Sign In

A subscription to JoVE is required to view this content. Sign in or start your free trial.

In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

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.

Abstract

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.

Introduction

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.

Protocol

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

  1. Produce the F1 generation of P0-GGFβ3;Trp53+/-;Erbb4fl/+ animals by mating P0-GGFβ3;Trp53+/- mice7 with Erbb4fl/fl mice11. Use a Punnett square (Figure 1) to guide the breeding scheme to ensure that enough male and female F1 pups are generated with the desired P0-GGFβ3;Trp53+/-;Erbb4fl/+ genotype.
  2. Genotype F1 offspring by isolating genomic DNA from a tail snip collected in accordance with IACUC guidelines and then perform PCR using previously described primers to detect the P0-GGFβ3 transgene12, Trp53 wild type (+) and null (-) alleles7, and Erbb4flox and Erbb4 wild-type alleles13.
    1. Isolate tail DNA using methods detailed on jacks-lab.mit.edu/protocols.
    2. Make the PCR reaction mix with 25 ng DNA, 0.25 nM dNTPs, 0.02 U/µL Taq, 0.5 µM of each primer, and 1x PCR buffer. Perform PCR reaction with a single 95 °C incubation (to melt the genomic DNA and activate Taq) for 1 min followed by 35 PCR cycles of 94 °C, 10 s (melting); 55 °C, 30 s (annealing); 72 °C, 40 s (extension) followed by a single 72 °C (extension) for 5 min. Store the reactions at 4 °C until ready to run on a 1.2-1.5% agarose gel.
      NOTE: Annealing temperature depends on the PCR buffer system used; performing an annealing temperature gradient to determine the proper annealing temperature is recommended.
  3. Produce the F2 generation of P0-GGFβ3;Trp53+/-;Erbb4fl/fl animals by mating the appropriate F1 progeny (P0-GGFβ3;Trp53-/+;Erbb4fl/+) with each other.
    NOTE: Figure 1 illustrates the Punnet square predictions used to calculate the expected number of F2 offspring with the desired genotype.
  4. Identify animals with the desired P0-GGFβ3;Trp53-/+;Erbb4fl/fl genotype as described in step 1.2.
  5. Mate F2 progeny to each other to maintain the P0-GGFβ3;Trp53-/+;Erbb4fl/fl colony and genotype all the pups. Confirm that the newly introduced floxed allele does not compromise survival or tumor latency. Achieve this by establishing cohorts (20 mice/cohort) of P0-GGFβ3;Trp53+/- and P0-GGFβ3;Trp53+/-;Erbb4fl/fl mice and follow their survival and frequency of tumor occurrence.
  6. Monitor animals several times per week until the experimental endpoint is reached (maximum allowable tumor size/humane endpoint approved by IACUC).
    1. During the weekly monitoring, assess body weight, normal social and grooming behavior, and tumor size measurements. Arrange for veterinary assessment in case of weight loss of >10% of body weight, social seclusion, and hunching.
    2. When a tumor-bearing mouse is identified and has reached its humane endpoint, humanely euthanize the animal using carbon dioxide inhalation followed by cervical dislocation and sterilely remove the tumor using a scalpel knife. Take tumor measurements by measuring length, width, and depth using a caliper and weight tumor (mass and volume). Work quickly to avoid autolysis.
  7. Section the tumor into three sections using breadloaf style cuts with a scalpel knife under sterile conditions to generate tissue segments for formalin fixation/paraffin-embedding (FFPE), early passage culture generation, and flash-frozen material (Figure 2A).
    1. Ensure that Section 1 (for early passage culture generation, step 1.7.2) is approximately 10% of the total tumor volume, Section 2 (for fixation and IHC, step 1.7.3) is 70% of the total tumor volume, and Section 3 (for flash freeze, step 1.7.4) is 20% of the total tumor volume.
    2. Take section 1 of the tumor for the preparation of early passage cultures (see below).
    3. Fix section 2 of the tumor in 4% paraformaldehyde overnight at 4 °C and then embed in paraffin (formalin-fixed paraffin-embedded (FFPE) for diagnostic workup.
    4. Flash-freeze section 3 for analytical analyses (e.g., immunoblots to verify that protein encoded by the targeted floxed gene is appropriately expressed).
  8. Stain 5 µm-thick FFPE tissue sections with hematoxylin and eosin (H&E) to confirm the tumor diagnosis by a qualified pathologist.If appropriate, perform immunohistochemical staining (IHC) to confirm the tumor diagnosis.
    1. Immunostain MPNSTs for S100 calcium-binding protein B (S100β), nestin, and sex-determining region Y (SRY)-Box transcription factor 10 (Sox10)-three markers that are expressed in both MPNSTs and Schwann cells (tumor cell origin)5,6,14,15. Stain the tumors with antibodies recognizing erbB4, the protein encoded by the gene targeted for ablation in downstream steps.
    2. To confirm the diagnosis, have a qualified veterinary or human pathologist assess all stained tumor slides following WHO diagnostic and grading criteria5,6,7,16.

