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Registered report: Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs

  1. Mitch Phelps
  2. Chris Coss
  3. Hongyan Wang
  4. Matthew Cook
  5. Reproducibility Project: Cancer Biology Is a corresponding author
  1. The Ohio State University, United States
  2. University of California San Francisco, United States
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Cite as: eLife 2016;5:e12470 doi: 10.7554/eLife.12470

Abstract

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 “Coding-Independent Regulation of the Tumor Suppressor PTEN by Competing Endogenous 'mRNAs' by Tay and colleagues, published in Cell in 2011 (Tay et al., 2011). The experiments to be replicated are those reported in Figures 3C, 3D, 3G, 3H, 5A and 5B, and in Supplemental Figures 3A and B. Tay and colleagues proposed a new regulatory mechanism based on competing endogenous RNAs (ceRNAs), which regulate target genes by competitive binding of shared microRNAs. They test their model by identifying and confirming ceRNAs that target PTEN. In Figure 3A and B, they report that perturbing expression of putative PTEN ceRNAs affects expression of PTEN. This effect is dependent on functional microRNA machinery (Figure 3G and H), and affects the pathway downstream of PTEN itself (Figures 5A and B). 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 by eLife.

https://doi.org/10.7554/eLife.12470.001

Introduction

microRNAs are one of the first identified classes of non-coding RNAs that can modulate the expression of mRNA-coding transcripts by binding to complementary regions in a target gene’s sequence and repressing its expression. Thus, expression levels and availability of these microRNAs can influence gene expression, and there is growing evidence that misregulation of microRNAs is correlated with some forms of cancer (Sen et al., 2014). Naturally occurring microRNA 'sponges' have been shown to be effective in regulating gene expression by altering the levels of their cognate microRNAs (Choi et al., 2007; Karreth and Pandolfi 2013). Poliseno and colleagues proposed that pseudogenes, long non-coding RNAs with strong homology to coding sequences, could act as the modulators of gene expression as microRNA sponges (Poliseno et al., 2010). They demonstrated that the pseudogene PTENP1 could regulate the expression levels of PTEN via their cognate microRNAs miR-19b and miR-20a (Poliseno et al., 2010).

In this study, Tay and colleagues expanded upon the previous work to propose a unifying hypothesis of regulatory networks composed of competing endogenous RNAs (ceRNAs) (Karreth and Pandolfi 2013; Sen et al., 2014; Kartha and Subramanian, 2014). They suggest that protein-coding RNAs, not just non-coding RNAs, can cross-regulate each other based on competition for shared microRNA regulators; ceRNAs can titrate microRNAs from their target genes (Tay et al., 2011). Continuing their focus on the regulation of PTEN, one of the most frequently mutated genes in cancer (Song et al., 2012), Tay and colleagues propose a computational model to identify ceRNAs de novo, termed MuTaME. Using MuTaME, they identified potential ceRNA regulators of PTEN, and validated if these candidate ceRNAs could modulate PTEN expression in a microRNA-dependent manner (Tay et al., 2011).

In Figure 3C, Tay and colleagues examine if silencing ceRNAs targeting PTEN would affect the expression levels of a luciferase construct carrying the 3’UTR of PTEN. They co-transfected DU145 cells with siRNAs against the candidate PTEN ceRNAs along with a luciferase-PTEN 3’UTR construct and measured luciferase activity. After confirming knockdown of each target ceRNA (Supplemental Figure 3A), they reported that the loss of three of their candidate ceRNAs - SERINC1, VAPA and CNOT6L, but not ZNF460 - reduced the luciferase activity of the PTEN 3’UTR construct. This experiment will be replicated in Protocol 1.

In Figure 3D, they demonstrated that only the 3’UTRs of the candidate ceRNAs were required to affect changes in the luciferase activity of the PTEN 3’UTR construct. Ectopic overexpression of the 3’UTRs of the three candidate ceRNAs relieved inhibition of the PTEN 3’UTR, as evidenced by increased luciferase activity as compared to controls. This experiment will be replicated in Protocol 2.

To test if this effect was dependent on microRNAs, Tay and colleagues repeated these experiments in DICER1 mutant HCT116 cells, in which the machinery required for microRNA function is abrogated. Transfection of wild type HCT116 cells with siRNAs targeting the candidate ceRNAs showed a marked reduction in PTEN protein levels, an effect that was not seen in the DICER1 mutant HCT116 cells (Figures 3G and H). Knockdown of the candidate ceRNAs was confirmed by RT-PCR (Supplemental Figure 3B). This experiment will be replicated in Protocol 3.

PTEN negatively regulates the PI3K/AKT pathway (Stambolic et al., 1998), so Tay and colleagues examined if ceRNA modulation affected the phosphorylation of AKT. Loss of CNOT6L and VAPA in DU145 cells elevated pAKT levels after serum stimulation, an effect that was also observed in wild-type HCT116 cells (Figure 5A). However, this effect was abrogated in DICER1 mutant HCT116 cells (Figure 5A). They also examined the effect of ceRNAs on the tumorigenic properties conferred by loss of PTEN. Silencing of the ceRNAs CNOT6L and VAPA increased cell proliferation of DU145 cells and wild-type HCT116 cells, similar to silencing of PTEN directly (Figure 5B). This effect was less pronounced in DICER1 mutant HCT116 cells (Figure 5B). These experiments will be replicated in Protocol 4 and 5.

Two papers published simultaneously provide support for the actions of ceRNA regulatory networks. Karreth and colleagues, from the same lab as Tay and colleagues, demonstrated in vivo evidence for the actions of ceRNA regulation using the sleeping beauty transposase system in a mouse model of melanoma to identify and confirm putative PTEN ceRNAs (Karreth et al., 2011). Karreth and colleagues identified CNOT6L as a putative PTEN ceRNA through the sleeping beauty transposase system, providing further evidence that CNOT6L is indeed involved in PTEN regulation. Karreth and colleagues focused on ZEB2; using siRNA silencing, they reported that the loss of ZEB2 reduced PTEN protein levels, and affected downstream phosphorylation of AKT (Karreth et al., 2011). As seen in Tay and colleagues, these effects were dependent on functional microRNA processing; ZEB2 depletion did not affect PTEN levels in DICER1 mutant HCT116 cells (Karreth et al., 2011). Sumazin and colleagues used a bioinformatics approach to identify post-translational regulation and elucidated over 7,000 genes they proposed acted as miRNA sponges. By comparing the miRNA programs of genes, they could identify genes with common miR programs, indicating the potential for miRNA-mediated crosstalk between those two genes (Sumazin et al., 2011). They tested their findings by exploring the regulation of PTEN, demonstrating that silencing of putative miRNA program-mediated regulators (mPRs) of PTEN decreased PTEN expression, and, conversely, that the perturbation of PTEN levels could inversely affect the expression of its mPRs. These manipulations also affected tumor cell growth rates, indicating potential in vivo effects of changes to mPR regulatory networks (Sumazin et al., 2011). Since the publication of these three papers, numerous other examples of ceRNA regulation have been reported in muscle differentiation (Cesana et al., 2011), human embryonic stem cell renewal (Wang et al., 2013), regulation of sex determination by SRY (Granados-Riveron and Aquino-Jarquin 2014), breast cancer (Yang et al., 2014; Zheng et al., 2015a; 2015b), lymphoma (Karreth et al., 2015) and the regulation of the tumor-related HMGA1 (Esposito et al., 2014).

The Pandolfi group followed up on their 2011 paper by generating a mathematical model to predict optimal conditions for ceRNA activity, based on a molecular titration mechanism whose effects were correlated to the relative levels of the ceRNA and its target (Ala et al., 2013). They then tested their in silico predictions by experimentally exploring the effect of VAPA on PTEN expression. While silencing of VAPA did decrease PTEN expression in all five cell lines tested, they noted that the amount of silencing was correlated with the initial VAPA:PTEN expression ratio (Ala et al., 2013). However, Denzler and colleagues challenge the notion that perturbations in ceRNA expression levels could affect target genes at all (Denzler et al., 2014). Denzler and colleagues and Ala and colleagues both state that ceRNA effects are dependent on the kinetics of binding, which in turn relies upon the ratio of microRNAs to target sites; increasing the number of target sites through expression of ceRNAs is postulated to affect target gene repression. By quantifying the absolute copy number of the well-studied highly abundant miR-122 and its target sites, Denzler and colleagues showed that large, physiologically unlikely changes in ceRNA expression levels would be required to alter the microRNA: target site ratio enough to perturb target gene expression, casting doubt on the ability of these putative ceRNAs to affect changes in target gene expression levels (Broderick and Zamore 2014; Denzler et al., 2014). This view was contradicted by Bosson and colleagues, who identified over 3,000 high affinity target sites they claimed could be affected by ceRNAs due to low endogenous microRNA: target site ratios (Bosson et al., 2014). The activity and impact of potential ceRNA networks is an area of active interest (for review, see de Giorgio et al., 2013).

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: Knock-down of ceRNA network genes results in decreased PTEN-3’UTR luciferase expression

This protocol describes how to silence expression of ceRNA network genes and measure effects on PTEN expression by measuring PTEN 3’UTR luciferase activity, as seen in Figures 3C and Supplementary S3A.

Sampling

  • This experiment will include four biological replicates (Luciferase assay) and four biological replicates (qRT-PCR) for a minimum power of 80%.

    • See Power Calculations section for details.

  • Each experiment consists of DU145 cells co-transfected with a luciferase-PTEN 3’UTR reporter construct and siRNA against PTEN ceRNAs:

    • Cohort 1: siRNA against nontargeting control 2 (siNC)

    • Cohort 2: siGENOME siRNA against SERINC1 (siSER)

    • Cohort 3: siGENOME siRNA against ZNF460 (siZNF)

    • Cohort 4: siGENOME siRNA against VAPA (siVAPA)

    • Cohort 5: siGENOME siRNA against CNOT6L (siCNO)

    • Cohort 6: siGENOME siRNA against PTEN (siPTEN)

    • Cohort 7: siGLO RISC-free siRNA (transfection control)

  • Effects of silencing ceRNAs will be tested with

    • Luciferase assay of PTEN 3’UTR expression (Figure 3C)

    • qRT-PCR to confirm target gene silencing (Supplementary Fig S3A)

