Interrogating open issues in cancer precision medicine with patient-derived xenografts

Targeting minimal residual disease: a path to cure?

Therapeutics that block kinases, transcriptional modifiers, immune checkpoints and other biological vulnerabilities are transforming cancer treatment. As a result, many patients achieve dramatic responses, including complete radiographical or pathological remission, yet retain minimal residual disease (MRD), which results in relapse. New functional approaches can characterize clonal heterogeneity and predict therapeutic sensitivity of MRD at a single-cell level. Preliminary evidence suggests that iterative detection, profiling and targeting of MRD would meaningfully improve outcomes and may even lead to cure.

Rituximab Treatment Prevents Lymphoma Onset in Gastric Cancer Patient-Derived Xenografts

Patient-Derived Xenografts (PDXs), entailing implantation of cancer specimens in immunocompromised mice, are emerging as a valuable translational model that could help validate biologically relevant targets and assist the clinical development of novel therapeutic strategies for gastric cancer.

More than 30% of PDXs generated from gastric carcinoma samples developed human B-cell lymphomas instead of gastric cancer. These lymphomas were monoclonal, Epstein Barr Virus (EBV) positive, originated tumorigenic cell cultures and displayed a mutational burden and an expression profile distinct from gastric adenocarcinomas. The ability of grafted samples to develop lymphomas did not correlate with patient outcome, nor with the histotype, the lymphocyte infiltration level, or the EBV status of the original gastric tumor, impeding from foreseeing lymphoma onset. Interestingly, lymphoma development was significantly more frequent when primary rather than metastatic samples were grafted.

Notably, the development of such lympho-proliferative disease could be prevented by a short rituximab treatment upon mice implant, without negatively affecting gastric carcinoma engraftment.

Due to the high frequency of human lymphoma onset, our data show that a careful histologic analysis is mandatory when generating gastric cancer PDXs. Such care would avoid misleading results that could occur if testing of putative gastric cancer therapies is performed in lymphoma PDXs. We propose rituximab treatment of mice to prevent lymphoma development in PDX models, averting the loss of human-derived samples.

Patient-derived conditionally reprogrammed cells maintain intra-tumor genetic heterogeneity

Preclinical in vitro models provide an essential tool to study cancer cell biology as well as aid in translational research, including drug target identification and drug discovery efforts. For any model to be clinically relevant, it needs to recapitulate the biology and cell heterogeneity of the primary tumor. We recently developed and described a conditional reprogramming (CR) cell technology that addresses many of these needs and avoids the deficiencies of most current cancer cell lines, which are usually clonal in origin. Here, we used the CR cell method to generate a collection of patient-derived cell cultures from non-small cell lung cancers (NSCLC). Whole exome sequencing and copy number variations are used for the first time to address the capability of CR cells to keep their tumor-derived heterogeneity. Our results indicated that these primary cultures largely maintained the molecular characteristics of the original tumors. Using a mutant-allele tumor heterogeneity (MATH) score, we showed that CR cells are able to keep and maintain most of the intra-tumoral heterogeneity, suggesting oligoclonality of these cultures. CR cultures therefore represent a pre-clinical lung cancer model for future basic and translational studies.

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.

Identifying and Targeting Sporadic Oncogenic Genetic Aberrations in Mouse Models of Triple-Negative Breast Cancer

Triple-negative breast cancers (TNBC) are genetically characterized by aberrations in TP53 and a low rate of activating point mutations in common oncogenes, rendering it challenging in applying targeted therapies. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) to identify somatic genetic alterations in mouse models of TNBCs driven by loss of Trp53 alone or in combination with Brca1 Amplifications or translocations that resulted in elevated oncoprotein expression or oncoprotein-containing fusions, respectively, as well as frameshift mutations of tumor suppressors were identified in approximately 50% of the tumors evaluated. Although the spectrum of sporadic genetic alterations was diverse, the majority had in common the ability to activate the MAPK/PI3K pathways. Importantly, we demonstrated that approved or experimental drugs efficiently induce tumor regression specifically in tumors harboring somatic aberrations of the drug target. Our study suggests that the combination of WES and RNA-seq on human TNBC will lead to the identification of actionable therapeutic targets for precision medicine-guided TNBC treatment.Significance: Using combined WES and RNA-seq analyses, we identified sporadic oncogenic events in TNBC mouse models that share the capacity to activate the MAPK and/or PI3K pathways. Our data support a treatment tailored to the genetics of individual tumors that parallels the approaches being investigated in the ongoing NCI-MATCH, My Pathway Trial, and ESMART clinical trials. Cancer Discov; 8(3); 354-69. ©2017 AACR.See related commentary by Natrajan et al., p. 272See related article by Matissek et al., p. 336This article is highlighted in the In This Issue feature, p. 253.

Patient-derived organoids model treatment response of metastatic gastrointestinal cancers

Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from metastatic, heavily pretreated colorectal and gastroesophageal cancer patients recruited in phase 1/2 clinical trials. Phenotypic and genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. Molecular profiling of tumor organoids was matched to drug-screening results, suggesting that PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared responses to anticancer agents ex vivo in organoids and PDO-based orthotopic mouse tumor xenograft models with the responses of the patients in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic and could be implemented in personalized medicine programs.

Establishing and Maintaining an Extensive Library of Patient-Derived Xenograft Models

Patient-derived xenograft (PDX) models have recently emerged as a highly desirable platform in oncology and are expected to substantially broaden the way in vivo studies are designed and executed and to reshape drug discovery programs. However, acquisition of patient-derived samples, and propagation, annotation and distribution of PDXs are complex processes that require a high degree of coordination among clinic, surgery and laboratory personnel, and are fraught with challenges that are administrative, procedural and technical. Here, we examine in detail the major aspects of this complex process and relate our experience in establishing a PDX Core Laboratory within a large academic institution.

