Xenografts faithfully recapitulate breast cancer-specific gene expression patterns of parent primary breast tumors

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories.

Translation Potential and Challenges of In Vitro and Murine Models in Cancer Clinic

As one of the leading causes of death from disease, cancer continues to pose a serious threat to human health globally. Despite the development of novel therapeutic regimens and drugs, the long-term survival of cancer patients is still very low, especially for those whose diagnosis is not caught early enough. Meanwhile, our understanding of tumorigenesis is still limited. Suitable research models are essential tools for exploring cancer mechanisms and treatments. Herein we review and compare several widely used in vitro and in vivo murine cancer models, including syngeneic tumor models, genetically engineered mouse models (GEMM), cell line-derived xenografts (CDX), patient-derived xenografts (PDX), conditionally reprogrammed (CR) cells, organoids, and MiniPDX. We will summarize the methodology and feasibility of various models in terms of their advantages and limitations in the application prospects for drug discovery and development and precision medicine.

In Vivo Modeling of Human Breast Cancer Using Cell Line and Patient-Derived Xenografts

Historically, human breast cancer has been modeled largely in vitro using long-established cell lines primarily in two-dimensional culture, but also in three-dimensional cultures of varying cellular and molecular complexities. A subset of cell line models has also been used in vivo as cell line-derived xenografts (CDX). While outstanding for conducting detailed molecular analysis of regulatory mechanisms that may function in vivo, results of drug response studies using long-established cell lines have largely failed to translate clinically. In an attempt to address this shortcoming, many laboratories have succeeded in developing clinically annotated patient-derived xenograft (PDX) models of human cancers, including breast, in a variety of host systems. While immunocompromised mice are the predominant host, the immunocompromised rat and pig, zebrafish, as well as the chicken egg chorioallantoic membrane (CAM) have also emerged as potential host platforms to help address perceived shortcomings of immunocompromised mice. With any modeling platform, the two main issues to be resolved are criteria for "credentialing" the models as valid models to represent human cancer, and utility with respect to the ability to generate clinically relevant translational research data. Such data are beginning to emerge, particularly with the activities of PDX consortia such as the NCI PDXNet Program, EuroPDX, and the International Breast Cancer Consortium, as well as a host of pharmaceutical companies and contract research organizations (CRO). This review focuses primarily on these important aspects of PDX-related research, with a focus on breast cancer.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

ESR1 mutations and therapeutic resistance in metastatic breast cancer: progress and remaining challenges

Breast cancer accounts for 25% of the cancers in women worldwide. The most common subtype of breast cancer diagnosed is hormone receptor positive, which expresses the oestrogen receptor (ER). Targeting of the ER with endocrine therapy (ET) is the current standard of care for ER-positive (ER+) breast cancer, reducing the mortality by up to 40%. Resistance to ET, however, remains a major issue for ER + breast cancer, leading to recurrence and metastasis. One major driver of ET resistance is mutations in the ER gene (ESR1) leading to constitutive transcriptional activity and reduced ET sensitivity. These mutations are particularly detrimental in metastatic breast cancer (MBC) as they are present in as high as 36% of the patients. This review summarises the pre-clinical characterisation of ESR1 mutations and their association with clinical outcomes in MBC and primary disease. The clinically approved and investigational therapeutic options for ESR1 mutant breast cancer and the current clinical trials evaluating ESR1 mutations and ET resistance are also discussed. Finally, this review addresses pre-clinical models and multi-'omics' approaches for developing the next generation of therapeutics for ESR1 mutant and ET-resistant breast cancer.

Investigating circulating tumor cells and distant metastases in patient-derived orthotopic xenograft models of triple-negative breast cancer

BACKGROUND

Circulating tumor cells (CTCs) represent a temporal "snapshot" of a patient's cancer and changes that occur during disease evolution. There is an extensive literature studying CTCs in breast cancer patients, and particularly in those with metastatic disease. In parallel, there is an increasing use of patient-derived models in preclinical investigations of human cancers. Yet studies are still limited demonstrating CTC shedding and metastasis formation in patient-derived models of breast cancer.

METHODS

We used seven patient-derived orthotopic xenograft (PDOX) models generated from triple-negative breast cancer (TNBC) patients to study CTCs and distant metastases. Tumor fragments from PDOX tissue from each of the seven models were implanted into 57 NOD scid gamma (NSG) mice, and tumor growth and volume were monitored. Human CTC capture from mouse blood was first optimized on the marker-agnostic Vortex CTC isolation platform, and whole blood was processed from 37 PDOX tumor-bearing mice.