    • siGLO fluorescence to confirm transfection efficiency

Materials and reagents

ReagentTypeManufacturerCatalog #Comments
DU145 human prostate cancer cellsCellsATCCHTB-81
psiCHECK-2-PTEN 3'UTR plasmidPlasmidAddgeneplasmid #50936Communicated by original authors
siGLO RISC-free siRNA siGLOsiRNADharmaconD-001600-01-05Catalog # communicated by original authors
siGenome siRNA for nontargeting control 2siRNADharmaconD-001210-02-05Catalog # communicated by original authors
siGenome siRNA for SERINC1siRNADharmaconM-010725-00-0005Catalog # communicated
by original authors
siGenome siRNA for ZNF460siRNADharmaconM-032012-01-0005Catalog # communicated
by original authors
siGenome siRNA for VAPAsiRNADharmaconM-021382-01-0005Catalog # communicated
by original authors
siGenome siRNA for CNOT6LsiRNADharmaconM-016411-01-0005Catalog # communicated
by original authors
siGenome siRNA for PTENsiRNADharmaconM-003023-02-0005Catalog # communicated
by original authors
Dulbecco's Modified Eagle's
Medium (DMEM)
Cell Culture ReagentInvitrogen10313-039Catalog # communicated
by original authors
Fetal Bovine Serum (FBS)Cell Culture ReagentInvitrogen10438-026Catalog # communicated
by original authors
Penicillin/StreptomycinCell Culture ReagentLife Technologies15140-163Communicated by original authors
GlutamineCell Culture ReagentLife Technologies25030-081Communicated by original authors
Lipofectamine 2000Transfection ReagentLife Technologies11668500Communicated by original authors
TrypsinTransfection ReagentLife Technologies15400-054Communicated by original authors
Dual Luciferase Reporter AssayLuciferase AssayPromegaE1960Catalog # communicated
by original authors
Lysis Buffer (included with
Dual-Luciferase Reporter Assay)
BufferPromegaE1960Original not specified
GLOMAX 96 Microplate LuminometerEquipmentPromegaE6501Replaces Promega E8032
(communicated by original authors)
TRIzol reagentqPCR reagentLife Technologies15596026Communicated by original authors
RNeasy kitqPCR reagentQiagen74104Communicated by original authors
High Capacity cDNA Archive kitqPCR reagentLife Technologies4368814Communicated by original authors
TaqMan probe PTENqPCR probesLife TechnologiesHs02621230_s1
TaqMan probe CNOT6LqPCR probesLife TechnologiesHs00375913_m1
TaqMan probe VAPAqPCR probesLife TechnologiesHs00427749_m1
TaqMan probe SERINC1qPCR probesLife TechnologiesHs00380375_m1
TaqMan probe ZNF460qPCR probesLife TechnologiesHs01104252_m1
TaqMan control probe ß-ACTINqPCR probesLife TechnologiesHs00969077_m1Communicated by original authors
TaqMan Fast Advanced Master MixqPCR reagentLife Technologies4444964Communicated by original authors
StepOne Plus Real-Time PCR systemEquipmentApplied BiosystemsReplaces LightCycler 480 System
Nanodrop 2000C SpectrometerEquipmentThermo Scientific

Procedure

Notes:

  • All cells will be sent for mycoplasma testing and STR profiling.

  • DU145 cells are maintained in DMEM supplemented with 10% FBS, #100 U/ml penicillin/100 µg/ml streptomycin, and #2 mM glutamine at 37°C in 5% CO2 in a humidified atmosphere.

  1. Co-transfect DU145 cells with PTEN 3’UTR and siRNAs:

    1. Split DU145 cells into four different cultures.

      1. These will be biological replicates.

    2. Seed cells at 1.2 x 105 cells per well in 12 well dishes for 24.

      1. Seed 13 wells: 6 transfection conditions x 2 wells per condition (for Steps 2 and 3) and 1 transfection condition (siGlo RISC free siRNA transfection control) x 1 well.

    3. Prepare separate transfection mixtures for each biological replicate.

    4. Add 100 ng of psiCHECK-2+PTEN3’UTR and 100 pmol of siRNA QS to 100 µl of Opti-MEM.

      1. Transfect a pair of wells with each of the following:

        1. siSERINC1

        2. siZNF460

        3. siVAPA

        4. siCNOT6L

        5. siPTEN

        6. non-targeting control (NC)

      2. Transfect a single well with the following:

        1. siGLO control siRNA

    5. In a separate tube mix 2 µl of Lipofectamine 2000 with 100 µl of Opti-MEM.

      1. Scale the volume according to number of replicates.

      2. Incubate for 10 min.

    6. Combine the plasmid/siRNA and Lipofectamine mixes with gentle mixing and incubate for an additional 20min.

    7. Aliquot 200 µl of the plasmid/siRNA and Lipofectamine transfection mix into appropriate well.

      1. Mix gently and incubate at 37˚C.

      2. Replace growth medium after 4.

      3. After 24-48, count the number of fluorescent cells transfected with siGLO relative to total to confirm >90% transfection efficiency.

        1. If transfection is less than 90%, record efficiency, exclude replicate and omit it from the rest of the procedure. Repeat procedure until >90% efficiency is obtained.

        2. If modification to transfection is needed, record and maintain modified steps for remaining replicates.

    8. Incubate for 72 at 37˚C in 5% CO2 in a humidified atmosphere

  2. Use one well for each transfection to measure luciferase activity:

    1. Wash cells with ice-cold PBS, aspirate and add 100 µl of 1X lysis buffer.

    2. Place on an orbital shaker for 10min to dissociate the cell layer.

    3. Pipette gently to mix and transfer 20 µl of each lysate into one well of a white-walled 96 well plate.

    4. Measure firefly and Renilla luciferase activities with the dual-luciferase reporter system with a luminometer according to the manufacturer’s instructions.

  3. Using the other well for each transfection, confirm siRNA target knock-down with qRT-PCR:

    1. Extract total RNA using TRIzol reagent according to manufacturer’s instructions.

    2. Purify samples with RNeasy kit according to manufacturer’s instructions.

    3. Quality check RNA by measuring A260/280 and A260/230 absorbance ratios.

    4. Total RNA can be frozen here until all biological replicates are performed after which the remaining steps will be conducted at one time.

    5. Reverse transcribe 1 µg total RNA using High Capacity cDNA Archive kit according to manufacturer’s instructions.

    6. Perform qRT-PCR to confirm mRNA expression knockdown. Measure mRNA expression for each siRNA transfection sample with its appropriate target and ß-ACTIN, and test each probe separately using RNA from the NC transfection.

      • PTEN

      • CNOT6L

      • VAPA

      • ZNF460

      • SERINC1

      • β-ACTIN [endogenous control communicated by original author]

        • Prepare 10 µl real-time PCR reaction in triplicate for each reaction consisting of:

      • 5 µl TaqMan mastermix

      • 0.5 µl TaqMan probe for the gene of interest

      • 4.5 µl cDNA (diluted 10x)

      • Use standard TaqMan cycling protocol:

        1. 50˚C 2 min

        2. 95˚C 20 s

        3. 40 cycles of 95˚C 1 s, 60˚C 20 s

    7. Normalize each mRNA expression to ß-ACTIN and then normalize each siRNA to siNC for that transcript.

  4. Repeat steps 1-3, 3 additional times

Deliverables

  • Data to be collected:

    • QC image data confirming transfection efficiency by measuring the number of fluorescent cells transfected with siGLO

    • Raw data of Renilla and firefly luciferase measures and a graph of luciferase activity for each cohort

    • QC data for total RNA (A260/280 and A260/230 absorbance ratios)qRT-PCR data to confirm silencing: raw qPCR data and for each sample and a graph of each target gene normalized with β-ACTIN and normalized relative to NC expression

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 quantile-quantile plot to assess the normality of the data. We will also perform Levene’s test to assess homoscedasticity. If the data appear skewed, we will perform the appropriate transformation to proceed with the proposed statistical analysis. If this is not possible, we will perform the equivalent non-parametric Wilcoxon-Mann-Whitney test.

    • Luciferase assay: One-way ANOVA of luciferase activity in DU145 cells transfected with siRNA against NC, SERINC1, ZNF460, VAPA, CNOT6L, or PTEN, with the following Bonferroni-corrected comparisons:

      • Non-coding siRNA vs. each of the ceRNA transfected cells (5 comparisons total).

    • qRT-PCR: Bonferroni corrected one-sample t-tests of normalized mRNA expression in DU145 cells transfected with siRNA against SERINC1, ZNF460, VAPA, CNOT6L, or PTEN compared to a constant (siNC = 1) (5 comparisons total).

  • 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

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

Extracted RNA integrity will be reported with A260/280 and A260/230 absorbance ratios, and transfection efficiency will be checked using the siGLO control. qRT-PCR will be performed to confirm the silencing of ceRNA expression. The cells will be sent for mycoplasma testing confirming lack of contamination and STR profiling confirming cell line authenticity. Transfection efficiency will be recorded for each replicate and any transfection that does not contain >90% efficiency will be excluded and not continue through the rest of the procedure. Any modifications to the transfection protocol will be recorded, and the procedure will be maintained for the remaining replicates. All data obtained from the experiment - raw data, data analysis, control data and quality control data - will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/oblj1/).

Protocol 2: Overexpression of PTEN ceRNA 3’UTRs network genes results in upregulation of PTEN3’UTR luciferase activity

This protocol describes how to measure the effect of ectopic overexpression of PTEN ceRNA 3’UTRs in DU145 cells on Luc-PTEN 3’UTR levels. This protocol replicates Figures 3D.

Sampling

  • This experiment will include six biological replicates for a minimum power of 88%.

    • See Power calculations for details.

  • Each experiment consists of DU145 cells co-transfected with a luciferase-PTEN 3’UTR reporter construct and:

    • Cohort 1: SERINC1 3’UTR (SER 3’U)

    • Cohort 2: VAPA 3’UTR1 (VAPA 3’U1)

    • Cohort 3: VAPA 3’UTR2 (VAPA 3’U2)

    • Cohort 4: CNOT6L 3’UTR1 (CNO 3’U1)

    • Cohort 5: CNOT6L 3’UTR2 (CNO 3’U2)

    • Cohort 6: PTEN 3’UTR (PTEN 3’U)

    • Cohort 7: Empty vector control

  • Effects of overexpressing ceRNAs will be tested with

    • Luciferase assay of PTEN 3’UTR expression (Figure 3D)

Materials and reagents

ReagentTypeManufacturerCatalog #Comments
DU145 human prostate cancer cellsCellsATCCHTB-81
psiCHECK-2-PTEN 3'UTR plasmidPlasmidAddgeneplasmid #50936Communicated by original authors
psiCHECK-2 empty vectorPlasmidPromegaC8021Catalog # communicated by original authors
Dulbecco's Modified Eagle's
Medium (DMEM)
Cell Culture ReagentInvitrogen10313-039Catalog # communicated by original authors
Fetal Bovine Serum (FBS)Cell Culture ReagentInvitrogen10438-026Catalog # communicated by original authors
Penicillin/StreptomycinCell Culture ReagentLife Technologies15140-163Communicated by original authors
GlutamineCell Culture ReagentLife Technologies25030-081Communicated by original authors
Lipofectamine 2000Transfection ReagentLife Technologies11668500Communicated by original authors
SERINC1 3’UTR vectorPlasmidProvided by original authors
VAPA 3’UTR1 vectorPlasmidProvided by original authors
VAPA 3’UTR2 vectorPlasmidProvided by original authors
CNOT6L 3’UTR1 vectorPlasmidProvided by original authors
CNOT6L 3’UTR2 vectorPlasmidProvided by original authors
PTEN 3’UTR vectorPlasmidProvided by original authors
TrypsinTransfection ReagentLife Technologies15400-054Communicated by original authors
Dual Luciferase Reporter AssayLuciferase AssayPromegaE1960Catalog # communicated by original authors
LuminometerEquipmentPromegaE8032Catalog # communicated by original authors

Procedure

Notes:

  • All cells will be sent for mycoplasma testing and STR profiling.

  • DU145 cells are maintained in DMEM supplemented with 10% FBS, #100 U/ml penicillin/100 μg/ml streptomycin, and #2 mM glutamine at 37˚C in 5% CO2 in a humidified atmosphere.

  1. Transfect DU145 cells with PTEN 3’UTR and ceRNA 3’UTRs:

    1. Separate DU145 cells into 6 different cultures.

      1. These will be biological replicates.

    2. Seed cells at 1.2 x 105 cells per well in 12 well dishes and incubate for 24 hr.

      1. Seed 1 well per biological replicate: 7 transfections x 6 replicates.

        1. 42 wells total seeded.