2. Ex vivo ablation of floxed Erbb4 alleles in MPNST cells

  1. Establish early passage cultures from freshly collected MPNST tissue by placing the tissue from section 1 (step 1.7.3) in 10 mL of ice-cold sterile phosphate-buffered saline (PBS) on ice and then transferring it to a sterile work area (Figure 2B)16.
    NOTE: All subsequent procedures are to be performed in a sterile tissue culture hood.
  2. Mince the tumor tissue into 2-4 mm pieces and triturate 8-10 times in a 10 cm2 treated tissue culture dish with 10 mL of growth medium. Culture these preparations in high glucose DMEM-10 growth medium (Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal calf serum, 1% glutamine, 10 µg/mL streptomycin, and 10 IU/mL penicillin) supplemented with 10 nM neuregulin-1β (NRG1β) and 2 µM forskolin. Add forskolin at this stage to inhibit the growth of common contaminating cell types such as fibroblasts.
  3. Maintain the mechanically dissociated tissue and cells for up to 3 days at 37 °C in a 5% CO2 atmosphere to establish an early passage culture. Do not separate dispersed cells and remaining tissue fragments at this point.
  4. Refresh the cultures with new medium every 3-4 days. Allow the tumor cells to proliferate until they are confluent.
  5. Expand the early passage cultures by splitting the confluent cultures into several dishes. Remove the growth medium and wash cells with 1x dPBS. Then, add 1 mL of 0.25% trypsin for 2-5 min at room temperature per 10 cm2 treated cell culture dish. Gently triturate the culture to facilitate detachment and generate a single-cell suspension.
    1. Terminate the trypsinization by adding 2 mL of DMEM-10 growth medium. Collect the trypsinized cell mixture and transfer it to a 5 mL sterile centrifuge tube. Pellet the cells by centrifugation for 5 min at 500 × g at room temperature.
    2. Resuspend the cell pellet in 5 mL of DMEM-10. Split the cells into two to four 10 cm cell culture dishes, each containing 10 mL of growth media (approximately 1 × 106 cells per dish).
  6. After 5 passages (repeating steps in 2.5), use growth medium without NRG1β and forskolin. Immunostain a sample of the culture with an anti-S100β antibody to verify that the culture is composed solely of tumor cells. Maintain the cells in DMEM-10 growth medium in all subsequent passages.
  7. At the next passage, count the cells and freeze down a portion of P0-GGFβ3;Trp53+/-;Erbb4fl/fl MPNST cells collected from confluent cultures (3 × 106 cells/vial).
  8. Plate P0-GGFβ3;Trp53+/-;Erbb4fl/fl early passage MPNST cells at a density of 1.5 × 106 cells per 10 cm treated cell culture dish in DMEM-10 growth medium.
  9.  Day 0: (Approximately 12-16 h after plating), wash the adherent cultures with 2-4 mL of dPBS and infect with Ad5CMV-Cre/eGFP or Ad5CMV-eGFP at approximately 400 plaque-forming units (pfu)/cell in 10 mL of serum-free DMEM (i.e., 30 µL of 2 × 1010 pfu of virus per 10 cm dish). Ablate the floxed Erbb4 alleles using the adenovirus at the maximum tolerated virus concentration (multiplicity of infection, MOI), as determined empirically. Refer to Figure 2C for a schematic of the workflow for this ablation.
  10. Day 1: Approximately 16 h later, rescue the cultures by adding 10 mL of DMEM-10 to the infection cocktail.
  11. Day 2 - 3: FACS sort infected cells following the recommended protocol from the core facility to sort eGFP-positive cells approximately 48 h after infection. Prior to FACS sorting, briefly check cells for eGFP signal on a fluorescence microscope to ensure that the cultures have been efficiently infected (~50-100% positive cells). Return cells recovered after FACS to 10 cm tissue culture dishes; reserve one dish for genomic DNA isolation.
  12. Day 4 - 5: After FACS sorting, let the cells recover in a tissue culture incubator for at least 24-48 h and then prepare the cells for in vitro cell-based analyses or in vivo grafting. Confirm Erbb4 deletion via PCR using genomic DNA isolated from a portion of the sorted eGFP-positive cells. Verify that eGFP-positive cells are ErbB4-negative by PCR or by immunostaining a sample of the culture with an anti-erbB4 antibody.
    1. Isolate genomic DNA from the cells using standard acid-guanidinium-phenol and chloroform-based DNA isolation method17.
    2. Perform standard PCR to distinguish floxed Erbb4 alleles and ablated Erbb4 alleles. Perform 40 cycles with 2 ng DNA, 20 µM primers 1 + 2 to produce a 250 bp Erbb4-null product and a 350 bp floxed product13. Perform both PCR and antibody-based approaches to confirm knockout when no reliable antibodies are available.
      ​NOTE: Cells are ready for in vitro cell-based assays as described below. Many types of downstream analyses can be performed with cells prepared in this manner. The purpose of the protocols presented below is to provide a few examples of in vitro and in vivo applications of these tumor cells post-ablation of the Erbb4 gene.

