Registered report: Diverse somatic mutation patterns and pathway alterations in human cancers

The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of selected experiments from a number of high-profile papers in the field of cancer biology. The papers, which were published between 2010 and 2012, were selected on the basis of citations and Altmetric scores (Errington et al., 2014). This Registered Report describes the proposed replication plan of key experiments from "Diverse somatic mutation patterns and pathway alterations in human cancers" by Kan and colleagues published in Nature in 2010 (Kan et al., 2010). The experiments to be replicated are those reported in Figures 3D-F and 4C-F. Kan and colleagues utilized mismatch repair detection (MRD) technology to identify somatic mutations in primary human tumor samples and identified a previously uncharacterized arginine 243 to histidine (R243H) mutation in the G-protein α subunit GNAO1 in breast carcinoma tissue. In Figures 3D-F, Kan and colleagues demonstrated that stable expression of mutant GNAO1R243D conferred a significant growth advantage in human mammary epithelial cells, confirming the oncogenic potential of this mutation. Similarly, expression of variants with somatic mutations in MAP2K4, a JNK pathway kinase (shown in Figures 4C-E) resulted in a significant increase in anchorage-independent growth. Interestingly, these mutants exhibited reduced kinase activity compared to wild type MAP2K4, indicating these mutations impose a dominant-negative influence to promote growth (Figure 4F). The Reproducibility Project: Cancer Biology is a collaboration between the Center for Open Science and Science Exchange and the results of the replications will be published in eLife. DOI: http://dx.doi.org/10.7554/eLife.11566.001