    3. Prepare the transfection mix by adding 100 ng of psiCHECK-2+PTEN3’UTR and 1 µg of 3’UTR plasmid to 100 µl of Opti-MEM.

      1. Transfect one well per replicate with each of the following:

        1. SER 3’U

        2. VAPA 3’U1

        3. VAPA 3’U2

        4. CNO 3’U1

        5. CNO 3’U2

        6. PTEN 3’U

        7. empty vector control

    4. In a separate tube, mix 2 µl of Lipofectamine 2000 with 100 µl of Opti-MEM.

      1. Scale the volume of reagents accordingly.

      2. Incubate for 10 min.

    5. Combine the plasmid and Lipofectamine mixes and incubate for an additional 20 min.

    6. Aliquot 200 µl of the plasmid and Lipofectamine transfection mix into each well. Mix gently and incubate at 37˚C in 5% CO2 in a humidified atmosphere.

      1. Replace growth medium after 4 hr.

    7. Incubate for 72 hr.

  2. Measure renilla and firefly luciferase activity as outlined in Protocol 1 Step 2.

Deliverables

  • Data to be collected:

    • Raw data of Renilla and firefly luciferase measures and a graph of luciferase activity for each cohort.

Confirmatory analysis plan

  • Statistical Analysis of the Replication Data:Note: At the time of analysis, we will test for normality and homoscedasticity of the data. If the data appears skewed, we will perform the appropriate transformation to proceed with the proposed statistical analysis. If this is not possible, we will perform the equivalent non-parametric Wilcoxon-Mann-Whitney test.

    • One-way ANOVA of luciferase activity in DU145 cells expressing 3’UTRs SER, VAPA 3’U1, VAPA 3’U2, CNO 3’U1, CNO 3’U2, PTEN, or empty vector control with the following Bonferroni-corrected planned comparisons:

      • Luciferase activity in each 3’UTR transfection vs. the empty vector control (6 comparisons total).

  • 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

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 cells will be sent for mycoplasma testing confirming lack of contamination and STR profiling confirming cell line authenticity. All data obtained from the experiment - raw data, data analysis, control data and quality control data - will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/oblj1/).

Protocol 3: Knock-down of ceRNA network genes results in decreased PTEN protein that is dependent on microRNA functioning

This protocol describes how to test the effects of siRNA-mediated depletion of SERINC1, VAPA, or CNOT6L expression on PTEN protein expression in wild-type HCT116 colon cancer cells. It also tests whether these effects are dependent on mature microRNA using Dicer mutant (DICEREx5) HCT116 cells. It replicates Figures 3G,H, and Supplementary Figure 3B.

Sampling

  • The experiment will be repeated four times (Western blot) and three times (qRT-PCR) for a minimum power of 80%.

    • See Power Calculations section for details.

  • Each experiment consists of HCT116 WT and HCT116 DICEREx5 cells transfected with siRNA against PTEN ceRNAs:

    • Cohort 1: siRNA against nontargeting control 2 (siNC)

    • Cohort 2: siGENOME siRNA against SERINC1 (siSER)

    • Cohort 3: siGENOME siRNA against VAPA (siVAPA)

    • Cohort 4: siGENOME siRNA against CNOT6L (siCNO)

    • Cohort 5: siGENOME siRNA against PTEN (siPTEN)

    • Cohort 6: siGLO RISC-free siRNA (siGLO)

  • Effects of silencing ceRNAs will be tested with

    • Western Blot for PTEN protein (Figure 3G & 3H)

    • qRT-PCR to confirm target genes were silenced (Supplementary Figure 3B)

    • siGLO fluorescence cell counts to confirm transfection efficiency

Materials and reagents

ReagentTypeManufacturerCatalog #Comments
HCT116 WT and DICEREx5 cellsCellsHorizon DiscoveryHD R02-019
siGLO RISC-free siRNA siGLOsiRNADharmaconD-001600-01-05
siGenome siRNA for
nontargeting control 2
siRNADharmaconD-001210-02-05Catalog # communicated
by original authors
siGenome siRNA for SERINC1siRNADharmaconM-010725-00-0005Catalog # communicated
by original authors
siGenome siRNA for VAPAsiRNADharmaconM-021382-01-0005Catalog # communicated
by original authors
siGenome siRNA for CNOT6LsiRNADharmaconM-016411-01-0005Catalog # communicated
by original authors
siGenome siRNA for PTENsiRNADharmaconM-003023-02-0005Catalog # communicated
by original authors
Dulbecco's Modified Eagle's Medium (DMEM)Cell Culture ReagentInvitrogen10313-039Catalog # communicated
by original authors
Fetal Bovine Serum (FBS)Cell Culture ReagentInvitrogen10438-026Catalog # communicated
by original authors
Penicillin/StreptomycinCell Culture ReagentLife Technologies15140-163Communicated by
original authors
GlutamineCell Culture ReagentLife Technologies25030-081Communicated by
original authors
TrypsinTransfection ReagentLife Technologies15400-054Communicated by
original authors
Dharmafect 1Transfection ReagentThermo Fisher ScientificT200104Communicated by
original authors
TRIzol reagentqPCR reagentLife Technologies15596026Communicated by
original authors
RNeasy kitqPCR reagentQiagen74104Communicated by
original authors
High Capacity cDNA Archive kitqPCR reagentLife Technologies4368814Communicated by
original authors
TaqMan probe PTENqPCR probesLife TechnologiesHs02621230_s1
TaqMan probe CNOT6LqPCR probesLife TechnologiesHs00375913_m1
TaqMan probe VAPAqPCR probesLife TechnologiesHs00427749_m1
TaqMan probe SERINC1qPCR probesLife TechnologiesHs00380375_m1
TaqMan control probe ß-ACTINqPCR probesLife TechnologiesHs00969077_m1Communicated by
original authors
TaqMan Fast Advanced Master MixqPCR reagentLife Technologies4444964Communicated by
original authors
StepOne Plus Real-Time PCR systemEquipmentApplied BiosystemsReplaces LightCycler 480 System
Nanodrop 2000c SpectrometerEquipmentThermo Scientific
PBSWestern ReagentLife Technologies14190250Communicated by
original authors
Lysis BufferWestern ReagentRIPA lysis buffer: 50mM Tris-HCl pH 7.4, 150mM NaCl, 1% NP-40, 0.5%
sodium deoxycholate, 0.1% SDS, 5mM EDTA supplemented with protease inhibitors
Protease inhibitorsWestern ReagentRoche Diagnostics11873580001Communicated by
original authors
Bradford AssayWestern ReagentBio-RadCatalog # communicated
by original authors
Bis-Tris acrylamide NuPAGE gels 4–15% Mini-PROTEAN TGX Precast Protein GelsWestern ReagentBiorad456–1084Replaces NuPage gels from Life Technologies (communicated by original authors)
Tris-Glycine SDS PAGE buffer (10x)Western ReagentNational DiagosticEC-870-4LReplaces MOPS buffer from Invitrogen
Nitrocellulose membranesWestern ReagentThermo Fisher Scientific45004006Catalog # communicated
by original authors
10xTBS bufferWestern ReagentBiorad170–6435Replaces NuPage buffer from Invitrogen
MethanolReagentPharmco339000ACSCSGLCommunicated by
original authors
Mouse anti-HSP90 monoclonal
antibody (90kDa)
AntibodyBecton Dickinson61041Catalog # communicated
by original authors
Rabbit anti-PTEN monoclonal
antibody (54kDa)
AntibodyCell Signaling9559Catalog # communicated
by original authors
Anti-mouse HRP-conjugated
secondary antibody
AntibodyAbcamAb6728Original not specified
Amersham ECL Western
Blotting Detection Kit
Western Blot ReagentAmershamRPN 2108Replaces ECL from Applied Biological Materials
X-ray Film (Hyblot CL, 8x10 inch)Western Blot ReagentDenvilleE3018Original not specified
SpectrophotometerEquipmentBeckman CoulterSpectra max M2Replaces Beckman Model DU-800 (communicated by original authors)

Procedure

Notes

  • All cells will be sent for mycoplasma testing and STR profiling.

  • HCT116 cells (wild-type and mutant) are maintained in DMEM with 10% FBS, #100 U/ml penicillin/100 µg/ml streptomycin, and #2 mM glutamine at 37°C/5% CO2 in a humidified atmosphere.

  1. Transfect HCT116 cells with siRNAs:

    1. Separate HCT116 WT and DICER Ex5 cells into four different cultures each.

      1. These will be biological replicates.

    2. For each cell type (WT and DICER Ex5) seed cells at 1.3 x 105 cells per well in 12 well dishes

      1. Seed 11 wells per replicate: 5 transfections x 2 wells each (one for Step 2, one for Step 3) and 1 transfection (siGlo) x 1 well.

      2. Note: During the last replicate, only seed 6 wells per cell type (5 transfection conditions for Step 2) and 1 transfection condition for siGlo RISC free siRNA transfection control.

    3. Transfect cells with 100 nM siRNA (or siGLO controls) using Dharmafect 1 according to manufacturer’s instructions.

      1. Note: make up a separate transfection mixture for each replicate.

      2. Transfect a pair of wells per replicate with each of the following:

        1. siNC

        2. siSER

        3. siVAPA

        4. siCNO

        5. siPTEN

      3. Transfect a single well per replicate with the following:

        1. siGLO

      4. After 24-48 hr, assess number of fluorescent cells transfected with siGLO to confirm >90% transfection efficiency.

        1. If transfection is less than 90%, record efficiency, exclude replicate and omit it from the rest of the procedure. Repeat procedure until >90% efficiency is obtained.

        2. If modification to transfection is needed, record and maintain modified steps for remaining replicates.

    4. Incubate for 72 hr at 37˚C in 5% CO2 in a humidified atmosphere.

      1. Replace growth medium after 4 hr.

  2. Using one of each pair of wells (except during replicate 4), confirm siRNA knock down with qRT-PCR as in Protocol 1 Step 3. Measure mRNA expression for each siRNA transfection sample with its appropriate target and ß-ACTIN, and test each probe separately using RNA from the NC control transfection.

    • PTEN

    • CNOT6L

    • VAPA

    • SERINC1

    • β-ACTIN [endogenous control communicated by original author]

      1. Prepare 10 µl real-time PCR reaction in triplicate for each reaction consisting of:

        1. 5 µl TaqMan mastermix

        2. 0.5 µl TaqMan probe for the gene of interest

        3. 4.5 µl cDNA (diluted 10x)

        4. Use standard TaqMan cycling protocol:

          1. 50˚C 2 min

          2. 95˚C 20 s

          3. 40 cycles of 95˚C 1 s, 60˚C 20 s

      2. Normalize each mRNA expression to ß-ACTIN and then normalize each siRNA to siNC for that transcript.

  3. Using the second well of each pair of wells, assess PTEN protein expression by Western Blot:

    1. Wash cells in chilled PBS

    2. Lyse cells directly in wells by incubating on ice for 20 min with RIPA lysis buffer containing protease inhibitors.

    3. Clear lysates by centrifugation at 4°C for 15 min at 12,100xg.

    4. Determine protein concentrations with Bradford assay following manufacturer’s instructions.

    5. Separate 5 µg of total protein by SDS-PAGE on 4–15% 4-15% Mini-PROTEAN TGX precast protein gels in Tris-Glycine SDS PAGE buffer.

