Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations

For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab.

Breast cancer PDxO cultures for drug discovery and functional precision oncology

Patient-derived xenografts (PDXs) have clinical value but are time-, cost-, and labor-intensive and thus ill-suited for large-scale experiments. Here, we present a protocol to convert PDX tumors into PDxOs for long-term cultures amenable to moderate-throughput drug screens, including in-depth PDxO validation. We describe steps for PDxO preparation and mouse cell removal. We then detail PDxO validation and characterization and drug response assay. Our PDxO drug screening platform can predict therapy response in vivo and inform functional precision oncology for patients. For complete details on the use and execution of this protocol, please refer to Guillen et al.1.

Transferred mitochondria accumulate reactive oxygen species, promoting proliferation

Recent studies reveal that lateral mitochondrial transfer, the movement of mitochondria from one cell to another, can affect cellular and tissue homeostasis. Most of what we know about mitochondrial transfer stems from bulk cell studies and have led to the paradigm that functional transferred mitochondria restore bioenergetics and revitalize cellular functions to recipient cells with damaged or non-functional mitochondrial networks. However, we show that mitochondrial transfer also occurs between cells with functioning endogenous mitochondrial networks, but the mechanisms underlying how transferred mitochondria can promote such sustained behavioral reprogramming remain unclear. We report that unexpectedly, transferred macrophage mitochondria are dysfunctional and accumulate reactive oxygen species in recipient cancer cells. We further discovered that reactive oxygen species accumulation activates ERK signaling, promoting cancer cell proliferation. Pro-tumorigenic macrophages exhibit fragmented mitochondrial networks, leading to higher rates of mitochondrial transfer to cancer cells. Finally, we observe that macrophage mitochondrial transfer promotes tumor cell proliferation in vivo. Collectively these results indicate that transferred macrophage mitochondria activate downstream signaling pathways in a ROS-dependent manner in cancer cells, and provide a model of how sustained behavioral reprogramming can be mediated by a relatively small amount of transferred mitochondria in vitro and in vivo.

Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC₅₀ values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.

A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology

Models that recapitulate the complexity of human tumors are urgently needed to develop more effective cancer therapies. We report a bank of human patient-derived xenografts (PDXs) and matched organoid cultures from tumors that represent the greatest unmet need: endocrine-resistant, treatment-refractory and metastatic breast cancers. We leverage matched PDXs and PDX-derived organoids (PDxO) for drug screening that is feasible and cost-effective with in vivo validation. Moreover, we demonstrate the feasibility of using these models for precision oncology in real time with clinical care in a case of triple-negative breast cancer (TNBC) with early metastatic recurrence. Our results uncovered a Food and Drug Administration (FDA)-approved drug with high efficacy against the models. Treatment with this therapy resulted in a complete response for the individual and a progression-free survival (PFS) period more than three times longer than their previous therapies. This work provides valuable methods and resources for functional precision medicine and drug development for human breast cancer.

Welm and colleagues present a biobank of human-derived xenografts and organoids and demonstrate its value for high-throughput drug screening and applied precision medicine.

An immune-humanized patient-derived xenograft model of estrogen-independent, hormone receptor positive metastatic breast cancer

BACKGROUND

Metastatic breast cancer (MBC) is incurable, with a 5-year survival rate of 28%. In the USA, more than 42,000 patients die from MBC every year. The most common type of breast cancer is estrogen receptor-positive (ER+), and more patients die from ER+ breast cancer than from any other subtype. ER+ tumors can be successfully treated with hormone therapy, but many tumors acquire endocrine resistance, at which point treatment options are limited. There is an urgent need for model systems that better represent human ER+ MBC in vivo, where tumors can metastasize. Patient-derived xenografts (PDX) made from MBC spontaneously metastasize, but the immunodeficient host is a caveat, given the known role of the immune system in tumor progression and response to therapy. Thus, we attempted to develop an immune-humanized PDX model of ER+ MBC.

