Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays
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PROVIDER: EGAC00001001387 | EGA |
REPOSITORIES: EGA
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Project description:Background and aimsSeveral major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient-derived xenograft (PDX) models. In Asia, HCCs from patients with hepatitis B virus have been efficiently converted into PDXs, but few parallel efforts from the west have been reported.Approach and resultsIn a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NOD Scid IL-2Rγ-/- (NSG) mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the United States. PDX models preserved the histology and genetic features of parental tumors, and ultimately, eight models were usable for preclinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib, and CCA PDXs were also highly sensitive to regorafenib.ConclusionsPDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the United States.
| S-EPMC7332388 | biostudies-literature
Project description:Several major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient derived xenograft (PDX) models. In Asia, HCCs from hepatitis B virus patients have been efficiently converted into PDXs, but few parallel efforts from the west have been reported. In a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NSG mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the US. PDX models preserved the histology and genetic features of parental tumors, and ultimately, 9 new models were usable for pre-clinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib and CCA PDXs were also highly sensitive to regorafenib. PDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the US.
| EGAS00001004020 | EGA
Project description:Lack of clinically relevant tumor models dramatically hampers development of effective therapies for hepatocellular carcinoma (HCC). Establishment of patient-derived xenograft (PDX) models that faithfully recapitulate the genetic and phenotypic features of HCC becomes important. In this study, we first established a cohort of 65 stable PDX models of HCC from corresponding Chinese patients. Then we showed that the histology and gene expression patterns of PDX models were highly consistent between xenografts and case-matched original tumors. Genetic alterations, including mutations and DNA copy number alterations (CNAs), of the xenografts correlated well with the published data of HCC patient specimens. Furthermore, differential responses to sorafenib, the standard-of-care agent, in randomly chosen xenografts were unveiled. Finally, in the models expressing high levels of FGFR1 gene according to the genomic data, FGFR1 inhibitor lenvatinib showed greater efficacy than sorafenib. Taken together, our data indicate that PDX models resemble histopathological and genomic characteristics of clinical HCC tumors, as well as recapitulate the differential responses of HCC patients to the standard-of-care treatment. Overall, this large collection of PDX models becomes a clinically relevant platform for drug screening, biomarker discovery and translational research in preclinical setting.
| S-EPMC4652995 | biostudies-literature
Project description:Background and aimsHepatoblastoma (HBL) is a devastating pediatric liver cancer with multiple treatment options, but it ultimately requires surgery for a cure. The most malicious form of HBL is a chemo-resistant aggressive tumor that is characterized by rapid growth, metastases, and poor response to treatment. Very little is known of the mechanisms of aggressive HBL, and recent focuses have been on developing alternative treatment strategies. In this study, we examined the role of human chromosomal regions, called aggressive liver cancer domains (ALCDs), in liver cancer and evaluated the mechanisms that activate ALCDs in aggressive HBL.ResultsWe found that ALCDs are critical regions of the human genome that are located on all human chromosomes, preferentially in intronic regions of the oncogenes and other cancer-associated genes. In aggressive HBL and in patients with Hepatocellular (HCC), JNK1/2 phosphorylates p53 at Ser6, which leads to the ph-S6-p53 interacting with and delivering the poly(adenosine diphosphate ribose) polymerase 1 (PARP1)/Ku70 complexes on the oncogenes containing ALCDs. The ph-S6-p53-PARP1 complexes open chromatin around ALCDs and activate multiple oncogenic pathways. We found that the inhibition of PARP1 in patient-derived xenografts (PDXs) from aggressive HBL by the Food and Drug Administration (FDA)-approved inhibitor olaparib (Ola) significantly inhibits tumor growth. Additionally, this is associated with the reduction of the ph-S6-p53/PARP1 complexes and subsequent inhibition of ALCD-dependent oncogenes. Studies in cultured cancer cells confirmed that the Ola-mediated inhibition of the ph-S6-p53-PARP1-ALCD axis inhibits proliferation of cancer cells.ConclusionsIn this study, we showed that aggressive HBL is moderated by ALCDs, which are activated by the ph-S6-p53/PARP1 pathway. By using the PARP1 inhibitor Ola, we suppressed tumor growth in HBL-PDX models, which demonstrated its utility in future clinical models.
| S-EPMC8463483 | biostudies-literature
Project description:Patient-derived xenograft (PDX) models are effective preclinical cancer models that reproduce the tumor microenvironment of the human body. The methods have been widely used for drug screening, biomarker development, co-clinical trials, and personalized medicine. However, the low success rate and the long tumorigenesis period have largely limited their usage. In the present studies, we compared the PDX establishment between hepatocellular cancer (HCC) and metastatic liver cancer (MLC), and identified the key factors affecting the transplantation rate of PDXs. Surgically resected tumor specimens obtained from patients were subcutaneously inoculated into immunodeficient mice to construct PDX models. The overall transplantation rate was 38.5% (20/52), with the HCC group (28.1%, 9/32) being lower than MLC group (56.2%, 9/16). In addition, HCC group took significantly longer latency period than MLC group to construct PDX models. Hematoxylin and eosin staining results showed that the histopathology of all generations in PDX models was similar to the original tumor in all three types of cancer. The transplantation rate of PDX models in HCC patients was significantly associated with blood type (P=0.001), TNM stage (P=0.023), lymph node metastasis (P=0.042) and peripheral blood CA19-9 level (P=0.049), while the transplantation rate of PDX models in MLC patients was significantly associated with tumor size (P=0.034). This study demonstrates that PDX models can effectively reproduce the histological patterns of human tumors. The transplantation rate depends on the type of original tumor. Furthermore, it shows that the invasiveness of the original liver cancer affects the possibility of its growth in immunodeficient mice.