      1. HCT116 cells express high levels of PTEN protein so 5 µg should be sufficient for detection.

    6. Transfer to nitrocellulose membranes in transfer buffer containing 10% methanol for 1 hr at 40V at room temperature.

      1. *Confirm protein transfer by Ponceau staining.

    7. Block membrane with 5% milk in #TBST for 30 min.

    8. Probe membranes specific primary antibodies:

      1. PTEN: 1:1000

      2. HSP90: 1:1000

    9. Wash membrane 3 times in 1X TBST for 5 min each on shaker.

    10. Incubate with #anti-rabbit (with PTEN primary) or #anti-mouse (for HSP90 primary) HRP conjugated secondary antibody (1:2000) for 1 hr on shaker at room temperature.

    11. Remove membrane from secondary antibody and wash three times in 1X TBST for 5 min each.

    12. Prepare ECL solution and incubate membrane.

    13. Expose membrane to X-ray film, develop and scan. Take a range of exposures (1 s, 15 s, 60 s) for each film.

      1. Note from the original author: Care should be taken not to overload the gel or to overexpose the film. ceRNA regulation may only result in a 50% increase or decrease in protein levels, this difference may be overlooked if the signal is saturated and not within the dynamic range of the film.

    14. Normalize PTEN to HSP90 for each sample.

  4. Repeat 3 additional times.

Deliverables

  • Data to be collected:

    • QC image data confirming transfection efficiency by measuring the number of fluorescent cells transfected with siGLO

    • QC data for total RNA (A260/280 and A260/230 absorbance ratios)

    • Raw qPCR data for each sample and a graph the mean of each target gene normalized with β-ACTIN and normalized relative to NC control. (Compare to Supplementary Figure 3B)

    • Full scans of each western blot with ladder (Compare to Figure 3G)

    • Raw data of band analysis and normalized bands for each sample (Compare to Figure 3H)

Confirmatory analysis plan

  • Statistical Analysis of the Replication Data:Note: At the time of analysis, we will test for normality and homoscedasticity of the data. If the data appears skewed, we will perform the appropriate transformation to proceed with the proposed statistical analysis. If this is not possible, we will perform the equivalent non-parametric Wilcoxon-Mann-Whitney test.

    • Western blot: Two-way ANOVA of normalized PTEN levels from HCT116 cells (wild type or DICEREx5 cells) transfected with siRNA for SERINC1, VAPA, CNOT6L, PTEN, or control NC followed by Bonferroni-corrected planned comparisons:

      • siNC vs. each siRNA for each cell line (8 comparisons total).

    • qRT-PCR: Bonferroni corrected one-sample t-tests of normalized mRNA expression in HCT116 cells (wild type or DICEREx5 cells) transfected with siRNA against SERINC1, VAPA, CNOT6L, or PTEN compared to a constant (siNC=1) (8 comparisons total).

  • 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

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

Extracted RNA integrity will be reported with A260/280 and A260/230 absorbance ratios, and transfection efficiency will be checked using the siGLO control. The cells will be sent for mycoplasma testing confirming lack of contamination and STR profiling confirming cell line authenticity. Transfection efficiency will be recorded for each replicate and any transfection that does not contain >90% efficiency will be excluded and not continue through the rest of the procedure. If the efficiency does not reach >90%, then any modifications to the transfection protocol will be recorded. qRT-PCR will be performed to confirm silencing of mRNA expression. Images of Ponceau staining to confirm protein transfer. All data obtained from the experiment - raw data, data analysis, control data, and quality control data - will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/oblj1/).

Protocol 4: Effect of knock-down of ceRNA network genes on cell proliferation

This experiment tests the effects of siRNA-mediated depletion of PTEN, CNOT6L, and VAPA expression on cell proliferation in DU145, HCT116 WT, and HCT116 DICEREx5 cells. It replicates Figure 5B.

Sampling

  • This experiment will be repeated five (DU145 cells) times and four (HCT116 cells) times for a minimum power of 80%.

    • See Power Calculations section for details.

  • Each experiment consists of DU145, HCT116 WT, and HCT116 DICEREx5 cells transfected with siRNA against PTEN ceRNAs:

    • Cohort 1: siGLO RISC-free siRNA (siGLO)

    • Cohort 2: siRNA against nontargeting control 2 (siNC)

    • Cohort 3: siGENOME siRNA against VAPA (siVAPA)

    • Cohort 4: siGENOME siRNA against CNOT6L (siCNO)

    • Cohort 5: siGENOME siRNA against PTEN (siPTEN)

  • Effects of silencing ceRNAs will be tested with

    • qRT-PCR to confirm target genes were silenced [additional QC]

    • siGLO fluorescence cell counts to confirm transfection efficiency

    • Assessment of cell proliferation (Figure 5B)

Materials and reagents

ReagentTypeManufacturerCatalog #Comments
DU145 human prostate cancer cellsCellsATCCHTB-81
HCT116 WT and DICEREx5 cellsCellsHorizon DiscoveryHD R02-019
siGLO RISC-free siRNA siGLOsiRNADharmaconD-001600-01-05
siGenome siRNA for
nontargeting control 2
siRNADharmaconD-001210-02-05Catalog # communicated
by original authors
siGenome siRNA for VAPAsiRNADharmaconM-021382-01-0005Catalog # communicated
by original authors
siGenome siRNA for CNOT6LsiRNADharmaconM-016411-01-0005Catalog # communicated
by original authors
siGenome siRNA for PTENsiRNADharmaconM-003023-02-0005Catalog # communicated
by original authors
Dulbecco's Modified Eagle's
Medium (DMEM)
Cell Culture ReagentInvitrogen10313-039Catalog # communicated
by original authors
Fetal Bovine Serum (FBS)Cell Culture ReagentInvitrogen10438-026Catalog # communicated
by original authors
Penicillin/StreptomycinCell Culture ReagentLife Technologies15140-163Communicated by
original authors
GlutamineCell Culture ReagentLife Technologies25030-081Communicated by
original authors
TrypsinTransfection ReagentLife Technologies15400-054Communicated by
original authors
Dharmafect 1Transfection ReagentThermo Fisher ScientificT200104Communicated by
original authors
TRIzol reagentqPCR reagentLife Technologies15596026Communicated by
original authors
RNeasy kitqPCR reagentQiagen74104Communicated by
original authors
High Capacity cDNA Archive kitqPCR reagentLife Technologies4368814Communicated by
original authors
TaqMan probe PTENqPCR probesLife TechnologiesHs02621230_s1
TaqMan probe CNOT6LqPCR probesLife TechnologiesHs00375913_m1
TaqMan probe VAPAqPCR probesLife TechnologiesHs00427749_m1
TaqMan control probe ß-ACTINqPCR probesLife TechnologiesHs00969077_m1Additional control
TaqMan Fast Advanced Master MixqPCR reagentLife Technologies4444964Communicated by original authors
StepOne Plus Real-Time PCR systemEquipmentApplied BiosystemsReplaces LightCycler 480 System
Nanodrop 2000C SpectrometerEquipmentThermo Scientific
PBSWestern ReagentLife Technologies14190250Communicated by
original authors
FormalinFixativeSigma AldrichHT501128-4lCommunicated by
original authors
Crystal VioletStainSigma AldrichC-3886Communicated by
original authors
10% acetic acidSolubilization reagentThermo Fisher ScientificA38212Communicated by
original authors
BioTek Synergy HT
Multi-mode Microplate Reader
EquipmentBioTek InstrumentReplaces Beckman Coulter Model DU-800 (communicated by original authors)

Procedure

Notes:

  • HCT116 cells (wild-type and mutant) are maintained in DMEM with 10% FBS, #100 U/ml penicillin/100 µg/ml streptomycin, and #2 mM glutamine at 37°C/5% CO2 in a humidified atmosphere.

  • DU145 cells are maintained in DMEM supplemented with 10% FBS, #100 U/ml penicillin/100 µg/ml streptomycin, and #2 mM glutamine at 37˚C in 5% CO2 in a humidified atmosphere.

  • All cells will be sent for mycoplasma testing and STR profiling.

  1. Transfect DU145, HCT116 WT, and HCT116 DICEREx5 cells with siRNAs

    1. Separate DU145 into five cultures each, and HCT116 WT, and HCT116 DICEREx5 cells each into 4 different cultures.

      1. These will be biological replicates for each cell line.

    2. Seed cells 1.3 x 105 cells per well of a 12-well plate for subsequent experiments:

      1. For measuring transfection efficiency (Step 1c ii):

        1. Seed 1 well (Cohort 1) per replicate per cell line.

          1. 5 wells for DU145 cells

          2. 4 wells for HCT116 WT cells

          3. 4 wells for HCT116 DicerEx5 cells

      2. For cell proliferation assay (Step 2).

        1. Seed 4 wells (Cohorts 2-5) per replicate per cell line.

          1. 20 wells for DU145 cells

          2. 16 wells for HCT116 WT cells

          3. 16 wells for HCT116 DicerEx5 cells

      3. For qPCR confirmation of siRNA knockdown (Step 3).

        1. Seed 4 wells (Cohorts 2-5) per replicate per cell line.

          1. 20 wells for DU145 cells

          2. 16 wells for HCT116 WT cells

          3. 16 wells for HCT116 DicerEx5 cells

    3. Transfect wells with 100 nM of appropriate siRNA using Dharmafect1 according to manufacturer’s instructions.

      1. Note: make up a separate transfection mix for each biological replicate.

      2. Incubate wells for measuring transfection efficiency for 24-48 hr, then assess number of fluorescent cells transfected with siGLO to confirm >90% transfection efficiency.

        1. If transfection is less than 90%, record efficiency for attempt, exclude attempt and do not continue with the rest of the procedure. Repeat procedure until >90% efficiency is obtained.

        2. If modification to transfection is needed during first attempt(s), record and maintain modified steps for remaining replicates.

      3. Incubate wells for seeding the cell proliferation assay for 8 hr, then proceed to Step 2.

      4. Incubate wells for qPCR for 72 hr, then proceed to Step 3.

  2. Measure cell proliferation

    1. Eight hours after transfection, trypsinize and resuspend cells. Split each well into 1 well each of four 12-well plates, seeding 20,000 cells/well. Incubate overnight.

      1. Two 12-well plates (a set) will provide sufficient wells to accommodate all replicates for one day of the time course per cell line.

      2. 8 plates will be needed per cell line for a full 4 day time course.

    2. Starting on the following day (d0), fix one set of plates per cell line per day.

      1. Wash cells with PBS.

      2. Fix cells in 10% formalin solution for 10 min at room temperature.

      3. Store cells in PBS at 4°C until all plates are fixed.

        1. Plates should be collected on day 0, 1, 2 and 3.

    3. c. On day 3, stain all wells of all plates with crystal violet.

      1. Add 1 ml 0.1% Crystal Violet solution in 20% methanol.

      2. Shake gently for 15 min at room temperature.

      3. Wash 2 times in distilled water and let plates dry completely.

      4. Solubilize remaining crystal violet by adding 1 ml of 10% acetic acid to each well.

      5. Shake gently for 15 min at room temperature.

      6. Transfer 100 µl to a 96-well plate and measure OD at 595 nm in a plate reader.

  3. Confirm siRNA knock down with qPCR as in Protocol 1 Step 3. Perform qRT-PCR to measure mRNA expression for each siRNA transfection sample with its appropriate target and ß-ACTIN, and test each probe separately using RNA from the NC control transfection.

