Literature DB >> 26335297

Registered report: A coding-independent function of gene and pseudogene mRNAs regulates tumour biology.

Dale Cowley1, Kumar Pandya1, Israr Khan2, John Kerwin3, Kate Owen4, Erin Griner4.   

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 'A coding-independent function of gene and pseudogene mRNAs regulates tumour biology' by Poliseno et al. (2010), published in Nature in 2010. The key experiments to be replicated are reported in Figures 1D, 2F-H, and 4A. In these experiments, Poliseno and colleagues report microRNAs miR-19b and miR-20a transcriptionally suppress both PTEN and PTENP1 in prostate cancer cells (Figure 1D; Poliseno et al., 2010). Decreased expression of PTEN and/or PTENP1 resulted in downregulated PTEN protein levels (Figure 2H), downregulation of both mRNAs (Figure 2G), and increased tumor cell proliferation (Figure 2F; Poliseno et al., 2010). Furthermore, overexpression of the PTEN 3' UTR enhanced PTENP1 mRNA abundance limiting tumor cell proliferation, providing additional evidence for the co-regulation of PTEN and PTENP1 (Figure 4A; Poliseno et al., 2010). The Reproducibility Project: Cancer Biology is collaboration between the Center for Open Science and Science Exchange, and the results of the replications will be published in eLife.

Entities:  

Keywords:  PTEN; Reproducibility Project: Cancer Biology; biochemistry; chromosomes; genes; human; methodology; noncoding RNA; pseudogene

Mesh：

Substances：

Year:  2015        PMID： 26335297      PMCID： PMC4558562          DOI： 10.7554/eLife.08245

Source DB:  PubMed          Journal:  Elife        ISSN： 2050-084X            Impact factor:   8.140


Introduction

The phosphatase and tensin homolog gene (PTEN) functions as a negative repressor of the PI3K/Akt survival pathway and is one of the most frequently deleted tumor suppressor genes in human cancer (Stambolic et al., 1998; Song et al., 2012). As a regulator of PI3K signaling, loss of PTEN results in over-activation of Akt, leading to unchecked cell proliferation, reduced apoptosis, and elevated tumor angiogenesis (Stambolic et al., 1998; Carracedo et al., 2008). In prostate cancer, decreases in PTEN protein expression, either by allelic deletion or functional loss caused by mutation and/or epigenetic modification, can lead to invasive prostate carcinoma (Trotman et al., 2003; Phin et al., 2013). In preclinical systems, the genetic restoration of PTEN induces apoptosis in cancer cell lines and has a significant negative effect on tumor growth in multiple in vivo models (Li et al., 1998; Lu et al., 1999; Tian et al., 1999; Chen et al., 2011). In contrast, clinical efforts to restore PTEN functionality have instead focused on targeting kinases in the PI3K pathway, including PI3K, Akt, and the mammalian target of rapamycin (Hopkins and Parsons, 2014). However, the development of PI3K targeting drugs has been complicated by the limited tolerability of current pharmacological treatments as well as tumor heterogeneity (Gerlinger et al., 2012; Bauer et al., 2014). It is increasingly apparent that a complex regulatory network exists between the diverse RNA species pervasive in the human transcriptome. MicroRNAs (miRNAs) are small non-coding RNAs that bind to complementary sequences in the 3′ untranslated regions (UTR) of target messenger RNAs (mRNA), resulting in transcriptional downregulation of the target gene (Sen et al., 2014). Meng and colleagues showed that PTEN was repressed by miR-21, one of the most frequently upregulated miRNAs in cancer, in hepatocarcinoma cells, suggesting that the oncogenic potential of miR-21 occurs via the downregulation of PTEN expression (Chan et al., 2005; Meng et al., 2006; Volinia et al., 2006; Meng et al., 2007; Si et al., 2007). Several miRNAs that target PTEN have since been reported (Jackson et al., 2014; Wang et al., 2015). While miRNAs play a functional role in silencing target gene expression, it is proposed that miRNAs themselves are subject to regulation by competing endogenous RNA (ceRNA) species, including pseudogenes, long non-coding RNAs, and circular RNAs (Salmena et al., 2011; Cesana and Daley, 2013). In plants, for example, the non-protein coding gene IPS1 sequesters miRNAs away from their mRNA targets, thereby leading to an accumulation of target transcripts (Franco-Zorrilla et al., 2007). Poliseno and colleagues proposed that pseudogenes, which are non-coding genomic DNA sequences closely related to parental genes, can modulate parental gene expression by influencing the available levels of miRNAs within a cell (Poliseno et al., 2010; Cesana and Daley, 2013). However, the extent and manner that ceRNAs can exert a consequential effect on the repression of targets for that miRNA is currently unclear (Broderick and Zamore, 2014). Recently, Denzler and colleagues analyzed the stoichiometric relationship of miR-122 and target sites in adult mouse liver and reported that the natural abundance of target sites exceeded miRNAs, making the ceRNA hypothesis unlikely (Denzler et al., 2014). PTENP1 is a pseudogene that shares close homology with PTEN, including the ability to bind miRNAs (Fujii et al., 1999). To determine whether PTEN and PTENP1 expression levels are modulated by miRNA activity, Poliseno and colleagues first established that the PTEN-targeting miRNAs miR-19b and miR-20a were able to target both PTEN and PTENP1 (Poliseno et al., 2010). As reported in Figure 1D, overexpression of miR-19b and miR-20a in prostate cancer cells resulted in a significant decrease in PTEN and PTENP1 mRNA transcription. This is supported by additional studies demonstrating that overexpression of either miR-19b or miR-20a in cancer cell lines resulted in reduced PTEN mRNA levels and protein expression (Luo et al., 2013; Tian et al., 2013; Wu et al., 2014). The ability of miR-19b and miR-20a to target PTEN in prostate cancer was further confirmed by Tay et al. (2011). These key findings established that PTEN and PTENP1 are regulated by interactions with miRNA in multiple cancer cell types and will be replicated in Protocol 1. In Figure 2F-H, Poliseno and colleagues tested the phenotypic consequences of PTENP1 downregulation by specifically targeting PTEN and/or PTENP1 expression. Downregulation of PTENP1 in DU145 prostate cancer cells resulted in a significant decrease in both PTEN and PTENP1 mRNA levels and protein expression (Figure 2G-H; Poliseno et al., 2010). Furthermore, downregulation of PTENP1 profoundly accelerated the proliferation of DU145 cells (Figure 2F), with silencing of both PTEN and PTENP1 having an additive effect (Poliseno et al., 2010). These experiments will be replicated in Protocols 2, 3, and 4. Recently, Tay and colleagues reported that PTEN-ceRNAs, including CNOT6L and VAPA, phenocopied PTENP1 activity, as downregulation of these non-coding transcripts in prostate and colon cancer cells were also able to modulate PTEN expression, Akt activity, and cell growth (Tay et al., 2011). Additionally, other PTEN-ceRNAs that regulate PTEN expression have been reported in brain, breast, and skin cancers (Lee et al., 2010; Karreth et al., 2011; Sumazin et al., 2011). Further to this, PTENP1 antisense RNA has been reported to regulate PTEN transcription and mRNA stability, suggesting a model where the PTENP1 pseudogene has biomodal functionality modulating PTEN (Johnsson et al., 2013). As an extension of the findings reported in Figure 2 and further genomic analysis, Poliseno and colleagues demonstrated that the PTEN 3′ UTR regulates pseudogene expression, since overexpression of the PTEN 3′ UTR was found to de-repress PTENP1 expression and inhibited DU145 proliferation (Figure 4A) (Poliseno et al., 2010). These experiments will be replicated in Protocols 5 and 6. These results were also confirmed by experiments by Yu and colleagues showing that overexpression of either PTEN or PTENP1 suppressed renal cancer cell proliferation (Yu et al., 2014). Further to this, the oncosuppressive properties of overexpressing PTENP1 3′ UTR have been reported in various cancer cells (Poliseno et al., 2010; Chen et al., 2015; Guo et al., 2015).