RESULTS

Staining and imaging revealed the presence of CTCs in 32/37 (86%). The total number of CTCs varied between different PDOX tumor models and between individual mice bearing the same PDOX tumors. CTCs were heterogeneous and showed cytokeratin (CK) positive, vimentin (VIM) positive, and mixed CK/VIM phenotypes. Metastases were detected in the lung (20/57, 35%), liver (7/57, 12%), and brain (1/57, less than 2%). The seven different PDOX tumor models displayed varying degrees of metastatic potential, including one TNBC PDOX tumor model that failed to generate any detectable metastases (0/8 mice) despite having CTCs present in the blood of 5/5 tested, suggesting that CTCs from this particular PDOX tumor model may typify metastatic inefficiency.

CONCLUSION

PDOX tumor models that shed CTCs and develop distant metastases represent an important tool for investigating TNBC.

The next generation personalized models to screen hidden layers of breast cancer tumorigenicity

BACKGROUND

Breast cancer (BC) is a challenging disease and major cause of death amongst women worldwide who die due to tumor relapse or sidelong diseases. BC main complexity comes from the heterogeneous nature of breast tumors that demands customized treatments in the form of personalized medicine.

REVIEW OF THE LITERATURE AND DISCUSSION

Spatiotemporally dynamic and heterogeneous nature of BC tumors is shaped by their clonal evolution and sub-clonal selections and shapes resistance to collective or group therapies that drives cancer recurrence and tumor metastasis. Personalized intervention promises to administer medications that selectively target each individual patient tumor and even further each colonized secondary tumor. Such personalized regimens will require creation of in vitro and in vivo models genuinely recapitulating characteristics of each tumor type as initiating platforms for two main purposes: to closely monitor the tumorigenic processes that shape tumor heterogeneity and evolution as the main driving forces behind tumor chemo-resistance and relapse, and subsequently to establish patient-specific preventive and therapeutic measures. While application of tumor modeling for personalized drug screening and design requires a separate review, here we discuss the personalized utilities of xenograft modeling in investigating BC tumor formation and progression toward metastasis. We will further elaborate on the impact of innovative technologies on personalized modeling of BC tumorigenicity at improved resolution.

CONCLUSION

Heterogeneous nature of each BC tumor requires personalized intervention implying that modeling breast tumors is inevitable for better disease understanding, detection and cure. Patient-derived xenografts are just the initiating piece of the puzzle for ideal management of breast cancer. Emerging technologies promise to model BC more personalized than before.

A patient derived xenograft model of cervical cancer and cervical dysplasia

Aim

To develop a patient derived xenograft (PDX) model of cervical cancer and cervical dysplasia using the subrenal capsule.

Methods

Cervical cancer (12 Squamous Cell Carcinoma, 1 Adenocarcinoma, 1 Adenosquamous Carcinoma), 7 cervical dysplasia biopsy and normal cervical tissues were transplanted beneath the renal capsule of immunocompromised NOD/SCID/gamma mice. Resulting tumours were harvested and portions serially transplanted into new recipient mice for up to three in vivo passages. Parent and xenograft tumours were examined by immunohistochemistry for p16^INK41, HPV, and CD-45. Single cell suspensions of mixed mouse and human, or human only cell populations were also transplanted.

Results

The overall engraftment rate for the primary cervical cancer PDX model was 71.4 ±12.5% (n = 14). Tumours maintained morphological, histoarchitecture and immunohistochemical features of the parent tumour, and demonstrated invasiveness into local tissues. Single cell suspensions did not produce tumour growth in this model. Mean length of time (32.4 +/- 3.5 weeks) for the transplanted tissue to generate a tumour in the animal was similar between successive transplantations. Three of four xenografted cervical dysplasia tissues generated microscopic cystic structures resembling dysplastic cervical tissue. Normal cervical tissue (4 of 5 xenografted) also developed microscopic cervical tissue grafts.

Conclusion

The subrenal capsule can be used for a PDX model of human cervical cancer with a good engraftment rate and the ability to model in vivo characteristics of cervical cancer. For the first time we have demonstrated that cervical dysplasia and normal cervical tissue generated microscopic tissues in a PDX model.