    • PTEN

    • CNOT6L

    • VAPA

    • ß-ACTIN [endogenous control communicated by original author]

      1. Prepare 10 µl real-time PCR reaction in triplicate for each reaction consisting of:

        1. 5 µl TaqMan mastermix

        2. 0.5 µl TaqMan probe for the gene of interest

        3. 4.5 µl cDNA (diluted 10x)

        4. Use standard TaqMan cycling protocol:

          1. 50˚C 2 min

          2. 95˚C 20 s

          3. 40 cycles of 95˚C 1 s, 60˚C 20 s

Deliverables

  • Data to be collected:

    • QC image data confirming transfection efficiency by measuring the number of fluorescent cells transfected with siGLO

    • QC data for total RNA (A260/280 and A260/230 absorbance ratios)

    • Raw qPCR data for each sample and a graph of the mean of each target gene normalized with ß-ACTIN and graphed relative to NC control.

    • Raw numbers for optical density measures of colonies for each sample.

Confirmatory analysis plan

  • Statistical Analysis of the Replication Data:Note: At the time of analysis, we will test for normality and homoscedasticity of the data. 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 Wilcoxon-Mann-Whitney test.

    • Cell proliferation data: One-way ANOVA of AUC values of DU145 cells transfected with siRNA for VAPA, CNOT6L, PTEN, or siNC followed by Bonferroni-corrected planned comparisons:

      • siNC vs each siRNA (3 comparisons total).

    • Cell proliferation data: Two-way ANOVA of AUC values of HCT116WT or HCT116 DICEREx5 cells transfected with siRNA for VAPA, CNOT6L, PTEN, or siNC followed by Bonferroni-corrected planned comparisons:

      • siNC vs. each siRNA, for each cell line (6 comparisons total).

  • 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.

  • Additional exploratory analysis:siRNA knockdown confirmation [additional control]

    • Two-way ANOVA of mRNA expression in HCT116 cells (wild type or DICEREx5 cells) transfected with siRNA against NC, VAPA, CNOT6L, or PTEN, with the following Bonferroni-corrected comparisons:

      • Non-coding siRNA vs. each of the ceRNA transfected cells (3 comparisons total).

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.

Provisions for quality control

Extracted RNA integrity will be reported with A260/280 and A260/230 absorbance ratios, and transfection efficiency will be checked using the siGLO control. Cells will be sent for mycoplasma testing confirming lack of contamination and STR profiling confirming cell line authenticity. Transfection efficiency will be recorded for each replicate and any transfection that does not contain >90% efficiency will be excluded and not continue through the rest of the procedure. Any modifications to the transfection protocol will be recorded and the procedure will be maintained for the remaining replicates. All data obtained from the experiment - raw data, data analysis, control data and quality control data - will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/oblj1/).

Protocol 5: Knock-down of ceRNA network genes results in AKT activation

This experiment tests the effects of siRNA-mediated depletion of PTEN, CNOT6L, and VAPA expression on AKT activation in DU145, HCT116 WT, and HCT116 DicerEx5 cells. It replicates Figure 5A.

Sampling

  • This experiment will be repeated at least 7 times for a minimum power of 80%. The original Western blot data is qualitative, thus to determine an appropriate number of replicates to initially perform, sample sizes based on a range of potential variance was determined.

    • See Power Calculations section for details.

  • Each experiment consists of DU145, HCT116 WT, and HCT116 DICEREx5 cells transfected with siRNA against PTEN ceRNAs:

    • Cohort 1: siGLO RISC-free siRNA (siGLO)

    • Cohort 2: siRNA against nontargeting control 2 (siNC)

    • Cohort 3: siGENOME siRNA against VAPA (siVAPA)

    • Cohort 4: siGENOME siRNA against CNOT6L (siCNO)

    • Cohort 5: siGENOME siRNA against PTEN (siPTEN)

  • Effects of silencing ceRNAs will be tested with

    • qRT-PCR to confirm target genes were silenced [additional QC]

    • siGLO fluorescence cell counts to confirm transfection efficiency

    • Assessment of AKT phosphorylation by Western blot (Figure 5A)

Materials and reagents

ReagentTypeManufacturerCatalog #Comments
DU145 human prostate cancer cellsCellsATCCHTB-81
HCT116 WT and DICEREx5 cellsCellsHorizon DiscoveryHD R02-019
siGLO RISC-free siRNA siGLOsiRNADharmaconD-001600-01-05
siGenome siRNA for
nontargeting control 2
siRNADharmaconD-001210-02-05Catalog # communicated
by original authors
siGenome siRNA for VAPAsiRNADharmaconM-021382-01-0005Catalog # communicated
by original authors
siGenome siRNA for CNOT6LsiRNADharmaconM-016411-01-0005Catalog # communicated
by original authors
siGenome siRNA for PTENsiRNADharmaconM-003023-02-0005Catalog # communicated
by original authors
TaqMan probe PTENqPCR probesLife TechnologiesHs02621230_s1
TaqMan probe CNOT6LqPCR probesLife TechnologiesHs00375913_m1
TaqMan probe VAPAqPCR probesLife TechnologiesHs00427749_m1
TaqMan control probe ß-ACTINqPCR probesLife TechnologiesHs00969077_m1Additional control
TaqMan Fast Advanced Master MixqPCR reagentLife Technologies4444964Communicated by original authors
StepOne Plus Real-Time PCR systemEquipmentApplied BiosystemsReplaces LightCycler 480 System
Nanodrop 2000C SpectrometerEquipmentThermo Scientific
Dulbecco's Modified Eagle's
Medium (DMEM)
Cell Culture ReagentInvitrogen10313-039Catalog # communicated
by original authors
Fetal Bovine Serum (FBS)Cell Culture ReagentInvitrogen10438-026Catalog # communicated
by original authors
Penicillin/StreptomycinCell Culture ReagentLife Technologies15140-163Communicated by
original authors
GlutamineCell Culture ReagentLife Technologies25030-081Communicated by
original authors
TrypsinTransfection ReagentLife Technologies15400-054Communicated by
original authors
Dharmafect 1Transfection ReagentThermo Fisher ScientificT200104Communicated by
original authors
PBSWestern ReagentLife Technologies14190250Communicated by
original authors
Lysis BufferWestern ReagentRIPA lysis buffer: 50mM Tris-HCl pH 7.4, 150mM NaCl, 1% NP-40, 0.5%
sodium deoxycholate, 0.1% SDS, 5mM EDTA supplemented with proteinase inhibitors
Protease inhibitorsWestern ReagentRoche Diagnostics11873580001Communicated by
original authors
Bradford DyeWestern ReagentBio-Rad500-0006Catalog # communicated by
original authors
4–15% Mini-PROTEAN
TGX Precast Protein Gels
Western ReagentBiorad456–1084Replaces NuPage gels from Life Technologies (communicated by original authors)
Tris-Glycine SDS PAGE buffer (10x)Western ReagentNational DiagnosticEC-870-4LReplaces MOPS buffer from Invitrogen
Nitrocellulose membranesWestern ReagentThermo Fisher Scientific45004006Catalog # communicated
by original authors
10xTBS bufferWestern ReagentBiorad170–6435
Replaces NuPage buffer from Invitrogen
MethanolChemicalPharmco339000ACSCSGLCommunicated by
original authors
Rabbit anti-pAKT (Ser473)
polyclonal antibody (60kDa)
AntibodyCell Signaling9271Catalog # communicated
by original authors
Rabbit anti-AKT polyclonal
antibody (60kDa)
AntibodyCell Signaling9272Catalog # communicated
by original authors
Amersham ECL Western
Blotting Detection Kit
Western Blot ReagentAmershamRPN2108Replaces ECL from Applied Biological Materials
SpectrophotometerEquipmentBeckman CoulterSpectra max M2Replaces Beckman Model DU-800 (communicated by original authors)

Procedure

Notes:

  • HCT116 cells (wild-type and mutant) are maintained in DMEM with 10% FBS, #100 U/ml penicillin/100 µg/ml streptomycin, and #2 mM glutamine at 37°C/5% CO2 in a humidified atmosphere.

  • DU145 cells are maintained in DMEM supplemented with 10% FBS, #100 U/ml penicillin/100 µg/ml streptomycin, and #2 mM glutamine at 37˚C in 5% CO2 in a humidified atmosphere.

  • All cells will be sent for mycoplasma testing and STR profiling.

  1. Transfect DU145, HCT116 WT, and HCT116 DICEREx5 cells with siRNAs

    1. Seed cells for subsequent experiments with 1.3 x 105 cells per well in a 12-well plate:

      1. For measuring transfection efficiency (Step 1c ii):

        1. Seed 1 well (Cohort 1) per replicate.

          1. DU145 cells

          2. HCT116 WT cells

          3. HCT116 DicerEx5 cells

      2. For AKT activation and Western blot (Step 2).

        1. Seed 3 well (Cohort 2-5) per replicate.

          1. 12 wells for DU145 cells

          2. 12 wells for HCT116 WT cells

          3. 12 wells for HCT116 DicerEx5 cells

    2. Transfect wells with 100 nM of appropriate siRNA using Dharmafect1 according to manufacturer’s instructions.

      1. Note: make up a separate transfection mix for each biological replicate.

      2. Incubate wells for measuring transfection efficiency for 24-48 hr, then assess number of fluorescent cells transfected with siGLO to confirm >90% transfection efficiency.

        1. If transfection is less than 90%, record efficiency, exclude attempt and do not continue with the rest of the procedure. Repeat procedure until >90% efficiency is obtained.

        2. If modification to transfection is needed, record and maintain modified steps for remaining replicates.

  2. Stimulate activation of AKT then measure levels of phosphorylated AKT by Western blot.

    1. After 72 hr, serum-starve cells overnight: replace media with serum-free media and incubate overnight (approximately 16 hr).

    2. The following morning, harvest one well at 0 min (pre-stimulation), re-stimulate the remaining cells by adding the appropriate volume of warmed 100% FBS to existing media in each trio of matched wells for a 10% final concentration. Incubate wells for 5 or 15 min.

      1. Harvest one well at 5 min and one well at 15 min post FBS addition.

    3. Harvest cells and perform Western blot as specified in Protocol 3 step 3.

      1. Note: load 10 µg of protein per well.

      2. Probe membranes specific primary antibodies

        1. pAKT (Ser473); 1:1000

        2. total AKT; 1:1000

          1. Loading control

      3. Note from original author: Phosphorylated proteins are less stable in lysis buffer than non-phosphorylated proteins. Try to use fresh lysates for subsequent western blotting as far as possible. Transfer samples to the protein loading buffer as fast as possible and keep freeze thaw cycles to an absolute minimum.

    4. Normalize pAKT to total AKT for each sample.

  3. Repeat at least 6 additional times.

Deliverables

  • Data to be collected:

    • QC image data confirming transfection efficiency by measuring the number of fluorescent cells transfected with siGLO

    • QC data for total RNA (A260/280 and A260/230 absorbance ratios)

    • Raw qPCR data for each sample and a graph of the mean of each target gene normalized with ß-ACTIN and graphed relative to NC control.

    • Full scans of all films for each western including ladder.