METHODS

NSG-SGM3 mice were immune-humanized with CD34+ hematopoietic stem cells, followed by engraftment of human ER+ endocrine resistant MBC tumor fragments. Strategies for exogenous estrogen supplementation were compared, and immune-humanization in blood, bone marrow, spleen, and tumors was assessed by flow cytometry and tissue immunostaining. Characterization of the new model includes assessment of the human tumor microenvironment performed by immunostaining.

RESULTS

We describe the development of an immune-humanized PDX model of estrogen-independent endocrine resistant ER+ MBC. Importantly, our model harbors a naturally occurring ESR1 mutation, and immune-humanization recapitulates the lymphocyte-excluded and myeloid-rich tumor microenvironment of human ER+ breast tumors.

CONCLUSION

This model sets the stage for development of other clinically relevant models of human breast cancer and should allow future studies on mechanisms of endocrine resistance and tumor-immune interactions in an immune-humanized in vivo setting.

Abstract 1301: Real-time single-cell drug response assay in metastatic breast cancer cell lines using quantitative phase imaging

Introduction: The ability for oncologists to predict a cancer's response to therapy is limited to a few biomarkers used for histologic diagnosis and targeted therapy. Often, in advanced and metastatic disease these biomarkers provide no alternative options for next step systemic treatments. There is a need in oncology for functional assays that can determine a tumor's response to a drug, regardless of its tissue of origin, previous treatments, or mutation status. Quantitative phase imaging (QPI) can measure changes in single cell mass in response to drug treatment in vitro and ex vivo. This platform offers advantages over other functional/metabolic assays in that it monitors changes in real-time and on a single cell basis, revealing heterogeneity in drug response.

Methods: Here, we describe the validation of QPI for the measurement of breast cancer cell response to therapy versus CellTiterGlo (CTG), an endpoint ATP assay. We ran a series of 3-day drug response assays using QPI alongside CTG. We used a 96 well plate with a 6-point dose response between 1.6 nM and 20 μM for multiple cell lines spanning a range of receptor statuses (MCF7, MDA-MB-231, BT-474) with two controls in triplicate. We analyzed single-cell data to measure the heterogeneity of response and assessed how cell-to-cell heterogeneity is affected by dose. Our response data were fitted to a four-parameter Hill equation to compute the IC50 and depth of response.

Results: We found that QPI can determine IC50s for effective treatments as validated by concordance to CTG. As measured by QPI, doxorubicin has a substantial depth of response, indicating cytotoxic effects. Doxorubicin data also show a tighter range of growth rates at high concentration than control, which implies low heterogeneity of response. As expected, ER positive MCF7 cells responded to hydroxy-tamoxifen. This response shows a similar reduction in heterogeneity to doxorubicin but with a reduced depth of response indicating a cytostatic effect. MDA-MB-231 response to palbociclib exhibits a wide range of growth rates, indicating an increase in heterogeneity as measured by QPI. Fluorouracil response shows no significant difference in heterogeneity from control.

Conclusion: In summary, QPI is a useful tool for functional assays that can capture IC50, depth of response, and single-cell heterogeneity of response. In particular, this additional information about single-cell behavior and heterogeneity cannot be measured using a typical endpoint assay. Future work is needed to prove the clinical utility of functional assays from QPI.

Citation Format: Tarek E. Moustafa, Edward R. Polanco, Andrew Butterfield, Sandra D. Scherer, Bryan E. Welm, Philip S. Bernard, Thomas A. Zangle. Real-time single-cell drug response assay in metastatic breast cancer cell lines using quantitative phase imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1301.