Patient-derived xenograft mouse models: A high fidelity tool for individualized medicine

Patient-derived xenograft (PDX) mouse models involve the direct transfer of fresh human tumor samples into immunodeficient mice following surgical resection or other medical operations. Gene expression in tumors may be maintained by serial passages of tumors from mouse to mouse. These models aid research into tumor biology and pharmacology without manual manipulation of cell cultures in vitro. and are widely used in individualized cancer therapy/translational medicine, drug development and coclinical trials. PDX models exhibit higher predictive values for clinical outcomes than cell line-derived xenograft models and genetically engineered mouse models. However, PDX models are associated with certain challenges in clinical application. The present study reviewed current collections of PDX models and assessed the challenges and future directions of this field.

In Vivo Expansion of Cancer Stemness Affords Novel Cancer Stem Cell Targets: Malignant Rhabdoid Tumor as an Example

Cancer stem cell (CSC) identification relies on transplantation assays of cell subpopulations sorted from fresh tumor samples. Here, we attempt to bypass limitations of abundant tumor source and predetermined immune selection by in vivo propagating patient-derived xenografts (PDX) from human malignant rhabdoid tumor (MRT), a rare and lethal pediatric neoplasm, to an advanced state in which most cells behave as CSCs. Stemness is then probed by comparative transcriptomics of serial PDXs generating a gene signature of epithelial to mesenchymal transition, invasion/motility, metastasis, and self-renewal, pinpointing putative MRT CSC markers. The relevance of these putative CSC molecules is analyzed by sorting tumorigenic fractions from early-passaged PDX according to one such molecule, deciphering expression in archived primary tumors, and testing the effects of CSC molecule inhibition on MRT growth. Using this platform, we identify ALDH1 and lysyl oxidase (LOX) as relevant targets and provide a larger framework for target and drug discovery in rare pediatric cancers.

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Human malignant rhabdoid tumor (MRT) can be propagated in vivo as tumor xenografts

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Long-term propagated PDX enrich for CSC frequency with no need for immune selection

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Distinct gene signature in stem-like MRT xenografts reveals putative CSC biomarkers

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Screening of putative CSC biomarkers allows identification of therapeutic targets

Using PDX for Preclinical Cancer Drug Discovery: The Evolving Field

The ability to create patient derived xenografts (PDXs) has evolved considerably from the breakthrough of the development of immune compromised mice. How researchers in drug discovery have utilized PDX of certain cancer types has also changed from traditionally selecting a few models to profile a drug, to opting to assess inter-tumor response heterogeneity by screening across a broad range of tumor models, and subsequently to enable clinical stratification strategies. As with all models and methodologies, imperfections with this approach are apparent, and our understanding of the fidelity of these models continues to expand. To date though, they are still viewed as one of the most faithful modeling systems in oncology. Currently, there are many efforts ongoing to increase the utility and translatability of PDXs, including introducing a human immune component to enable immunotherapy studies.

Modeling anti-IL-6 therapy using breast cancer patient-derived xenografts

The pleiotropic cytokine IL-6 accelerates the progression of breast cancer in a variety of preclinical models through the activation of the STAT3 (signal transducer and activator of transcription 3) signaling pathway. However, the proportion of breast cancers sensitive to anti-IL-6 therapies is not known. This study evaluates the efficacy of anti-IL-6 therapies using breast cancer patient derived xenografts (PDXs). During the generation of our collection of PDXs, we showed that the successful engraftment of tumor tissue in immunodeficient mice correlates with bad prognosis. Four PDXs out of six were resistant to anti-IL-6 therapies and the expression of IL-6, its receptor or the levels of phospho-STAT3 (the active form of the signal transducer) did not correlate with sensitivity. Using cell cultures established from the PDXs as well as samples from in vivo treatments, we showed that only tumors in which the activation of STAT3 depends on IL-6 respond to the blocking antibodies. Our results indicate that only a fraction of breast tumors are responsive to anti-IL-6 therapies. In order to identify responsive tumors, a functional assay to determine the dependence of STAT3 activation on IL-6 should be performed.

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer

Background

Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown.

Methods

We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient-derived xenografts (PDXs) using core needle biopsies. Chemotherapy response was assessed at surgery.

Results

Recurrent "targetable" alterations were not enriched in patients without pathologic complete response (pCR); however, upregulation of steroid receptor signaling and lower pCR rates (16.7%, 1/6) were observed in triple-negative breast cancer (TNBC) patients with luminal androgen receptor (LAR) vs basal subtypes (60.0%, 21/35). Within TNBC, TP53 mutation frequency (75.6%, 31/41) did not differ comparing basal (74.3%, 26/35) and LAR (83.3%, 5/6); however, TP53 stop-gain mutations were more common in basal (22.9%, 8/35) vs LAR (0.0%, 0/6), which was confirmed in The Cancer Genome Atlas and British Columbia data sets. In luminal B tumors, Ki-67 responses were observed in tumors that harbored mutations conferring endocrine resistance ( p53, AKT, and IKBKE ). PDX take rate (27.4%, 31/113) varied according to tumor subtype, and in a patient with progression on NAC, sequencing data informed drug selection (olaparib) with in vivo antitumor activity observed in the primary and resistant (postchemotherapy) PDXs.