Acute Drug Effects on the Human Placental Tissue: The Development of a Placental Murine Xenograft Model

OBJECTIVE

A pilot study was conducted to establish a human placental xenograft, which could serve as a model to evaluate the effect of toxic exposures during pregnancy.

STUDY DESIGN

The protocol consisted of engraftment of third-trimester human placental tissue in immunocompromised mice, after induction of a pseudo-pregnancy state by ovariectomy and progesterone supplementation. To validate the model, the placental tissue before and after engraftment was examined by immunohistochemistry, fluorescence-activated cell sorting (FACS), single-nucleotide polymorphism (SNP) genotyping, and whole transcriptome sequencing (WTSS). The human chorion gonadotropin (hCG) production in serum and urine was examined by enzyme-linked immunosorbent assay.

RESULTS

Microscopic evaluation of the placental tissue before and after engraftment revealed a stable morphology and preserved histological structure of the human tissue. Viable trophoblast was present after engraftment and remained stable over time. Vascularization and hormonal secretion (hCG) were present till 3 weeks after engraftment. Thirty-one SNPs were equally present, and there was a stable expression level for 56 451 genes evaluated by whole transcriptome sequencing.

CONCLUSION

Although this human placental xenograft model cannot copy the unique uterine environment in which the placenta develops and interacts between the mother and the fetus, it could be a suitable tool to evaluate the acute impact and adaptive processes of the placental tissue to environmental changes.

From Chemotherapy to Combined Targeted Therapeutics: In Vitro and in Vivo Models to Decipher Intra-tumor Heterogeneity

Recent advances in next-generation sequencing and other omics technologies capable to map cell fate provide increasing evidence on the crucial role of intra-tumor heterogeneity (ITH) for cancer progression. The different facets of ITH, from genomic to microenvironmental heterogeneity and the hierarchical cellular architecture originating from the cancer stem cell compartment, contribute to the range of tumor phenotypes. Decoding these complex data resulting from the analysis of tumor tissue complexity poses a challenge for developing novel therapeutic strategies that can counteract tumor evolution and cellular plasticity. To achieve this aim, the development of in vitro and in vivo cancer models that resemble the complexity of ITH is crucial in understanding the interplay of cells and their (micro)environment and, consequently, in testing the efficacy of new targeted treatments and novel strategies of tailoring combinations of treatments to the individual composition of the tumor. This challenging approach may be an important cornerstone in overcoming the development of pharmaco-resistances during multiple lines of treatment. In this paper, we report the latest advances in patient-derived 3D (PD3D) cell cultures and patient-derived tumor xenografts (PDX) as in vitro and in vivo models that can retain the genetic and phenotypic heterogeneity of the tumor tissue.

Patient Derived Xenografts (PDX) for personalized treatment of pancreatic cancer: emerging allies in the war on a devastating cancer?

The prognosis of pancreatic ductal adenocarcinoma (PDAC), the eighth most lethal cancer for men and ninth for women worldwide, remains dismal. The increasing rates of deaths by PDAC indicate that the overall management of the disease in 21st century is still insufficient. Thus it is obvious that there is an unmet need to improve management of PDAC by finding new biomarkers to screen high risk patients, confirm diagnosis, and predict response to treatment as well more efficacious and safer treatments. Patient Derived Xenografts (PDX) have been developed as a new promising tool in an effort to mirror genetics, tumor heterogeneity and cancer microenvironment of the primary tumor. Herein we aim to give an updated overview of the current status and the perspectives of PDX in the search for the identification of novel biomarkers and improved therapeutic outcomes for PDAC but also their use as a valuable tool towards individualized treatments to improve the outcome of the disease. Furthermore, we critically review the applications, advantages, limitations, and perspectives of PDX in the research towards an improved management of PDAC.

SIGNIFICANCE

This review provides a comprehensive overview of the current status and the potential role as well as the challenges of PDX in the road to fight one of the most lethal cancers in the developed countries, pancreatic ductal adenocarcinoma.

Organoids: An intermediate modeling platform in precision oncology

Cancer harbors variable heterogeneity and plasticity. Thus far, our comprehension is greatly based on cell lines, organoids, and patient-derived tumor xenografts (PDTXs). Organoids are a three-dimensional in vitro culture platform constructed from self-organizing stem cells. They can almost accurately recapitulate tumor heterogeneity and microenvironment "in a dish," which surpass established cell lines and are not as expensive and time-consuming as PDTXs. As an intermediate model, tumor organoids are also used to study the fundamental issues of tumorigenesis and metastasis. They are specifically applied for drug testing and stored as "living biobanks." In this review, we highlight the translational applications of organoid technologies in tumor research and precision medicine, discuss the advantages and limitations compared with other mentioned methods, and provide our outlook on its future.

Tumor heterogeneity in small cell lung cancer defined and investigated in pre-clinical mouse models

Small cell lung carcinoma (SCLC) is a fast-growing, highly metastatic form of lung cancer. A major difference between SCLC and other forms of lung cancer is that SCLC tumors often respond well to chemotherapy initially; unfortunately, resistant tumors rapidly recur. In addition, despite a large number of clinical trials with a variety of therapeutic agents, little progress has been achieved in the past three decades in improving the survival of SCLC patients. These clinical observations indicate that SCLC tumors have a high degree of plasticity and rapid adaptability to changes in growth conditions. Here we consider recent evidence pointing to several levels of heterogeneity in SCLC that may explain the ability of these tumors to adjust to different microenvironment and therapeutics. In particular, we review new data pointing to the existence of several subpopulations of tumor cells that interact with each other to promote tumor growth. We also discuss how SCLC tumors that look similar at the histopathological level may actually represent distinct subtypes of tumors and how these differences impact the response to specific therapeutic agents. A better understanding of genetic and cellular heterogeneity will guide the development of personalized approaches to help SCLC patients.

