PDXliver: a database of liver cancer patient derived xenograft mouse models

He, Sheng; Hu, Bo; Li, Chao; Lin, Ping; Tang, Wei‐Guo; Sun, Yun-Fan; Feng, Fangyoumin; Wei, Guo; Li, Jia; Xu, Yang; Yao, Qianlan; Zhang, Xin; Qiu, Shuang–Jian; Zhou, Jian; Fan, Jia; Li, Yixue; Li, Hong; Yang, Xin‐Rong

doi:10.1186/s12885-018-4459-6

Cited by 26 publications

(19 citation statements)

References 29 publications

(22 reference statements)

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“…We have assembled copy number alteration (CNA) profiles of 1451 unique samples (324 patient tumor, PT, and 1127 PDX samples) corresponding to 509 PDX models contributed by participating centers of the PDXNET, the EurOPDX consortium, and other published datasets 9,34 (see METHODS, Supplementary Table 1 and Supplementary Fig. 1).…”

Section: Resultsmentioning

confidence: 99%

“…Gene expression and copy number data, generated by the Affymetrix Human Genome U133 Plus 2.0 Array and Affymetrix Human SNP 6.0 platforms respectively, of hepatocellular carcinoma (HCC) PDX models were retrieved from the Gene Expression Omnibus (GEO) accession ID GSE90653 10 . Expression microarray data generated by the Affymetrix Human Genome U133 Plus 2.0 Array for normal liver were downloaded from GEO and ArrayExpress: GSE3526 11 , GSE33006 12 and E-MTAB-1503-3 13 .…”

Section: Methodsmentioning

confidence: 99%

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Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Woo¹,

Giordano

Srivastava³

et al. 2019

Preprint

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41 a PDXNET consortium 42 b EurOPDX consortium 43 # These authors contributed equally to this work.44 § These authors jointly supervised this work. ABSTRACT 107Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical 108 studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution 109 during PDX engraftment and propagation, impacting the accuracy of PDX modeling of human 110 cancer. Here we exhaustively analyze copy number alterations (CNAs) in 1451 PDX and matched 111 patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing 112 and microarray data displayed substantially higher resolution and dynamic range than gene 113 expression-based inferences, and they also showed strong CNA conservation from PTs through 114 late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-115 late trios confirmed high-resolution CNA retention. We observed no significant enrichment of 116 cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between 117 patient and PDX tumors were comparable to variations in multi-region samples within patients. 118Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse 119 host. 121 MAIN 122A variety of models of human cancer have been used to study basic biological processes and 123 predict responses to treatment. For example, mouse models with genetically engineered 124 mutations in oncogenes and tumor suppressor genes have clarified the genetic and molecular 125 basis of tumor initiation and progression 1,2 , though responses sometimes differ between human 126 and mouse 3 . Cell lines have also been widely used to study cancer cells, but they lack the 127 heterogeneity and microenvironment of in vivo tumors and have shown limitations for predicting 128 clinical response 4 . Human tumors engrafted into transplant-compliant recipient mice (patient-129 derived xenografts, PDX) have advantages over prior systems for preclinical drug efficacy studies 130 because they allow researchers to directly study human cells and tissues in vivo 5-8 . Comparisons131 of genome characteristics and histopathology of primary tumors and xenografts of human breast 132 cancer 9-13 , ovarian cancer 14 , colorectal cancer 15 and lung cancer 16-18 , have demonstrated that the 133 biological properties of patient-derived tumors are largely preserved in xenografts. A growing body 134 of literature supports their use in cancer drug discovery and development 19-21 . 135A caveat to PDX models is that intratumoral evolution can occur during engraftment and 136 passaging 11,22-25 . Such evolution could potentially modify treatment response of PDXs with 137 respect to the patient tumors 23,26,27 , particularly if the evolution were to systematically alter cancer-138 related genes. This issue is related to multi-region comparisons of patient tumors 28-31 , for which 139 local mutational and immune infiltration variations have sugg...