Materials and methods

Protocol 1: Quantitative PCR after miR transfection

This experiment utilizes quantitative RT-PCR to analyze the effect of miR-19b or miR-20a on the mRNA levels of PTEN and PTENP1. It is a replication of Figure 1D.

Sampling

■ Experiment to be repeated a total of six times for a minimum power of 88%. ○ See ‘Power calculations’ section for details. ■ Experiment has 5 conditions: ○ Cohort 1: siGENOME non-targeting siRNA #2 (siLUC) transfected DU145 cells. ○ Cohort 2: miR-19b transfected DU145 cells. ○ Cohort 3: miR-20a transfected DU145 cells. ○ Cohort 4: Untransfected DU145 cells (additional negative control). ○ Transfection control: siGLO RISC-free siRNA transfected DU145 cells. ■ Quantitative RT-PCR performed in technical triplicate for the following genes: ○ PTEN. ○ PTENP1. ○ ACTIN (internal control). ○ 36B4 (additional internal control).

Materials and reagents

Procedure

Notes

Cells will be sent for mycoplasma testing and short tandem repeat (STR) profiling. DU145 cells are grown in complete RPMI 1640 supplemented with 2 mM glutamine, 10% FBS, 100 U/ml penicillin and 100 µg/ml streptomycin at 37°C and 6% CO2. Seed 1.5 × 105 DU145 cells per well in a 12-well dish. Grow overnight. Transfect with 100 nM siLuc, si-miR-19b, and si-miR-20a using 3 µl of Dharmafect 1 according to manufacturer's instructions. Transfect control cells with siGLO RISC-free control siRNA following manufacturer's instructions. Include untransfected control cells. Grow overnight. Confirm that >90% of siGLO transfected control cells show fluorescence, indicating they were successfully transfected. a. 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. b. If modification to transfection (step 2) is needed, record and maintain modified steps for remaining replicates. 24 hr after transfection, extract total RNA from cells directly on the culture dish using TRI reagent and 1-bromo-3-chloropropane according to manufacturer's instructions. Treat RNA with DNAse I following manufacturer's instructions. a. Record RNA concentration and purity (A280/A260). Reverse transcribe 1 µg RNA/sample into cDNA using first-strand cDNA synthesis kit with primers following manufacturer's instructions. Perform quantitative PCR reaction using the QuantiTect Sybr Green PCR kit: a. Use 2 µl of reverse transcription reaction per 20 µl real-time PCR reaction. b. Perform quantitative PCR for PTEN, PTENP1, ACTIN, and 36B4. i. PTEN forward primer: 5′-GTTTACCGGCAGCATCAAAT-3′ ii. PTEN reverse primer: 5′-CCCCCACTTTAGTGCACAGT-3′ iii. PTENP1 forward primer: 5′-TCAGAACATGGCATACACCAA-3′ iv. PTENP1 reverse primer: 5′-TGATGACGTCCGATTTTTCA-3′ v. ACTIN forward primer: 5′-CATGTACGTTGCTATCCAGGC-3′ vi. ACTIN reverse primer: 5′-CTCCTTAATGTCACGCACGAT-3′ vii. 36B4 forward primer: 5′-GTGTTCGACAATGGCAGCAT-3′ viii. 36B4 reverse primer: 5′-GACACCCTCCAGGAAGCGA-3′ i. 36B4 primer sequences reported in Fullwood et al. (2009). c. Do not pre-treat with uracil-N-glycosylase. d. All reactions should be optimized and run in technical triplicate. Using ACTIN as an internal standard, calculate the relative PTEN and PTENP1 expression for each sample using the comparative Ct method. a. Additionally perform normalization using 36B4 as an internal standard (additional control). Repeat independently five additional times.

Deliverables

■ Data to be collected: ○ Images of fluorescence and phase/contrast of siGLO transfected cells. ○ Purity (A260/280 ratio) and concentration of isolated total RNA from cells. ○ Raw data for all qPCR reactions. ○ Quantification of PTEN and PTENP1 mRNA levels relative to ACTIN. ○ Quantification of fold change PTEN and PTENP1 mRNA levels relative to siLuc transfected cells. (Compare to Figure 1D).

Confirmatory analysis plan

This replication attempt will perform the statistical analysis listed below. ■ Statistical Analysis: ○ 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 in order to proceed with the proposed statistical analysis. If this is not possible we will perform the planned comparisons using the Wilcoxon–Mann Whitney test. ○ One-way MANOVA of normalized PTEN or PTENP1 mRNA fold change in siLuc, 19b, or 20a siRNA transfected cells with the following planned comparisons using the Bonferroni correction: PTEN mRNA levels of siLuc transfected cells compared to 19b transfected cells. PTEN mRNA levels of siLuc transfected cells compared to 20a transfected cells. PTENP1 mRNA levels of siLuc transfected cells compared to 19b transfected cells. PTENP1 mRNA levels of siLuc transfected cells compared to 20a transfected cells. ■ Meta-analysis of effect sizes: ○ Compute the effect sizes of each comparison, compare them against the effect size in the original paper and use a random effects meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot. ■ Additional exploratory analysis: ○ The same analysis described above will be performed with 36B4 normalized values, which serves as an independent normalization control not included in the original analysis.

Known differences from the original study

The PTEN and PTENP1 mRNA levels will be normalized with an independent control (36B4) in addition to ACTIN. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.

Provisions for quality control

The cell line used in this experiment will undergo STR profiling to confirm its identity and will be sent for mycoplasma testing to ensure there is no contamination. 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 in the first attempt(s) does not obtain >90%, then any modifications to the transfection protocol will be recorded and the procedure will be maintained for the remaining replicates. The sample purity (A260/280 ratio) of the isolated RNA from each sample will be reported. The PTEN and PTENP1 mRNA levels will be normalized with an independent control (36B4). All the raw data, including the analysis files, will be uploaded to the project page on the Open Science Framework (OSF) (https://osf.io/yyqas) and made publically available.

Protocol 2: Cell growth assay following siRNA transfection

This experiment tests the effect of siRNA mediated depletion of PTEN, PTENP1, or both on the growth of DU145 cells. It is a replication of Figure 2F. ■ Experiment to be repeated a total of five times for a minimum power of 94%. ○ See ‘Power calculations’ section for details. ■ Experiment has 6 conditions: ○ Cohort 1: siGENOME non-targeting siRNA #2 (siLUC) transfected DU145 cells. ○ Cohort 2: siPTEN Smartpool (targets PTEN and PTENP1) transfected DU145 cells. ○ Cohort 3: siPTEN transfected DU145 cells. ○ Cohort 4: siPTENP1 transfected DU145 cells. ○ Cohort 5: Untransfected DU145 cells (additional negative control). ○ Transfection control: siGLO RISC-free siRNA transfected DU145 cells. ■ Each cohort is harvested on the following days performed in technical triplicate: ○ Day 0 (after O/N incubation). ○ Day 1. ○ Day 2. ○ Day 3. ○ Day 4. ○ Day 5.