3. Proliferation and viability assays in MPNST cells with ablated Erbb4 alleles

  1. Perform proliferation assays over the next seven days on sorted MPNST cells plated in a multiwell plate using an image-based automated cytometer.
    1. Day 6: Plate 2,000 cells per well in a final volume of 150 µL (~13,300 cells/mL) of growth medium in a 96-well plate. Perform measurements in triplicate for each experimental cohort and 4 daily endpoint reads (3 replicates x 2 conditions x 4 days).
    2. Days 7, 9, 11, 13: Stain cells with Hoechst and propidium iodide (PI) dyes and image them on an automated plate reader to count the number of live and dead cells in each well. To achieve this, simultaneously stain the cells with Hoechst dye to stain the nuclei of both living and dead cells and with propidium iodide (PI) to label the dead cells. Perform all reads at the same time every day or every other day.
      1. Add 50 µL of a 4x PI/Hoechst staining solution (4 µg/mL each) to each well quantified that day (e.g., Day 7 only), and incubate for 30 min at 37 °C in the tissue culture incubator. Keep the plate protected from light.
        NOTE: The staining concentration of Hoechst needs to be empirically determined and can range from 1 to 10 µg/mL depending on the cell type.
      2. Read the stained wells after incubation using the appropriate fluorescent channel on the automated cell imager. After reading, return the plate to the incubator for future reads on subsequent days (i.e., Days 9, 11, 13).
      3. Quantify the staining intensities based on the imaging system used and calculate the number of dead cells, living cells, and total cells using the following settings: blue channel (377/50 nm, Hoechst): total cells (live and dead); red channel (531/40 nm, PI): dead cells only; blue - red (total - dead) = live cells.
  2. Perform the cell viability assay over three days, if desired, following the assay manufacturers' protocol.
    NOTE: Viability assays can be combined with proliferation assays by performing a triple stain including calcein AM (488/32 nm; green channel, specifically labels living cells), PI, and Hoechst. An apoptosis assay may also be performed using cultures set up as described above; the specific protocol will depend on the imaging system.
    1. Day 6: Plate 4,000 cells per well in a final volume of 150 µL in a 96-well plate in triplicate.
    2. Days 7 - 9: Add 2,000x bioluminescent cell viability assay reagents (Table of Materials), return the plate to the incubator, and read the plate 1 h later. Perform subsequent reads at the same time every day. For the bioluminescence (MTT) assays, perform the assay exactly as outlined in the manufacturer's instructions every 24 h for 72 h using a luminometer plate reader.

