Here, we present a protocol for performing gene knockouts that are embryonic lethal in vivo in genetically engineered mouse model-derived tumors and then assessing the effect that the knockout has on tumor growth, proliferation, survival, migration, invasion, and the transcriptome in vitro and in vivo.
The development of new drugs that precisely target key proteins in human cancers is fundamentally altering cancer therapeutics. However, before these drugs can be used, their target proteins must be validated as therapeutic targets in specific cancer types. This validation is often performed by knocking out the gene encoding the candidate therapeutic target in a genetically engineered mouse (GEM) model of cancer and determining what effect this has on tumor growth. Unfortunately, technical issues such as embryonic lethality in conventional knockouts and mosaicism in conditional knockouts often limit this approach. To overcome these limitations, an approach to ablating a floxed embryonic lethal gene of interest in short-term cultures of malignant peripheral nerve sheath tumors (MPNSTs) generated in a GEM model was developed.
This paper describes how to establish a mouse model with the appropriate genotype, derive short-term tumor cultures from these animals, and then ablate the floxed embryonic lethal gene using an adenoviral vector that expresses Cre recombinase and enhanced green fluorescent protein (eGFP). Purification of cells transduced with adenovirus using fluorescence-activated cell sorting (FACS) and the quantification of the effects that gene ablation exerts on cellular proliferation, viability, the transcriptome, and orthotopic allograft growth is then detailed. These methodologies provide an effective and generalizable approach to identifying and validating therapeutic targets in vitro and in vivo. These approaches also provide a renewable source of low-passage tumor-derived cells with reduced in vitro growth artifacts. This allows the biological role of the targeted gene to be studied in diverse biologic processes such as migration, invasion, metastasis, and intercellular communication mediated by the secretome.
Before the last two decades, the treatment of human cancers relied heavily on radiotherapy and chemotherapeutic agents that broadly targeted rapidly proliferating cellular populations by damaging DNA or inhibiting DNA synthesis. Although these approaches did inhibit cancer cell growth, they also had deleterious side effects on normal rapidly proliferating cell types such as intestinal epithelial cells and hair follicle cells. More recently, cancer therapy has begun to utilize chemotherapeutic agents that precisely target proteins within signaling pathways that are critically important for the growth of an individual patient's neoplasm. This approach, commonly referred to as "Precision Medicine," has led to the development of an ever-expanding repertoire of monoclonal antibodies and small molecular inhibitors. These agents effectively inhibit tumor cell proliferation and survival while avoiding the deleterious side effects on normal cell types seen with conventional chemotherapeutic agents and radiotherapy. Monoclonal antibodies used for the treatment of human cancers most commonly target cell surface molecules such as growth factor receptors1 (e.g., the large family of membrane-spanning receptor tyrosine kinases) and immune response modulators2 (e.g., programmed cell death protein 1, programmed death-ligand 1). Small molecular inhibitors can inhibit either cell surface proteins or signaling proteins that are located intracellularly3. However, to effectively employ these new therapeutic agents, it must be established that a particular cancer is dependent upon the molecule that is being targeted by a candidate therapeutic agent.
Although these new therapeutic agents have more focused effects, many of them still inhibit the action of more than one protein. In addition, multiple agents with varying effectiveness and specificity are often available to target a specific protein. Consequently, during preclinical investigations, it is wise to use additional approaches such as genetic ablation to validate a candidate protein as a therapeutic target. One especially useful approach to validating a protein as a therapeutic target is to ablate the gene encoding the candidate protein in a genetically engineered animal model that develops the specific cancer type of interest. This approach can be relatively straightforward if mice with a null mutation (either a natural mutation, a genetically engineered null mutation [a "knockout"], or a null mutation introduced by a gene trap) are available, and the mice are viable into adulthood. Unfortunately, mice with a null mutation that meet these criteria are often not available, typically because the null mutation results in death embryonically or in the first days of postnatal life. In this circumstance, mice prone to develop the tumor type of interest may instead be crossed to mice in which key segments of the gene of interest are flanked by loxP sites ("floxed"), which allows the gene to be ablated by introducing a transgene expressing Cre recombinase into the tumor cells (a conditional knockout). This approach provides several advantages. First, if a Cre driver is available that is expressed in the tumor but not in the cell type that led to death in conventional knockouts, this approach can potentially validate the candidate therapeutic target. Second, ablating the gene encoding the candidate protein in tumor cells but not in other intratumoral elements such as tumor-associated fibroblasts or immune cells allows the investigator to distinguish between cell-autonomous and non-cell-autonomous effects of the therapeutic target. Finally, a tamoxifen-inducible Cre driver (CreERT2) allows the investigator to delete the gene of interest at different stages in tumor development and define the window in which the candidate therapeutic agent is most likely to be effective.