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Woo¹,

Giordano

Srivastava³

et al. 2019

Preprint

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“…Recently, a comprehensive dataset named PDXliver was assembled with 116 HCC PDXs: 51 newly generated, and the remainder from the established literature. 86 The database contains information about clinical features, expression profiles, and genetic alterations, and the models adequately represent the diversity seen in patients with HCC. 13,14 Moreover, drug response data is also included, which may lead to the nomination of biomarkers for specific therapies.…”

Section: Patient-derived Xenograftsmentioning

confidence: 99%

Novel patient-derived preclinical models of liver cancer

Bresnahan

Ramadori

Heikenwälder

et al. 2020

Journal of Hepatology

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Preclinical models of cancer based on the use of human cancer cell lines and mouse models have enabled discoveries that have been successfully translated into patients. And yet the majority of clinical trials fail, emphasising the urgent need to improve preclinical research to better interrogate the potential efficacy of each therapy and the patient population most likely to benefit. This is particularly important for liver malignancies, which lack highly efficient treatments and account for hundreds of thousands of deaths around the globe. Given the intricate network of genetic and environmental factors that contribute to liver cancer development and progression, the identification of new druggable targets will mainly depend on establishing preclinical models that mirror the complexity of features observed in patients. The development of new 3D cell culture systems, originating from cells/tissues isolated from patients, might create new opportunities for the generation of more specific and personalised therapies. However, these systems are unable to recapitulate the tumour microenvironment and interactions with the immune system, both proven to be critical influences on therapeutic outcomes. Patient-derived xenografts, in particular with humanised mouse models, more faithfully mimic the physiology of human liver cancer but are costly and time-consuming, which can be prohibitive for personalising therapies in the setting of an aggressive malignancy. In this review, we discuss the latest advances in the development of more accurate preclinical models to better understand liver cancer biology and identify paradigm-changing therapies, stressing the importance of a bi-directional communicative flow between clinicians and researchers to establish reliable model systems and determine how best to apply them to expanding our current knowledge.

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“…Mouse tumour cell lines harbour mutations that are neutral or not relevant in human cancer making xenograft models more genetically applicable to human disease [35] . Patient-derived xenograft (PDX) models in which cells from a specific patient with HCC are transplanted into immunocompromised mice have been established [36] . PDXs faithfully recapitulate histologic, genomic and biological characteristics of the primary tumour and have been shown to predict drug response in HCC patients.…”

Section: Implantation Modelsmentioning

confidence: 99%

“…PDXs faithfully recapitulate histologic, genomic and biological characteristics of the primary tumour and have been shown to predict drug response in HCC patients. However, this model is limited by engraftment failure rates of up to 60%, long time to engraftment (several months) and high cost, which make it unsuitable for large-scale drug screening [36,37] . Furthermore, the major drawback of xenograft models (PDX or otherwise) is the lack of a tumoural immune response, which has become increasingly important as we enter the era of immunotherapies for HCC.…”

Section: Implantation Modelsmentioning

confidence: 99%

Animal models for hepatocellular carcinoma arising from alcoholic and metabolic liver diseases

Liu¹,

Chen²,

McCaughan³

2020

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Hepatocellular carcinoma (HCC) is a major and increasing cause of clinical and economic burden worldwide. Now that there are effective therapies to control or eradicate viral aetiologies, the landscape of HCC is changing with alcoholic and metabolic liver diseases becoming major catalysts. The pathogenesis of HCC is complex and incompletely understood, hampering improvements in therapy. Animal models are essential tools for advancing study on the cellular and molecular processes in HCC and for screening potential novel therapies. Many models of hepatocarcinogenesis have been established using various methods including genetic engineering, chemotoxic agents and dietary manipulation to direct implantation of tumour cells. However, none of these can accurately replicate all features found in human diseases. In this review, we provide an overview of different mouse models of HCC with a particular focus on cancer arising from alcoholic liver disease, non-alcoholic fatty liver disease and hereditary haemochromatosis. We also highlight their strengths and limitations and provide perspectives for future study.

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PDXliver: a database of liver cancer patient derived xenograft mouse models

Cited by 26 publications

References 29 publications

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Novel patient-derived preclinical models of liver cancer

Animal models for hepatocellular carcinoma arising from alcoholic and metabolic liver diseases

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