Note

All cells will be sent for mycoplasma testing and STR profiling. DU145 cells grown in complete RPMI 1640: RPMI 1640 supplemented with 2 mM glutamine, 10% FBS, 100 U/ml penicillin and 100 µg/ml streptomycin at 37°C and 6% CO2. Seed 1.5 × 105 DU145 cells per well in a 12-well dish. Grow overnight. Transfect with 100 nM siRNAs (siPTEN, siPTENP1, siPTEN Smartpool (siPTEN and PTENP1), or siLuc in separate wells) using Dharmafect 1 according to manufacturer's instructions or leave untransfected. Transfect control cells with siGLO RISC-free control siRNA according to manufacturer's instructions. Grow overnight. Confirm that >90% of siGLO transfected control cells show fluorescence, indicating they were successfully transfected. a. 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. b. If modification to transfection (step 2) is needed, record and maintain modified steps for remaining replicates. The day after transfection, resuspend 2 × 105 siLuc, siPTEN, siPTENP1, siPTEN/PTENP1, or untransfected cells in 50 ml fresh media. Seed three wells of six sets of 12-well plates with 2 ml of each cell line. Each set of 12 well plates should have three wells of each cell line. Incubate overnight. Fix one plate every 24 hr starting after overnight incubation (the first plate fixed will be called day 0). a. Wash wells once in PBS. b. Fix wells with 10% formalin for 10 min at room temperature. c. Store plates in PBS at 4°C. d. All wells should be fixed by day 6. Stain cells with 0.1% crystal violet, 20% methanol for 15 min. Wash cells. Lyse all wells with 10% acetic acid for 10 min. Read optical density at 590 or 595 nm. a. Reading can be done at 595 nm if 590 is not available. Repeat independently four additional times. ■ Data to be collected: ○ Images of fluorescence and phase/contrast of siGLO transfected cells. ○ Raw data of absorbance from plate reader. ○ Graph of relative cell number for each cell line over time. (Compare to Figure 2F). This replication attempt will perform the following statistical analysis listed below. ■ Statistical Analysis: ○ 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 in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ Two-way ANOVA comparing Day 5 absorbance in siLuc, siPTEN, siPTENP1, or siPTEN/PTENP1 transfected cells with the following planned comparisons using the Bonferroni correction: siLuc compared to siPTEN. siLuc compared to siPTENP1. siLuc compared to siPTEN/PTENP1. siPTEN/PTENP1 compared to siPTEN. siPTEN/PTENP1 compared to siPTENP1. ○ Two-way ANOVA comparing area under the curve (AUC) measurements (determined from day 0, 1, 2, 3, 4, and 5 for each replicate) from absorbance in siLuc, siPTEN, siPTENP1, or siPTEN/PTENP1 transfected cells with the following planned comparisons using the Bonferroni correction. siLuc compared to siPTEN. siLuc compared to siPTENP1. siLuc compared to siPTEN/PTENP1. siPTEN/PTENP1 compared to siPTEN. siPTEN/PTENP1 compared to siPTENP1. ■ Meta-analysis of effect sizes: ○ Compute the effect sizes of each comparison, compare them against the effect size in the original paper and use a random effects meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design. The cell line used in this experiment will undergo STR profiling to confirm its identity and will be sent for mycoplasma testing to ensure there is no contamination. 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 in the first attempt(s) does not obtain >90%, then any modifications to the transfection protocol will be recorded and the procedure will be maintained for the remaining replicates. All the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/yyqas) and made publically available.

Protocol 3: Quantitative PCR following transfected with siRNA against PTEN and/or PTENP1

This experiment analyzes the effect of depletion of PTEN, PTENP1, or both on the mRNA expression of PTEN or PTENP1. Quantitative real time PCR is utilized to assess the levels of expression following transfection of siRNA. This protocol is a replication of Figure 2G. ■ Experiment to be repeated a total of five times for a minimum power of 89%. ○ See ‘Power calculations’ section for details. ■ Experiment has 6 conditons: ○ Cohort 1: Uninfected DU145 cells (additional negative control). ○ Cohort 1: siGENOME non-targeting siRNA #2 (siLUC) transfected DU145 cells. ○ Cohort 2: siPTEN Smartpool (targets PTEN and PTENP1) transfected DU145 cells. ○ Cohort 3: siPTEN transfected DU145 cells. ○ Cohort 4: siPTENP1 transfected DU145 cells. ○ Cohort 5: Uninfected DU145 cells (additional negative control). ○ Transfection control: siGLO RISC-free siRNA transfected DU145 cells. ■ Quantitative RT-PCR performed in technical triplicate for the following genes: ○ PTEN. ○ PTEN1P. ○ ACTIN (internal control). ○ 36B4 (additional internal control). All cells will be sent for mycoplasma testing and STR profiling. DU145 cells grown in complete RPMI 1640: RPMI 1640 supplemented with 2 mM glutamine, 10% FBS, 100 U/ml penicillin and 100 µg/ml streptomycin at 37°C and 6% CO2. Seed 1.5 × 105 DU145 cells per well in a 12-well dish. Grow overnight. Transfect with 100 nM siRNAs (siPTEN, siPTENP1, siPTEN Smartpool (siPTEN/PTENP1), or siLuc in separate wells) using Dharmafect 1 according to manufacturer's instructions or leave untransfected. Transfect control cells with siGLO RISC-free control siRNA according to manufacturer's instructions. Grow overnight. Confirm that >90% of siGLO transfected control cells show fluorescence, indicating they were successfully transfected. a. 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. b. If modification to transfection (step 2) is needed, record and maintain modified steps for remaining replicates. 24 hr after transfection, extract total RNA directly on the culture dish using TRI reagent and 1-bromo-3-chloropropane according to manufacturer's instructions. Treat RNA with DNAse following manufacturer's instructions. Reverse transcribe 1 µg RNA/sample into cDNA using first-strand cDNA synthesis kit with primers following manufacturer's instructions. a. Record RNA concentration and purity (A280/A260). Perform quantitative PCR reaction using the QuantiTect Sybr Green PCR kit: a. Use 2 µl of reverse transcription reaction per 20 µl real-time PCR reaction. b. Perform quantitative PCR for PTEN, PTENP1, ACTIN, and 36B4. i. PTEN forward primer: 5′-GTTTACCGGCAGCATCAAAT-3′ ii. PTEN reverse primer: 5′-CCCCCACTTTAGTGCACAGT-3′ iii. PTENP1 forward primer: 5′-TCAGAACATGGCATACACCAA-3′ iv. PTENP1 reverse primer: 5′-TGATGACGTCCGATTTTTCA-3′ v. ACTIN forward primer: 5′-CATGTACGTTGCTATCCAGGC-3′ vi. ACTIN reverse primer: 5′-CTCCTTAATGTCACGCACGAT-3′ vii. 36B4 forward primer: 5′-GTGTTCGACAATGGCAGCAT-3′ viii. 36B4 reverse primer: 5′-GACACCCTCCAGGAAGCGA-3′ i. 36B4 primer sequences reported in Fullwood et al. (2009). c. Do not pre-treat with uracil-N-glycosylase. d. All reactions should be optimized and run in technical triplicate. Using ACTIN as an internal standard, calculate the relative PTEN and PTENP1 expression for each sample using the comparative Ct method. a. Additionally perform normalization using 36B4 as an internal standard (additional control). Repeat independently four additional times. ■ Data to be collected: ○ Images of fluorescence and phase/contrast of siGLO transfected cells. ○ Purity (A260/280 ratio) and concentration of isolated total RNA from cells. ○ Raw data for all qPCR reactions. ○ Quantification of PTEN and PTENP1 mRNA levels relative to ACTIN or 36B4. ○ Quantification of fold change PTEN and PTENP1 mRNA levels relative to siLuc transfected cells. ○ Graph of fold change PTEN mRNA expression relative to siLuc. (Compare to Figure 2G, left). ○ Graph of fold change PTENP1 mRNA expression relative to siLuc. (Compare to Figure 2G, right). This replication attempt will perform the following statistical analysis listed below. ■ Statistical Analysis: ○ 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 in order to proceed with the proposed statistical analysis. If this is not possible we will perform the planned comparisons using the Wilcoxon–Mann Whitney test. ○ One-way MANOVA of PTEN and PTENP1 mRNA levels in siLuc, siPTEN, siPTENP1, or siPTEN/PTENP1 siRNA transfected cells with the following planned comparisons using the Bonferroni correction: PTEN mRNA levels of siLuc transfected cells compared to siPTEN transfected cells. PTEN mRNA levels of siLuc transfected cells compared to siPTENP1 transfected cells. PTEN mRNA levels of siLuc transfected cells compared to siPTEN/PTENP1 transfected cells. PTENP1 mRNA levels of siLuc transfected cells compared to siPTEN transfected cells. PTENP1 mRNA levels of siLuc transfected cells compared to siPTENP1 transfected cells. PTENP1 mRNA levels of siLuc transfected cells compared to siPTEN/PTENP1 transfected cells. ■ Meta-analysis of effect sizes: ○ Compute the effect sizes of each comparison, compare them against the effect size in the original paper and use a random effects meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot. ■ Additional exploratory analysis: ○ The same analysis described above will be performed with 36B4 normalized values, which serves as an independent normalization control not included in the original analysis. The PTEN and PTENP1 mRNA levels will be normalized with an independent control (36B4) in addition to ACTIN. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design. The cell line used in this experiment will undergo STR profiling to confirm their identity and will be sent for mycoplasma testing to ensure there is no contamination. 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 in the first attempt(s) does not obtain >90%, then any modifications to the transfection protocol will be recorded and the procedure will be maintained for the remaining replicates. The sample purity (A260/280 ratio) of the isolated RNA from each sample will be reported. The PTEN and PTENP1 mRNA levels will be normalized with an independent control (36B4). All the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/yyqas) and made publically available.