4. RNA-Seq analyses and identification of genes whose expression is altered by Erbb4 loss

  1. Day 6: Isolate total RNA from sorted MPNST cells using standard acid-guanidinium-phenol and chloroform-based methods. For experiments designed to detect changes in mRNA levels between two cohorts, prepare total RNA from at least three biological replicates in each cohort.
    1. To eliminate events caused by the adenoviral vector or eGFP expression rather than Erbb4 loss, isolate RNA from three biological replicates of P0-GGFβ3;Trp53+/-;Erbb4fl/fl MPNST cells transduced with Ad5CMV-Cre/eGFP and three biological replicates transduced with Ad5CMV-eGFP.
      NOTE: Isolated RNA must have an RNA integrity number (RIN) score ≥ 8 for RNA-Seq analysis. Ensure that the sequencing core determines the RIN of all samples prior to constructing libraries.
  2. Use 100-200 ng of high-quality total RNA from each sample to prepare RNA-Seq libraries (work with the core sequencing facility for this step). Perform high-throughput sequencing using a next-generation DNA sequencer. For mRNA quantification, perform single-ended sequencing to generate Fastq files. Ensure a minimum of 50 million reads for each sample.
    NOTE: Refer to Figure 3 for a schematic illustrating the workflow used to process RNA-Seq data and to quantify the expression of differentially expressed transcripts. Sequence data, in the form of Fastq files, are subjected to quality control procedures; >80% of the reads should yield a Phred score of 30 to be considered appropriate for subsequent analysis. The sequences are also preprocessed (trimmed) using Trimmomatic18 to remove adaptor sequences and filter out low-quality reads.
  3. Perform RNA-Seq alignment and analysis on the fastq generated files using any capable software program (e.g., DNAStar19,20 or Partek21). Follow the program-specific steps using the default settings to align the fastq files to the mouse reference genome (GRCm38/mm10).
    NOTE: Using DNAStar as an example, the general workflow is described below (Supplemental Figure 1).
    1. Select the analysis method, RNA-Seq.
    2. Select the reference genome, Mouse.
    3. Upload the BED file if provided one by the sequencing core.
    4. Upload the fastq sequencing files, assigning them unique replicate names.
    5. Group-replicate the fastq files and designate them to a replicate set (i.e., GFP, CRE)
      NOTE: Each alignment program has its specific steps, and the user must consult with the program user guide for the program-specific protocol. The program will then generate gene-specific raw count data from these Fastq files.
  4. Perform statistical and normalization analysis (DESeq2, EdgeR) on the raw count data using any capable software programs, as described in 4.3, with the Ad5CMV-eGFP sample set as the control data set and Ad5CMV-Cre set as the test data set to identify differential gene expression signals with robust statistical power22,23.
    1. Select GFP fastq files as the control data set.
    2. Select DESeq2 as the statistical and normalization method .
    3. Start assembly and analysis.
      NOTE: Each alignment program has its specific steps, and the user must consult with the program user guide for the program-specific protocol. The program will then generate gene-specific raw count data from these Fastq files. The statistical and normalization analysis is a built-in step in many programs, as shown in the example here, within the sequence alignment protocol. If an alternative sequence alignment software program is used that does not offer this subsequent built-in step, perform the statistical and normalization analysis on the raw count data at the terminal level using the DESeq2 or EdgeR coding packages written in R, freely available for download on Bioconductor.org.
  5. Use these approaches to identify changes representing at least a 1.5 fold increase or decrease relative to the control (in this case, cells transduced with the Ad5CMV-eGFP virus). Use only those differentially expressed genes (DEGs) determined to be statistically significant that show ≥1.5-fold changes and a p-value 0.05 or a padj of 0.1 for subsequent functional enrichment analysis.
    NOTE: This will generate a list of DEG genes and their statistical power for functional enrichment analysis.
  6. Perform functional enrichment analysis on statistically significant Erbb4-mediated DEG identified in 4.4 with a ranked gene list file using any of the freely available web-based tools. Determine biological and pathway significance of Erbb4 gene loss through gene ontology datasets integrated in these open-access functional enrichment analysis tools24,25,26,27 (see the Table of Materials for examples and Figure 3 for an example workflow using Panther).
    1. Export the data obtained in step 4.4 as a spreadsheet.
    2. Rank the data by log2 fold change, p/padj value, or both.
    3. Be sure to remove all non-statistically significant data.
    4. Export the ranked gene list with gene ID only as a .txt file and upload it to the website.
      NOTE: Use only statistically significant DEG (p/padj values < 0.05 or 0.1, respectively) to generate a ranked input gene list using log2 fold changes (highest to lowest), p/padj-values (lowest to highest) or both [(-log10(pval)*sign(log2FC)]. There are several approaches to generate a ranked gene list and is empirically determined for the dataset and the question being asked. The specific type of functional enrichment analysis tool being used can also assist in determining the appropriate type of rank gene list. For additional resources on RNA-Seq, see the following papers28,29,30.

