Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models.Significance: PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field. Cancer Discov; 4(9); 998-1013.

Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer evolutionary dynamics during tumour progression and under drug pressure, and the mechanisms of resistance to treatment. The ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions. This Opinion article discusses aspects of PDX modelling that are relevant to these questions and highlights the merits of shared PDX resources to advance cancer medicine from the 6 perspective of EurOPDX, an international initiative devoted to PDX-based research.Response to anticancer therapies varies owing to the substantial molecular heterogeneity of human tumours and to poorly defined mechanisms of drug efficacy and resistance 1 . Immortalized cancer cell lines, either cultured in vitro or grown as xenografts, cannot interrogate the complexity of human tumours, and only provide determinate insights into human disease, as they are limited in number and diversity, and have been cultured on plastic over decades 2 .This disconnection in scale and biological accuracy contributes considerably to attrition in drug development [3][4][5] .Surgically derived clinical tumour samples that are implanted in mice (known as patient-derived xenografts (PDXs)) are expected to better inform therapeutic development strategies. As intact tissue -in which the tumour architecture and the relative proportion of cancer cells and stromal cells are both maintained -is directly implanted into recipient animals, the alignment with human disease is enhanced. More importantly, PDXs retain the idiosyncratic characteristics of different tumours from different patients; hence, they can effectively recapitulate the intra-tumour and inter-tumour heterogeneity that typifies human cancer 6-9 . 7 Exhaustive information on the key characteristics and the practical applications of PDXs can be found in recent reviews [10][11][12][13] . In this Opinion article, we discuss basic methodological concepts, as well as challenges and opportunities in developing "next-generation" models to improve the reach of PDXs as preclinical tools for in vivo studies (TABLE 1). We also elaborate on the merits of PDXs for exploring the intrinsic heterogeneity and subclonal genetic evolution of individual tumours, and discuss how this may influence therapeutic resistance. Finally, we examine the utility of PDXs in navigating complex variables in clinical decision-making, such as the discovery of predictive and prognostic biomarkers, and the categorization of genotype-drug response correlations in high-throughput formats. Being primarily co-authored by leading members of the EurOPDX Consortium (see Further information), we provide...

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Valosin-containing protein (VCP, also called p97) is an essential and highly conserved adenosine triphosphate-dependent chaperone implicated in a wide range of cellular processes in eukaryotes, and mild VCP mutations can cause severe neurodegenerative disease. Here we show that mammalian VCP is trimethylated on Lys315 in a variety of cell lines and tissues, and that the previously uncharacterized protein mETTL21D (denoted here as VCP lysine methyltransferase, VCP-KmT) is the responsible enzyme. VCP methylation was abolished in three human VCPKmT knockout cell lines generated with zinc-finger nucleases. Interestingly, VCP-KmT was recently reported to promote tumour metastasis, and indeed, VCP-KmT-deficient cells displayed reduced growth rate, migration and invasive potential. Finally, we present data indicating that VCP-KmT, calmodulin-lysine methyltransferase and eight uncharacterized proteins together constitute a novel human protein methyltransferase family. The present work provides new insights on protein methylation and its links to human disease.

Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression, we apply genome-wide expression–methylation quantitative trait loci (emQTL) analysis between DNA methylation and gene expression. On a whole genome scale, in cis and in trans, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association in three breast cancer cohorts (n = 104, n = 253 and n = 277). The expression–methylation quantitative trait loci associations form two main clusters; one relates to tumor infiltrating immune cell signatures and the other to estrogen receptor signaling. In the estrogen related cluster, using ChromHMM segmentation and transcription factor chromatin immunoprecipitation sequencing data, we identify transcriptional networks regulated in a cell lineage-specific manner by DNA methylation at enhancers. These networks are strongly dominated by ERα, FOXA1 or GATA3 and their targets were functionally validated using knockdown by small interfering RNA or GRO-seq analysis after transcriptional stimulation with estrogen.

The present data provide further indications that increased MDM2 expression level, caused by gene amplification or altered regulation of transcription, is involved in tumor progression of some, but not all, sarcoma subtypes.