Protocol 4: Western blot of cells transfected with siRNA

This experiment utilizes western blot to assess the protein levels of PTEN after depletion of PTEN, PTENP1, or both. It is a replication of Figure 2H. ■ Experiment to be repeated a total of five times for a minimum power of 80%. The original data are 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. ■ Experiment has 6 conditons: ○ Cohort 1: siGENOME non-targeting siRNA #2 (siLUC) transfected DU145 cells. ○ Cohort 2: siPTEN Smartpool (targets PTEN and PTENP1) transfected DU145 cells. ○ Cohort 3: siPTEN transfected DU145 cells. ○ Cohort 4: siPTENP1 transfected DU145 cells. ○ Cohort 5: Uninfected DU145 cells (additional negative control). ○ Transfection control: siGLO RISC-free siRNA transfected DU145 cells. ■ Western blots performed for: ○ PTEN. ○ Hsp90 (loading control). All cells will be sent for mycoplasma testing and STR profiling. DU145 cells grown in complete RPMI 1640: RPMI 1640 supplemented with 2 mM glutamine, 10% FBS, 100 U/ml penicillin and 100 µg/ml streptomycin at 37°C and 6% CO2. Seed 3.75 × 105 DU145 cells per well in a 6-well dish. Grow overnight. Transfect with 100 nM siRNAs (siPTEN, siPTENP1, siPTEN Smartpool (siPTEN/PTENP1), or siLuc in separate wells) using Dharmafect 1 according to manufacturer's instructions or leave untransfected. Transfect control cells with siGLO RISC-free control siRNA according to manufacturer's instructions. Grow overnight. Confirm that >90% of siGLO transfected control cells show fluorescence, indicating they were successfully transfected. a. 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. b. If modification to transfection (step 2) is needed, record and maintain modified steps for remaining replicates. 48 hr after transfection lyse cells transfected with siRNAs and uninfected cells in lysis buffer on ice for 30 min. a. Lysis buffer: 50 mM Tris pH8.0, 1 mM EDTA, 1 mM MgCl2, 150 mM NaCl, 1% NP-40, 1 mM β-glycerophosphate, 1 mM Na3VO4, 1 mM NaF, protease inhibitors. Gently sonicate protein lysate for 3 to 4 bursts for 5 to 10 s. Clear lysate by centrifugation at 10,000×g for 10 min at 4°C. Perform Bradford protein determination assay following manufacturer's instructions. Separate 30 µg of protein (in 1× sample buffer and sample reducer) per lane on a 4–12% Tris Glycine SDS-PAGE gel with protein ladder following manufacturer's instructions. a. Sample run per gel: i. Protein molecular weight marker. ii. Untransfected DU145 cells. iii. DU145 cells transfected with siGENOME non-targeting siRNA #2. iv. DU145 cells transfected with siPTEN. v. DU145 cells transfected with siPTENP1. vi. DU145 cells transfected with siPTEN/PTENP1. Transfer to nitrocellulose membrane (pre-wetted with methanol before use) at 25 V constant for 1–2 hr in 1× transfer buffer with 20% methanol following manufacturer's instructions. a. After transfer, stain membrane with Ponceau S solution following manufacturer's instructions to visualize transferred protein. Image membrane, then wash out the Ponceau stain (additional quality control step). Perform western blotting with the following antibodies following manufacturer's instructions. Use 1× TBS for washes and blocking reagent recommended by manufacturer. a. rabbit anti-PTEN; use at 1:1000 dilution; 54 kDa. b. mouse anti-Hsp90; use at 1:1000 dilution; 90 kDa. Detect signal with appropriate HRP conjugated secondary antibody followed by chemiluminescence following manufacturer's instructions. Analyze scanned images using Image J software. a. Equal-sized regions of interest (ROI) will be positioned on specific bands. b. Background will be located within each individual lane but not occupied by any other discrete band. c. Subtract background pixel intensity from ROI pixel intensity. d. Normalize PTEN values by Hsp90 values from the same sample. Repeat independently four additional times. ■ Data to be collected: ○ Images of fluorescence and phase/contrast of siGLO transfected cells. ○ Images of Ponceau stained membranes and full films for all western blots with ladder. (Compare to Figure 2H). ○ Raw data file of ROI and background pixel intensities. ○ Normalize PTEN values for each sample. This replication attempt will perform the following statistical analysis listed below. ■ Statistical Analysis: ○ 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 in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ Two-way ANOVA of normalized PTEN levels in siLuc, siPTEN, siPTENP1, or siPTEN/PTENP1 siRNA transfected cells with the following planned comparisons using the Bonferroni correction: siLuc compared to siPTEN. siLuc compared to siPTENP1. siLuc compared to siPTEN/PTENP1. siPTEN/PTENP1 compared to siPTEN. siPTEN/PTENP1 compared to siPTENP1. ■ Meta-analysis of 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. The original study used 12 well plates seeded with 1.5 × 105 DU145 cells per well, which was increased 2.5× to account for the difference in cell surface area. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design. The cell line used in this experiment will undergo STR profiling to confirm their identity and will be sent for mycoplasma testing to ensure there is no contamination. 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 in the first attempt(s) does not obtain >90%, then any modifications to the transfection protocol will be recorded and the procedure will be maintained for the remaining replicates. Ponceau stained membranes will be used to assess completeness of transfer. All the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/yyqas) and made publically available.

