Patient derived models of bladder cancer amplify tumor specific gene expression compared to surgical specimen while maintaining gene expression of molecular subtype and epithelial mesenchymal transition markers
Mastri, M.; Ramakrishnan, S.; Shah, S.; Karasik, E.; Gillard, B. M.; Moser, M. M.; Farmer, B. K.; Chatta, G. S.; Woloszynska, A.; Eng, K. H.; Foster, B. A.; HUSS, W. J.
Show abstract
Patient derived models (PDMs) are a powerful tool to study preclinical responses. However, the benefits of each model have not been compared head-to-head when models are derived from the same surgical specimen. PDMs derived from surgical specimens were established as xenografts (PDX), organoids (PDO), and spheroids (PDS). PDMs were molecularly characterized by RNA sequencing. Differential gene expression was determined between the PDMs and surgical specimens. Surgical specimens had the most differentially expressed genes reflecting loss of immune and stromal compartments in PDMs. PDMs and surgical specimens were clustered using the Euclidian distance analysis to test model fidelity. PDMs upregulated a clear, patient-specific bladder cancer signal. Overall, the molecular profiles of PDXs were the most similar to the matching patient surgical specimen than the PDO and PDS from that patient. The epithelial mesenchymal transition (EMT) gene expression profile is maintained in the PDMs showing the persistence of EMT in both in vivo and in vitro model setting. The consensus molecular subtype was determined in order to compare PDMs to each other and their matching surgical specimen, and only surgical specimens with Basal/Squamous or Luminal Papillary molecular subtype established PDMs. Patient derived models reduce tumor heterogeneity and allow analysis of specific tumor compartments while maintaining the gene expression profile representative of the original tumor.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Use of high-plex data reveals novel insights into the tumour microenvironment of clear cell renal cell carcinoma 94%
- Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics 94%
- Characterization of SOX2, OCT4 and NANOG in ovarian cancer tumor-initiating cells 94%
Similar papers in this journal
- CD117/c-kit Represents a Prostate Cancer Stem-Like Subpopulation Driving Progression, Migration, and TKI Resistance 94%
- Drug resistant pancreatic cancer cells exhibit altered biophysical interactions with stromal fibroblasts in imaging studies of 3D co-culture models 94%
- Periostin facilitates ovarian cancer recurrence by enhancing cancer stemness 94%
Similar papers in this journal
- Evaluation of deacetylase inhibition in metaplastic breast carcinoma using multiple derivations of preclinical models of a new patient-derived tumor 94%
- Comprehensive cancer-oriented biobanking resource of human samples for studies of post-zygotic genetic variation involved in cancer predisposition 94%
- Automated Clear Cell Renal Carcinoma Grade Classification with Prognostic Significance 94%
Similar papers in this journal
- Syngeneic model of carcinogen-induced tumor mimics basal/squamous, stromal-rich, and neuroendocrine molecular and immunological features of muscle-invasive bladder cancer 95%
- Integrated molecular and pharmacological characterization of patient-derived xenografts from bladder and ureteral cancers identifies new potential therapies. 94%
- Extracellular vesicle molecular signatures characterize metastatic dynamicity in ovarian cancer 94%
Similar papers in this journal
- Role of Gut Microbiome in Neoadjuvant Chemotherapy Response in Urothelial Carcinoma: A Multi-Institutional Prospective Cohort Evaluation 91%
- Inhibitor of the nuclear transport protein XPO1 enhances the anticancer efficacy of KRAS G12C inhibitors in preclinical models of KRAS G12C mutant cancers 90%
- Spatial landscape of malignant pleural and peritoneal mesothelioma tumor immune microenvironment 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.