| S-EPMC7646096 | biostudies-literature
Project description:Patient-derived cancer xenografts (PDCX) generally represent more reliable models of human disease in which to evaluate a potential drugs preclinical efficacy. However to date, only a few patient-derived gastric cancer xenograft (PDGCX) models have been reported. In this study, we aimed to establish additional PDGCX models and to evaluate whether these models accurately reflected the histological and genetic diversities of the corresponding patient tumors. By engrafting fresh patient gastric cancer (GC) tissues into immune-compromised mice (SCID and/or nude mice), thirty two PDGCX models were established. Histological features were assessed by a qualified pathologist based on H&E staining. Genomic comparison was performed for several biomarkers including ERBB1, ERBB2, ERBB3, FGFR2, MET and PTEN. These biomarkers were profiled to assess gene copy number by fluorescent in situ hybridization (FISH) and/or protein expression by immunohistochemistry (IHC). All 32 PDGCX models retained the histological features of the corresponding human tumors. Furthermore, among the 32 models, 78% (25/32) highly expressed ERBB1 (EGFR), 22% (7/32) were ERBB2 (HER2) positive, 78% (25/32) showed ERBB3 (HER3) high expression, 66% (21/32) lost PTEN expression, 3% (1/32) harbored FGFR2 amplification, 41% (13/32) were positive for MET expression and 16% (5/32) were MET gene amplified. Between the PDGCX models and their parental tumors, a high degree of similarity was observed for FGFR2 and MET gene amplification, and also for ERBB2 status (agreement rate = 94~100%; kappa value = 0.81~1). Protein expression of PTEN and MET also showed moderate agreement (agreement rate = 78%; kappa value = 0.46~0.56), while ERBB1 and ERBB3 expression showed slight agreement (agreement rate = 59~75%; kappa value = 0.18~0.19). ERBB2 positivity, FGFR2 or MET gene amplification was all maintained until passage 12 in mice. The stability of the molecular profiles observed across subsequent passages within the individual models provides confidence in the utility and translational significance of these models for in vivo testing of personalized therapies.
| S-EPMC4517891 | biostudies-literature
Project description:We have generated a collection of patient-derived xenograft (PDX) tumor models and characterized them at the molecular level to facilitate precision oncology. Surgically resected HCC specimens were subcutaneously implanted in immunodeficient mice. Resulting xenografts were serially implanted to establish transplantable PDX models, which were sequentially subject to whole exome sequencing (WES), gene expression array, genome-wide human single nucleotide polymorphism (SNP) array 6.0, and serum a–fetoprotein (AFP) detection assay. The feasibility as a preclinical model was validated by efficacy studies using a standard-of-care (SOC) and a targeted agent, respectively.
2014-03-13 | E-GEOD-55828 | biostudies-arrayexpress
Project description:This data article presents datasets associated with the research article entitled "Generation of matched patient-derived xenograft in vitro-in vivo models using 3D macroporous hydrogels for the study of liver cancer" (Fong et al., 2018) [1]. A three-dimensional macroporous sponge system was used to generate in vitro counterparts to various hepatocellular carcinoma patient-derived xenograft (HCC-PDX) lines. This article describes the viability, proliferative capacity and molecular features (genomic and transcriptomic profiles) of the cultured HCC-PDX cells. The sequencing datasets are made publicly available to enable critical or further analyzes.
| S-EPMC5996264 | biostudies-literature
Project description:MET plays an important role in the development and progression of papillary renal cell carcinoma (pRCC). Evaluation of efficacy of MET inhibitors against pRCC has been hampered by limited preclinical models depicting MET abnormalities. We established a new patient-derived xenograft (PDX) model of pRCC carrying an activating mutation of MET and tested the ability of cabozantinib, an inhibitor of receptor tyrosine kinases including MET, to inhibit tumor growth and metastasis. Precision-cut, thin tissue slices from a pRCC specimen obtained by nephrectomy were implanted under the renal capsule of RAG2-/-?C-/- mice to establish first generation TSG-RCC-030. Histologic and genetic fidelity and metastatic potential of this model were characterized by immunohistochemistry, direct DNA sequencing and quantitative polymerase chain reaction (qPCR). The effect of cabozantinib on tumor growth and metastasis was evaluated. Whether measurements of circulating tumor DNA (ctDNA) by allele-specific qPCR could be used as a biomarker of tumor growth and response to therapy was determined. Subrenal and subcutaneous tumor grafts showed high take rates and metastasized to the lung. Both primary tumors and metastases expressed typical markers of pRCC and carried the same activating MET mutation as the parental tumor. Cabozantinib treatment caused striking tumor regression and inhibited lung metastasis in TSG-RCC-030. Plasma ctDNA levels correlated with tumor volume in control mice and changed in response to cabozantinib treatment. TSG-RCC-030 provides a realistic preclinical model to better understand the development and progression of pRCC with MET mutation and accelerate the development of new therapies for pRCC.
| S-EPMC5710673 | biostudies-literature
Project description:We have generated a collection of patient-derived xenograft (PDX) tumor models and characterized them at the molecular level to facilitate precision oncology.
2014-03-13 | GSE55828 | GEO