Protocol 5: Quantitative PCR following PTEN 3′ UTR transfection

This experiment tests the effect of expressing the 3′ UTR of PTENP1 on mRNA expression levels of PTENP1. It is a replication of the left panel of Figure 4A. ■ Experiment to be repeated a total of three times for a minimum power of 98%. ○ See ‘Power calculations’ section for details. ■ Experiment has 3 conditions: ○ Cohort 1: pCMV transfected DU145 cells. ○ Cohort 2: pCMV/PTEN 3′ UTR transfected DU145 cells. ○ Cohort 3: Uninfected DU145 cells (additional negative control). ■ Quantitative RT-PCR performed in technical triplicate for the following genes: ○ PTENP1. ○ ACTIN (internal control). ○ 36B4 (additional internal control). All cells will be sent for mycoplasma testing and STR profiling. DU145 cells grown in complete RPMI 1640: RPMI 1640 supplemented with 2 mM glutamine, 10% FBS, 100 U/ml penicillin and 100 µg/ml streptomycin at 37°C and 6% CO2. Grow and prepare endotoxin-free plasmid constructs following manufacturer's instructions for an endotoxin-free plasmid maxiprep kit. a. pCMV (empty vector). b. pCMV/PTEN 3′ UTR. i. Sequence gene of interest in each plasmid and run whole plasmids on agarose gel to confirm vector integrity. Seed 3.5 × 105 DU145 cells per dish in 6 cm dishes. Grow overnight. Transfect with pCMV or pCMV/PTEN 3′ UTR plasmids using Effectene according to manufacturer's instructions and recommended DNA and reagent amounts. 24 hr after transfection, extract total RNA from each cohort directly on the culture dish using TRI reagent and 1-bromo-3-chloropropane according to manufacturer's instructions. Treat RNA with DNase I following manufacturer's instructions. Reverse transcribe 1 µg RNA/sample into cDNA using first-strand cDNA synthesis kit with primers following manufacturer's instructions. a. Record RNA concentration and purity (A280/A260). Perform quantitative PCR reaction using the QuantiTect SYBR Green PCR kit: a. Use 2 µl of reverse transcription reaction per 20 µl real-time PCR reaction. b. Perform quantitative PCR for PTENP1, ACTIN, and 36B4. i. PTENP1 forward primer: 5′-TCAGAACATGGCATACACCAA-3′ ii. PTENP1 reverse primer: 5′-TGATGACGTCCGATTTTTCA-3′ iii. ACTIN forward primer: 5′-CATGTACGTTGCTATCCAGGC-3′ iv. ACTIN reverse primer: 5′-CTCCTTAATGTCACGCACGAT-3′ v. 36B4 forward primer: 5′-GTGTTCGACAATGGCAGCAT-3′ vi. 36B4 reverse primer: 5′-GACACCCTCCAGGAAGCGA-3′ c. 36B4 primer sequences reported in Fullwood et al. (2009). d. Do not pre-treat with uracil-N-glycosylase. e. All reactions should be optimized and run in technical triplicate. Using ACTIN as an internal standard, calculate the fold change in PTEN1P expression relative to pCMV expressing cells using the comparative Ct method. a. Additionally perform normalization using 36B4 as an internal standard (additional control). Repeat independently two additional times. ■ Data to be collected: ○ Purity (A260/280 ratio) and concentration of isolated total RNA from cells. ○ Raw data for all qPCR reactions. ○ Quantification of PTENP1 mRNA levels relative to ACTIN or 36B4. ○ Quantification of fold change PTENP1 mRNA levels relative to pCMV transfected cells. (Compare to Figure 4A, left panel). This replication attempt will perform the following statistical analysis listed below. ■ Statistical Analysis: ○ 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 in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ Unpaired two-tailed t-test of PTENP1 mRNA levels of pCMV transfected cells compared to pCMV/PTEN 3′ UTR transfected cells. ■ Meta-analysis of effect sizes: ○ Compute the effect sizes of each comparison, compare them against the effect size in the original paper and use a random effects meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot. ■ Additional exploratory analysis: ○ The same analysis described above will be performed with 36B4 normalized values, which serves as an independent normalization control not included in the original analysis. The PTENP1 mRNA levels will be normalized with an independent control (36B4) in addition to ACTIN. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design. The cell line used in this experiment will undergo STR profiling to confirm their identity and will be sent for mycoplasma testing to ensure there is no contamination. The sample purity (A260/280 ratio) of the isolated RNA from each sample will be reported. The PTENP1 mRNA levels will be normalized with an independent control (36B4). All the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/yyqas) and made publically available.

Protocol 6: Cell growth assay following PTEN 3′ UTR transfection

This experiment tests the effect of expressing the 3′ UTR of PTENP1 on cell growth. It is a replication of the right panel of Figure 4A. ■ Experiment to be repeated a total of three times for a minimum power of 98%. ○ See ‘Power calculations’ section for details. ■ Experiment has 3 conditions: ○ Cohort 1: pCMV transfected DU145 cells. ○ Cohort 2: pCMV/PTEN 3′ UTR transfected DU145 cells. ○ Cohort 3: Uninfected DU145 cells (additional negative control). ■ Each cohort is harvested on the following days performed in technical triplicate: ○ Day 0 (after O/N incubation). ○ Day 1. ○ Day 2. ○ Day 3. ○ Day 4. ○ Day 5. All cells will be sent for mycoplasma testing and STR profiling. DU145 cells grown in complete RPMI 1640: RPMI 1640 supplemented with 2 mM glutamine, 10% FBS, 100 U/ml penicillin and 100 µg/ml streptomycin at 37°C and 6% CO2. Seed 3.5 × 105 DU145 cells per dish in 6 cm dishes. Grow overnight. Transfect with pCMV or pCMV/PTEN 3′ UTR plasmids using Effectene according to manufacturer's instructions and recommended DNA and reagent amounts. a. Plasmids prepped in Protocol 7. 6 hr after transfection, resuspend 2 × 105 pCMV, pCMV/PTEN 3′ UTR, and untransfected cells in 50 ml fresh media. Seed three wells of six sets of 12-well plates with 2 ml of each cell line. Each set of 12 well plates should have three wells containing untransfected cells, three wells containing pCMV-transfected cells, and three wells containing pCMV/PTEN 3′ UTR-transfected cells. Incubate overnight. Fix one plate every 24 hr starting after overnight incubation (the first plate fixed will be called day 0). a. Wash wells once in PBS. b. Fix wells with 10% formalin for 10 min at room temperature. c. Store plates in PBS at 4°C. d. All wells should be fixed by day 6. Stain cells with 0.1% crystal violet, 20% methanol for 15 min. Wash cells. Lyse all wells with 10% acetic acid for 10 min. Read optical density at 590 nm. a. Reading can be done at 595 nm if 590 nm is not available. Repeat independently two additional times. ■ Data to be collected: ○ Raw data of absorbance from plate reader. ○ Relative absorbance for each cohort over time. (Compare to Figure 4A, right panel). This replication attempt will perform the following statistical analysis listed below. ■ Statistical Analysis: ○ 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 in order to proceed with the proposed statistical analysis. If this is not possible we will perform the equivalent non-parametric test. ○ Unpaired two-tailed t-test of Day 5 absorbance of pCMV transfected cells compared to pCMV/PTEN 3′ UTR transfected cells. ○ Unpaired two-tailed t-test of AUC measurements (determined from day 0, 1, 2, 3, 4, and 5 for each replicate) of pCMV transfected cells compared to pCMV/PTEN 3′ UTR transfected cells. ■ Meta-analysis of effect sizes: ○ Compute the effect sizes of each comparison, compare them against the effect size in the original paper and use a random effects meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot. All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design. The cell line used in this experiment will undergo STR profiling to confirm their identity and will be sent for mycoplasma testing to ensure there is no contamination. All the raw data, including the analysis files, will be uploaded to the project page on the OSF (https://osf.io/yyqas) and made publically available.