CD10+GPR77+ Cancer-Associated Fibroblasts Promote Cancer Formation and Chemoresistance by Sustaining Cancer Stemness

Carcinoma-associated fibroblasts (CAFs) are abundant and heterogeneous stromal cells in tumor microenvironment that are critically involved in cancer progression. Here, we demonstrate that two cell-surface molecules, CD10 and GPR77, specifically define a CAF subset correlated with chemoresistance and poor survival in multiple cohorts of breast and lung cancer patients. CD10⁺GPR77⁺ CAFs promote tumor formation and chemoresistance by providing a survival niche for cancer stem cells (CSCs). Mechanistically, CD10⁺GPR77⁺ CAFs are driven by persistent NF-κB activation via p65 phosphorylation and acetylation, which is maintained by complement signaling via GPR77, a C5a receptor. Furthermore, CD10⁺GPR77⁺ CAFs promote successful engraftment of patient-derived xenografts (PDXs), and targeting these CAFs with a neutralizing anti-GPR77 antibody abolishes tumor formation and restores tumor chemosensitivity. Our study reveals a functional CAF subset that can be defined and isolated by specific cell-surface markers and suggests that targeting the CD10⁺GPR77⁺ CAF subset could be an effective therapeutic strategy against CSC-driven solid tumors.

Estrogens and Their Receptors in Prostate Cancer: Therapeutic Implications

A major challenge in clinical management of prostate cancer (PC) is to limit tumor growth and prevent metastatic spreading. Considerable efforts have been made to discover new compounds for PC therapy and recent years have seen promising progress in this field. Pharmacological approaches have been designed to achieve benefits in PC treatment and avoid the negative side effects resulting from administration of antagonists or agonists or new drugs. Nonetheless, the currently available therapies frequently induce resistance and PC progresses toward castration-resistant forms that can be caused by the androgen receptor reactivation and/or mutations, or derangement of signaling pathways. Preclinical and clinical findings have also shown that other nuclear receptors are frequently altered in PC. In this review, we focus on the role of estradiol/estradiol receptor (ER) axis, which controls PC growth and progression. Selective targeting of ER subtypes (α or β) may be an attractive way to limit the growth and spreading of prostatic cancer cells.

Generation and characterisation of two D2A1 mammary cancer sublines to model spontaneous and experimental metastasis in a syngeneic BALB/c host

Studying the complex mechanisms underlying breast cancer metastasis and therapy response necessitates relevant in vivo models, particularly syngeneic models with an intact immune system. Two syngeneic spontaneously metastatic sublines, D2A1-m1 and D2A1-m2, were generated from the poorly metastasising BALB/c-derived D2A1 cell line by serial in vivo passaging. In vivo and in vitro analyses revealed distinct and shared characteristics of the metastatic D2A1-m1 and D2A1-m2 sublines. In particular, D2A1-m1 cells are more aggressive in experimental metastasis assays, while D2A1-m2 cells are more efficient at disseminating from the primary tumour in spontaneous metastasis assays. Surprisingly, classical metastasis-associated in vitro phenotypes, such as enhanced proliferation, migration and invasion, are reduced in the sublines compared to the parental cell line. Further, evasion of immune control cannot fully explain their enhanced metastatic properties. By contrast, both sublines show increased resistance to apoptosis when cultured in non-adherent conditions and, for the D2A1-m2 subline, increased 3D tumour spheroid growth. Moreover, the enhanced spontaneous metastatic phenotype of the D2A1-m2 subline is associated with an increased ability to recruit an activated tumour stroma. The metastatic D2A1-m1 and D2A1-m2 cell lines provide additional syngeneic models for investigating the different steps of the metastatic cascade and thereby represent valuable tools for breast cancer researchers. Finally, this study highlights that morphology and cell behaviour in 2D cell-based assays cannot be used as a reliable predictor of metastatic behaviour in vivo.

Summary: We describe two D2A1 mouse mammary cancer sublines with enhanced spontaneous metastasis in a syngeneic host, and highlight the limitations of in vitro assays to predict in vivo metastatic behaviour.

Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts

BACKGROUND

Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human.

RESULTS

In this study we generated Whole Exome Sequencing (WES), Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA and from a cohort of human breast cancers and their derived PDTXs. We show that using an In silico Combined human-mouse Reference Genome (ICRG) for alignment discriminates between human and mouse reads with up to 99.9% accuracy and decreases the number of false positive somatic mutations caused by misalignment by >99.9%. We also derived a model to estimate the human DNA content in independent PDTX samples. For RNA-seq and RRBS data analysis, the use of the ICRG allows dissecting computationally the transcriptome and methylome of human tumour cells and mouse stroma. In a direct comparison with previously reported approaches, our method showed similar or higher accuracy while requiring significantly less computing time.

CONCLUSIONS

The computational pipeline we describe here is a valuable tool for the molecular analysis of PDTXs as well as any other mixture of DNA or RNA species.