B7-H3, an immunoregulatory protein, is known to play a role in tumor progression. In many cancer types, observed correlations between high B7-H3 expression and poor prognosis have been attributed to involvement in antitumor immunity.However, here we demonstrate a nonimmunological alternative function of B7-H3 in cancer metastasis. Since advanced malignant melanoma is a disease with a poor survival rate and a broad pattern of metastasis, we used this disease as a model in our studies. We found that shRNA silencing of B7-H3 reduced the in vitro migratory potential and matrigel invasiveness of MDA-MB-435 and FEMX-I melanoma cells. In an experimental metastasis model in vivo, B7-H3 silencing of MDA-MB-435 cells resulted in reduced metastatic capacity and significantly increased the median symptom-free survival of nude mice (147 vs. 65 days, p < 0.001) and rats (53 vs. 42 days, p 5 0.025) injected with MDA-MB-435 cells. Furthermore, a smaller fraction of mice had microscopically detectable metastases compared to control animals, and the pattern of metastases was slightly different between the two groups but with the brain as the predominant organ. Immunohistochemistry on samples from two melanoma patients showed strong B7-H3 staining in both a primary tumor and metastases. Notably, the metastasis-associated proteins, matrix metalloproteinase (MMP)-2, signal transducer and activator of transcription 3 (Stat3), and the level of secreted interleukin-8 (IL-8) were reduced in the B7-H3 knock-down cell variants, whereas tissue inhibitor of metalloproteinase (TIMP)-1 and-2 levels were increased. Taken together, our findings indicate a novel role for B7-H3 in the regulation of the metastatic capacity of melanoma cells and it might be a potential therapeutic target for anti-metastasis therapy.B7-H3 (CD276) is a type I transmembrane protein with immunoglobulin-like structure. Two different isoforms are described having either two or four immunoglobulin domains, the latter being dominant in humans. 1,2 B7-H3 is a member of the B7/CD28 immunoglobulin superfamily which consists of several ligands that have inhibitory and stimulatory effects on the regulation of immune responses to transformed cells, thus being involved in tumor immunity, 3 and the protein is known to both activate and inhibit T-cell responses. 4,5 This is reflected in the conflicting reports on its role in cancer describing both beneficial and adverse effects. Thus, several immunohistochemical studies have demonstrated a correlation between high expression of the protein and tumor progression, 6-11 whereas other studies suggest a positive effect on the clinical outcome. 12,13 Although the effects of B7-H3 in cancer have been attributed to its involvement in antitumor immunity, its exact function remains unclear.In contrast to previous reports, we have investigated the B7-H3 protein in nonimmunological systems and conclude that it also plays a direct role in cancer progression. In vitro studies on cancer cells showed that siRNA down-regulation of B7-H3 reduced cel...

The number of relevant and well‐characterized cell lines and xenograft models for studying human breast cancer are few, and may represent a limitation for this field of research. With the aim of developing new breast cancer model systems for in vivo studies of hormone dependent and independent tumor growth, progression and invasion, and for in vivo experimental therapy studies, we collected primary mammary tumor specimens from patients, and implanted them in immunodeficient mice. Primary tumor tissue from 29 patients with breast cancer was implanted subcutaneously with matrigel in SCID mice, in the presence of continuous release of estradiol. The tumors were transferred into new animals when reaching a diameter of 15mm and engrafted tumors were harvested for morphological and molecular characterization from passage six. Further, gene expression profiling was performed using Agilent Human Whole Genome Oligo Microarrays, as well as DNA copy number analysis using Agilent Human Genome CGH 244K Microarrays. Of the 30 primary tumors implanted into mice (including two implants from the same patient), two gave rise to viable tumors beyond passage ten. One showed high expression levels of estrogen receptor‐α protein (ER) while the other was negative. Histopathological evaluation of xenograft tumors was carried out at passage 10–12; both xenografts maintained the morphological characteristics of the original tumors (classified as invasive grade III ductal carcinomas). The genomic profile of the ER‐positive xenograft tumor resembled the profile of the primary tumor, while the profile obtained from the ER‐negative parental tumor was different from the xenograft. However, the ER‐negative parental tumor and xenograft clustered on the same branch using unsupervised hierarchical clustering analysis on RNA microarray expression data of “intrinsic genes”. A significant variation was observed in the expression of extracellular matrix (ECM)‐related genes, which were found downregulated in the engrafted tumors compared to the primary tumor. By IHC and qRT‐PCR we found that the downregulation of stroma‐related genes was compensated by the overexpression of such molecules by the mouse host tissue. The two established breast cancer xenograft models showed different histopathological characteristics and profound diversity in gene expression patterns that in part can be associated to their ER status and here described as basal‐like and luminal‐like phenotype, respectively. These two new breast cancer xenografts represent useful preclinical tools for developing and testing of new therapies and improving our knowledge on breast cancer biology.