5. Orthotopic allografting of MPNST cells with ablated Erbb4 alleles and analysis of the effects of Erbb4 ablation

  1. Before performing orthotopic allografting of sorted MPNST cells, ensure that all procedures are reviewed and approved by the Institutional Animal Care and Use Committee, and that all procedures are performed by properly trained personnel.
  2. On the day of injection, remove low passage cells (approximately 85% confluency) from cell culture plates or flasks using a non-enzymatic cell dissociation solution (e.g., a mixture of chelators; see the Table of Materials) and count the cells using a hemocytometer. For orthotopic injections into the sciatic nerve, reconstitute the cells at 16,667 cells/mL (50,000 cells per 3 µL for each animal) in DMEM-1031. Keep the cells on ice.
    NOTE: Some cultures will not successfully establish grafts unless the cells are injected in low-growth factor basement membrane matrix. The requirement for a basement membrane matrix (10-50%) must be empirically determined.
  3. Assess in vivo allograft growth potential in post-infected cells by injecting MPNST cells into the sciatic nerve of 8-10 anesthetized Hsd: Athymic Nude-Foxn1nu mice per cohort (aged 4-8 weeks). For orthotopic injection of tumor cells, refer to Turk et al31Here, a subcutaneous injection is demonstrated.
    NOTE: To determine the number of experimental animals needed for statistical significance, consult with a biostatistician or it is recommended to use G*Power3, a freely available software32.
  4. Monitor the animals closely twice daily for the first week post-injection for any signs of pain. Thereafter, monitor the grafted mice three times per week for caliper measurements and assess body condition scores (BCSs) as previously described5,31. As outlined in IACUC guidelines, euthanize animals with a BCS of 2 or less.
  5. As grafted cells grow at different rates, determine graft times empirically using control (unmodified) cells before performing experiments described in this section. To collect the grafts at the experimental endpoint, euthanize the mice humanely using carbon dioxide inhalation followed by cervical dislocation as a secondary measure. Record the final volume and mass measurements of each graft.
    NOTE: As unmodified P0-GGFβ3;Trp53+/-;Erbb4fl/fl MPNST cells typically reach the maximum size allowed by IACUC within 30-45 days, a typical timeline is around 30-45 days after injection.
  6. Isolate and section tissue as described in steps 1.6-1.8. Fix part of the graft tissue overnight in 4% paraformaldehyde (Figure 2) and then embed it in paraffin. Prepare 5 µm sections from the FFPE tissue and mount them on slides. Perform H&E staining and other necessary immunostaining to confirm that the graft tissue is composed of tumor cells as described in 1.8.1. Snap-freeze the rest of the tumor tissue for downstream analyses, such as validating the loss of Erbb4 expression and assessing the effects of Erbb4 loss on the expression of other Erbb family members.
    NOTE: Confirmation of tumor cells in the graft tissue must be done because immunodeficient mice are prone to develop neoplasms. In the case of small grafts, it is important to ensure that scar tissue or inflammation is not mistaken for a neoplasm.
    1. Perform standard IHC staining on the FFPE tissue to compare the expression of proteins of interest in allografts grown from Ad5CMV-eGFP and Ad5CMV-Cre/eGFP treated cells. Stain the excised graft tissue using erbB4-specific antibodies to confirm differences in in vivo erbB4 expression between the two experimental conditions. Determine the proliferative index via Ki67 staining and the level of apoptosis via terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining.
      ​NOTE: Any protein target of interest can also be assessed via IHC. For example, assess vascular density by immunostaining allografts with an anti-CD31 antibody (1:50 dilution) to determine in vivo vascular microenvironment differences mediated by gene ablation. The number of vascular profiles per 40x field can be counted for quantification. For these IHC-based assays, follow standard IHC protocols for the staining procedures and the manufacturer's protocol for TUNEL staining. For quantification of images, use the ImageJ plug-in "automated counting of single-color image."