Consensus molecular subtypes of colorectal cancer are recapitulated in in vitro and in vivo models

Colorectal cancer (CRC) is a highly heterogeneous disease both from a molecular and clinical perspective. Several distinct molecular entities, such as microsatellite instability (MSI), have been defined that make up biologically distinct subgroups with their own clinical course. Recent data indicated that CRC can be best segregated into four groups called consensus molecular subtypes (CMS1-4), each of which has a unique biology and gene expression pattern. In order to develop improved, subtype-specific therapies and to gain insight into the molecular wiring and origin of these subtypes, reliable models are needed. This study was designed to determine the heterogeneity and identify the presence of CMSs in a large panel of CRC cell lines, primary cultures and patient-derived xenografts (PDX). We provide a repository encompassing this heterogeneity and moreover describe that a large part of the models can be robustly assigned to one of the four CMSs, independent of the stromal contribution. We subsequently validate our CMS stratification by functional analysis which for instance shows mesenchymal enrichment in CMS4 and metabolic dysregulation in CMS3. Finally, we observe a clear difference in sensitivity to chemotherapy-induced apoptosis, specifically between CMS2 and CMS4. This relates to the in vivo efficacy of chemotherapy, which delays outgrowth of CMS2, but not CMS4 xenografts. Combined our data indicate that molecular subtypes are faithfully modelled in CRC cell cultures and PDXs, representing tumour cell intrinsic and stable features. This repository provides researchers with a platform to study CRC using the existing heterogeneity.

A Road Map for Precision Cancer Medicine Using Personalized Models

<b/> A study by Pauli and colleagues in this issue of Cancer Discovery describes the creation of a precision cancer platform for patients with advanced disease, integrating DNA sequencing of patient tumors with the generation of patient-derived organoids and xenografts. They propose the use of this platform for drug testing to nominate therapeutic options for individual patients and for therapeutic biomarker discovery. Cancer Discov; 7(5); 456-8. ©2017 AACRSee related article by Pauli et al., p. 462.

Establishment of a Patient-Derived Tumor Xenograft Model and Application for Precision Cancer Medicine

Patient-derived xenograft (PDX) models can be created with the transplantation of cancerous cells or tissues from patients' primary tumors into immunodeficient mice. PDXs are now in the spotlight as more accurate human cancer models compared with mouse tumor and human cancer cell lines transplanted into mice. PDX technology leads to breakthroughs with the introduction of novel, highly immunodeficient mice such as NOG (NOD/Scid/IL2Rγnull), NSG (NOD/Scid/IL2Rγnull), and NOJ (NOD/Scid/Jak3null) mice. Xenograft efficiency differs by type of tumor, site of implantation, and tumor aggressiveness. Subcutaneous implantation is a standard method for PDX, and renal capsule or orthotropic implantation improves the efficiency. Despite positive test results in animal cancer models, significant numbers of novel drug candidates fail in clinical trials because conventional animal models such as murine tumor and human cancer cell line transplantation models do not always reflect the nature of human cancers. Since PDXs conserve the original tumor characteristics such as heterogeneous histology, clinical biomolecular signatures, malignant phenotypes and genotypes, tumor architecture, and tumor vasculature, they are currently believed to offer relevant predictive insights into clinical outcomes when evaluating the efficacy of novel cancer therapies. PDX banks with integrated genomic signatures are now established in many organizations including pharmaceutical companies. These PDX databases are becoming powerful tools for advancing precision cancer medicine.

Bridging the divide: preclinical research discrepancies between triple-negative breast cancer cell lines and patient tumors

Triple-negative breast cancer (TNBC) is the most refractory subtype of breast cancer and disproportionately accounts for the majority of breast cancer related deaths. Effective treatment of this disease remains an unmet medical need. Over the past several decades, TNBC cell lines have been used as the foundation for drug development and disease modeling. However, ever-mounting research demonstrates striking differences between cell lines and clinical TNBC tumors, disconnecting bench research and actual clinical responses. In this review, we discuss the limitations of cell lines and the importance of using patients' tumors for translational research, and highlight the usage of patient-derived xenograft (PDXs) models that have emerged as a clinically relevant platform for preclinical studies. PDX tumors possess tumor heterogeneity with similar cellular, molecular, genetic and epigenetic properties akin to those found within patients' tumors. Moreover, PDX and clinical tumors possess abnormal vasculature with higher blood vessel permeability, a feature that is not always demonstrated in in vivo cell line xenografts. Development of clinically relevant, novel drug-nanoparticles capable of accumulating in PDX tumors through the enhanced permeability and retention effect in tumor vasculature may lead to new and effective TNBC treatments.

The Central Role of Wnt Signaling and Organoid Technology in Personalizing Anticancer Therapy

The Wnt pathway is at the heart of organoid technology, which is set to revolutionize the cancer field. We can now predetermine a patient's response to any given anticancer therapy by exposing tumor organoids established from the patient's own tumor. This cutting-edge biomedical platform translates to patients being treated with the correct drug at the correct dose from the outset, a truly personalized and precise medical approach. A high throughput drug screen on organoids also allows drugs to be tested in limitless combinations. More recently, the tumor cells that are resistant to the therapy given to a patient were selected in culture using the patient's organoids. The resistant tumor organoids were then screened empirically to identify drugs that will kill the resistant cells. This information allows diagnosis in real-time to either prevent tumor recurrence or effectively treat the recurring tumor. Furthermore, the ability to culture stem cell-derived epithelium as organoids has enabled us to begin to understand how a stem cell becomes a cancer cell or to pin-point the genetic alteration that underlies a given genetic syndrome. Here we summarize these advances and the central role of Wnt signaling, and identify the next challenges for organoid technology.

