Project description:We developed preclinical PDX models, recapitulating the molecular heterogeneity of MIBCs and UTUC, which will represent an essential tool in therapy development. Pharmacological characterization of the PDXs suggested that upper urinary tract and bladder cancers (UCC/ SCC) with similar molecular characteristics could benefit from the same treatments, and showed a benefit for combined FGFR/EGFR inhibition in FGFR3-mutant PDXs, compared to FGFR inhibition alone.
Project description:Treatment paradigms for patients with upper tract urothelial carcinoma (UTUC) are typically extrapolated from studies of bladder cancer despite their distinct clinical and molecular characteristics. A major hurdle to the advancement of UTUC research is the lack of disease-specific models. Here, we report the establishment of patient derived xenograft (PDX) and cell lines models that reflect the heterogeneity of the human disease. Models demonstrated high genomic concordance with the tumors from which they were derived with muscle-invasive tumors more likely to successfully engraft. Treatment of PDX with chemotherapy recapitulated responses observed in the patients. Analysis of a S310F HER2 mutant PDX suggested that an antibody drug conjugate targeting HER2 would have superior efficacy to HER2-selective kinase inhibitors. In sum, the biologic and phenotypic concordance between patient and PDXs suggests that these models could facilitate studies of intrinsic and acquired resistance and the development of personalized medicine strategies for UTUC patients.
Project description:Developing animal models representating the cancer biology of advanced prostate cancer patients is challenging but essential for delivering individualized medical therapies. In an effort to develop patient derived xenograft (PDX) models, we took the metastatic site tissue from the rib lesion twice (ie, before and after enzalutamide treatment) over a twelve week period and implanted subcutaneously and under the renal capsule in immuno-deficient mice. To characterize and compare the genome and transcriptome landscapes of patient tumor tissues and the corresponding PDX models, we performed whole exome and transcriptome sequencing for metastatic tumor tissue as well as its derived PDXs. We demonstrated the feasibility of developping PDX models from patient who developed castrate-resistant prostate cancer. Our data suggested PDX models preserve the patient’s genomic and transcriptomic alterations in high fidelity, as illustrated by somatic mutation, copy number variation, gene fusion and gene expression. RNA sequencing of prostate cancer tumor tissue and derived xenograft using Illumina HiSeq 2000.
Project description:To probe the tissue source (cancer cell VS stromal cell) of gene expression in the mixed tumor samples, we took advantage of a set of Urothelial Cancer patient-derived xenograft (PDX) models given that the transcriptome in these models is a mixture of human RNA (derived from cancer cells) and mouse RNA (derived from stromal cells).
Project description:Developing animal models representating the cancer biology of advanced prostate cancer patients is challenging but essential for delivering individualized medical therapies. In an effort to develop patient derived xenograft (PDX) models, we took the metastatic site tissue from the rib lesion twice (ie, before and after enzalutamide treatment) over a twelve week period and implanted subcutaneously and under the renal capsule in immuno-deficient mice. To characterize and compare the genome and transcriptome landscapes of patient tumor tissues and the corresponding PDX models, we performed whole exome and transcriptome sequencing for metastatic tumor tissue as well as its derived PDXs. We demonstrated the feasibility of developping PDX models from patient who developed castrate-resistant prostate cancer. Our data suggested PDX models preserve the patient’s genomic and transcriptomic alterations in high fidelity, as illustrated by somatic mutation, copy number variation, gene fusion and gene expression.
Project description:The treatment of urothelial carcinoma (UC) is challenging given its molecular heterogeneity and variable response to current therapies. To address this, many tools, including tumor biomarker assessment and liquid biopsies, have been developed to predict prognosis and treatment response. Approved therapeutic modalities for UC currently include chemotherapy, immune checkpoint inhibitors, receptor tyrosine kinase inhibitors, and antibody drug conjugates. Ongoing investigations to improve the treatment of UC include the search for actionable alterations and the testing of novel therapies. An important objective in recent studies has been to increase efficacy while decreasing toxicity by taking into account unique patient and tumor-related factors-an endeavor called precision medicine. The aim of this review is to highlight advancements in the treatment of UC, describe ongoing clinical trials, and identify areas for future study in the context of precision medicine.
Project description:For human and canine invasive urothelial carcinoma (InvUC), there is growing interest in using the molecular characteristics of a tumor to guide individualized treatment strategies. The objective of this study was to use a noninvasive, urine-based method to characterize gene expression signatures in dogs with InvUC.
Project description:Breast cancer (BC) is a prevalent form of cancer affecting women worldwide. However, the effectiveness of current BC drugs is limited by issues such as systemic toxicity, drug resistance, and severe side effects. Consequently, there is an urgent need for new therapeutic targets and improved tumor tracking methods. This study aims to address these challenges by proposing a strategy for identifying membrane proteins in tumors that can be targeted for specific BC therapy and diagnosis. The strategy involves the analyses of gene expressions in breast tumor and non-tumor tissues and other healthy tissues by using comprehensive bioinformatics analysis from The Cancer Genome Atlas (TCGA), UALCAN, TNM Plot, and LinkedOmics. By employing this strategy, we identified four transcripts (LRRC15, EFNA3, TSPAN13, and CA12) that encoded membrane proteins with an increased expression in BC tissue compared to healthy tissue. These four transcripts also demonstrated high accuracy, specificity, and accuracy in identifying tumor samples, as confirmed by the ROC curve. Additionally, tissue microarray (TMA) analysis revealed increased expressions of the four proteins in tumor tissues across all molecular subtypes compared to the adjacent breast tissue. Moreover, the analysis of human interactome data demonstrated the important roles of these proteins in various cancer-related pathways. Taken together, these findings suggest that LRRC15, EFNA3, TSPAN13, and CA12 can serve as potential biomarkers for improving cancer diagnosis screening and as suitable targets for therapy with reduced side effects and enhanced efficacy.