Results

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 pe...

Discussion

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 do...

Disclosures

The authors have no conflicts of interest to disclose.

Acknowledgements

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).

Materials

NameCompanyCatalog NumberComments
Ad5CMV-eGFPGene Transfer Vector Core, Univ of IowaVVC-U of Iowa-4
Ad5CMVCre-eGFPGene Transfer Vector Core, Univ of IowaVVC-U of Iowa-1174
alexa 568 secondary antibodyThermo/FisherGaR A11036
Bioconductor Open Source Software for BioninformaticsBioconductorhttp://www.bioconductor.orgalternative statistical analysis tool used for step 4.4
CD31Abcamab28364
Celigo Image CytometerNexcelom BioscienceN/A
Cell StripperCorning25-056-Clmixture of chelators
DAB staining kitVector LabsMP-7800
DAVID (Database for Annotation, Visualization, and Integrated Discovery)DAVIDhttps://david.ncifcrf.govfunctional enrichment analysis software used for step 4.5
DMEMCorning15-013-Cl
DreamTaq and Buffer (Genotyping PCR)Thermo/FisherEP0701 and K1072
erbB4 antibodiesSanta Cruzsc-284
erbB4 antibodiesAbcamab35374
erbB4 antibodiesMilliporeHFR1: 05-1133
FACS SorterBD BiosciencesAria II
ForskolinSigmaF6886
GenomeSpace Tools and Data SourcesGenomeSpacehttps://genomespace.org/support/tools/general resource for several types of open source bioinformatic tools for step 4.5
GlutamineCorning25-005-Cl
Gorilla Gene Ontology enRIchment anaLysis and visuaLizAtion toolGorillaN/A, http://cbl-gorilla.cs.technion.ac.ilfunctional enrichment analysis software used for step 4.5
GSEA Gene Set Enrichment AnalysisBroad InstituteN/A, https://www.gsea-msigdb.org/gsea/index.jspfunctional enrichment analysis software used for step 4.5
HSD: Athymic Nude-FOxn1nu miceEnvigo (Previously Harlan Labs)69
Illumina HiSeq2500 (next generation DNA sequencer)IlluminaHi Seq 2500DNA sequencer used for step 4.2
Lasergene: ArrayStar Gene expression and variant analysisDNAStar LaserGene softwareN/Asoftware statistical and normalization analysis used for step 4.4
Lasergene: SeqMan NGen sequence alignment assemblysoftware alignment used for step 4.3N/Asoftware alignment used for step 4.3
Matrigel, low growth factor basement membrane matrixCorning354230
NRG1-betaIn houseGenerated by SLC, also commercially available from R & D Systems(396-HB-050/CF).
Nuclear Stain Hoeschst 33342Thermo62249
Panther Gene Ontology Classification SystemPantherhttp://pantherdb.orgfunctional enrichment analysis software used for step 4.5
Partek (BWA aligner and analyzer)Partek, Ver 7N/Asoftware alignment and statistical/normalization used for step 4.3
Pen/StrepCorning30-002-Cl
Primer 1: 5′-CAAATGCTCTCTCTGTTCTTTGT
GTCTG- 3′
Eurofins GenomicsPrimer 1 + 2: 250 bp ErbB4 null product and a 350 bp Floxed ErbB4 product;
Primer 2: 5′-TTTTGCCAAGTTCTAATTCCATC
AGAAGC-3′
Eurofins GenomicsPrimer 1 + 2: 250 bp ErbB4 null product and a 350 bp Floxed ErbB4 product;