Confirmatory analysis plan

  • Statistical Analysis of the Replication Data:Note: At the time of analysis, we will test for normality and homoscedasticity of the data. If the data appears skewed, we will perform the appropriate transformation to proceed with the proposed statistical analysis. If this is not possible, we will perform the equivalent non-parametric Wilcoxon-Mann-Whitney test.

    • Two-way ANOVA of normalized pAKT levels of DU145 cells transfected with siRNA for VAPA, CNOT6L, PTEN, or siNC measured at 0 min, 5 min, and 15 min followed by Bonferroni-corrected planned contrasts:

      • siNC vs each siRNA, collapsed across all times (3 contrasts total).

    • Three-way ANOVA (3x4x2) of normalized pAKT levels of HCT116WT or HCT116 DICEREx5 cells transfected with siRNA for VAPA, CNOT6L, PTEN, or siNC measured at 0 min, 5 min, and 15 min:

      • HCT116WT cells with the following Bonferroni-corrected planned contrasts:

        • siNC vs. each siRNA, collapsed across all times (3 contrasts total).

      • HCT116 DICEREx5 cells with the following Bonferroni-corrected planned contrasts:

        • siNC vs. each siRNA, collapsed across all times (3 contrasts total).

  • Meta-analysis of original and replication attempt effect sizes:

    • The replication data (mean and 95% confidence interval) will be plotted with the original reported data value plotted as a single point on the same plot for comparison.

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.

Provisions for quality control

The cells will be sent for mycoplasma testing confirming lack of contamination and STR profiling confirming cell line authenticity. Transfection efficiency will be recorded for each replicate and any transfection that does not contain >90% efficiency will be excluded and not continue through the rest of the procedure. Any modifications to the transfection protocol will be recorded, and the procedure will be maintained for the remaining replicates. Images of Ponceau staining to confirm protein transfer. All data obtained from the experiment - raw data, data analysis, control data, and quality control data - will be made publicly available, either in the published manuscript or as an open access dataset available on the Open Science Framework (https://osf.io/oblj1/).

Power calculations

For additional details on power calculations, please see analysis scripts and associated files on the Open Science Framework:

https://osf.io/c8hb5

Protocol 1

Summary of original luciferase activity data:

  • Note: data provided by original authors for Figure 3C

siRNALuciferase activitySDN
siNC1009.284
siSER70.296.994
siZNF108.629.24
siVAPA47.542.894
siCNO69.823.694
siPTEN20.321.114

Test family

  • 2 tailed t test, Wilcoxon-Mann-Whitney test, Bonferroni’s correction: alpha error = 0.01

Power Calculations performed with G*Power software, version 3.1.7 (Faul et al., 2007).

Group 1Group 2Effect size dA priori powerGroup 1
sample size
Group 2
sample size
siNCsiSER3.6164781.9%44
siNCsiZNF0.932980.2%2302302
siNCsiVAPA7.6330098.5%13131
siNCsiCNO4.2737793.2%44
siNCsiPTEN12.056899.9%13131
  1. 1 4 samples per group will be used making the power >99.9%.

  2. 2 A sensitivity calculation was performed since the original data showed a non-significant effect. The effect size that can be detected with 80% power and a sample size n=4 per group is 3.5378.

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • ANOVA: Fixed effects, omnibus, one-way: alpha error = 0.05

Power calculations

  • Performed with G*Power software, version 3.1.7 (Faul et al., 2007).

  • ANOVA F test statistic and partial ηperformed with R software, version 3.1.2 (R Core Team 2015).

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siRNA silencing groupsF(5,18)=106.00.96725.4302>99.9%121
  1. 1 24 total samples (4 per group) will be used based on the planned comparisons making the power >99.9%.

Test family

  • Two-tailed t test, difference between two independent means, Bonferroni correction: alpha error = 0.01

Power calculations

Group 1Group 2Effect size dA priori powerGroup 1
sample size
Group 2 sample size
siNCsiSER3.6164785.8%44
siNCsiZNF0.932980.8%2292292
siNCsiVAPA7.6330099.4%13131
siNCsiCNO4.2737795.4%44
siNCsiPTEN12.056899.9%13131
  1. 1 4 samples per group will be used making the power >99.9%.

  2. 2 A sensitivity calculation was performed since the original data showed a non-significant effect. The effect size that can be detected with 80% power and a sample size n=4 per group is 3.3711.

Summary of original qPCR gene expression data:

  • Note: data provided by original authors for Figure S3A

  • We estimated SD to be 0.001, when it was reported as zero.

siRNAmRNA expressionSDAssumed N
siSER0.030.0014
siZNF0.350.114
siVAPA0.030.0014
siCNO0.070.014
siPTEN0.10.044

Test family

  • 2 tailed t test, Wilcoxon-Signed Ranks one-sample test, Bonferroni’s correction: alpha error = 0.01

Power Calculations performed with G*Power software, version 3.1.7 (Faul et al., 2007).

GroupEffect size dA priori powerSample size
siSER970.0099.9%3
siZNF5.9197.7%4
siVAPA970.0099.9%3
siCNO93.0099.9%3
siPTEN22.5099.9%3

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • Two-tailed t test, difference from a constant, Bonferroni correction: alpha error = 0.01

Power calculations

GroupEffect size dA priori powersample size
siSER970.0099.9%3
siZNF5.9199.0%4
siVAPA970.0099.9%3
siCNO93.0099.9%3
siPTEN22.5099.9%3

Protocol 2

Summary of original Luciferase data:

  • Note: data provided by original authors for Figure 3D.

siRNALuciferase ActivitySDN
Empty Vector1008.834
SER 3'U127.8611.594
VAPA 3'U1140.8417.84
VAPA 3'U2150.259.374
CNO 3'U1142.919.924
CNO 3'U2145.8810.594
PTEN 3'U153.322.064

Test family

  • 2 tailed t test, Wilcoxon-Mann-Whitney test, Bonferroni’s correction: alpha error = 0.00833

Power Calculations performed with G*Power software, version 3.1.7 (Faul et al., 2007).

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
Empty VectorSER 3'U2.7041185.7%66
Empty VectorVAPA 3'U12.9067591.0%66
Empty VectorVAPA 3'U25.5195581.3%13131
Empty VectorCNO 3'U14.5693594.6%14141
Empty VectorCNO 3'U24.7057495.7%14141
Empty VectorPTEN 3'U8.3164299.0%13131
  1. 1 6 samples per group will be used making the power >99.9%.

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • ANOVA: Fixed effects, omnibus, one-way: alpha error = 0.05

Power calculations

  • Performed with G*Power software, version 3.1.7 (Faul et al., 2007).

  • ANOVA F test statistic and partial η2performed with R software, version 3.1.2 (R Core Team 2015).

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
PTEN ceRNAs 3’UTRsF(6, 21)=11.3470.76435.430299.9%141
  1. 1 42 total samples (6 per group) will be used based on the planned comparisons making the power >99.9%.

Test family

  • Two-tailed t test, difference between two independent means, Bonferroni correction: alpha error = 0.00833

Power calculations

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
Empty VectorSER 3'U2.7041188.5%66
Empty VectorVAPA 3'U12.9067582.4%15151
Empty VectorVAPA 3'U25.5195586.9%23232
Empty VectorCNO 3'U14.5693596.5%24242
Empty VectorCNO 3'U24.7057497.4%24242
Empty VectorPTEN 3'U8.3164299.6%23232
  1. 1 6 samples per group will be used making the power 96.2%.

  2. 2 6 samples per group will be used making the power 99.9%.

Protocol 3

Summary of original Western blot data:

  • Note: data provided by original authors for Figure 3H.

siRNACell typePTEN expressionSDN
siNCWT1008.34
DicerEx51004.84
siSERWT52.68.94
DicerEx51176.54
SiVAPAWT51.76.54
DicerEx5107.59.44
siCNOWT58.74.54
DicerEx51134.44
siPTENWT1.90.24
DicerEx51.30.0014

Test family

  • 2 tailed t test, Wilcoxon-Mann-Whitney test, Bonferroni’s correction: alpha error = 0.00625

Power Calculations performed with G*Power software, version 3.1.7 (Faul et al., 2007).

Group 1Group 2Effect size dA priori powerGroup 1
sample size
Group 2
sample size
WT siNCWT siSER5.5082898.4%44
WT siNCWT siVAPA6.4792887.2%13131
WT siNCWT siCNO6.1862783.9%13131
WT siNCWT siPTEN16.7101399.9%13131
Sensitivity CalculationsDetectable Effect size dA priori powerGroup 1
sample size
Group 2
sample size
Dicer siNCDicer siSER3.89580%44
Dicer siNCDicer siVAPA3.89580%44
Dicer siNCDicer siCNO3.89580%44
Dicer siNCDicer siPTEN3.89580%44
  1. 1 4 samples per group will be used making the power >99%.

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • Two-way ANOVA: Fixed effects, main effects, special and interactions: alpha error = 0.05

Power calculations

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siRNA silencing groups
in WT or DicerEx5 cells
F(4,30)= 54.237
(interaction)
0.878522.689289.9%1141
  1. 1 40 total samples (4 per group) will be used based on the planned comparisons making the power >99.9%.

Test family

  • Two-tailed t test, difference between two independent means, Bonferroni correction: alpha error = 0.00625

Power calculations

Group 1Group 2Effect size dA priori powerGroup 1
sample size
Group 2
sample size
WT siNCWT siSER5.5082881.1%3131
WT siNCWT siVAPA6.4792892.0%3131
WT siNCWT siCNO6.1862789.5%3131
WT siNCWT siPTEN16.7101382.6%12121
Sensitivity CalculationsDetectable Effect size dA priori powerGroup 1
sample size
Group 2
sample size
Dicer siNCDicer siSER3.69780%44
Dicer siNCDicer siVAPA3.69780%44
Dicer siNCDicer siCNO3.69780%44
Dicer siNCDicer siPTEN3.69780%44
  1. 1 4 samples per group will be used making the power >99.9%.

Summary of original mRNA expression data:

  • Note: data provided by original authors for Figure S3B.

siRNACell TypemRNA expressionSDN
siSERWT0.0360.00494
DicerEx50.0280.00074
SiVAPAWT0.0270.00194
DicerEx50.0340.00054
siCNOWT0.1070.0334
DicerEx50.0330.00254
siPTENWT0.0750.02374
DicerEx50.1150.04144

Test family

  • 2 tailed t test, Wilcoxon-Signed Ranks one-sample test, Bonferroni’s correction: alpha error = 0.00625

Power calculations

GroupEffect size dA priori powerGroup 1 sample size
WT siSER196.7599.5%3
WT siVAPA512.0099.5%3
WT siCNO27.0699.5%3
WT siPTEN39.0399.5%3
Dicer siSER1388.5099.5%3
Dicer siVAPA1932.0099.5%3
Dicer siCNO386.8099.5%3
Dicer siPTEN21.3899.5%3

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • Two-tailed t test, difference from a constant (mu=1), Bonferroni correction: alpha error = 0.00625

Power calculations

GroupEffect size dA priori powerGroup 1 sample size
WT siSER196.7599.9%3
WT siVAPA512.0099.9%3
WT siCNO27.0699.9%3
WT siPTEN39.0399.9%3
Dicer siSER1388.5099.9%3
Dicer siVAPA1932.0099.9%3
Dicer siCNO386.8099.9%3
Dicer siPTEN21.3899.9%3

Protocol 4

Summary of original cell proliferation data:

  • Note: data of mean values provided by original authors for Figure 5B.