Establishing and characterizing patient-derived xenografts using pre-chemotherapy percutaneous biopsy and post-chemotherapy surgical samples from a prospective neoadjuvant breast cancer study

Background

Patient-derived xenografts (PDXs) are increasingly used in cancer research as a tool to inform cancer biology and drug response. Most available breast cancer PDXs have been generated in the metastatic setting. However, in the setting of operable breast cancer, PDX models both sensitive and resistant to chemotherapy are needed for drug development and prospective data are lacking regarding the clinical and molecular characteristics associated with PDX take rate in this setting.

Methods

The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant chemotherapy (NAC) trial of stage I-III breast cancer patients treated with neoadjuvant weekly taxane+/-trastuzumab followed by anthracycline-based chemotherapy. Using percutaneous tumor biopsies (PTB), we established and characterized PDXs from both primary (untreated) and residual (treated) tumors. Tumor take rate was defined as percent of patients with the development of at least one stably transplantable (passed at least for four generations) xenograft that was pathologically confirmed as breast cancer.

Results

Baseline PTB samples from 113 women were implanted with an overall take rate of 27.4% (31/113). By clinical subtype, the take rate was 51.3% (20/39) in triple negative (TN) breast cancer, 26.5% (9/34) in HER2+, 5.0% (2/40) in luminal B and 0% (0/3) in luminal A. The take rate for those with pCR did not differ from those with residual disease in TN (p = 0.999) and HER2+ (p = 0.2401) tumors. The xenografts from 28 of these 31 patients were such that at least one of the xenografts generated had the same molecular subtype as the patient. Among the 35 patients with residual tumor after NAC adequate for implantation, the take rate was 17.1%. PDX response to paclitaxel mirrored the patients’ clinical response in all eight PDX tested.

Conclusions

The generation of PDX models both sensitive and resistant to standard NAC is feasible and these models exhibit similar biological and drug response characteristics as the patients’ primary tumors. Taken together, these models may be useful for biomarker discovery and future drug development.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0920-8) contains supplementary material, which is available to authorized users.

Preclinical mouse solid tumour models: status quo, challenges and perspectives

Oncology research in humans is limited to analytical and observational studies for obvious ethical reasons, with therapy-focused clinical trials being the one exception to this rule. Preclinical mouse tumour models therefore serve as an indispensable intermediate experimental model system bridging more reductionist in vitro research with human studies. Based on a systematic survey of preclinical mouse tumour studies published in eight scientific journals in 2016, this Analysis provides an overview of how contemporary preclinical mouse tumour biology research is pursued. It thereby identifies some of the most important challenges in this field and discusses potential ways in which preclinical mouse tumour models could be improved for better relevance, reproducibility and translatability.

Establishment and proteomic characterization of patient-derived clear cell sarcoma xenografts and cell lines

Clear cell sarcoma (CCS) is an aggressive mesenchymal malignancy characterized by the unique chimeric EWS-ATF1 fusion gene. Patient-derived cancer models are essential tools for the understanding of tumorigenesis and the development of anti-cancer drugs; however, only a limited number of CCS cell lines exist. The objective of this study was to establish patient-derived CCS models. We established patient-derived CCS models from a 43-yr-old female patient. We prepared the patient-derived xenografts (PDXs) from tumor tissues obtained through biopsy or surgery and isolated stable cell lines from PDXs and the original tumor tissue. The presence of gene fusions was examined by RT-PCR, and Sanger sequencing. The established cell lines were characterized by short tandem repeat, viability, colony and spheroid formation, and invasion analyses. Differences in gene enrichment between the primary tumor and cell lines were examined by mass spectrometry and KEGG pathway analysis. The cell lines were maintained for more than 80 passages, and had tumorigenic characteristics such as colony and spheroid formation and invasion. Mass spectrometric proteome analysis demonstrated that the cell lines were enriched for similar but distinct molecular pathways, compared to those in the xenografts and original tumor tissue. Next, tyrosine kinase inhibitors were screened for their suppressive effects on viability. We found that ponatinib, vandetanib, and doxorubicin suppressed the growth of cell lines, and had equivalent IC₅₀ values. Further in-depth investigation and understanding of drug-sensitivity mechanisms will be important for the clinical applications of our cell lines.

Characterization of ascites-derived tumor cells from an endometrial cancer patient

Improved treatment outcomes for the endometrial cancer patient requires precision methods to investigate the biology of this disease and clinically relevant models to test treatment drugs. Hence, we applied a personalized platform to investigate whether in vitro and in vivo models could accurately predict effective treatment regimens. We successfully expanded ascites-derived tumor cells from an endometrial cancer patient with malignant ascites using ascites collected prior to chemotherapy treatment. Hematoxylin-eosin and immunohistochemistry staining of ascites-derived tumor cells confirmed the source of endometrial cancer cells. Ascites-derived tumor cells were sensitive to cisplatin and doxorubicin single-agent treatments in CCK-8 assay and 3-D culture, a condition that more closely mimics the in vivo environment. We further showed that ascites-derived tumor cells from this patient could form tumors in NOD/SCID mice with preserved morphological characteristics. A remarkable concordance between the clinical response of cisplatin and the results of in vitro and in vivo drug tests reflected the reliability of our personalized approach in this case. Together, our results indicated that an effective platform for ex vivo and in vivo culture of ascites-derived tumor cells from our endometrial cancer patient could be applied to identify treatment options, and may be commonly used in treating cancer patients with malignant ascites in the future.

