Gene expression differences between matched pairs of ovarian cancer patient tumors and patient-derived xenografts

Liu, Yuanhang; Chanana, Pritha; Davila, Jaime; Hou, Xiaonan; Zanfagnin, Valentina; McGehee, Cordelia D.; Goode, Ellen L.; Polley, Eric C.; Haluska, Paul; Weroha, S. John; Wang, Chen

doi:10.1038/s41598-019-42680-2

Cited by 40 publications

(40 citation statements)

References 44 publications

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“…This can result in variability in the expression signal which can be wrongly inferred as CN changes, both from the tumor itself and through cross hybridization of mouse RNA to the human microarray. Although improved concordance in expression between PT and PDX can be achieved with RNA sequencing with the removal of mouse reads 67,68 , we observed that expression-based copy number inferences still have low resolution and robustness. Hence, many cancer-driving genes, which are found mainly in focal events with a size of 3Mb or lower 69–72 , cannot be evaluated for PDX-specific alterations.…”

Section: Discussionmentioning

confidence: 79%

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: Discussionmentioning

confidence: 79%

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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“…Although PDX models retain the majority of the single nucleotide variants (SNVs) in parental tumors, the characteristics of SNVs within xenograft tumors are distinct from those in parental tumors . A previous study established 20 PDX CRC models and detected an increased number of variant alleles within xenograft tumors.…”

Section: Differences In Molecular Characteristics Among Pdx Modelsmentioning

confidence: 99%

“…With regard to 34 PDX‐specific missense mutations, 11 were expressed based on the RNA‐seq results. Two recent studies in ovarian cancer and identified 1,935 and 4,180 genes that are differentially expressed between PDXs and parental tumors, among which 168 and 918 were upregulated in PDX models and 1,767 and 3,262 were downregulated (Table ) …”

Section: Differences In Molecular Characteristics Among Pdx Modelsmentioning

confidence: 99%

The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance

Shi

Jia

et al. 2019

Intl Journal of Cancer

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Patient‐derived xenograft (PDX) models are widely used as preclinical cancer models and are considered better than cell culture models in recapitulating the histological features, molecular characteristics and intratumoral heterogeneity (ITH) of human tumors. While the PDX model is commonly accepted for use in drug discovery and other translational studies, a growing body of evidence has suggested its limitations. Recently, the fidelity of cancer cells within a PDX has been questioned, which may impede the future application of these models. In this review, we will focus the variable phenotypes of xenograft tumors and the genomic instability and molecular inconsistency of PDX tumors after serial transplantation. Next, we will discuss the underlying mechanism of ITH and its clinical relevance. Stochastic selection bias in the sampling process and/or deterministic clonal dynamics due to murine selective pressure may have detrimental effects on the results of personalized medicine and drug screening studies. In addition, we aim to identify a possible solution for the issue of fidelity in current PDX models and to discuss emerging next‐generation preclinical models.

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“…Primary patient tumour cluster together with PDX tumours clustering together but separate from the primary tumour. RNASeq data in ovarian PDX models demonstrate this differential clustering is predominantly due to the loss of human stroma and the growth of murine stroma [35]. By comparing the adjacent normal to the tumour and the tumour to the F1 PDX tumour we aimed to map the genes associated with tumour growth, proliferation and tumour in engraftment.…”

Section: Discussionmentioning

confidence: 99%

Establishment and Characterisation by Expression Microarray of Patient-Derived Xenograft Panel of Human Pancreatic Adenocarcinoma Patients

Roche

O’Neill

Murphy

et al. 2020

IJMS

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Pancreatic cancer remains among the most lethal cancers worldwide, with poor early detection rates and poor survival rates. Patient-derived xenograft (PDX) models have increasingly been used in preclinical and clinical research of solid cancers to fulfil unmet need. Fresh tumour samples from human pancreatic adenocarcinoma patients were implanted in severe combined immunodeficiency (SCID) mice. Samples from 78% of treatment-naïve pancreatic ductal adenocarcinoma patients grew as PDX tumours and were confirmed by histopathology. Frozen samples from F1 PDX tumours could be later successfully passaged in SCID mice to F2 PDX tumours. The human origin of the PDX was confirmed using human-specific antibodies; however, the stromal component was replaced by murine cells. Cell lines were successfully developed from three PDX tumours. RNA was extracted from eight PDX tumours and where possible, corresponding primary tumour (T) and adjacent normal tissues (N). mRNA profiles of tumour vs. F1 PDX and normal vs. tumour were compared by Affymetrix microarray analysis. Differential gene expression showed over 5000 genes changed across the N vs. T and T vs. PDX samples. Gene ontology analysis of a subset of genes demonstrated genes upregulated in normal vs. tumour vs. PDX were linked with cell cycle, cycles cell process and mitotic cell cycle. Amongst the mRNA candidates elevated in the PDX and tumour vs. normal were SERPINB5, FERMT1, AGR2, SLC6A14 and TOP2A. These genes have been associated with growth, proliferation, invasion and metastasis in pancreatic cancer previously. Cumulatively, this demonstrates the applicability of PDX models and transcriptomic array to identify genes associated with growth and proliferation of pancreatic cancer.

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Gene expression differences between matched pairs of ovarian cancer patient tumors and patient-derived xenografts

Cited by 40 publications

References 44 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

The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance

Establishment and Characterisation by Expression Microarray of Patient-Derived Xenograft Panel of Human Pancreatic Adenocarcinoma Patients

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