Spatiotemporally controlled induction of gene expression in vivo allows tracking the fate of tumor cells that traffic through the lymphatics

Metastasis is a multistep process, during which circulating tumor cells traffic through diverse anatomical locations. Stable inducible marking of tumor cells in a manner that is tightly spatially and temporally controlled would allow tracking the contribution of cells passing through specific locations to metastatic dissemination. For example, tumor cells enter the lymphatic system and can form metastases in regional lymph nodes, but the relative contribution of tumor cells that traffic through the lymphatic system to the formation of distant metastases remains controversial. Here, we developed a novel genetic switch based on mild transient warming (TW) that allows cells to be marked in a defined spatiotemporal manner in vivo. Prior to warming, cells express only EGFP. Upon TW, the EGFP gene is excised and expression of mCherry is permanently turned on. We employed this system in an experimental pancreatic cancer model and used localized TW to induce the genetic switch in tumor cells trafficking through tumor-draining lymph nodes. Thereby we found that tumor cells disseminating via the lymphatics make a major contribution to the seeding of lung metastases. The inducible genetic marking system we have developed is a powerful tool for the tracking of metastasizing cells in vivo.

ETV4 Is Necessary for Estrogen Signaling and Growth in Endometrial Cancer Cells

Estrogen signaling through estrogen receptor alpha (ER) plays a major role in endometrial cancer risk and progression, however, the molecular mechanisms underlying ER's regulatory role in endometrial cancer are poorly understood. In breast cancer cells, ER genomic binding is enabled by FOXA1 and GATA3, but the transcription factors that control ER genomic binding in endometrial cancer cells remain unknown. We previously identified ETV4 as a candidate factor controlling ER genomic binding in endometrial cancer cells, and here we explore the functional importance of ETV4. Homozygous deletion of ETV4, using CRISPR/Cas9, led to greatly reduced ER binding at the majority of loci normally bound by ER. Consistent with the dramatic loss of ER binding, the gene expression response to estradiol was dampened for most genes. ETV4 contributes to estrogen signaling in two distinct ways. ETV4 loss affects chromatin accessibility at some ER bound loci and impairs ER nuclear translocation. The diminished estrogen signaling upon ETV4 deletion led to decreased growth, particularly in 3D culture, where hollow organoids were formed and in vivo in the context of estrogen-dependent growth. These results show that ETV4 plays an important role in estrogen signaling in endometrial cancer cells. SIGNIFICANCE: Estrogen receptor alpha (ER) is a key oncogene in endometrial cancer. This study uncovers ETV4 as an important factor in controlling the activity of ER and the growth of endometrial cancer cells. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/6/1234/F1.large.jpg.

Abstract LB-038: Predicting breast cancer therapy response using a patient-derived xenograft organoid screening platform