Power calculations

For additional details on power calculations, please see analysis scripts and associated files on the OSF: https://osf.io/cd2yq/

Protocol 1

Summary of original data estimated from graph reported in Figure 1D:

Test family

■ 2 tailed t test, Wilcoxon–Mann-Whitney test, Bonferroni's correction: alpha error = 0.0125. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 99.9%. 6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 91.6%. ■ Due to the large variance, these 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. ○ Due to a lack of raw original data, we are unable to perform power calculations using a MANOVA. We are using a two-way ANOVA to estimate sample size. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). ANOVA F test statistic and partial η2 performed with R software, version 3.1.2 (R Development Core Team, 2014). 36 total samples (6 per group) will be used based on the planned comparisons making the power 99.9%. ■ Due to the large variance, these parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above. ■ 2 tailed t test, difference between two independent means, Bonferroni's correction: alpha error = 0.0125. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 99.9%. 6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 93.4%. 6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 91.9%.

Protocol 2

Summary of original data estimated from graph reported in Figure 2F: AUC calculations from estimated values. Calculations performed with R software 3.1.2 (R Development Core Team, 2014). ■ 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 η2 performed with R software, version 3.1.2 (R Development Core Team, 2014).

Day 5 values

16 total samples (4 per group) will be used based on the planned comparisons making the power 99.9%.

AUC values

16 total samples (4 per group) will be used based on the planned comparisons making the power 99.9%. ■ 2 tailed t test, difference between two independent means, Bonferroni's correction: alpha error = 0.01. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 5 samples per group will be used based on the AUC calculation planned comparisons making the power 99.9%. 5 samples per group will be used based on the siLuc to siPTENP1 comparison making the power 99.9%. 5 samples per group will be used based on the siLuc to siPTENP1 comparison making the power 95.0%.

Protocol 3

Summary of original data estimated from graph reported in Figure 2G: ■ 2 tailed t test, Wilcoxon–Mann-Whitney test, Bonferroni's correction: alpha error = 0.008333. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.8%. 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.9%. 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.3%. ■ Due to the large variance, these 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. ○ Due to a lack of raw original data, we are unable to perform power calculations using a MANOVA. We are using a two-way ANOVA to estimate sample size. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). ANOVA F test statistic and partial η2 performed with R software, version 3.1.2 (R Development Core Team, 2014). 40 total samples (5 per group) will be used based on the planned comparisons making the power 99.9%. ■ Due to the large variance, these parametric tests are only used for comparison purposes. The sample size is based on the non-parametric tests listed above. ■ 2 tailed t test, difference between two independent means, Bonferroni's correction: alpha error = 0.008333. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.9%. 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 95.1%. 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.9%. 5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.6%.

Protocol 4

Summary of original data reported in Figure 2H: 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. ■ 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 η2 performed with R software, version 3.1.2 (R Development Core Team, 2014). 2% variance: 15% variance: 28% variance: 40% variance: ■ 2 tailed t test, difference between two independent means, Bonferroni's correction: alpha error = 0.01. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 2% variance: 15% variance: 28% variance: 40% variance: In order to produce quantitative replication data, we will run the experiment five 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.

Protocol 5

Summary of original data estimated from graph reported in Figure 4A, left panel: ■ 2 tailed t test, difference between two independent means, alpha error = 0.05. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007).