Conclusions

In this study, we demonstrate the feasibility of tumor sequencing and PDX generation in the NAC setting. "Targetable" alterations were not enriched in chemotherapy-resistant tumors; however, prioritization of drug testing based on sequence data may accelerate drug development.

Patient-derived Mammosphere and Xenograft Tumour Initiation Correlates with Progression to Metastasis

Breast cancer specific mortality results from tumour cell dissemination and metastatic colonisation. Identification of the cells and processes responsible for metastasis will enable better prevention and control of metastatic disease, thus reducing relapse and mortality. To better understand these processes, we prospectively collected 307 patient-derived breast cancer samples (n = 195 early breast cancers (EBC) and n = 112 metastatic samples (MBC)). We assessed colony-forming activity in vitro by growing isolated cells in both primary (formation) and secondary (self-renewal) mammosphere culture, and tumour initiating activity in vivo through subcutaneous transplantation of fragments or cells into mice. Metastatic samples formed primary mammosphere colonies significantly more frequently than early breast cancers and had significantly higher primary mammosphere colony formation efficiency (0.9 % vs. 0.6 %; p < 0.0001). Tumour initiation in vivo was significantly higher in metastatic than early breast cancer samples (63 % vs. 38 %, p = 0.04). Of 144 breast cancer samples implanted in vivo, we established 20 stable patient-derived xenograft (PDX) models at passage 2 or greater. Lung metastases were detected in mice from 14 PDX models. Mammosphere colony formation in vitro significantly correlated with the ability of a tumour to metastasise to the lungs in vivo (p = 0.05), but not with subcutaneous tumour initiation. In summary, the breast cancer stem cell activities of colony formation and tumour initiation are increased in metastatic compared to early samples, and predict metastasis in vivo. These results suggest that breast stem cell activity will predict for poor outcome tumours, and therapy targeting this activity will improve outcomes for patients with metastatic disease.

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.

Steroid Hormone Receptor Positive Breast Cancer Patient-Derived Xenografts

The vast majority of breast cancers are positive for estrogen receptor (ER) and depend on estrogens for growth. These tumors are treated with a variety of ER-targeted endocrine therapies, although eventual resistance remains a major clinical problem. Other steroid hormone receptors such as progesterone receptor (PR) and androgen receptor (AR) are emerging as additional prospective targets in breast cancer. The fundamental mechanism of action of these steroid receptors in gene regulation has been defined mainly by several breast cancer cell lines that were established in the late 1970s. More recently, breast cancer patient-derived xenografts (PDX) have been developed by multiple groups at institutions in several countries. These new models capture the large degree of heterogeneity between patients and within tumors and promise to advance our understanding of steroid hormone receptor positive breast cancer and endocrine resistance. Unfortunately, steroid hormone receptor positive breast cancers are much more difficult than their receptor negative counterparts to establish into sustainable PDX. Herein we discuss the derivation of steroid hormone receptor positive breast cancer PDX, several pitfalls in their genesis, and their utility in preclinical and translational steroid hormone receptor research.

Ovarian carcinoma patient derived xenografts reproduce their tumor of origin and preserve an oligoclonal structure

Advanced Epithelial Ovarian Cancer (EOC) patients frequently relapse by 24 months and develop resistant disease. Research on EOC therapies relies on cancer cell lines established decades ago making Patient Derived Xenografts (PDX) attractive models, because they are faithful representations of the original tumor. We established 35 ovarian cancer PDXs resulting from the original graft of 77 EOC samples onto immuno-compromised mice. PDXs covered the diversity of EOC histotypes and graft take was correlated with early patient death. Fourteen PDXs were characterized at the genetic and histological levels. PDXs reproduced phenotypic features of the ovarian tumors of origin and conserved the principal characteristics of the original copy number change (CNC) profiles over several passages. However, CNC fluctuations in specific subregions comparing the original tumor and the PDXs indicated the oligoclonal nature of the original tumors. Detailed analysis by CGH, FISH and exome sequencing of one case, for which several tumor nodules were sampled and grafted, revealed that PDXs globally maintained an oligoclonal structure. No overgrowth of a particular subclone present in the original tumor was observed in the PDXs. This suggested that xenotransplantation of ovarian tumors and growth as PDX preserved at least in part the clonal diversity of the original tumor. We believe our data reinforce the potential of PDX as exquisite tools in pre-clinical assays.