Unfortunately, there are also technical issues that can limit the use of conditional knockouts in tumors arising in GEM models. For instance, a Cre driver that is expressed in tumor cells and avoids gene deletion in normal cells essential for life may not be available. Another issue, which may be underestimated, is that Cre and CreERT2 drivers often variably ablate floxed alleles in mice, resulting in mosaicism for the null mutation in a GEM cancer. When this occurs, tumor cells in which the targeted gene has not been ablated will continue to proliferate rapidly, overgrowing the tumor cells with ablated alleles. Mosaicism in Cre driver lines can occur due to non-ubiquitous Cre expression in the lineage targeted and by failed recombination in individual cells independent of Cre expression4. This is a known phenomenon of Cre drivers that is cell-type dependent and should be considered during experimental design and data interpretation. Mosaicism can mask the effect of the knockout and lead an investigator to erroneously conclude that the gene of interest is not essential for tumor cell proliferation and/or survival and thus is not a valid therapeutic target.
Several of these problems were encountered in a previous study that attempted to determine whether the receptor tyrosine kinase erbB4 was a potential therapeutic target in MPNST cells5. In these studies, mice were used that express a transgene encoding the neuregulin-1 (NRG1) isoform glial growth factor-β3 (GGFβ3) under the control of the Schwann cell-specific myelin protein zero promoter (P0-GGFβ3 mice). P0-GGFβ3 mice develop multiple plexiform neurofibromas that progress to become MPNSTs via a process that recapitulates the processes of neurofibroma pathogenesis and plexiform neurofibroma-MPNST progression seen in patients with the autosomal dominant tumor susceptibility syndrome neurofibromatosis type 1 (NF1)6. When crossed to mice with a Trp53 null mutation, the resulting P0-GGFβ3;Trp53+/- mice develop MPNSTs de novo as is seen in cis–Nf1+/-;Trp53+/- mice.
These MPNSTs recapitulate the progression from World Health Organization (WHO) grade II to WHO grade IV lesions seen in humans7. In P0-GGFβ3 mice, MPNSTs arise within pre-existing plexiform neurofibromas in the trigeminal nerve (58%) and spinal dorsal nerve roots (68%)7; the MPNSTs arising in P0-GGFβ3;Trp53+/- mice have a highly similar distribution. In humans, MPNSTs most commonly arise in the sciatic nerve followed by the brachial plexus, spinal nerve roots, vagus, femoral, median, sacral plexus, popliteal obturator, and posterior tibial and ulnar nerves8. This tumor distribution in these GEM models is somewhat different from what is seen in humans. However, the MPNSTs that arise in P0-GGFβ3 and P0-GGFβ3;Trp53+/- mice are histologically identical to human MPNSTs, carry many of the same mutations seen in human MPNSTs, and recapitulate the process of neurofibroma-MPNST progression seen in NF1 patients. The generation of P0-GGFβ3 or P0-GGFβ3;Trp53+/- mice that were Erbb4-/- was not feasible as mice with two Erbb4 null alleles die in utero at embryonic day 10.5 secondary to cardiac defects9. Because rescuing Erbb4 expression in the heart by introducing a cardiac-specific Erbb4 transgene (α-myosin heavy chain (MHC)-Erbb4) results in viable Erbb4-/- mice10, the generation of mice with a complicated P0-GGFβ3;Trp53+/-;α-MHC-Erbb4;Erbb4-/- genotype was attempted.
However, the matings did not produce mice in the expected Mendelian ratios, indicating that the desired genotype was deleterious. Therefore, the generation of P0-GGFβ3;Trp53+/- mice with floxed Erbb4 alleles11 and a CreERT2 driver was attempted to allow the deletion of Erbb4 in the MPNSTs arising in these mice. In these animals, numerous tumor cells with intact Erbb4 alleles were still present (mosaicism). The mosaicism observed could result from inefficient tamoxifen delivery, which resulted in differences in recombination efficiency within the tissue. The possibility of spontaneous compensatory mechanisms could further contribute to mosaicism in tamoxifen-mediated recombination by bypassing the requirement for Erbb4 expression. It is feasible that the loss of Trp53 makes tumor cells susceptible to additional spontaneous "permissive" mutations that could confuse the interpretation of the data. As it seemed likely that the Erbb4-intact MPNST cells would mask the consequences of ablating Erbb4 in other tumor cells, this approach was abandoned.