Primer 3: 5′-TATTGTGTTCATCTATCATTGCA
ACCCAG-3′

Eurofins GenomicsPrimer 1 + 3: 350 bp wild-type ErbB4 product.
Propidium IodineFisher51-351-0
Proteom Profiler Phospho-Kinase ArraysR&D SystemsARY003B
Real time gloPromegaG9712bioluminescent cell viability assay
ToppGene SuiteToppGenehttps://toppgene.cchmc.orgfunctional enrichment analysis software used for step 4.5
Trizol (acid-quanidinium-phenol and choloroform based reagent)Invitrogen15596026
Tyramide Signal Amplification KitPerkin ElmerNEL721001EA

References

  1. Ricciuti, B., et al. Antibody-drug conjugates for lung cancer in the era of personalized oncology. Seminars in Cancer Biology. 69, 268-278 (2019).
  2. Litak, J., Mazurek, M., Grochowski, C., Kamieniak, P., Rolinski, J. PD-L1/PD-1 axis in glioblastoma multiforme. International Journal of Molecular Sciences. 20 (21), 5347 (2019).
  3. Roskoski, R. Properties of FDA-approved small molecule protein kinase inhibitors. Pharmacological Research. 144, 19-50 (2019).
  4. Heffner, C. S., et al. Supporting conditional mouse mutagenesis with a comprehensive cre characterization resource. Nature Communications. 3, 1218 (2012).
  5. Longo, J. F., et al. ErbB4 promotes malignant peripheral nerve sheath tumor pathogenesis via Ras-independent mechanisms. Cell Communication and Signaling. 17 (1), 74 (2019).
  6. Kazmi, S. J., et al. Transgenic mice overexpressing neuregulin-1 model neurofibroma-malignant peripheral nerve sheath tumor progression and implicate specific chromosomal copy number variations in tumorigenesis. American Journal of Pathology. 182 (3), 646-667 (2013).
  7. Brosius, S. N., et al. Neuregulin-1 overexpression and Trp53 haploinsufficiency cooperatively promote de novo malignant peripheral nerve sheath tumor pathogenesis. Acta Neuropatholica. 127 (4), 573-591 (2014).
  8. Ducatman, B. S., Scheithauer, B. W., Piepgras, D. G., Reiman, H. M., Ilstrup, D. M. Malignant peripheral nerve sheath tumors. A clinicopathologic study of 120 cases. Cancer. 57 (10), 2006-2021 (1986).
  9. Gassmann, M., et al. Aberrant neural and cardiac development in mice lacking the ErbB4 neuregulin receptor. Nature. 378 (6555), 390-394 (1995).
  10. Tidcombe, H., et al. Neural and mammary gland defects in ErbB4 knockout mice genetically rescued from embryonic lethality. Proceedings of the Nationall Academy of Sciences of the United States of America. 100 (14), 8281-8286 (2003).
  11. Golub, M. S., Germann, S. L., Lloyd, K. C. Behavioral characteristics of a nervous system-specific erbB4 knock-out mouse. Behavioral Brain Research. 153 (1), 159-170 (2004).
  12. Huijbregts, R. P., Roth, K. A., Schmidt, R. E., Carroll, S. L. Hypertrophic neuropathies and malignant peripheral nerve sheath tumors in transgenic mice overexpressing glial growth factor beta3 in myelinating Schwann cells. Journal of Neuroscience. 23 (19), 7269-7280 (2003).
  13. Jackson-Fisher, A. J., et al. Formation of Neu/ErbB2-induced mammary tumors is unaffected by loss of ErbB4. Oncogene. 25 (41), 5664-5672 (2006).
  14. Byer, S. J., et al. Tamoxifen inhibits malignant peripheral nerve sheath tumor growth in an estrogen receptor-independent manner. Neuro-oncology. 13 (1), 28-41 (2011).
  15. Kang, Y., Pekmezci, M., Folpe, A. L., Ersen, A., Horvai, A. E. Diagnostic utility of SOX10 to distinguish malignant peripheral nerve sheath tumor from synovial sarcoma, including intraneural synovial sarcoma. Modern Pathology. 27 (1), 55-61 (2014).
  16. Longo, J. F., et al. Establishment and genomic characterization of a sporadic malignant peripheral nerve sheath tumor cell line. Scientific Reports. 11 (1), 5690 (2021).
  17. Chomczynski, P. A reagent for the single-step simultaneous isolation of RNA, DNA and proteins from cell and tissue samples. Biotechniques. 15 (3), 532-537 (1993).