Characterization of Breast Cancer Preclinical Models Reveals a Specific Pattern of Macrophage Polarization

Drug discovery efforts have focused on the tumor microenvironment in recent years. However, few studies have characterized the stroma component in patient-derived xenografts (PDXs) and genetically engineered mouse models (GEMs). In this study, we characterized the stroma in various models of breast cancer tumors in mice. We performed transcriptomic and flow cytometry analyses on murine populations for a series of 25 PDXs and the two most commonly used GEMs (MMTV-PyMT and MMTV-erBb2). We sorted macrophages from five models. We then profiled gene expression in these cells, which were also subjected to flow cytometry for phenotypic characterization. Hematopoietic cell composition, mostly macrophages and granulocytes, differed between tumors. Macrophages had a specific polarization phenotype related to their M1/M2 classification and associated with the expression of genes involved in the recruitment, invasion and metastasis processes. The heterogeneity of the stroma component of the models studied suggests that tumor cells modify their microenvironment to satisfy their needs. Our observations suggest that such models are of relevance for preclinical studies.

Patient-Derived Xenograft: An Adjuvant Technology for the Treatment of Metastatic Disease

The occurrence of metastases severely affects prognosis for patients with cancer, making metastatic disease a daily societal challenge. Because of resistance to drugs, the potential curability with chemotherapy at the metastatic stage remains low. Large genomic analyses to identify new targets have their limitations due to intratumor heterogeneity when they are performed on tumor samples from primary tumors and because the functional value of molecular abnormalities in a cancer is usually not known. Additional tools are thus required for the development of new anticancer agents. The use of preclinical models is a key component of translational research in oncology. For four decades, xenograft models of human cancer cell lines injected subcutaneously in immunocompromised mice have been widely used, with disappointing results for predicting the clinical benefit of a new drug. Patient-derived xenografts are preclinical models rediscovered as innovative pharmacological tools, both for the preclinical development of anticancer drugs and as individual models for personalized treatment of metastatic disease. Here, we review the recent progress reported using patient-derived xenografts for the treatment of metastatic disease, and discuss the feasibility of their implementation in daily oncological care.

Bioengineering Models for Breast Cancer Research

Despite substantial advances in early diagnosis, breast cancer (BC) still remains a clinical challenge. Most BC models use complex in vivo models and two-dimensional monolayer cultures that do not fully mimic the tumor microenvironment. The integration of cancer biology and engineering can lead to the development of novel in vitro approaches to study BC behavior and quantitatively assess different features of the tumor microenvironment that may influence cell behavior. In this review, we present tissue engineering approaches to model BC in vitro. Recent advances in the use of three-dimensional cell culture models to study various aspects of BC disease in vitro are described. The emerging area of studying BC dormancy using these models is also reviewed.

The bone marrow niche in support of breast cancer dormancy

Despite the success in detecting breast cancer (BC) early and, with aggressive therapeutic intervention, BC remains a clinical problem. The bone marrow (BM) is a favorable metastatic site for breast cancer cells (BCCs). In BM, the survival of BCCs is partly achieved by the supporting microenvironment, including the presence of immune suppressive cells such as mesenchymal stem cells (MSCs). The heterogeneity of BCCs brings up the question of how each subset interacts with the BM microenvironment. The cancer stem cells (CSCs) survive in the BM as cycling quiescence cells and, forming gap junctional intercellular communication (GJIC) with the hematopoietic supporting stromal cells and MSCs. This type of communication has been identified close to the endosteum. Additionally, dormancy can occur by soluble mediators such as cytokines and also by the exchange of exosomes. These latter mechanisms are reviewed in the context of metastasis of BC to the BM for transition as dormant cells. The article also discusses how immune cells such as macrophages and regulatory T-cells facilitate BC dormancy. The challenges of studying BC dormancy in 2-dimensional (2-D) system are also incorporated by proposing 3-D system by engineering methods to recapitulate the BM microenvironment.