These obstacles led to the development of a methodology for ablating Erbb4 in very early passage MPNST cells using an adenovirus expressing Cre recombinase and eGFP. These cells can be separated from non-infected cells using FACS, which markedly reduces mosaicism for the ablated Erbb4 gene. Below, the methods used to achieve this, together with the methods used to assess the effects of gene ablation in vitro and in vivo, are described. The following protocol is an example of how to produce tumor-bearing mice that yield tumors carrying floxed alleles of embryonic lethal genes of interest for ex vivo excision prior to in vivo allograft tumor growth assessment. This includes a description of the approaches used to analyze the effect that Erbb4 ablation exerts on tumor cell proliferation, survival, and gene expression in vitro and proliferation, survival, and angiogenesis in orthotopic allografts.
Prior to performing any procedures with mice, all procedures must be reviewed and approved by the Institutional Animal Care and Use Committee. The protocol described in this manuscript was approved by the Institutional Animal Care and Use Committee of the Medical University of South Carolina. This protocol was performed by properly trained personnel following MUSC's institutional animal care guidelines.
1. Generation of mice that develop MPNSTs homozygous for Erbb4 flox alleles
2. Ex vivo ablation of floxed Erbb4 alleles in MPNST cells
3. Proliferation and viability assays in MPNST cells with ablated Erbb4 alleles
4. RNA-Seq analyses and identification of genes whose expression is altered by Erbb4 loss
5. Orthotopic allografting of MPNST cells with ablated Erbb4 alleles and analysis of the effects of Erbb4 ablation
Figure 4 illustrates a typical result obtained when transducing P0-GGFβ3;Trp53-/+;Erbb4fl/fl MPNST cells with either the Ad5CMV-eGFP adenovirus or Ad5CMV-Cre/eGFP adenovirus (Figure 4A). Cultures are viewed with fluorescence microscopy to identify eGFP-expressing cells and by phase-contrast microscopy to determine the total number of cells present in the same field at 10x (top) and 40x (bottom). The percentage of cells expressing eGFP can then be calculated if desired. Representative FACS output data are shown in Supplemental Figure S2. Following FACS, the percentage of eGFP-expressing cells will be markedly increased, with virtually all the cells in each field expressing eGFP. Typical PCR genotyping results expected after Cre-mediated gene ablation, depending on the transfection efficiency, are complete gene knockout (100% efficiency) or a heterogeneous population of induced and uninduced cells (<100% efficiency) compared to control transduction results (GFP only, fl/fl) (Figure 4B). Figure 4C illustrates the characteristic histopathology found in orthotopic allografts of P0-GGFβ3;Trp53+/-;Erbb4fl/fl MPNSTs compared to the tumors derived from the original GEM animal models.
In these experiments, Erbb4 ablation resulted in decreases in cellular proliferation and cellular density in vitro and in vivo, increases in TUNEL labeling indices in vivo, and decreased vascular density in vivo. Figure 5 illustrates representative results obtained with an image-based automated cytometer showing decreased cellular proliferation in Ad5CMV-Cre ablated cells vs. control Ad5CMV-GFP transduced cells (Figure 5A); these experiments were performed with early passage cultured cells. Expression of ErbB4 via immunohistochemistry in P0-GGFβ3;Trp53+/-;Erbb4fl/fl MPNST cells transduced with Ad5CMV-Cre or eGFP virus was decreased in the resultant Ad5CMV-Cre transduced allografts compared to control Ad5CMV-eGFP treated allograft tumors (Figure 5B). Vascular density was assessed via immunoreactivity detection for CD31; vascular density can be seen to be markedly reduced in allografts of Ad5CMV-Cre transduced cells (Figure 5C). Signal intensity can be quantified, if desired, using ImageJ.
Figure 1: Punnet square calculations of the ratios of expected genotypes when generating and crossing P0-GGFβ3;Trp53+/- mice with Erbb4fl/fl mice (F1). Punnet square calculations of the ratios of expected genotypes when generating and maintaining P0-GGFβ3;Trp53-/+;Erbb4fl/+ with each other (F2). Abbreviation: fl = Floxed. Please click here to view a larger version of this figure.