  18. Bolger, A. M., Lohse, M., Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 30 (15), 2114-2120 (2014).
  19. Grozdanov, P. N., Li, J., Yu, P., Yan, W., MacDonald, C. C. Cstf2t regulates expression of histones and histone-like proteins in male germ cells. Andrology. 6 (4), 605-615 (2018).
  20. Kaur, S., et al. CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs. Scientific Reports. 8 (1), 2577 (2018).
  21. Avraham, O., et al. Satellite glial cells promote regenerative growth in sensory neurons. Nature Communications. 11 (1), 4891 (2020).
  22. Love, M. I., Huber, W., Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 15 (12), 550 (2014).
  23. Lin, Y., et al. Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster. BMC Genomics. 17, 28 (2016).
  24. Eden, E., Navon, R., Steinfeld, I., Lipson, D., Yakhini, Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics. 10, 48 (2009).
  25. Huang, D. W., et al. The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biology. 8 (9), 183 (2007).
  26. Mi, H., Muruganujan, A., Casagrande, J. T., Thomas, P. D. Large-scale gene function analysis with the PANTHER classification system. Nature Protocols. 8 (8), 1551-1566 (2013).
  27. Subramanian, A., et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the Nationall Academy of the Sciences of the United States of America. 102 (43), 15545-15550 (2005).
  28. Merico, D., Isserlin, R., Stueker, O., Emili, A., Bader, G. D. Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. PLoS One. 5 (11), 13984 (2010).
  29. Yoon, S., Kim, S. Y., Nam, D. Improving gene-set enrichment analysis of RNA-Seq data with small replicates. PLoS One. 11 (11), 0165919 (2016).
  30. Koch, C. M., et al. A beginner's guide to analysis of RNA sequencing data. American Journal of Respiratory Cell and Molecular Biology. 59 (2), 145-157 (2018).
  31. Turk, A. N., Byer, S. J., Zinn, K. R., Carroll, S. L. Orthotopic xenografting of human luciferase-tagged malignant peripheral nerve sheath tumor cells for in vivo testing of candidate therapeutic agents. Journal of Visualized Experiments: JoVE. (49), e2558 (2011).
  32. Faul, F. E., Lang, A. G., Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods. 39 (2), 175 (2007).
  33. Chen, Z., et al. Cells of origin in the embryonic nerve roots for NF1-associated plexiform neurofibroma. Cancer Cell. 26 (5), 695-706 (2014).
  34. Mo, J., et al. Humanized neurofibroma model from induced pluripotent stem cells delineates tumor pathogenesis and developmental origins. Journal of Clinical Investigation. 131 (1), 139807 (2021).
  35. Chau, V., et al. Preclinical therapeutic efficacy of a novel pharmacologic inducer of apoptosis in malignant peripheral nerve sheath tumors. Cancer Research. 74 (2), 586-597 (2014).
  36. Dodd, R. D., et al. NF1(+/-) Hematopoietic cells accelerate malignant peripheral nerve sheath tumor development without altering chemotherapy response. Cancer Research. 77 (16), 4486-4497 (2017).
  37. Eckert, J. M., Byer, S. J., Clodfelder-Miller, B. J., Carroll, S. L. Neuregulin-1 beta and neuregulin-1 alpha differentially affect the migration and invasion of malignant peripheral nerve sheath tumor cells. Glia. 57 (14), 1501-1520 (2009).

Reprints and Permissions

Request permission to reuse the text or figures of this JoVE article

Request Permission

Explore More Articles

Gene FunctionsTumorigenesisEmbryonic Lethal Gene KnockoutMalignant Peripheral Nerve Sheath TumorIn Vivo StudyMouse ModelAdenoviral InfectionImmunohistochemical StainingEarly Passage CulturesTissue CultureNeuregulin 1 BetaForskolinDMEM MediumTumor BiopsyFluorescence Microscopy

This article has been published

Video Coming Soon

JoVE Logo

Privacy

Terms of Use

Policies

Research

Education

ABOUT JoVE

Copyright © 2025 MyJoVE Corporation. All rights reserved