Introduction
Human cancer is driven by the acquisition of mutations in cells of somatic origin. Somatic mutations comprise several distinct classes of DNA sequence changes, including single-nucleotide substitutions, small insertions and deletions (indels), copy number alterations, and structural rearrangements (Weir et al., 2007;Chin and Gray, 2008;Stratton et al., 2009;Pleasance et al., 2010). Somatic mutations can be further characterized based on their oncogenic ability: genetic variations that are directly involved in cancer development are termed "driver" mutations, whereas mutations that do not confer any obvious advantage are referred to as "passenger" mutations (Davies et al., 2005). In all cases, genetic changes in somatic cells arise as a result of defective DNA repair mechanisms and/ or imprecise DNA replication, and can develop spontaneously, be acquired over the lifetime of an individual, or by direct exposure to mutagens, such as tobacco smoke and ionizing UV radiation (Pfeifer, 2010;Pleasance et al., 2010;Helleday et al., 2014). Over the past 10 years, technologies for the detection of wide-spread genetic alterations have been developed and used to analyze cancer genomes (Stratton et al., 2009;Watson et al., 2013). Its is clear that cancer cell genomes often harbor substantial somatic mutation burdens, thus the ability to generate a comprehensive genetic cancer profile has the potential to significantly improve patient diagnosis and treatment.
The combination of PCR and Sanger sequencing to identify mutations in tumor genomes has proven to be a powerful approach in the study of cancer genomics (Collins et al., 2003). However, this technology is constrained by limited throughput and cost (Chin et al., 2011). Here, Kan and colleagues utilized mismatch repair detection (MRD) technology as a low-cost, high throughput alternative to identify somatic mutations in a large number of primary human tumor samples (Peters et al., 2007). Using this technique, Kan and colleagues identified an uncharacterized somatic mutation in GNAO1 from breast carcinoma tissue (Kan et al., 2010). GNAO1 encodes the Gao subunit of heterotrimeric guanine-binding proteins (G proteins) (Jastrzebska, 2013). G proteins function as molecular switches that alternate between "on" (GTP-bound) and "off" (GDP-bound) states to control signal transduction in eukaryotes (Gilman, 1987;Birnbaumer, 2007b;2007a). While previous studies have reported oncogenic mutations in the Ga subunits of other G proteins, including GNAS, GNAI2 and GNAQ (Landis et al., 1989;Lyons et al., 1990;Forbes et al., 2008;Van Raamsdonk et al., 2009), the arginine 243 to histidine (R243H) conversion identified in GNAO1 does not correspond to any previously described mutations within G proteins (Garcia-Marcos et al., 2011). In Figure 3D-F, the oncogenic potential of this mutation was tested. Human mammary epithelial cells (HMECs) stably expressing equivalent levels of wild type GNAO1 or GNAO1 R243H were suspended in agar before assessment for colony formation. This key experiment reported that the R243H mutation promotes a two-fold increase in anchorage-independent growth compared to cells expressing wild type GNAO1, and will be replicated in Protocol 1. Subsequent work on GNAO1 has characterized the molecular basis underlying the oncogenic properties of the R243H mutation. Importantly, these studies have determined that the R243H mutation renders Gao constitutively active via Src-STAT3 signaling (Garcia-Marcos et al., 2011;Leyme et al., 2014).
Kan and colleagues also identified a number of somatic mutations in mitogen activated protein kinase kinase 4 (MAP2K4) (Kan et al., 2010). MAP2K4 is a component of a triple kinase cascade that involves the successive activation of downstream MAP kinases, culminating in the activation of c-Jun NH2-terminal kinases (JNK) and p38 (Derijard et al., 1995;Chang and Karin, 2001;Johnson and Lapadat, 2002). Both the JNK and p38 signaling pathways mediate cellular responses to cytokine signals, stress and other extracellular stimuli (Johnson and Lapadat, 2002). While mutations in MAP2K4 have been reported here (Kan et al., 2010) and elsewhere (Teng et al., 1997;Parsons et al., 2005;Greenman et al., 2007;Forbes et al., 2008), the role of MAP2K4 in cancer has remained complex and contradictory. Some studies have suggested MAP2K4 functions as a prooncogenic molecule in breast and pancreatic tumors (Wang et al., 2004), melanoma (Finegan and Tournier, 2010), and in prostate cancer tumors (Lotan et al., 2007;Pavese et al., 2014), whereas other early reports identified MAP2K4 as a putative tumor suppressor gene due to its frequent inactivation in human cancer cell lines and tumor tissues, including pancreatic, breast, ovarian, and colon cancer cells and tissues (Su et al., 1998;Nakayama et al., 2006;Ahn et al., 2011).
In Figure 4C-E, the functional relevance of six select MAP2K4 mutants (5 located in the kinase domain, 1 outside the kinase domain) were tested in vitro (Kan et al., 2010). NIH3T3 fibroblasts stably expressing equivalent levels of either WT or mutant MAP2K4 were assessed for their ability to promote anchorage-independent growth. Importantly, all six MAP2K4 variants resulted in significantly enhanced agar colony formation compared to cells expressing wild type MAP2K4. A majority of the MAP2K4 mutants resulted in reduced activity to either JNK or myelin basic protein (MBP) when tested in an in vitro kinase assay suggesting that reduced MAP2K4 signaling plays a dominantnegative role in the control of cell growth. A related study examined the invasiveness of cells where endogenous MAP2K4 was depleted and various MAP2K4 mutants were added back, including four of the mutants tested by Kan and colleagues (Ahn et al., 2011). The effect on invasion was directly proportional to the kinase activities of the mutants. The mutations that resulted in loss-of-function kinase activity (including R154W, S251N, and N234I examined by Kan and colleagues) resulted in increased invasion, while mutations with gain-of-function kinase activity, or comparable kinase activity to wild-type (including A279T examined by Kan and colleagues), did not (Ahn et al., 2011). More recent studies have confirmed these findings, showing that MAP2K4 genetic inactivation is prevalent in high grade serous and endometrioid carcinomas, breast cancer, and pancreatic cancer (Davis et al., 2011;Yeasmin et al., 2011b;Yeasmin et al., 2011a;Curtis et al., 2012;Huang et al., 2013). Furthermore, genetic polymorphisms that increase MAP2K4 promoter activity are associated with reduced risk of prostate, lung, and sporadic colorectal cancers (Wei et al., 2009;Liu et al., 2010;Shao et al., 2012). A recent study by Haeusgen and colleagues (Haeusgen et al., 2014) suggests that the balance between MAP2K4 and a novel MAP2K4 splice variant may be important in regulating appropriate cell growth. The key experiments described in Figures 4C-F will be replicated in Protocol 2.