Protocol 6

Summary of original data estimated from graph reported in Figure 4A, right panel: AUC calculations from estimated values. Calculations performed with R software 3.1.2 (R Development Core Team, 2014). ■ 2 tailed t test, difference between two independent means, alpha error = 0.05. ‘Power calculations’ performed with G*Power software, version 3.1.7 (Faul et al., 2007). 3 samples per group will be used based on the AUC calculation. eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers. Thank you for submitting your work entitled “Registered report: A coding-independent function of gene and pseudogene mRNAs regulates tumour biology” for peer review at eLife. Your submission has been favorably evaluated by Charles Sawyers (Senior Editor), and three reviewers, one of whom is a member of our Board of Reviewing Editors. The reviewers have discussed their comments with one another, and the Reviewing Editor has drafted this decision to help you prepare a revised submission. This Registered Report describes a proposed replication study that is focused on Poliseno et al. (2010, Nature 465, 1033-1038). The central conclusion of Poliseno et al. (2010) is that expression of an endogenous miRNA competitor (e.g. a pseudogene) can de-repress miRNA function. There are four important points that the authors should address: 1) The Introduction lays out the background, the results of Poliseno et al. (2010), and consistent data reported in other studies. However, the Introduction should include other studies that lead to questions concerning the ceRNA hypothesis (e.g. PMID: 24793693 & PMID: 24905003 and references therein). The ceRNA hypothesis remains an active area for inquiry. The impression given by the Introduction is that the overwhelming balance of evidence favors the ceRNA hypothesis – this is not correct. 2) It is well established that over-expression of miRNA can repress target mRNA (Figure 1D) and that over-expression of a miRNA sponge can de-repress a miRNA target (Figure 2A-D and Figure 4A). While repetition of these figures panels is useful, none of these experiments tackle the central conclusions of Poliseno et al. (2010) – that expression of an endogenous miRNA competitor (e.g. a pseudogene) can de-repress miRNA function. This is because of the reliance on over-expression strategies in Figure 1D, Figure 2A-D, and Figure 4A. Studies of the endogenous genes are required to test reproducibility of the central conclusion of the original study. The major conclusion of Poliseno et al. (2010) is that decreased expression of PTEN or PTENP1 mRNA should cause mutual changes in miRNA-mediated repression. The only experimental test on endogenous PTEN and PTENP1 mRNA (rather than over-expression of cDNA or miRNA) is represented by Figure 2F-H. It is therefore essential that Figure 2F-H are the focus of the replication study because these are the only experiments that address the central conclusion of Poliseno et al. (2010). 3) The normalization used for the mRNA measurements by Poliseno et al. (2010) and this Registered Report is ACTIN. This is a problem because Actin mRNA is dynamically regulated in cells and is a target of cell signaling pathway. Perhaps the ACTIN measurements can be retained in the replication study, but we would strongly recommend that an independent normalization control is also employed – for example 36B4 or another control gene. 4) The authors adopt two statistical procedures, ANOVA and 2 tailed t-test, in the analysis. However, neither of them is used correctly. Take Protocol 1 as an example. A) In ANOVA, for testing the main effect of siRNA, there are only 3 different levels: siLUC, 19b and 20a, but the numerator degree of freedom of the F-test is stated to be 4 by the authors. I also couldn't follow how the authors got the denominator d.f. to be 20 given there are only 18 observations in total. B) In 2 tailed t-test, the effective size calculated by the authors assumed that the two populations have the same variance, which is apparently not true for many pairs, according to the data. For example, in the comparison of siLuc PTENP1 and 19b PTENP1, the two sample standard deviations are 0.386 and 0.065, respectively. The former is almost 6-fold of the later. Moreover, given this small sample size, t-test is not recommended unless one is very confident that the two population distributions are normal. 5) Besides the paper that the authors intend to replicate, the oncosuppressive properties of PTEN 3'UTR have been shown also in Tay et al. (Cell, 2015), a paper which should be quoted. Analogously, the oncosuppressive properties of PTENP1 have been shown in other papers besides Yu et al. (2014), namely Chen et al. (2015) and Guo et al. (2015). 6) In more general terms, we suggest that the Introduction should include a comprehensive review of all the papers in which the ceRNA-based relationship between PTEN and PTENP1 has been confirmed: Poliseno, L., et al., Deletion of PTENP1 pseudogene in human melanoma. J Invest Dermatol, 2011. 131(12): p. 2497-500. Ioffe, Y.J., et al., Phosphatase and tensin homolog (PTEN) pseudogene expression in endometrial cancer: a conserved regulatory mechanism important in tumorigenesis? Gynecol Oncol, 2012. 124(2): p. 340-6. Johnsson, P., et al., A pseudogene long-noncoding-RNA network regulates PTEN transcription and translation in human cells. Nat Struct Mol Biol, 2013. 20(4): p. 440-6. Yu, G., et al., Pseudogene PTENP1 functions as a competing endogenous RNA to suppress clear cell renal cell carcinoma progression. Mol Cancer Ther, 2014. Chen, C.L., et al., Suppression of hepatocellular carcinoma by baculovirus-mediated expression of long non-coding RNA PTENP1 and MicroRNA regulation. Biomaterials, 2015. 44: p. 71-81. Guo, X., et al., Pseudogene PTENP1 Suppresses Gastric Cancer Progression by Modulating PTEN. Anticancer Agents Med Chem, 2015. 1) The Introduction lays out the background, the results of , and consistent data reported in other studies. However, the Introduction should include other studies that lead to questions concerning the ceRNA hypothesis (e.g. PMID: 24793693 & PMID: 24905003 and references therein). The ceRNA hypothesis remains an active area for inquiry. The impression given by the Introduction is that the overwhelming balance of evidence favors the ceRNA hypothesis – this is not correct. We have updated the Introduction to include these references and reflect a more balanced view of the ceRNA hypothesis. 2) It is well established that over-expression of miRNA can repress target mRNA (Figure 1D) and that over-expression of a miRNA sponge can de-repress an miRNA target (Figure 2A-D and Figure 4A). While repetition of these figures panels is useful, none of these experiments tackle the central conclusions of – that expression of an endogenous miRNA competitor (e.g. a pseudogene) can de-repress miRNA function. This is because of the reliance on over-expression strategies in Figure 1D, Figure 2A-D, and Figure 4A. Studies of the endogenous genes are required to test reproducibility of the central conclusion of the original study. The major conclusion of is that decreased expression of PTEN or PTENP1 mRNA should cause mutual changes in miRNA-mediated repression. The only experimental test on endogenous PTEN and PTENP1 mRNA (rather than over-expression of cDNA or miRNA) is represented by Figure 2F-H. It is therefore essential that Figure 2F-H are the focus of the replication study because these are the only experiments that address the central conclusion of . Thank you for the suggestion. We have included Figures 2F-H in the revised manuscript. We are also removing Figures 2A, 2C, and 2D from the replication attempt. 3) The normalization used for the mRNA measurements by and the Registered Report is ACTIN. This is a problem because Actin mRNA is dynamically regulated in cells and is a target of cell signaling pathway. Perhaps the ACTIN measurements can be retained in the replication study, but I would strongly recommend that an independent normalization control is also employed – for example 36B4 or another control gene. Thank you for the suggestion. We have included 36B4 as an additional control gene. We will maintain the original analysis (using ACTIN measurements for normalization) and include an additional exploratory analysis from the original, using 36B4 to normalize the gene expression. 