Figure 2: Workflow of the processused to ablate floxed Erbb4 alleles in early passage cultures of MPNST cells derived from P0-GGFβ3;Trp53-/+;Erbb4fl/fl mice. (A) Harvest the tumor expressing the floxed gene. (B) Create early passage cultures from the excised tumor. (C) Infect early passage cultures to ablate the floxed gene and perform downstream assays. Abbreviations: MPNST = malignant peripheral nerve sheath tumor; IHC = Immunohistochemistry; PFA = Paraformaldehyde; FFPE = Formalin-fixed paraffin-embedded; H&E = Hematoxylin and eosin; FACS = fluorescence-activated cell sorting; GFP = green fluorescent protein; K/O = knockout; PCR = polymerase chain reaction. Please click here to view a larger version of this figure.
Figure 3: Schematic illustrating the RNA-Seq workflow. The workflow is used to identify differentially expressed transcripts between control (GFP-induced) and Erbb4-null (Cre-induced) cells and the resultant biological significance. Abbreviations: GFP = green fluorescent protein; RNA-Seq = RNA sequencing. Please click here to view a larger version of this figure.
Figure 4: Representative transduction efficiency results assessed by microscopy in P0-GGFβ3;Trp53-/+;Erbb4fl/fl MPNST cells. (A) Cells transduced with either Ad5CMV-eGFP adenovirus or Ad5CMV-Cre/eGFP adenovirus. (B) PCR results of potential gene populations post-Ad5CMV infection. (C) Characteristic histopathology comparing the tumors generated in the originating GEM models to the orthotopically allografted P0-GGFβ3;Trp53-/+;Erbb4fl/fl MPNST cells via H&E staining. Images were taken at 40x. Isotype-matched negative control antibodies were used for control staining. Scale bars = 400 µm (A, upper panel); 100 µm (A, lower panel), 20 µm (C). Abbreviations: MPNST = malignant peripheral nerve sheath tumor; GFP = green fluorescent protein; BF = brightfield; FACS = fluorescence-activated cell sorting; Neg Ctrl = negative control; PCR = polymerase chain reaction; GEM = genetically engineered mouse; fl = floxed. Please click here to view a larger version of this figure.
Figure 5: Representative results obtained in cultured MPNST early passage cultures and orthotopically allografted MPNST cells following transduction with either Ad5CMV-eGFP or Ad5CMV-Cre/eGFP. (A) Proliferation assay of cultured MPNST cells demonstrating decreased cellular density in cells transduced with Ad5CMV-Cre/eGFP compared to those transduced with Ad5CMV-eGFP. Quantified data are graphed on days 1, 3, and 5 (left). Day 1 and Day 5 confluency images taken on the image-based automatic cytometer are shown on the right (Images taken at 4x magnification with brightfield microscopy). Error bars represent the standard error of the mean (SEM) of at least 3 different independent experiments. (B) Representative ErbB4 staining in allograft tumors transduced with Ad5CMV-eGFP or Ad5CMV-Cre/eGFP adenovirus taken at 20x magnification. Red channel (Alexa 564, CD31), blue channel (Hoechst, nuclei). (C) Representative images of vascular density in allografts of P0-GGFβ3;Trp53+/-;Erbb4fl/fl MPNST cells transduced with Ad5CMV-eGFP versus Ad5CMV-Cre/eGFP virus. Images were taken at 40x. Isotype-matched negative control antibodies were used for control staining. Scale bars = 100 µm. Abbreviations: MPNST = malignant peripheral nerve sheath tumor; eGFP = enhanced green fluorescent protein; IgG = immunoglobulin G; NEG = negative control; CD = cluster of differentiation. Please click here to view a larger version of this figure.
Supplemental Figure S1: Schematic illustrating a sequence alignment and analysis workflow. The workflow used in DNAStar to align and analyze RNA-sequencing files (fastq files). Abbreviations: GFP = green fluorescent protein; RNA-Seq = RNA sequencing., DEG = differentially expressed genes. Please click here to download this File.
Supplemental Figure S2: Representative FACS data from early passage cultures using green fluorescent protein. (A) GFP-expressing cells are sorted by FACS after setting fluorescent gate parameters from non-infected cells. (B) After the appropriate detection gate is set, GFP-positive (transduced) cells are separated from GFP-negative (non-transduced) cells. Abbreviations: SSC-A = side scatter-area of peak; FSC-H = forward scatter-height of peak; FSC-W = forward scatter-width of peak; GFP = green fluorescent protein; FACS = Fluorescence-activated cell sorting. Please click here to download this File.