A quantitative proteomics analysis of MCF7 breast cancer stem and progenitor cell populations

Accumulating evidence has demonstrated that breast cancers are initiated and develop from a small population of stem-like cells termed cancer stem cells (CSCs). These cells are hypothesized to mediate tumor metastasis and contribute to therapeutic resistance. However, the molecular regulatory networks responsible for maintaining CSCs in an undifferentiated state have yet to be elucidated. In this study, we used CSC markers to isolate pure breast CSCs fractions (ALDH+ and CD44+CD24- cell populations) and the mature luminal cells (CD49f-EpCAM+) from the MCF7 cell line. Proteomic analysis was performed on these samples and a total of 3304 proteins were identified. A label-free quantitative method was applied to analyze differentially expressed proteins. Using the criteria of greater than twofold changes and p value <0.05, 305, 322 and 98 proteins were identified as significantly different in three pairwise comparisons of ALDH+ versus CD44+CD24-, ALDH+ versus CD49f-EpCAM+ and CD44+CD24- versus CD49f-EpCAM+, respectively. Pathway analysis of differentially expressed proteins by Ingenuity Pathway Analysis (IPA) revealed potential molecular regulatory networks that may regulate CSCs. Selected differential proteins were validated by Western blot assay and immunohistochemical staining. The use of proteomics analysis may increase our understanding of the underlying molecular mechanisms of breast CSCs. This may be of importance in the future development of anti-CSC therapeutics.

Prognostic and functional importance of the engraftment-associated genes in the patient-derived xenograft models of triple-negative breast cancers

We aimed to identify the factors affecting the successful tumor engraftment in breast cancer patient-derived xenograft (PDX) models. Further, we investigated the prognostic significance and the functional importance of the PDX engraftment-related genes in triple-negative breast cancers (TNBC). The clinico-pathologic features of 81 breast cancer patients whose tissues were used for PDX transplantation were analyzed to identify the factors affecting the PDX engraftment. A gene signature associated with the PDX engraftment was discovered and its clinical importance was tested in a publicly available dataset and in vitro assays. Nineteen out of 81 (23.4 %) transplanted tumors were successfully engrafted into the PDX models. The engraftment rate was highest in TNBC when compared to other subtypes (p = 0.001) and in recurrent or chemotherapy-resistant tumors compared to newly diagnosed primary tumors (p = 0.024). PDX tumors originated from the TNBC cases showed more rapid tumor growth in mice. Gene expression profiling showed that down-regulation of genes involved in the tumor-immune interaction was significantly associated with the successful PDX engraftment. The engraftment gene signature was associated with worse survival outcome when tested in publicly available mRNA datasets of TNBC cases. Among the engraftment-related genes, PHLDA2, TKT, and P4HA2 showed high expression in triple-negative breast cancer cell lines, and siRNA-based gene silencing resulted in reduced cell invasion and proliferation in vitro. Our results show that the PDX engraftment may reflect the aggressive phenotype in breast cancer. Genes associated with the PDX engraftment may provide a novel prognostic biomarker and therapeutic targets in TNBC.

Patient-derived xenograft models of breast cancer and their predictive power

Despite advances in the treatment of patients with early and metastatic breast cancer, mortality remains high due to intrinsic or acquired resistance to therapy. Increased understanding of the genomic landscape through massively parallel sequencing has revealed somatic mutations common to specific subtypes of breast cancer, provided new prognostic and predictive markers, and highlighted potential therapeutic targets. Evaluating new targets using established cell lines is limited by the inexact correlation between responsiveness observed in cell lines versus that elicited in the patient. Patient-derived xenografts (PDXs) generated from fresh tumor specimens recapitulate the diversity of breast cancer and reflect histopathology, tumor behavior, and the metastatic properties of the original tumor. The high degree of genomic preservation evident across primary tumors and their matching PDXs over serial passaging validate them as important preclinical tools. Indeed, there is accumulating evidence that PDXs can recapitulate treatment responses of the parental tumor. The finding that tumor engraftment is an independent and poor prognostic indicator of patient outcome represents the first step towards personalized medicine. Here we review the utility of breast cancer PDX models to study the clonal evolution of tumors and to evaluate novel therapies and drug resistance.

