XenofilteR: computational deconvolution of mouse and human reads in tumor xenograft sequence data

Kluin, Roelof J.C.; Kemper, Kristel; Kuilman, Thomas; Ruiter, Julian R. de; Iyer, Vivek; Forment, Josep V.; Cornelissen-Steijger, Paulien; Rink, Iris de; Brugge, Petra ter; Song, Ji‐Ying; Klarenbeek, Sjoerd; McDermott, Ultan; Jonkers, Jos; Velds, Arno; Adams, David J.; Peeper, Daniel S.; Krijgsman, Oscar

doi:10.1186/s12859-018-2353-5

Cited by 117 publications

(123 citation statements)

References 33 publications

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“…As PDX tumors grow, their human tumor stroma is replaced by mouse stroma [48]. In our comparison of transcriptomes of original brain metastasis from one patient and its xenografts in mouse brain and MFP, we observed that approximately 15% of RNA transcripts of PDXs were murine.…”

Section: Discussionmentioning

confidence: 85%

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

Oshi

Okano

Maiti

et al. 2020

Cancers

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The vast majority of mortality in breast cancer results from distant metastasis. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Pre-clinical animal models that reliably reflect the biology of breast cancer brain metastasis are needed to develop and test new treatments for this deadly condition. The patient-derived xenograft (PDX) model maintains many features of a donor tumor, such as intra-tumor heterogeneity, and permits the testing of individualized treatments. However, the establishment of orthotopic PDXs of brain metastasis is procedurally difficult. We have developed a method for generating such PDXs with high tumor engraftment and growth rates. Here, we describe this method and identify variables that affect its outcomes. We also compare the brain-orthotopic PDXs with ectopic PDXs grown in mammary pads of mice, and show that the responsiveness of PDXs to chemotherapeutic reagents can be dramatically affected by the site that they are in.

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Section: Discussionmentioning

confidence: 85%

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

Oshi

Okano

Maiti

et al. 2020

Cancers

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“…Whole-genome sequence reads from EuroPDX BRCA tumors and corresponding tumor grafts at different passages were mapped to the reference human genome (GRCh38) and mouse genome (GRCm38/mm10, Ensembl 76) using Burrows-Wheeler Aligner (BWA) v0.7.15. Subsequently, mouse reads were excluded with XenofilteR 32 . Other processing steps are similar as described above.…”

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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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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“…Bioinformatics analyses have recently been developed to distinguish human‐specific results from mixed human and mouse results. By using this approach, the possible contamination of results can largely be avoided . Moreover, considering the accumulated changes in xenograft tumors, PDX models do not reliably preserve the original information of parental tumors upon serial transplantation.…”

Section: Conclusion and Perspectivementioning

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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XenofilteR: computational deconvolution of mouse and human reads in tumor xenograft sequence data

Cited by 117 publications

References 33 publications

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

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

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