Identification and Characterization of Neoantigens As Well As Respective Immune Responses in Cancer Patients

Cancer immunotherapy has recently emerged as a powerful tool for the treatment of diverse advanced malignancies. In particular, therapeutic application of immune checkpoint modulators, such as anti-CTLA4 or anti-PD-1/PD-L1 antibodies, have shown efficacy in a broad range of malignant diseases. Although pharmacodynamics of these immune modulators are complex, recent studies strongly support the notion that altered peptide ligands presented on tumor cells representing neoantigens may play an essential role in tumor rejection by T cells activated by anti-CTLA4 and anti-PD-1 antibodies. Neoantigens may have diverse sources as viral and mutated proteins. Moreover, posttranslational modifications and altered antigen processing may also contribute to the neoantigenic peptide ligand landscape. Different approaches of target identification are currently applied in combination with subsequent characterization of autologous and non-self T-cell responses against such neoantigens. Additional efforts are required to elucidate key characteristics and interdependences of neoantigens, immunodominance, respective T-cell responses, and the tumor microenvironment in order to define decisive determinants involved in effective T-cell-mediated tumor rejection. This review focuses on our current knowledge of identification and characterization of such neoantigens as well as respective T-cell responses. It closes with challenges to be addressed in future relevant for further improvement of immunotherapeutic strategies in malignant diseases.

A Comprehensive Patient-Derived Xenograft Collection Representing the Heterogeneity of Melanoma

Therapy of advanced melanoma is changing dramatically. Following mutational and biological subclassification of this heterogeneous cancer, several targeted and immune therapies were approved and increased survival significantly. To facilitate further advancements through pre-clinical in vivo modeling, we have established 459 patient-derived xenografts (PDX) and live tissue samples from 384 patients representing the full spectrum of clinical, therapeutic, mutational, and biological heterogeneity of melanoma. PDX have been characterized using targeted sequencing and protein arrays and are clinically annotated. This exhaustive live tissue resource includes PDX from 57 samples resistant to targeted therapy, 61 samples from responders and non-responders to immune checkpoint blockade, and 31 samples from brain metastasis. Uveal, mucosal, and acral subtypes are represented as well. We show examples of pre-clinical trials that highlight how the PDX collection can be used to develop and optimize precision therapies, biomarkers of response, and the targeting of rare genetic subgroups.

PDX-MI: Minimal Information for Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62-66. ©2017 AACR.

Current status of proteomics of soft tissue sarcomas

INTRODUCTION

Proteomics has been used in soft tissue sarcoma (STS) research in the attempts to improve the understanding of the disease background and develop novel clinical applications. Using various proteomics modalities, aberrant regulations of numerous intriguing proteins were identified in STSs, and the possible utilities of identified proteins as biomarkers or therapeutic targets have been explored. STS is an exceptionally diverse group of malignant diseases with highly complex molecular backgrounds and, therefore, an overview of the achievements and prospects of STS proteomics could enhance our knowledge of the possibilities and limitations of cancer proteomics. Areas covered: This review examines all STSs that have been examined using proteomics modalities, discussing unique aspects, limitations, and possible improvements of individual reports. To contribute to the current progress in cancer treatment development using novel anti-cancer drugs, proteomics plays a central role in linking cutting-edge technologies, application of proteogenomics, patient-derived cancer models, and biobanking system. Expert commentary: Therefore, proteomic-based STS research will be developed as an interdisciplinary science. STS proteomics will be further developed based on the interaction of oncologists with basic researchers in various fields, aimed at obtaining an enhanced understanding of the biology of the disease and achieving superior clinical outcomes for patients.

A Molecularly Annotated Model of Patient-Derived Colon Cancer Stem-Like Cells to Assess Genetic and Nongenetic Mechanisms of Resistance to Anti-EGFR Therapy

Purpose: Patient-derived xenografts ("xenopatients") of colorectal cancer metastases have been essential to identify genetic determinants of resistance to the anti-EGFR antibody cetuximab and to explore new therapeutic strategies. From xenopatients, a genetically annotated collection of stem-like cultures ("xenospheres") was generated and characterized for response to targeted therapies.Experimental Design: Xenospheres underwent exome-sequencing analysis, gene expression profile, and in vitro targeted treatments to assess genetic, biological, and pharmacologic correspondence with xenopatients, and to investigate nongenetic biomarkers of therapeutic resistance. The outcome of EGFR family inhibition was tested in an NRG1-expressing in vivo model.Results: Xenospheres faithfully retained the genetic make-up of their matched xenopatients over in vitro and in vivo passages. Frequent and rare genetic lesions triggering primary resistance to cetuximab through constitutive activation of the RAS signaling pathway were conserved, as well as the vulnerability to their respective targeted treatments. Xenospheres lacking such alterations (RAS^wt) were highly sensitive to cetuximab, but were protected by ligands activating the EGFR family, mostly NRG1. Upon reconstitution of NRG1 expression, xenospheres displayed increased tumorigenic potential in vivo and generated tumors completely resistant to cetuximab, and sensitive only to comprehensive EGFR family inhibition.Conclusions: Xenospheres are a reliable model to identify both genetic and nongenetic mechanisms of response and resistance to targeted therapies in colorectal cancer. In the absence of RAS pathway mutations, NRG1 and other EGFR ligands can play a major role in conferring primary cetuximab resistance, indicating that comprehensive inhibition of the EGFR family is required to achieve a significant therapeutic response. Clin Cancer Res; 24(4); 807-20. ©2017 AACRSee related commentary by Napolitano and Ciardiello, p. 727.

Precision Oncology: The Road Ahead

Current efforts in precision oncology largely focus on the benefit of genomics-guided therapy. Yet, advances in sequencing techniques provide an unprecedented view of the complex genetic and nongenetic heterogeneity within individual tumors. Herein, we outline the benefits of integrating genomic and transcriptomic analyses for advanced precision oncology. We summarize relevant computational approaches to detect novel drivers and genetic vulnerabilities, suitable for therapeutic exploration. Clinically relevant platforms to functionally test predicted drugs/drug combinations for individual patients are reviewed. Finally, we highlight the technological advances in single cell analysis of tumor specimens. These may ultimately lead to the development of next-generation cancer drugs, capable of tackling the hurdles imposed by genetic and phenotypic heterogeneity on current anticancer therapies.

