benchmarked against the mutations identified from Illumina whole-exome sequencing (WES) of the corresponding fresh-frozen tumors (105×), 98% (61 of 62) and 100% (104 of 104) of the mutations from WES were detected in the 10 fresh-frozen tumors and the 36 FFPE tumors, respectively, using the HCC panel. In addition, 18 and 70 somatic mutations in coding and noncoding genes, respectively, not found by WES were identified by using our HCC panel. Copy number alterations between WES and our HCC panel showed an overall concordance of 86%. In conclusion, we established a cost-effective assay for the detection of genomic alterations in HCC.
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