Patient-derived xenografts (PDX) are valuable, clinically-relevant models of cancer. Their close genomic, phenotypic, and temporal association with patient tumors makes them well-suited for pre-clinical and co-clinical studies that assess the potential of new therapeutics. However, PDX models are not amenable to large-scale drug sensitivity studies due to their high cost and low throughput capacity. To address this, we established and characterized long-term PDX organoid (PDxO) cultures from breast cancer (BC) PDXs and evaluated their utility in therapeutic studies. To establish PDxO culture conditions, we extensively tested medium supplements, including growth factors, kinase inhibitors, conditioned medium, and antioxidants, along with extracellular matrix composition in 3D gels. Using optimized culture conditions for each BC subtype, we established PDxOs from 16 PDX lines in the HCI series, with a PDX to PDxO success rate of 85%. Around 20% of PDxOs contained aggressive mouse stroma, which had to be eliminated by FACS for long-term culture success. PDxOs were maintained for over 1 year, during which we tracked viability, doubling time, organoid size, genomics, epithelial character, and tumorigenicity. Doubling times stabilized after 60 days of initial culture, with a mean of 6.4±1.7 days for triple negative (TN) lines and 7.2±1 days for ER+ lines. Mean organoid size remained stable, with ER+ PDxOs significantly smaller than TN PDxOs, at 91 and 262 cells/organoid respectively (p=0.0012). PDxOs histologically resembled their PDX counterparts when stained for H&E, Vimentin, and CAM 5.2. RNA-Seq and copy-number variation analyses showed that PDxOs clustered with their PDXs and patient tumors. To assess if culturing affected tumorigenicity, we re-implanted PDxOs into mice following early and late passaging. 5/5 early passage and 5/6 late passage PDxOs engrafted and formed tumors. Resulting tumors showed similar gene expression profiles as their original PDXs by RNA-Seq. These data suggest that PDxOs generally recapitulate the molecular and genomic features of their originating PDXs and patient tumors. Having established PDxO cultures, we evaluated their utility as a therapeutic screening platform. We developed a screen to differentiate compounds with cytotoxic and cytostatic effects. NCI CTEP and clinically-approved BC therapies (n=40) were screened in quadruplicate 8-point dose response curves on all 16 PDxOs across three biological replicates. Drug response profiles were stable across biological replicates, spanning up to 1 year in culture. PDxOs exhibited diverse responses to therapies targeting cIAP1, PI3K, and CHK1/2. Initial work to evaluate concordance between PDxO and in vivo PDX responses returned trending linear correlations between PDxO dose response data and change in PDX growth rate following treatment (R2 = 0.52-0.77; p = 0.045-0.12, across 3 PDXs and 9 compounds). Ongoing work aims to confirm concordance between PDX and PDxO models. Our work demonstrates that PDxO models are cost-efficient, easy to maintain, and grow indefinitely - making them renewable and accessible cancer models. PDxOs are a powerful parallel resource to PDX models, especially useful for efficient determination of PDX drug response. We are currently expanding our PDxO bank to include 100 models which will be deposited with the NCI as part of the PDXNet effort.

Citation Format: Katrin P. Guillen, Sandra D. Scherer, Yi Qiao, Satya S. Pathi, James M. Graham, Maihi Fujita, Yoko S. DeRose, Jason Gertz, Gabor T. Marth, Katherine E. Varley, Alana L. Welm, Bryan E. Welm. Predicting breast cancer therapy response using a patient-derived xenograft organoid screening platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-038.

Macrophage-Induced Lymphangiogenesis and Metastasis following Paclitaxel Chemotherapy Is Regulated by VEGFR3

While chemotherapy strongly restricts or reverses tumor growth, the response of host tissue to therapy can counteract its anti-tumor activity by promoting tumor re-growth and/or metastases, thus limiting therapeutic efficacy. Here, we show that vascular endothelial growth factor receptor 3 (VEGFR3)-expressing macrophages infiltrating chemotherapy-treated tumors play a significant role in metastasis. They do so in part by inducing lymphangiogenesis as a result of cathepsin release, leading to VEGF-C upregulation by heparanase. We found that macrophages from chemotherapy-treated mice are sufficient to trigger lymphatic vessel activity and structure in naive tumors in a VEGFR3-dependent manner. Blocking VEGF-C/VEGFR3 axis inhibits the activity of chemotherapy-educated macrophages, leading to reduced lymphangiogenesis in treated tumors. Overall, our results suggest that disrupting the VEGF-C/VEGFR3 axis not only directly inhibits lymphangiogenesis but also blocks the pro-metastatic activity of macrophages in chemotherapy-treated mice.

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Chemotherapy promotes macrophage colonization of tumors

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Macrophages induce lymphangiogenesis in chemotherapy-treated tumors

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Macrophages secrete cathepsins, VEGF-C, and heparanase in a VEGFR3-dependent manner

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Blocking VEGFR3 in macrophages inhibits lymphangiogenesis and subsequent metastasis

Regulation of gene expression by GC-rich DNA cis-elements

GC-rich DNA cis elements are important transcriptional regulatory elements present in the promoter, enhancer and locus control regions of many eukaryotic genes from several species. This review attempts to examine the structure, function and biological significance of GC-rich cis -regulatory elements and their cognate binding proteins, with a view to understanding their role in regulation of gene expression.