A Small Molecule Inhibitor of the β-Catenin-TCF4 Interaction Suppresses Colorectal Cancer Growth In Vitro and In Vivo

Colorectal cancer is associated with aberrant activation of the Wnt pathway. β-Catenin plays essential roles in the Wnt pathway by interacting with T-cell factor 4 (TCF4) to transcribe oncogenes. We synthesized a small molecule, referred to as HI-B1, and evaluated signaling changes and biological consequences induced by the compound. HI-B1 inhibited β-catenin/TCF4 luciferase activity and preferentially caused apoptosis of cancer cells in which the survival is dependent on β-catenin. The formation of the β-catenin/TCF4 complex was disrupted by HI-B1 due to the direct interaction of HI-B1 with β-catenin. Colon cancer patient-derived xenograft (PDX) studies showed that a tumor with higher levels of β-catenin expression was more sensitive to HI-B1 treatment, compared to a tumor with lower expression levels of β-catenin. The different sensitivities of PDX tumors to HI-B1 were dependent on the β-catenin expression level and potentially could be further exploited for biomarker development and therapeutic applications against colon cancer.

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HI-B1 is a synthesized compound identified as a β-catenin inhibitor suppressing the β-catenin-TCF4 protein interaction.

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HI-B1 preferentially causes apoptosis in β-catenin-dependent cancer cells.

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A colon cancer PDX mouse model with a high level of β-catenin is sensitive to HI-B1.

β-catenin is an important protein that facilitates colon cancer. Shin et al. synthesized and identified HI-B1 as a direct β-catenin inhibitor. HI-B1 disrupted formation of the β-catenin-TCF4 protein complex. HI-B1 preferentially caused apoptosis of cancer cells in which the survival is dependent on β-catenin. In a comparison of two colon cancer PDX models with different β-catenin levels, they showed that β-catenin-high PDX is more sensitive to HI-B1 treatment than β-catenin-low PDX. HI-B1 could thus be further developed as a colon cancer drug, and β-catenin expression levels might be a predictive biomarker for colon cancer therapy using β-catenin inhibitors.

Interrogating open issues in cancer medicine with patient-derived xenografts

This corrects the article DOI: 10.1038/nrc.2016.140.

Addressing the challenges of applying precision oncology

Precision oncology is described as the matching of the most accurate and effective treatments with the individual cancer patient. Identification of important gene mutations, such as BRCA1/2 that drive carcinogenesis, helped pave the way for precision diagnosis in cancer. Oncoproteins and their signaling pathways have been extensively studied, leading to the development of target-based precision therapies against several types of cancers. Although many challenges exist that could hinder the success of precision oncology, cutting-edge tools for precision diagnosis and precision therapy will assist in overcoming many of these difficulties. Based on the continued rapid progression of genomic analysis, drug development, and clinical trial design, precision oncology will ultimately become the standard of care in cancer therapeutics.

Pancreas Cancer Precision Treatment Using Avatar Mice from a Bioinformatics Perspective

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related death among solid malignancies. Unfortunately, PDAC lethality has not substantially decreased over the past 20 years. This aggressiveness is related to the genomic complexity and heterogeneity of PDAC, but also to the absence of an effective screening for the detection of early-stage tumors and a lack of efficient therapeutic options. Therefore, there is an urgent need to improve the arsenal of anti-PDAC drugs for an effective treatment of these patients. Patient-derived xenograft (PDX) mouse models represent a promising strategy to personalize PDAC treatment, offering a bench testing of candidate treatments and helping to select empirical treatments in PDAC patients with no therapeutic targets. Moreover, bioinformatics-based approaches have the potential to offer systematic insights into PDAC etiology predicting putatively actionable tumor-specific genomic alterations, identifying novel biomarkers and generating disease-associated gene expression signatures. This review focuses on recent efforts to individualize PDAC treatments using PDX models. Additionally, we discuss the current understanding of the PDAC genomic landscape and the putative druggable targets derived from mutational studies. PDAC molecular subclassifications and gene expression profiling studies are reviewed as well. Finally, latest bioinformatics methodologies based on somatic variant detection and prioritization, in silico drug response prediction, and drug repositioning to improve the treatment of advanced PDAC tumors are also covered.

Mouse models of metastasis: progress and prospects

Metastasis is the spread of cancer cells from a primary tumor to distant sites within the body to establish secondary tumors. Although this is an inefficient process, the consequences are devastating as metastatic disease accounts for >90% of cancer-related deaths. The formation of metastases is the result of a series of events that allow cancer cells to escape from the primary site, survive in the lymphatic system or blood vessels, extravasate and grow at distant sites. The metastatic capacity of a tumor is determined by genetic and epigenetic changes within the cancer cells as well as contributions from cells in the tumor microenvironment. Mouse models have proven to be an important tool for unraveling the complex interactions involved in the metastatic cascade and delineating its many stages. Here, we critically appraise the strengths and weaknesses of the current mouse models and highlight the recent advances that have been made using these models in our understanding of metastasis. We also discuss the use of these models for testing potential therapies and the challenges associated with the translation of these findings into the provision of new and effective treatments for cancer patients.