The detailed methods presented here were developed using a GEM model of MPNSTs. However, if the tumor tissue of interest can be dispersed into individual cells, these methodologies are easily adaptable for various tumor types arising in GEMs. It is important to ensure that the floxed allele does not result in i) decreased survival that can make it difficult to obtain sufficient mice to screen for tumors, or ii) increased tumor latency that can make it difficult to obtain enough tumor-bearing mice. If the floxed allele does not affect survival, the survival of both cohorts will be equivalent. If it has no effect on tumor latency, equivalent numbers of tumor-bearing mice should arise in both cohorts with a similar time course.
Similar approaches have been used to study neurofibromas and MPNSTs using conditional knockouts and tamoxifen-inducible Cre animals to generate inducible conditional knockout animals33,34. The difference between these studies and this one, aside from the use of tamoxifen for Cre induction as previously discussed, is that these studies focus on tumor development with a tissue-specific knockout of NF1. As this study and these other studies also use GEMM-generated tumors, the difference lies with the question being asked. In this protocol, we are not studying the role that NF1 loss plays in MPNST pathogenesis but are instead studying the role that a specific gene (Erbb4) in GEMM-generated MPNSTs exerts on in vivo tumor growth, which would otherwise be impossible due to being embryonic lethal. Furthermore, this protocol avoids the use of tamoxifen for those approaches requiring such parameters.
Others have studied established human MPNST cell lines in xenograft models35. That study differs from this one in that the grafted cells used are well-studied but high-passage human MPNST cell lines, and it focuses on establishing drug responses in xenografts. Those researchers are not studying the role of a specific gene in these MPNST cells for in vivo growth and the effects of gene loss on drug response. Another study similar to this one was performed by Dodd et al., using adenovirus Cre recombinase (Ad-Cre)-mediated NF1 loss in a temporal and spatial dependent manner, again a powerful method for expanding MPNST translational efforts36. The study focused on the role of NF1 and Ink4a/Arf loss, two very commonly co-deleted genes in human MPNSTs, in the sciatic nerve by Ad-Cre injection. The P0-GGFβ3;Trp53+/-;Erbb4fl/fl mice described in this study could be used in this fashion by injecting Ad-Cre into Schwann cell precursor lineages. However, the questions asked in this study are not focused on the evolutionary role of Erbb4 on MPNST initiation but on how MPNSTs may hijack Erbb4 signaling for tumor growth advantage.
There are alternatives to the approach described here, including knocking down gene expression via RNA interference (RNAi) or inactivating the gene of interest with CRISPR in human cancer cell lines. These alternative approaches are valuable and can be partnered with gene ablation in cells derived from GEM tumors to verify that the effects observed in mouse tumor cells are recapitulated in their human counterparts. However, there are some clear advantages to the methodology described here. First, genetically ablating floxed genes in GEM cancer cells is rapid and produces complete inactivation of the targeted gene. In contrast, it is often observed that the use of short hairpin RNAs results in only a partial knockdown of gene expression. Although CRISPR can produce complete gene inactivation, the identification of clones that have complete inactivation requires a prolonged selection process.
Further, multiple clones must be examined to ensure that the effects resulting from CRISPR ablation do not differ between different clones. Second, the ability to ablate floxed alleles in early passage GEM tumor cultures is advantageous as this minimizes the possibility of selecting for distinct tumor cell subpopulations that grow effectively in culture. In comparison, human cell lines, which have typically been maintained in culture for years, are often derived from distinct subpopulations that are well adapted for culture and frequently undergo genetic drift during this process. This results in these cell lines developing new mutations that were not present in their parent tumor. Finally, although the grafting of GEM tumor cells into immunodeficient mice is described in this manuscript, it is noted that GEM tumor cells derived from tumors arising in inbred mouse strains can be allografted into mice of the same strain. This would allow the investigator to assess tumor biology in animals with an intact immune system in the presence or absence of the targeted gene.