Materials and methods
Unless otherwise noted, all protocol information was derived from the original paper, references from the original paper, or information obtained directly from the authors. An asterisk (*) indicates data or information provided by the Reproducibility Project: Cancer Biology core team. A hashtag (#) indicates information provided by the replicating lab.
Protocol 1: Generation of N-terminally Flag-tagged MAP2K4 and GNAO1 wild-type and mutant vectors This protocol generates N-terminally flag-tagged wild type or mutant GNAO1 and wild type or mutant MAP2K4 vectors. These vectors will be used in Protocols 2 and 4.

Sampling
. This experiment will be performed once in order to generate vectors. . Plasmids for use in Protocols 2 and 4:

Materials and reagents
Confirmatory analysis plan . None applicable.

Known differences from the original study
The vector backbone pRetroX-IRES-ZsGreen1 will be used instead of pRetroX-IRES-FLAG because the latter is no longer available. The replicating lab will use a cDNA with an ORF tagged with myc-DDK (the same as FLAG) for downstream protocols. Not all mutants used in the original study will be replicated. We will not generate MAP2K4 mutations G85R, R154W, N234I or S251N. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.

Provisions for quality control
Sequencing and gel analysis of plasmids will be reported. All of the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/jpeqg/) and made publically available.
Protocol 2: Generation of human mammary epithelial cells stably expressing wild-type or GNAO1 R243H This protocol describes the generation of HMECs stably expressing WT or mutant GNAO1 R243H protein. Expression of GNAO1 will be confirmed by Western blot that will be a replication of Figure 3F. These cells will subsequently be used in Protocol 3.

Sampling
. This experiment to be conducted one time to confirm stable expression of GNAO1 WT or GNAO1 R243H protein.
. Phoenix cells are grown in complete DMEM medium: DMEM supplemented with 10% (v/v) FBS, 2 mM L-glutamine and 4.5 g/L glucose, 100 U/mL penicillin and 100 mg/ml streptomycin cultured at 37˚C and 5% CO 2 .
. All cells will be sent for mycoplasma testing and STR profiling.
1. # Transfect Phoenix cells with the appropriate retroviral constructs using Lipofectamine 2000 according to manufacturer's instructions. a. On the day before transfection, transfer Phoenix cells to fresh medium in 6 well plates and maintain at 37˚C and 5% CO 2 . b. On the day of transfection, dilute 2.5 mg plasmid DNA in 500 ml Opti-MEM medium and mix gently.
i. Change media after 4-6 hr to complete media containing serum. g. Harvest virus-containing supernatants 48 hr post transfection and re-feed cells with DMEM. Incubate at 37˚C in a humidified 5% CO 2 incubator. Note: Multiple rounds of collection may be required for concentrating stock.
i. This initial collected media can be stored briefly at 4˚C. h. After an additional 12-24 hr of culture, collect viral supernatants again and pool with first collection. i. # Concentrate viral stock.
i. Centrifuge the viral supernatant at 3000 rpm for 15 min to remove any cell debris.
ii. Filter the supernatant through a 0.45 mm syringe filter.
iii. Ultracentrifuge at 22,000 rpm for 2 hr at 4˚C to produce concentrated viral stocks. iv. Aliquot virus into screw-cap centrifuge tubes and store at -70˚C. j. # Titre retrovirus i. One day before harvesting viral supernatant, plate 1.2 Â 10 5 HMECs per well of a 6 well dish. ii. On the day of viral supernatant harvesting, count the number of cells in one well to determine cell number at time of infection. iii. Add a range of volumes between 2 to 5 ml of concentrated viral supernatant to the wells. Incubate for 72 hr. iv. Remove culture medium, wash the wells once with 2 ml PBS. v. Add 0.5 ml of 0.25% trypsin EDTA vi. Incubate 5 min at 37˚C. vii. Add 0.5 ml DMEM-10 or 15 (10-15% FBS). viii. Pipette up and down with 1 ml pipette and transfer cells to a FACS tube. ix. Determine the percentage of GFP-positive cells by FACS analysis. ii. # Mouse Anti-ß-ACTIN ( # 1:1000 dilution) g. Wash membrane 3 times in 1X TBS for 5 min each on shaker. h. Incubate with anti-mouse HRP conjugated secondary antibody ( # 1:1000) for 1 hr on shaker at room temperature. i. Remove membrane from secondary antibody and wash three times in 1X TBS for 5 min each. j. Prepare ECL solution and incubate membrane. k. Expose membrane to X-ray film, develop and scan.
Deliverables . Data to be collected: . Data for viral titration . Flow cytometry data (for viral titration and sorting of transduced cells) . Protein determination assay data. . Figure 3F: Full scans of all films for each western blot with ladder. . Sample delivered for further analysis: . HMECs transduced with: Confirmatory analysis plan . None applicable.
Known differences from the original study All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.
The cell line used in this experiment will undergo STR profiling to confirm its identity and will be sent for mycoplasma testing to ensure there is no contamination. GNAO1 expression will be confirmed in the top 10% GFP positive HMECs with western blots. All of the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/jpeqg/) and made publically available.
Protocol 3: Anchorage-independent colony formation assay of HMECs transduced with wild-type or mutant GNAO1 This experiment tests the effect of WT or mutant GNAO1 expression on anchorage-independent colony formation of HMECs. It is a replication of the experiments reported in Figure 3D-E.