Trial watch: Immune checkpoint blockers for cancer therapy

Immune checkpoint blockers (ICBs) are literally revolutionizing the clinical management of an ever more diversified panel of oncological indications. Although considerable attention persists around the inhibition of cytotoxic T lymphocyte-associated protein 4 (CTLA4) and programmed cell death 1 (PDCD1, best known as PD-1) signaling, several other co-inhibitory T-cell receptors are being evaluated as potential targets for the development of novel ICBs. Moreover, substantial efforts are being devoted to the identification of biomarkers that reliably predict the likelihood of each patient to obtain clinical benefits from ICBs in the absence of severe toxicity. Tailoring the delivery of specific ICBs or combinations thereof to selected patient populations in the context of precision medicine programs constitutes indeed a major objective of the future of ICB-based immunotherapy. Here, we discuss recent preclinical and clinical advances on the development of ICBs for oncological indications.

Natural Agents-Mediated Targeting of Histone Deacetylases

In the past few years, basic and clinical scientists have witnessed landmark achievements in many research projects, such as those conducted by the US National Institutes of Health Roadmap Epigenomics Mapping Consortium, the International Human Epigenome Consortium, The Cancer Genome Atlas Network and the International Cancer Genome Consortium, which have provided near-complete resolution of epigenetic landscape in different diseases. Furthermore, genome sequencing of tumors has provided compelling evidence related to frequent existence of mutations in readers, erasers and writers of epigenome in different cancers. Histone acetylation is an intricate mechanism modulated by two opposing sets of enzymes and deeply studied as a key biological phenomenon in 1964 by Vincent Allfrey and colleagues. The research group suggested that this protein modification contributed substantially in transcriptional regulation. Subsequently, histone deacetylases (HDACs), histone acetyltransferases and acetyl-Lys-binding proteins were identified as transcriptional mediators, which further deepened our comprehension regarding biochemical modifications. Overwhelmingly increasing high-impact research is improving our understanding of this molecularly controlled mechanism; moreover, quantification and identification of lysine acetylation by mass spectrometry has added new layers of information. We partition this multi-component review into how both activity and expression of HDAC are targeted using natural agents. We also set spotlight on how oncogenic fusion proteins tactfully utilize HDAC-associated nano-machinery to modulate expression of different genes and how HDAC inhibitors regulate TRAIL-induced apoptosis in cancer cells. HDAC inhibitors have been reported to upregulate expression of TRAIL receptors and protect TRAIL from proteasomal degradation. Deeper understanding of HDAC biology will be useful for stratification and selection of patients who are responders, non-responders and poor-responders for HDACi therapy, and for the rational design of combination studies using HDACi.

Clinical Factors That Affect the Establishment of Soft Tissue Sarcoma Patient-Derived Orthotopic Xenografts: A University of California, Los Angeles, Sarcoma Program Prospective Clinical Trial

Purpose

Given the diverse and aggressive nature of soft tissue sarcomas (STSs), a need exists for more-precise therapy. Patient-derived orthotopic xenografts (PDOXs) provide a unique platform for personalized treatment. Thus, identification of patient and treatment factors that predict PDOX establishment is important. This study assessed the feasibility of incorporating PDOXs into the clinical setting and identifying factors associated with PDOX establishment.

Patients and Methods

From May 2015 to May 2016, 107 patients with biopsy-proven or potential STS were enrolled. Tumor samples were obtained intraoperatively and orthotopically implanted into nude mice in the corresponding anatomic location. PDOXs were considered established after engraftment and serial passage. Factors associated with establishment were analyzed by logistic regression and time to establishment by time-to-event analysis.

Results

Only high-grade tumors established (32 of 72 [44.4%]). The establishment rate (ER) varied by neoadjuvant therapy and treatment response, with the highest ER among untreated high-grade tumors (26 of 42 [61.9%]). Tumors exposed to radiation preoperatively did not establish (zero of 11 [0%]), and tumors exposed to neoadjuvant chemotherapy had a lower ER(31.9%) than untreated tumors. Only STSs with minimal pathologic response to neoadjuvant treatment (≤ 30%) established a PDOX (six of 18 [33.3%]). Median establishment time was 54 days, which varied by neoadjuvant therapy but was not statistically significant (P = .180).

Conclusion

To our knowledge, in the largest STS PDOX study to date, we demonstrate a 62% ER among untreated high-grade tumors with a median establishment time of 54 days. Neoadjuvant therapy, particularly radiation, and pathologic response to treatment were associated with a reduced rate of PDOX establishment.

Tumor Organoids as a Pre-clinical Cancer Model for Drug Discovery

Tumor organoids are 3D cultures of cancer cells that can be derived on an individual patient basis with a high success rate. This creates opportunities to build large biobanks with relevant patient material that can be used to perform drug screens and facilitate drug development. The high take rate will also allow side-by-side comparison to evaluate the translational potential of this model system to the patient. These tumors-in-a-dish can be established for a variety of tumor types including colorectal, pancreas, stomach, prostate, and breast cancers. In this review, we highlight what is currently known about tumor organoid culture, the advantages and challenges of the model system, compare it with other pre-clinical cancer models, and evaluate its value for drug development.

Tumor-initiating CD49f cells are a hallmark of chemoresistant triple negative breast cancer

Taxanes are mainstay treatment of triple negative breast cancer (TNBC) patients but resistance often develops. Using TNBC patient-derived orthoxenografts (PDX) we have recently discovered that a CD49f+ chemoresistant population with tumor-initiating ability is present in sensitive tumors and expands in tumors that have acquired resistance. Importantly, sensitivity to taxanes is recovered after long-term drug interruption. The characterization of this chemoresistant CD49f+ cells provides a unique opportunity to identify novel targets for the treatment of chemoresistant TNBC.