Patient-derived ovarian tumor xenografts recapitulate human clinicopathology and genetic alterations

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy. On the basis of its histopathology and molecular-genomic changes, ovarian cancer has been divided into subtypes, each with distinct biology and outcome. The aim of this study was to develop a panel of patient-derived EOC xenografts that recapitulate the molecular and biologic heterogeneity of human ovarian cancer. Thirty-four EOC xenografts were successfully established, either subcutaneously or intraperitoneally, in nude mice. The xenografts were histologically similar to the corresponding patient tumor and comprised all the major ovarian cancer subtypes. After orthotopic transplantation in the bursa of the mouse ovary, they disseminate into the organs of the peritoneal cavity and produce ascites, typical of ovarian cancer. Gene expression analysis and mutation status indicated a high degree of similarity with the original patient and discriminate different subsets of xenografts. They were very responsive, responsive, and resistant to cisplatin, resembling the clinical situation in ovarian cancer. This panel of patient-derived EOC xenografts that recapitulate the recently type I and type II classification serves to study the biology of ovarian cancer, identify tumor-specific molecular markers, and develop novel treatment modalities.

Molecular markers for breast cancer diagnosis, prognosis and targeted therapy

Precision medicine involves understanding the molecular drivers unique to an individual patient's cancer so that specific factors may be targeted with the goal of improved patient outcomes. The purpose of this article is to review standard of care and research grade (non-standard of care) biomarkers in breast cancer that may be useful for diagnosis, prognosis and targeted therapy.

Personalising pancreas cancer treatment: When tissue is the issue

The treatment of advanced pancreatic cancer has not moved much beyond single agent gemcitabine until recently when protocols such as FOLFIRINOX (fluorouracil, leucovorin, irinotecan and oxaliplatin) and nab-paclitaxel-gemcitabine have demonstrated some improved outcomes. Advances in technology especially in massively parallel genome sequencing has progressed our understanding of the biology of pancreatic cancer especially the candidate signalling pathways that are involved in tumourogenesis and disease course. This has allowed identification of potentially actionable mutations that may be targeted by new biological agents. The heterogeneity of pancreatic cancer makes tumour tissue collection important with the aim of being able to personalise therapies for the individual as opposed to a one size fits all approach to treatment of the condition. This paper reviews the developments in this area of translational research and the ongoing clinical studies that will attempt to move this into the everyday oncology practice.

Advances in patient-derived tumor xenografts: from target identification to predicting clinical response rates in oncology

Most oncology compounds entering clinical development have passed stringent preclinical pharmacology evaluation criteria. However, only a small fraction of experimental agents induce meaningful antitumor activities in the clinic. Low predictability of conventional preclinical pharmacology models is frequently cited as a main reason for the unusually high clinical attrition rates of therapeutic compounds in oncology. Therefore, improvement in the predictive values of preclinical efficacy models for clinical outcome holds great promise to reduce the clinical attrition rates of experimental compounds. Recent reports suggest that pharmacology studies conducted with patient derived xenograft (PDX) tumors are more predictive for clinical outcome compared to conventional, cell line derived xenograft (CDX) models, in particular when therapeutic compounds were tested at clinically relevant doses (CRDs). Moreover, the study of the most malignant cell types within tumors, the tumor initiating cells (TICs), relies on the availability of preclinical models that mimic the lineage hierarchy of cells within tumors. PDX models were shown to more closely recapitulate the heterogeneity of patient tumors and maintain the molecular, genetic, and histological complexity of human tumors during early stages of sequential passaging in mice, rendering them ideal tools to study the responses of TICs, tumor- and stromal cells to therapeutic intervention. In this commentary, we review the progress made in the development of PDX models in key areas of oncology research, including target identification and validation, tumor indication search and the development of a biomarker hypothesis that can be tested in the clinic to identify patients that will benefit most from therapeutic intervention.

Lessons learned from the intrinsic subtypes of breast cancer in the quest for precision therapy

BACKGROUND

Wide variability in breast cancer, between patients and within each individual neoplasm, adds confounding complexity to the treatment of the disease. In clinical practice, hormone receptor status has been used to classify breast tumours and to guide treatment. Modern classification systems should take the wide tumour heterogeneity into account to improve patient outcome.

METHODS

This article reviews the identification of the intrinsic molecular subtypes of breast cancer, their prognostic and therapeutic implications, and the impact of tumour heterogeneity on cancer progression and treatment. The possibility of functionally addressing tumour-specific characteristics in in vivo models to inform decisions for precision therapies is also discussed.

RESULTS

Despite the robust breast tumour classification system provided by gene expression profiling, heterogeneity is also evident within these molecular portraits. A complicating factor in breast cancer classification is the process of selective clonality within developing neoplasms. Phenotypically and functionally distinct clones representing the intratumour heterogeneity might confuse molecular classification. Molecular portraits of the heterogeneous primary tumour might not necessarily reflect the subclone of cancer cells that causes the disease to relapse. Studies of reciprocal relationships between cancer cell subpopulations within developing tumours are therefore needed, and are possible only in genetically engineered mouse models or patient-derived xenograft models, in which the treatment-induced selection pressure on individual cell clones can be mimicked.