Materials and reagents
1. Grow 3 flasks of transduced and untransduced control HMECs in complete HMEC medium: HMEC medium supplemented with HMEC supplement, # 0.5 mg/mL bovine pituitary extract, 100 U/mL penicillin and 100 mg/mL streptomycin cultured at 37˚C and 5% CO 2 (these will be the biological replicates). 2. Plate a lower layer of # 1 ml 0.5% agar per well in twelve wells of 6-well plates.
a. # Refresh growth media on top layer every 2-3 days. 6. Assess the presence of colonies.
3. Remove and stain with 500 ml 0.01% crystal violet for 1 hr. 4. Remove stain and wash wells. b. Image entire well with high-resolution camera.
1. Include calibration scale in image. c. Quantify the number of colonies greater than 200 mm in diameter using ImageJ software.
1. Set threshold using calibration scale taken during image acquisition.
Deliverables . Data to be collected: . Figure 3D: Images of colonies. . Raw numbers for quantification of colonies for each sample. . Figure 3E: Graph of mean number of colonies for each cohort.

Confirmatory analysis plan
. Statistical Analysis of the Replication Data: . Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantilequantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test.
. Unpaired two-tailed t-test of the mean number of colonies in HMECs expressing exogenous GNAO1 WT or GNAO1 R243H .
. Meta-analysis of original and replication attempt effect sizes: . This replication attempt will perform the statistical analysis listed above, compute the effects sizes, compare them against the reported effect size in the original paper and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot

Known differences from the original study
The original study counted cell colonies using GelCount to image, count, and analyze colonies, while the replication attempt will stain with crystal violet to enhance detection of cell colonies, image wells with a high-resolution camera, and use ImageJ software to count and analyze colonies. Since the software and approach used by the original and replication attempt are different, there will likely be some differences in sensitivity and error rates. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.
The cell line used in this experiment will undergo STR profiling to confirm its identity and will be sent for mycoplasma testing to ensure there is no contamination. All of the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/jpeqg/) and made publically available.