Cell Proliferation (Optical Density)
Cell TypesiRNADay 0Day 1Day 2Day 3
DU145siNC00.080.370.92
siPTEN00.160.831.96
siCNO00.060.631.66
siVAPA00.120.781.75
HCT116 WTsiNC00.300.911.35
siPTEN00.601.632.07
siCNO00.771.982.19
siVAPA00.661.651.98
HCT116 Dicer Ex5siNC00.120.490.74
siPTEN00.691.721.90
siCNO00.491.091.75
siVAPA00.300.951.34
  • Area under the curve calculation with R software, version 3.1.2 (R Core Team 2015).

Cell TypesiRNAArea under the curveSDN
DU145siNC0.9100.2353
siPTEN1.9700.1403
siCNO1.5200.1413
siVAPA1.7750.0763
HCT116 WTsiNC1.8850.1803
siPTEN3.2650.1563
siCNO3.8450.2903
siVAPA3.3000.2753
HCT116 Dicer Ex5siNC0.9800.0123
siPTEN3.3600.3103
siCNO2.4550.1453
siVAPA1.9200.2853

DU145 cells

Test family

  • 2 tailed, Wilcoxon-Mann-Whitney test, Bonferroni’s correction: alpha error = 0.0167

Power Calculations performed with G*Power software, version 3.1.7 (Faul et al., 2007).

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siNCsiPTEN5.11589.5%33
siNCsiCNO2.94489.4%55
siNCsiVAPA4.17496.3%44

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • One way ANOVA: Fixed effects, special, main effects and interactions, alpha error = 0.05

Power calculations

  • Performed with G*Power software, version 3.1.7 (Faul et al., 2007).

  • ANOVA F test statistic and partial ηperformed with R software, version 3.1.2 (R Core Team 2015).

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
Optical density of DU145 cells
transfected with siRNAs
F(6, 24) =14.260.78101.888482.73%161
  1. 160 total samples (5 per group) will be used based on the planned comparisons making the power >99.99%.

Test family

  • Two-tailed t test, difference between two independent means, Bonferroni correction: alpha error = 0.0167

Power calculations

CellsGroup 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
DU145siNCsiPTEN5.11592.9%13131
siNCsiCNO2.94491.7%55
siNCsiVAPA4.17497.6%14141
  1. 15 samples per group will be used making the power >99%.

HCT116 cells

Test family

  • 2 tailed, Wilcoxon-Mann-Whitney test, Bonferroni’s correction: alpha error = 0.00833

Power Calculations performed with G*Power software, version 3.1.7 (Faul et al., 2007).

CellsGroup 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
HCT116 WTsiNCsiPTEN6.69593.4%33
siNCsiCNO3.85384.1%44
siNCsiVAPA5.46380.5%33
HCT116 Dicer Ex5siNCsiPTEN10.45299.9%33
siNCsiCNO6.47891.8%33
siNCsiVAPA4.12889.1%44

Test family

  • Due to the large variance, the following parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above.

  • Two way ANOVA: Fixed effects, special, main effects and interactions, alpha error = 0.05

Power calculations

  • Performed with G*Power software, version 3.1.7 (Faul et al., 2007).

  • ANOVA F test statistic and partial η2performed with R software, version 3.1.2 (R Core Team 2015).

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
Optical density of
HCT116 WT, and DICEREx5
cells transfected with siRNAs
F(3, 23) =14.080.72531.624981.69%121
  1. 124 total samples (3 per group) will be used based on the planned comparisons making the power >99.99%.

Test family

  • Two-tailed t test, difference between two independent means, Bonferroni correction: alpha error = 0.00833

Power calculations

CellsGroup 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
HCT116 WTsiNCsiPTEN6.69596.3%33
siNCsiCNO3.85387.9%33
siNCsiVAPA5.46386.2%33
Sensitivity CalculationsDetectable Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
HCT116 Dicer Ex5siNCsiPTEN3.49580%44
siNCsiCNO3.49580%44
siNCsiVAPA3.49580%44

Protocol 5

Summary of original AKT Activation data

  • Note: data provided by original authors for Figure 5A.

    • We used the average band intensity for siNC since they were measured twice.

pAkt/Total Akt
Cell TypesiRNA0 min5 min15 min
DU145siNC13.21.95
siPTEN58.16.9
siCNO0.84.13.4
siVAPA2.110.96.6
HCT116 WTsiNC12.352.45
siPTEN6.39.59.5
siCNO1.24.13
siVAPA1.84.43.5
HCT116 Dicer Ex5siNC15.152.25
siPTEN5.314.77.2
siCNO0.74.80.8
siVAPA0.873.1

DU145 cells

Note: The original data does not indicate the error associated with multiple biological replicates. To identify a suitable sample size, power calculations were performed using different levels of relative variance.

Test family

  • 2-Way ANOVA: Fixed effects, special, main effects and interactions, alpha error = 0.05 for DU145 cells

Power calculations

  • Performed with G*Power software, version 3.1.7 (Faul et al., 2007).

  • ANOVA F test statistic and partial η2performed with R software, version 3.1.2 (R Core Team 2015).

GroupsVariance estimateF test statistic F(3,24) (siRNA main effect)Partial η2Effect size fA priori powerTotal sample size
Akt activation in DU145
Cells transfected with
siRNAs after 0, 5, and 15 min
2%4598.790.998323.97399.9%13
15%81.7560.91093.196891.4%14
28%23.4630.74571.712680.4%15
40%11.4970.58971.198887.2%18

Test family

  • ANOVA F test statistic and planned contrasts with Bonferroni correction: alpha error = 0.01667

Power calculations

CellsGroup 1
across time
Group 2
across time
Estimated
variance
Effect size fA priori
power
Samples
per group
DU145siNCsiPTEN2%18.53392.0%2
15%2.471098.6%2
28%1.323882.6%2
40%0.926683.7%2
siNCsiCNO2%2.877085.5%2
15%0.383680.3%7
28%0.205580.0%21
40%0.143880.0%43
siNCsiVAPA2%17.99791.1%2
15%2.40098.1%2
28%1.285580.3%2
40%0.899981.2%2

HCT 116 cells

Note: The original data do not indicate the error associated with multiple biological replicates. To identify a suitable sample size, power calculations were performed using different levels of relative variance.

Test family

  • 3-Way ANOVA: Fixed effects, special, main effects and interactions, alpha error = 0.025 for HCT116WT and HCT116DicerEx5 cells comparing AKT activation over time.

Power calculations

  • Performed with G*Power software, version 3.1.7 (Faul et al., 2007).

  • ANOVA F test statistic and partial η2performed with R software, version 3.1.2 (R Core Team 2015).

    • For a given relative variance, 10,000 simulations were run and the F statistic and partial η2 was calculated for each simulated data set.

GroupsVariance EstimateF test statistic F(3,48) (cell line, siRNA interaction)Partial η2Effect size fA priori powerTotal sample size
Akt activation in HCT116WT
or HCT116DicerEx5 cells
transfected with siRNAs
after 0, 5 and 15 min
2%201.700.91733.331099.3%26
15%4.74100.21620.525180.1%47
28%2.18920.11280.356680.1%91
40%1.66360.08780.310380.4%119

Test family

  • ANOVA F test statistic and planned contrasts with Bonferroni correction: alpha error = 0.01667 for each group of comparisons (cell type).

Power calculations

CellsGroup 1
across time
Group 2
across time
Effect size fA priori
power
Samples
per group
HCT116WTsiNCsiPTEN2%18.32299.9%2
15%2.442999.9%2
28%1.308799.9%2
40%0.916199.9%2
siNCsiCNO2%2.348999.9%2
15%0.313283.8%5
28%0.167881.1%16
40%0.117480.4%32
siNCsiVAPA2%3.664399.9%2
15%0.488694.8%3
28%0.261783.3%7
40%0.183282.9%14
CellsGroup 1
across time
Group 2
across time
Effect size fA priori
power
Samples
per group
HCT116DicerEx5siNCsiPTEN2%17.66499.92
15%2.355299.92
28%1.261799.9%2
40%0.883299.9%2
Sensitivity calculationDetectable effect size fA priori powerSamples per group
siNCsiCNO2%0.497180.0%2
15%0.299980.0%5
28%0.174280.0%16
40%0.117080.0%32
Sensitivity calculationDetectable effect size fA priori powerSamples per group
siNCsiVAPA2%0.497180.0%2
15%0.299980.0%5
28%0.174280.0%16
40%0.117080.0%32

In order to produce quantitative replication data, we will run the experiment seven times. Each time we will quantify band intensity. We will determine the standard deviation of band intensity across the biological replicates and combine this with the reported value from the original study to simulate the original effect size. We will use this simulated effect size to determine the number of replicates necessary to reach a power of at least 80%. We will then perform additional replicates, if required, to ensure that the experiment has more than 80% power to detect the original effect.

References

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Decision letter

  1. Timothy W Nilsen
    Reviewing Editor; Case Western Reserve University, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your work entitled "Registered report: Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs" for consideration by eLife. Your article has been reviewed by four peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Tony Hunter as the Senior Editor. One of the four reviewers, Klaus Rajewsky (Reviewer 4), has agreed to reveal his identity.

Your Registered report has been reviewed by four expert referees. As you will see, all are quite positive about the proposed work. Please address the very minor points raised by the reviewers before uploading your final files but consider the Report to be In Press.

Reviewer #1:

This Registered report describes the proposed replication plan of key experiments from "Coding-Independent Regulation of the Tumor Suppressor PTEN by Competing Endogenous mRNAs" by Tay and colleagues, published in Cell in 2011 (Tay et al., 2011).

For all protocols, the authors propose use ANOVA to analyze the data. Please check for outliers and make sure that the data do not violate the assumptions of the ANOVA: normality and homoscedasticity. If the data do not fit the assumptions well enough, try to find a data transformation that makes them fit. If this doesn't work, suggest/apply a nonparametric counterpart of ANOVA.

Reviewer #2:

The authors of this report propose to replicate experiments within Coding-independent Regulation of the Tumor Suppressor PTEN by Competing Endogenous mRNAs, by Tay et al., 2011. This study reported a set of genes (NCOA7, BCL11B, SERINC1, ZNF460, NUDT13, DTWD2, and VAPA) regulating the expression of the tumor suppressor PTEN by acting as competing endogenous RNAs (ceRNAs). The authors describe the following as the essential results of Tay et al., 2011: 1.) When DU145 cells are transfected with a luciferase construct containing the PTEN 3′UTR and siRNAs against each of the putative ceRNAs, luciferase activity decreases in comparison to transfections with the construct and a control siRNA. 2.) When the same cells are transfected with a luciferase construct containing the PTEN 3′UTR and a construct containing the 3′UTR of one of the ceRNAs, luciferase activity increases in comparison to when transfected with the construct and a control construct. 3.) When HCT WT cells are transfected with siRNAs against each of the identified ceRNAs, PTEN expression as measured by protein blot decreases in comparison to transfections with a control siRNA. When this experiment is repeated in HCT DicerEx5, which is impaired in production of miRNA levels, the reduction of PTEN upon ceRNA knockdown is abrogated, supporting the idea that the response to modulating the ceRNAs is miRNA dependent. 4.) When DU125 and HCT WT cells are transected with an siRNA against PTEN or one of two ceRNAs (CNO a VAPA), cell proliferation increases in comparison to when transfected with a control siRNA. When this experiment is repeated in HCT DicerEx5, the increased proliferation upon knockdown of either of the two ceRNAs, but not PTEN, is reduced. 5.) When DU125 and HCT WT cells are transected with an siRNA against PTEN or one of two ceRNAs (CNO a VAPA) and serum starved, phosphorylation of Akt increases after restimulation, in comparison to when transfected with a control siRNA. When this experiment is repeated in HCT DicerEx5, the increase in Akt phosphorylation upon knockdown of either of the two ceRNAs, but not PTEN, is abrogated.