CONCLUSION

In the future, more refined classifications, based on integration of information at several molecular levels, are required to improve treatment guidelines. Large-scale translational research efforts paved the way for identification of the intrinsic subtypes, and are still fundamental for ensuring future progress in cancer care.

Patient-derived xenografts of triple-negative breast cancer reproduce molecular features of patient tumors and respond to mTOR inhibition

INTRODUCTION

Triple-negative breast cancer (TNBC) is aggressive and lacks targeted therapies. Phosphatidylinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) pathways are frequently activated in TNBC patient tumors at the genome, gene expression and protein levels, and mTOR inhibitors have been shown to inhibit growth in TNBC cell lines. We describe a panel of patient-derived xenografts representing multiple TNBC subtypes and use them to test preclinical drug efficacy of two mTOR inhibitors, sirolimus (rapamycin) and temsirolimus (CCI-779).

METHODS

We generated a panel of seven patient-derived orthotopic xenografts from six primary TNBC tumors and one metastasis. Patient tumors and corresponding xenografts were compared by histology, immunohistochemistry, array comparative genomic hybridization (aCGH) and phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) sequencing; TNBC subtypes were determined. Using a previously published logistic regression approach, we generated a rapamycin response signature from Connectivity Map gene expression data and used it to predict rapamycin sensitivity in 1,401 human breast cancers of different intrinsic subtypes, prompting in vivo testing of mTOR inhibitors and doxorubicin in our TNBC xenografts.

RESULTS

Patient-derived xenografts recapitulated histology, biomarker expression and global genomic features of patient tumors. Two primary tumors had PIK3CA coding mutations, and five of six primary tumors showed flanking intron single nucleotide polymorphisms (SNPs) with conservation of sequence variations between primary tumors and xenografts, even on subsequent xenograft passages. Gene expression profiling showed that our models represent at least four of six TNBC subtypes. The rapamycin response signature predicted sensitivity for 94% of basal-like breast cancers in a large dataset. Drug testing of mTOR inhibitors in our xenografts showed 77 to 99% growth inhibition, significantly more than doxorubicin; protein phosphorylation studies indicated constitutive activation of the mTOR pathway that decreased with treatment. However, no tumor was completely eradicated.

CONCLUSIONS

A panel of patient-derived xenograft models covering a spectrum of TNBC subtypes was generated that histologically and genomically matched original patient tumors. Consistent with in silico predictions, mTOR inhibitor testing in our TNBC xenografts showed significant tumor growth inhibition in all, suggesting that mTOR inhibitors can be effective in TNBC, but will require use with additional therapies, warranting investigation of optimal drug combinations.

Breast tumor PDXs are genetically plastic and correspond to a subset of aggressive cancers prone to relapse

Patient derived xenografts (PDXs) are increasingly appreciated models in cancer research, particularly for preclinical testing, as they reflect the patient's tumor biology more accurately than cancer cell lines. We have established a collection of 20 breast PDXs and characterized their biological and clinical features, as well as their genetic stability. While most PDXs originated from triple negative breast cancers (70%), our collection comprised five ER + cases (25%). Remarkably, the tumors that produced PDXs derived from a subset of aggressive breast cancers with a high proportion of grade 3 tumors and reduced recurrence-free survival. Consistent with this, we found significant differences between the transcriptomic signatures of tumors that produced a PDX (Take) and those that did not (No Take). The PDXs faithfully recapitulate the histological features of their primary tumors, and retain an excellent conservation of molecular classification assignment and Copy Number Change (CNC). Furthermore, the CNC profiles of different PDXs established from the same tumor overlap significantly. However, a small fraction of CNCs in the primary tumor that correspond to oligoclonal events were gradually lost during sequential passaging, suggesting that the PDXs' genetic structure eventually stabilizes around a dominant clone present in the tumor of origin. Finally, de novo occurring genetic events covering up to 9% of the genome were found in only a minority of the PDXs, showing that PDXs have limited genetic instability. These data show that breast cancer PDXs represent a subset of aggressive tumors prone to relapse, and that despite of an excellent conservation of original features, they remain genetically dynamic elements.

Patient-derived breast tumor xenografts facilitating personalized cancer therapy

Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone (American Cancer Society, Cancer Facts &Figures 2012. Atlanta: American Cancer Society; 2012). Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions. To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity. In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.