Protocol 4: Generation of NIH3T3 cells stably expressing wild-type or mutant MAP2K4
This protocol describes the generation of NIH3T3 cells stably expressing wild-type or mutant MAP2K4 proteins. This protocol also describes verification of expression of MAP2K4 by western blot that will be a replication of Figure 4E. These cells will subsequently be used in Protocols 4 and 5.

Sampling
. This experiment will be conducted one time to confirm stable expression of exogenous MAP2K4.
. All cells will be sent for mycoplasma testing and STR profiling. Deliverables . Data to be collected: . Data for viral titration . Flow cytometry data (for viral titration and sorting of transduced cells) . Protein determination assay data. . Figure 4E: Full scans of all films for each western with ladder. . Sample delivered for further analysis: . NIH3T3 cells transduced with: Confirmatory analysis plan . None applicable.

Known differences from the original study
Not all mutants used in the original study will be replicated. We will not generate MAP2K4 mutations G85R, R154W, N234I or S251N. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.

Provisions for quality control
The cell lines used in this experiment will undergo STR profiling to confirm their identity and will be sent for mycoplasma testing to ensure there is no contamination. MAP2K4 expression will be confirmed in the top 10% GFP positive HMECs with Western blots. All of the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/jpeqg/) and made publically available.
Protocol 5: Anchorage-independent colony formation assay of NIH3T3 cells transduced with wild-type or mutant MAP2K4 This experiment tests the effect of WT or mutant MAP2K4 expression on anchorage-independent colony formation of NIH3T3 cells. It is a replication of the experiments reported in Figure 4C and 4D.
Sampling . Experiment to be repeated a total of 3 times for a minimum power of 99%.  . All cells will be sent for mycoplasma testing and STR profiling.

Materials and reagents
1. Grow 3 flasks each of transduced NIH3T3 cells generated in Protocol 4 in complete DMEM medium: DMEM medium supplemented with 10% (v/v) FBS, 2 mM L-glutamine, 100 U/mL penicillin and 100 mg/mL streptomycin cultured at 37˚C and 5% CO 2 . (these will be the biological replicates) 2. Plate a lower layer of # 1 ml 0.5% agar per well in 16 wells of 6-well plates.
a. # Refresh growth media from top layer every 2-3 days. 6. Assess the presence of colonies.
3. Remove and stain with 500 ml 0.01% crystal violet for 1 hr. 4. Remove stain and wash wells. b. Image entire well with a high-resolution camera.
1. Include calibration scale in image. c. Quantify the number of colonies greater than 100 mm in diameter using ImageJ software.
1. Set threshold using scale taken during image acquisition.

Deliverables
. Data to be collected: . Figure 4C: Images of colonies. . Raw numbers for quantification of colonies for each sample. . Figure 4D: Graph of mean number of colonies for each cohort.

Confirmatory analysis plan
. Statistical Analysis of the Replication Data: . Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantilequantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test.
. One-way ANOVA of the mean number of colonies in NIH3T3 cells expressing exogenous MAP2K4 WT , MAP2K4 R228K , or MAP2K4 A279T followed by planned comparisons using Fisher's LSD: . MAP2K4 WT vs MAP2K4 R228K . MAP2K4 WT vs MAP2K4 A279T . Meta-analysis of original and replication attempt effect sizes: . Compute the effect sizes of each comparison, compare them against the effect size in the original paper and use a random effects meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.

Known differences from the original study
Not all mutants used in the original study will be replicated. We will not generate MAP2K4 mutations G85R, R154W, N234I or S251N. The original study counted cell colonies using GelCount to image, count, and analyze colonies, while the replication attempt will stain with crystal violet to enhance detection of cell colonies, image wells with a high-resolution camera, and use ImageJ software to count and analyze colonies. Since the software and approach used by the original and replication attempt are different, there will likely be some differences in sensitivity and error rates. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.