The critical step in the protocol described here is the ablation of the floxed gene with Ad5CMV-Cre/eGFP and ensuring the survival of the tumor cells following gene ablation and FACS. As this is a process that is dependent on the ability of Cre recombinase to ablate the floxed gene, it is potentially subject to some of the same problems that can be encountered when ablating a floxed gene in vivo; these issues would manifest as an incomplete ablation of the targeted allele. Note that the ability to purify cells that have been successfully transduced with the eGFP-expressing adenoviral vector does appear to minimize mosaicism compared to in vivo gene ablation with CreERT2. However, in the case of targeted genes encoding proteins, such as ErbB4 that are expressed on the cell surface, it may be possible to further ensure the loss of the targeted gene by performing FACS utilizing both eGFP and an antibody recognizing the protein of interest (i.e., sort the eGFP-positive/erbB4-negative cells).
Because, as was noted in the introduction, many of the proteins targeted therapeutically by monoclonal antibodies are cell surface proteins, this approach should frequently be feasible. It should also be noted that it is important to let the tumor cells recover for at least 2-3 days after FACS if RNA-Seq is to be performed on them to assess the effect that gene ablation has had on the transcriptome. RNA-Seq datasets obtained very soon after FACS often show more variability in gene expression between biological replicates in some cell types. This may be a consequence of the trauma that cells suffer when going through FACS; hence, the cells must be allowed a recovery period after this process. RNA-Seq datasets can be analyzed using DESeq2, which uses the negative binomial distribution and a shrinkage estimator for the distribution's variance. In these analyses, samples are sorted according to their q-value, which is the smallest false discovery rate (FDR) at which changes in transcript levels are significant; FDRs are calculated using the Benjamini-Hochberg multiple testing adjustment procedure. Alternatively, DEGs can be identified using other available software capable of RNA-Seq analysis workflows.
For this MPNST animal model, identifying the experimental endpoint requires an understanding of the natural history of the neoplasms in the animal model that is being used. The natural history of MPNSTs in this GEM was determined by following the survival of a series of 44 P0-GGFβ3 mice6 and 19 P0-GGFβ3;Trp53+/- mice7 and then performing complete necropsies on all of these animals when they reached their survival endpoint. The typical survival times and the location where MPNSTs typically arose were determined in each animal model. In most of these mice, MPNSTs arose in the trigeminal nerve. MPNSTs arising in the trigeminal nerve typically produced ptosis associated with corneal cloudiness (a result of problems with tear distribution produced by the ptosis), which provided a clinically useful sign to identify tumor-bearing mice. Tumor diagnosis should be confirmed by performing H&E stains and several additional diagnostic stains (S100β, nestin Sox 10, H&E, Mart1) followed by an examination by a qualified veterinary or human pathologist. This is also important because the Trp53 null allele in this model predisposes the mice to the development of other neoplasms such as lymphomas, and these tumors must be distinguished from MPNSTs.
Finally, this methodology has several potential applications not yet explored but may be feasible in future investigations. For example, neuregulin 1 (NRG1), the ligand that activates both erbB3 and erbB4, promotes the migration of MPNST cells in a chemotactic fashion; both erbB3 and erbB4 are located in the invadopodia of MPNST cells37. However, it is not clear whether erbB3 or erbB4 mediates the chemotactic response to NRG1. Consequently, cells in which erbB4 is ablated with this methodology can be used to address this question. A natural follow-up to these experiments is to assess whether erbB4 is required for metastasis using the commonly utilized approach in which tumor cells are injected via the tail vein and the number of pulmonary metastases then assessed. This methodology offers a clear advantage over other approaches, such as using shRNAs to knock down erbB4 expression because shRNA expression is often silenced in cells after a while. Further, early passage cultures are anticipated to contain a mixture of tumor-derived subpopulations, including subpopulations of cells prone to metastasis. Performing metastasis assays with cells prepared using the methodology described here will allow an assessment of metastatic potential that is more representative of the parent tumor than an established cell line. This is, of course, just one example of the future applications that could utilize this methodology. We hope that other investigators will combine this methodology with problems of particular interest to enhance the ability to identify proteins that are key therapeutic targets in human cancers.
The authors have nothing to disclose.
This work was supported by grants from the National Institute of Neurological Diseases and Stroke (R01 NS048353, R01 NS109655), the National Cancer Institute (R01 CA122804), the Department of Defense (X81XWH-09-1-0086, W81XWH-11-1-0498, W81XWH-12-1-0164, W81XWH-14-1-0073, and W81XWH-15-1-0193), and The Children's Tumor Foundation (2014-04-001 and 2015-05-007).