Considered questions:

1) Do the experiments chosen embody the main conclusions drawn from the original article?

These experiments embody the main conclusions. Protocols 1 and 2 are designed to demonstrate that each ceRNA positively regulates PTEN protein levels through the 3′ UTR of both the ceRNA and PTEN transcript. Protocol 3 is designed to demonstrate that this effect is dependent on miRNAs. Protocol 4 is designed to demonstrate that loss of PTEN or its ceRNAs increases cell proliferation, and Protocol 5 is designed to demonstrate that loss of PTEN or its ceRNAs increases Akt phosphorylation, which is a proliferation signal.

2) Do the authors accurately summarize the literature, especially with respect to other direct replications?

Yes.

3) Are the proposed experiments appropriately designed?

The original experiments corresponding to each of the five protocols had only a single siRNA or UTR control. If the authors had the latitude to add more controls, the results would be more robust, although this would go beyond the scope of simply repeating the published experiments. In Protocol 3 and 5 the protein blots could be performed loading a dilution series of total protein (e.g., 5 µg, 2 µg, 1 µg) from the control sample, to ensure that quantitation is in the linear range and not confounded by overexposure (a concern of the original authors).

3) Are the proposed statistical analyses rigorous and appropriate?

Yes.

4) What can the replication team do to maximize the quality of the replication?

The team has done a thorough job in designing this attempted replication.

Reviewer #3:

The authors present a clear, well-controlled plan for this replication study. They have also included comments and experimental details provided by the original authors. They should address the minor comments listed below before this manuscript can be accepted for publication.

Comments for the authors:

Paragraph one, Introduction – cognante should be cognate.

Paragraph three, Introduction – CNOTL6 should be CNOT6L.

Paragraph eight, Introduction – The Poliseno group should be The Pandolfi group.

Protocol 1, “Materials and Reagents” table (and all other mentions of the TaqMan probes) – The original product numbers are specified in the extreme left column. For example, the PTEN TaqMan probe used is Hs02621230_s1.

Protocol 5, “Materials and Reagents” table – The P-Akt antibody should be 9271 (Cell signalling). This is for P-Akt Ser473, which is what was examined in the original paper. Cat number 9275 is for the P-Akt Thr308 antibody.

Reviewer #4:

We have carefully checked the proposal with respect to the 5 criteria specified in the reviewers' guidelines and found the proposal just perfect. Of course nowadays one would like to see the Pandolfi experiments controlled by CRISPR/Cas mutagenesis, but this is apparently not part of the present replication program.

https://doi.org/10.7554/eLife.12470.002

Author response

Reviewer #1:

For all protocols, the authors propose use ANOVA to analyze the data. Please check for outliers and make sure that the data do not violate the assumptions of the ANOVA: normality and homoscedasticity. If the data do not fit the assumptions well enough, try to find a data transformation that makes them fit. If this doesn't work, suggest/apply a nonparametric counterpart of ANOVA.

We appreciate the point that the reviewer has brought up. We have added the following statement to the analysis sections where appropriate.

“Note: At the time of analysis we will perform the Shapiro-Wilk test and generate a quantile-quantile 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 Wilcoxon-Mann-Whitney test.”

Reviewer #2:

The authors of this report propose to replicate experiments within Coding-independent Regulation of the Tumor Suppressor PTEN by Competing Endogenous mRNAs, by Tay et al., 2011. This study reported a set of genes (NCOA7, BCL11B, SERINC1, ZNF460, NUDT13, DTWD2, and VAPA) regulating the expression of the tumor suppressor PTEN by acting as competing endogenous RNAs (ceRNAs). The authors describe the following as the essential results of Tay et al., 2011: 1.) When DU145 cells are transfected with a luciferase construct containing the PTEN 3′UTR and siRNAs against each of the putative ceRNAs, luciferase activity decreases in comparison to transfections with the construct and a control siRNA. 2.) When the same cells are transfected with a luciferase construct containing the PTEN 3′UTR and a construct containing the 3′UTR of one of the ceRNAs, luciferase activity increases in comparison to when transfected with the construct and a control construct. 3.) When HCT WT cells are transfected with siRNAs against each of the identified ceRNAs, PTEN expression as measured by protein blot decreases in comparison to transfections with a control siRNA. When this experiment is repeated in HCT DicerEx5, which is impaired in production of miRNA levels, the reduction of PTEN upon ceRNA knockdown is abrogated, supporting the idea that the response to modulating the ceRNAs is miRNA dependent. 4.) When DU125 and HCT WT cells are transected with an siRNA against PTEN or one of two ceRNAs (CNO a VAPA), cell proliferation increases in comparison to when transfected with a control siRNA. When this experiment is repeated in HCT DicerEx5, the increased proliferation upon knockdown of either of the two ceRNAs, but not PTEN, is reduced. 5.) When DU125 and HCT WT cells are transected with an siRNA against PTEN or one of two ceRNAs (CNO a VAPA) and serum starved, phosphorylation of Akt increases after restimulation, in comparison to when transfected with a control siRNA. When this experiment is repeated in HCT DicerEx5, the increase in Akt phosphorylation upon knockdown of either of the two ceRNAs, but not PTEN, is abrogated.

Considered questions:

1) Do the experiments chosen embody the main conclusions drawn from the original article?These experiments embody the main conclusions. Protocols 1 and 2 are designed to demonstrate that each ceRNA positively regulates PTEN protein levels through the 3′ UTR of both the ceRNA and PTEN transcript. Protocol 3 is designed to demonstrate that this effect is dependent on miRNAs. Protocol 4 is designed to demonstrate that loss of PTEN or its ceRNAs increases cell proliferation, and Protocol 5 is designed to demonstrate that loss of PTEN or its ceRNAs increases Akt phosphorylation, which is a proliferation signal.2) Do the authors accurately summarize the literature, especially with respect to other direct replications?Yes.

3) Are the proposed experiments appropriately designed?The original experiments corresponding to each of the five protocols had only a single siRNA or UTR control. If the authors had the latitude to add more controls, the results would be more robust, although this would go beyond the scope of simply repeating the published experiments. In Protocol 3 and 5 the protein blots could be performed loading a dilution series of total protein (e.g., 5 µg, 2 µg, 1 µg) from the control sample, to ensure that quantitation is in the linear range and not confounded by overexposure (a concern of the original authors).

We agree with the reviewer that there can be much performed outside of what would be considered a direct replication and that these questions should be answered outside of this experimental setup. As for the Western blotting protocols, multiple exposures will be taken at various times to minimize the risk of overexposure with all images made publically available.

Reviewer #3:Paragraph one, Introduction – cognante should be cognate

This has been corrected in the revised manuscript.

Paragraph three, Introduction – CNOTL6 should be CNOT6L

This has been corrected in the revised manuscript.

Paragraph eight, Introduction – The Poliseno group should be The Pandolfi group

This has been corrected in the revised manuscript.

Protocol 1, “Materials and Reagents” table (and all other mentions of the TaqMan probes) – The original product numbers are specified in the extreme left column. For example, the PTEN TaqMan probe used is Hs02621230_s1.

We have moved the product numbers for each TaqMan probe to the appropriate fourth column and removed the comment that the original product number was not specified.

Protocol 5, “Materials and Reagents” table – The P-Akt antibody should be 9271 (Cell signalling). This is for P-Akt Ser473, which is what was examined in the original paper. Cat number 9275 is for the P-Akt Thr308 antibody.

Thank you for this comment. We confirmed with the original authors that the catalog number 9271 (for the P-Akt Ser473) should be used and have corrected this in the revised manuscript.

Reviewer #4:We have carefully checked the proposal with respect to the 5 criteria specified in the reviewers' guidelines and found the proposal just perfect. Of course nowadays one would like to see the Pandolfi experiments controlled by CRISPR/Cas mutagenesis, but this is apparently not part of the present replication program.

We appreciate the reviewers’ note and agree that such exploratory analyses would be appropriate for future replication attempts.

https://doi.org/10.7554/eLife.12470.003

Article and author information

Author details

  1. Mitch Phelps

    1. Pharmacoanalytic Shared Resource, The Ohio State University, Columbus, United States
    Contribution
    MP, Drafting or revising the article
    Competing interests
    MP: The Ohio State University Pharmacoanalytical Shared Resource is a Science Exchange associated laboratory.
  2. Chris Coss

    1. Pharmacoanalytic Shared Resource, The Ohio State University, Columbus, United States
    Contribution
    CC, Drafting or revising the article
    Competing interests
    CC: The Ohio State University Pharmacoanalytical Shared Resource is a Science Exchange associated laboratory.
  3. Hongyan Wang

    1. Pharmacoanalytic Shared Resource, The Ohio State University, Columbus, United States
    Contribution
    HW, Drafting or revising the article
    Competing interests
    HW: The Ohio State University Pharmacoanalytical Shared Resource is a Science Exchange associated laboratory.
  4. Matthew Cook

    1. University of California San Francisco, San Francisco, United States
    Contribution
    MC, Drafting or revising the article
    Competing interests
    No competing interests declared.
  5. Reproducibility Project: Cancer Biology

    Contribution
    RP:CB, Conception and design, Drafting or revising the article
    For correspondence
    1. nicole@scienceexchange.com
    Competing interests
    RP:CB: EI, FT, NP, and JL are employed and hold shares in Science Exchange, Inc.
    1. Elizabeth Iorns, Science Exchange, Palo Alto, United States
    2. William Gunn, Mendeley, London, United Kingdom
    3. Fraser Tan, Science Exchange, Palo Alto, United States
    4. Joelle Lomax, Science Exchange, Palo Alto, United States
    5. Nicole Perfito, Science Exchange, Palo Alto, United States
    6. Timothy Errington, Center for Open Science, Charlottesville, United States

Funding

Laura and John Arnold Foundation

  • Reproducibility Project: Cancer Biology

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The Reproducibility Project: Cancer Biology core team would like to thank Yvonne Tay and Pier Paolo Pandolfi for generously sharing critical information as well as reagents to ensure the fidelity and quality of this replication attempt. We thank Dr. Bert Vogelstein for directing us to the appropriate facility to obtain HCT116 DICER mutant cells. We thank Courtney Soderberg at the Center for Open Science for assistance with statistical analyses. We would also like to thank the following companies for generously donating reagents to the Reproducibility Project: Cancer Biology; American Type and Tissue Collection (ATCC), Applied Biological Materials, BioLegend, Charles River Laboratories, Corning Incorporated, DDC Medical, EMD Millipore, Harlan Laboratories, LI-COR Biosciences, Mirus Bio, Novus Biologicals, Sigma-Aldrich, and System Biosciences (SBI).

Reviewing Editor

  1. Timothy W Nilsen, Reviewing Editor, Case Western Reserve University, United States

Publication history

  1. Received: November 23, 2015
  2. Accepted: February 4, 2016
  3. Version of Record published: March 1, 2016 (version 1)
  4. Version of Record updated: March 23, 2016 (version 2)

Copyright

© 2016, Phelps et al

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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