Provisions for quality control
The cell line used in this experiment will undergo STR profiling to confirm its identity and will be sent for mycoplasma testing to ensure there is no contamination. All of the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/jpeqg/) and made publically available.
Protocol 6: Assessing the kinase activity of wild-type or mutant MAP2K4 This experiment tests the in vitro kinase activity of WT or mutant MAP2K4 immunoprecipitated from NIH3T3 cells. It is a replication of the experiment reported in Figure 4F.
Sampling . Experiment to be repeated a total of 4 times. . The original data is qualitative, thus to determine an appropriate number of replicates to initially perform, sample sizes were determined based on a range of potential variance.
. See Power Calculations section for details. . Experiment has 5 cohorts: . . Transduced NIH3T3 cells are generated in Protocol 4. . All cells will be sent for mycoplasma testing and STR profiling. Deliverables . Data to be collected: . Protein determination assay data. . Figure 4F: Full images of autoradiographs for each kinase assay substrate with ladder. . Figure 4F: Scans of full films for western blot of MAP2K4 input with ladder.

Confirmatory analysis plan
. Statistical Analysis of the Replication Data: . Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantilequantile plot to assess the normality of the data. We will also perform Levene's test to assess homoscedasticity. If the data appears skewed we will perform the appropriate transformation in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test.
. Bonferroni corrected one-sample t-tests of normalized pMBP levels from the following MAP2K4 variants compared to 1 (MAP2K4 WT ): . MAP2K4 R228K . MAP2K4 A279T . Bonferroni corrected one-sample t-tests of normalized pMAPK9/pJNK levels from the following MAP2K4 variants compared to 1 (MAP2K4 WT ): . MAP2K4 R228K . MAP2K4 A279T . Meta-analysis of effect sizes: . Since some of the band intensities in the original paper were unable to be quantified the replication study will record and make accessible all autoradiographs collected. This will allow for a subjective comparison of the original images and the replication images. Additionally, the replication will quantify the results in an additional exploratory measure. This cannot be compared to the original reported results, but will be presented to understand the utility of analyzing the data in a quantitative manner.

Known differences from the original study
Not all mutants used in the original study will be replicated. We will not generate MAP2K4 mutations G85R, R154W, N234I or S251N. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.

Provisions for quality control
The cell line used in this experiment will undergo STR profiling to confirm its identity and will be sent for mycoplasma testing to ensure there is no contamination. All of the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/jpeqg/) and made publically available.

Power calculations
For additional details on power calculations, please see analysis scripts and associated files on the Open Science Framework: Note; values are from data shared by authors, which was reported in Figure 3E. . Two-tailed t test, difference between two independent means, alpha error = 0.050
Group 1 Group 2 Effect size d A priori power Group 1 sample size Group 2 sample size WT R243H 6.40954 87.2% 1,2 2 1 2 1 1 3 samples per group will be used making the achieved power of 99.9%.
2 The calculation was also performed with the non-parametric Wilcoxon-Mann-Whitney test, which gives an achieved power of 99.9% with a sample size of 3 per group.

Protocol 4:
. Not applicable Protocol 5: Summary of original data . Note: values are from data shared by authors, which was reported in Figure 4D:

Power calculations
. Performed with G*Power software, version 3.1.7 (Faul et al., 2007). . ANOVA F test statistic and partial h 2 performed with R software, version 3.1.2 (Team, 2014). 1 3 samples per group will be used making the power 99.9%.
2 The calculation was also performed with the non-parametric Wilcoxon-Mann-Whitney test, which gives an achieved power of 99.9% with a sample size of 3 per group.

Protocol 6
Summary of original data . Note: data estimated from the image reported in Figure 4F. . The original data presented is qualitative (images of Western blots). We used ImageJ version 1.50a (Schneider et al., 2012) to perform densitometric analysis of the presented bands to quantify the original effect size where possible. The data presented in Figure 4F for Input MAP2K4 were unable to be quantified for all bands and were thus excluded from the normalization. Additionally, the WT values provide under-estimates of the actual values since the WT bands were saturated and unable to be quantified. . Based on these ranges of variance, which use a conservative effect size estimate since the original data were unable to be quantified, we will run the experiment four times.