Ad5CMV-eGFP | Gene Transfer Vector Core, Univ of Iowa | VVC-U of Iowa-4 | |
Ad5CMVCre-eGFP | Gene Transfer Vector Core, Univ of Iowa | VVC-U of Iowa-1174 | |
alexa 568 secondary antibody | Thermo/Fisher | GaR A11036 | |
Bioconductor Open Source Software for Bioninformatics | Bioconductor | http://www.bioconductor.org | alternative statistical analysis tool used for step 4.4 |
CD31 | Abcam | ab28364 | |
Celigo Image Cytometer | Nexcelom Bioscience | N/A | |
Cell Stripper | Corning | 25-056-Cl | mixture of chelators |
DAB staining kit | Vector Labs | MP-7800 | |
DAVID (Database for Annotation, Visualization, and Integrated Discovery) | DAVID | https://david.ncifcrf.gov | functional enrichment analysis software used for step 4.5 |
DMEM | Corning | 15-013-Cl | |
DreamTaq and Buffer (Genotyping PCR) | Thermo/Fisher | EP0701 and K1072 | |
erbB4 antibodies | Santa Cruz | sc-284 | |
erbB4 antibodies | Abcam | ab35374 | |
erbB4 antibodies | Millipore | HFR1: 05-1133 | |
FACS Sorter | BD Biosciences | Aria II | |
Forskolin | Sigma | F6886 | |
GenomeSpace Tools and Data Sources | GenomeSpace | https://genomespace.org/support/tools/ | general resource for several types of open source bioinformatic tools for step 4.5 |
Glutamine | Corning | 25-005-Cl | |
Gorilla Gene Ontology enRIchment anaLysis and visuaLizAtion tool | Gorilla | N/A, http://cbl-gorilla.cs.technion.ac.il | functional enrichment analysis software used for step 4.5 |
GSEA Gene Set Enrichment Analysis | Broad Institute | N/A, https://www.gsea-msigdb.org/gsea/index.jsp | functional enrichment analysis software used for step 4.5 |
HSD: Athymic Nude-FOxn1nu mice | Envigo (Previously Harlan Labs) | 69 | |
Illumina HiSeq2500 (next generation DNA sequencer) | Illumina | Hi Seq 2500 | DNA sequencer used for step 4.2 |
Lasergene: ArrayStar Gene expression and variant analysis | DNAStar LaserGene software | N/A | software statistical and normalization analysis used for step 4.4 |
Lasergene: SeqMan NGen sequence alignment assembly | software alignment used for step 4.3 | N/A | software alignment used for step 4.3 |
Matrigel, low growth factor basement membrane matrix | Corning | 354230 | |
NRG1-beta | In house | Generated by SLC, also commercially available from R & D Systems(396-HB-050/CF). | |
Nuclear Stain Hoeschst 33342 | Thermo | 62249 | |
Panther Gene Ontology Classification System | Panther | http://pantherdb.org | functional enrichment analysis software used for step 4.5 |
Partek (BWA aligner and analyzer) | Partek, Ver 7 | N/A | software alignment and statistical/normalization used for step 4.3 |
Pen/Strep | Corning | 30-002-Cl | |
Primer 1: 5′-CAAATGCTCTCTCTGTTCTTTGT GTCTG- 3′ |
Eurofins Genomics | Primer 1 + 2: 250 bp ErbB4 null product and a 350 bp Floxed ErbB4 product; | |
Primer 2: 5′-TTTTGCCAAGTTCTAATTCCATC AGAAGC-3′ |
Eurofins Genomics | Primer 1 + 2: 250 bp ErbB4 null product and a 350 bp Floxed ErbB4 product; | |
Primer 3: 5′-TATTGTGTTCATCTATCATTGCA |
Eurofins Genomics | Primer 1 + 3: 350 bp wild-type ErbB4 product. | |
Propidium Iodine | Fisher | 51-351-0 | |
Proteom Profiler Phospho-Kinase Arrays | R&D Systems | ARY003B | |
Real time glo | Promega | G9712 | bioluminescent cell viability assay |
ToppGene Suite | ToppGene | https://toppgene.cchmc.org | functional enrichment analysis software used for step 4.5 |
Trizol (acid-quanidinium-phenol and choloroform based reagent) | Invitrogen | 15596026 | |
Tyramide Signal Amplification Kit | Perkin Elmer | NEL721001EA |