4) The authors adopt two statistical procedures, ANOVA and 2 tailed t-test, in the analysis. However, neither of them is used correctly. Take Protocol 1 as an example. A) In ANOVA, for testing the main effect of siRNA, there are only 3 different levels: siLUC, 19b and 20a, but the numerator degree of freedom of the F-test is stated to be 4 by the authors. I also couldn't follow how the authors got the denominator d.f. to be 20 given there are only 18 observations in total. Thank you for catching this error. We have gone through and checked all calculations. Regarding Protocol 1 in particular, the error with d.f. was an error upon transferring the information to the manuscript. The d.f. of the F-test is indeed (2,12) (3 levels with 18 total measurements). We have corrected any other location where this might have occurred in error. B) In 2 tailed t-test, the effective size calculated by the authors assumed that the two populations have the same variance, which is apparently not true for many pairs according to the data. For example, in the comparison of siLuc PTENP1 and 19b PTENP1, the two sample standard deviations are 0.386 and 0.065, respectively. The former is almost 6-fold of the later. Moreover, given this small sample size, t-test is not recommended unless one is very confident that the two population distributions are normal. Thank you for the comment. We have gone through and included non-parametric comparisons (Wilcoxon-Mann-Whitney) along with the student’s t-tests whenever the standard deviations are large. We have also included a statement in the confirmatory analysis plan where the normality and homoscedasticity of the data will be assessed prior to performing the proposed statistical analysis. We have also included a link to the scripts, other files, and summary of calculations (https://osf.io/cd2yq/?view_only=c9c2497ac93c46b6a8ab786769fcff74). 5) Besides the paper that the authors intend to replicate, the oncosuppressive properties of PTEN 3'UTR have been shown also in Tay et al. ( PTENP1 have been shown in other papers besides , namely and . We have updated the Introduction to reflect a more balanced view of the ceRNA hypothesis. 6) In more general terms, we suggest that the Introduction should include a comprehensive review of all the papers in which the ceRNA-based relationship between PTEN and PTENP1 has been confirmed: Poliseno, L., et al., Deletion of PTENP1 pseudogene in human melanoma. J Invest . Ioffe, Y.J., et al., Phosphatase and tensin homolog (PTEN) pseudogene expression in endometrial cancer: a conserved regulatory mechanism important in tumorigenesis? Gynecol . Johnsson, P., et al., A pseudogene long-noncoding-RNA network regulates PTEN transcription and translation in human cells. Nat Struct Mol . Yu, G., et al., Pseudogene PTENP1 functions as a competing endogenous RNA to suppress clear cell renal cell carcinoma progression. Mol Cancer . Chen, C.L., et al., Suppression of hepatocellular carcinoma by baculovirus-mediated expression of long non-coding RNA PTENP1 and MicroRNA regulation. . Guo, X., et al., Pseudogene PTENP1 Suppresses Gastric Cancer Progression by Modulating PTEN. Anticancer Agents Med . We have included a more balanced discussion of the literature of the ceRNA hypothesis. In the Introduction, we try to focus on the experiments being replicated and any direct replications of them, instead of a comprehensive review of all the literature on this subject, which includes many conceptual or related experiments, which would be more appropriate for a review.
ReagentTypeManufacturerCatalog #Comments
DU145 cellsCell lineATCCHTB-81–
RPMI 1640 mediumCell cultureSigma–AldrichR8758Replaces Invitrogen brand used in original study
Fetal bovine serum (FBS)Cell cultureSigma–AldrichF2442Replaces Invitrogen brand used in original study
L-glutamineCell cultureSigma–AldrichG7513Original brand not specified
100× Penicillin/streptomycinCell cultureSigma–AldrichP4333Original brand not specified
0.05% trypsin/0.48 mM EDTACell cultureSigma–AldrichT3924Original brand not specified
Phosphate buffered saline (PBS), without MgCl2 and CaCl2Cell cultureSigma–AldrichD8537Original brand not specified
12 well tissue culture dishesLabwareCorning3513Original brand not specified
siGLO RISC-free siRNANucleic acidDharmaconD-001600-01–
siGENOME non-targeting siRNA #2 (siLUC)Nucleic acidDharmaconD-001210-02–
miRIDIAN microRNA hsa-miR-19b-3p (si-miR-19b)Nucleic acidDharmaconIH-300489-05-0002–
miRIDIAN microRNA hsa-miR-20a-5p (si-miR20a)Nucleic acidDharmaconIH-300491-05-0002–
Dharmafect 1Cell cultureDharmaconT-2001-01–
PTENP1 forward and reverse primersNucleic acidSpecific brand information will be left up to the discretion of the replicating lab and recorded later
PTEN forward and reverse primersNucleic acid
ACTIN forward and reverse primersNucleic acid
36B4 forward and reverse primersNucleic acid
TRI reagentChemicalSigma–AldrichT9424Replaces Trizol reagent from Invitrogen
1-bromo-3-chloropropaseChemicalSigma–AldrichB9673Reagent needed from TRI reagent protocol
Nuclease free waterChemicalSigma–AldrichW4502Reagent needed from TRI reagent protocol
MicroscopeInstrumentZeiss–Original brand not specified
AxiovisionSoftwareZeiss–Original brand not specified
DNAse I amplification gradeChemicalSigma–AldrichAMPD1Replaces Invitrogen brand used in original study
First-strand cDNA synthesis kit (includes pd(N)6 random hexamers and NotI-(dT)18 primers)KitSigma–AldrichGE27-9261-01Replaces SuperScript II reverse transcriptase from Invitrogen used in original study
QuantiTect Sybr Green PCR kitKitQiagen204141–
Real Time System with a C1000 Thermal CyclerInstrumentBioRadCFX 96Replaces Roche Lightcycler 2.0 used in original study
ReagentTypeManufacturerCatalog #Comments
DU145 cellsCell lineATCCHTB-81–
RPMI 1640 mediumCell cultureSigma–AldrichR8758Replaces Invitrogen brand used in original study
Fetal bovine serum (FBS)Cell cultureSigma–AldrichF2442Replaces Invitrogen brand used in original study
L-glutamineCell cultureSigma–AldrichG7513Original brand not specified
100× Penicillin/streptomycinCell cultureSigma–AldrichP4333Original brand not specified
0.05% trypsin/0.48 mM EDTACell cultureSigma–AldrichT3924Original brand not specified
Phosphate buffered saline (PBS), without MgCl2 and CaCl2Cell cultureSigma–AldrichD8537Original brand not specified
12 well tissue culture dishesLabwareCorning3513Original brand not specified
siGLO RISC-free siRNANucleic acidDharmaconD-001600-01–
siGENOME non-targeting siRNA #2 (siLUC)Nucleic acidDharmaconD-001210-02–
siPTENNucleic acidDharmaconCustomSee Supplemental Figure 6 of original paper for sequence
ON-TARGETplus siPTEN SmartpoolNucleic acidDharmaconL-003023-00Composed of: J-003023-09; J-003023-10; J-003023-11; J-003023-12
siPTENP1Nucleic acidDharmaconCustomSee Supplemental Figure 6 of original paper for sequence
Dharmafect 1Cell cultureDharmaconT-2001-01–
MicroscopeInstrumentOlympusLX81Original brand not specified
Crystal violetDyeSigma–AldrichC0775Original brand not specified
FormalinChemicalSpecific brand information will be left up to the discretion of the replicating lab and recorded later
Acetic acidChemical
MethanolChemical
Spectrophotometer capable of reading at 590 nm (or 595 nm)InstrumentBioTek InstrumentsSynergy 2 (SLFA configuration)Original brand not specified
ReagentTypeManufacturerCatalog #Comments
DU145 cellsCell lineATCCHTB-81–
RPMI 1640 mediumCell cultureSigma–AldrichR8758Replaces Invitrogen brand used in original study
Fetal bovine serum (FBS)Cell cultureSigma–AldrichF2442Replaces Invitrogen brand used in original study
L-glutamineCell cultureSigma–AldrichG7513Original brand not specified
100× Penicillin/streptomycinCell cultureSigma–AldrichP4333Original brand not specified
0.05% trypsin/0.48 mM EDTACell cultureSigma–AldrichT3924Original brand not specified
Phosphate buffered saline (PBS), without MgCl2 and CaCl2Cell cultureSigma–AldrichD8537Original brand not specified
12 well tissue culture dishesLabwareCorning3513Original brand not specified
siGLO RISC-free siRNANucleic acidDharmaconD-001600-01–
siGENOME non-targeting siRNA #2 (siLUC)Nucleic acidDharmaconD-001210-02–
ON-TARGETplus siPTEN SmartpoolNucleic acidDharmaconL-003023-00Composed of: J-003023-09; J-003023-10; J-003023-11; J-003023-12
siPTENNucleic acidDharmaconCustomSee Supplemental Figure 6 of original paper for sequence
siPTENP1Nucleic acidDharmaconCustomSee Supplemental Figure 6 of original paper for sequence
Dharmafect 1Cell cultureDharmaconT-2001-01–
MicroscopeInstrumentOlympusLX81Original brand not specified
ACTIN forward and reverse primersNucleic acidSpecific brand information will be left up to the discretion of the replicating lab and recorded later
PTEN forward and reverse primersNucleic acid
PTENP1 forward and reverse primersNucleic acid
36B4 forward and reverse primersNucleic acid
TRI reagentChemicalSigma–AldrichT9424Replaces Trizol reagent from Invitrogen
1-bromo-3-chloropropaseChemicalSigma–AldrichB9673Reagent needed from TRI reagent protocol
Nuclease free waterChemicalSigma–AldrichW4502Reagent needed from TRI reagent protocol
DNase I amplification gradeChemicalSigma–AldrichAMPD1Replaces Invitrogen brand used in original study
First-strand cDNA synthesis kit (includes pd(N)6 random hexamers and NotI-(dT)18 primers)KitSigma–AldrichGE27-9261-01Replaces SuperScript II reverse transcriptase from Invitrogen used in original study
QuantiTect Sybr Green PCR kitKitQiagen204141–
Real-time PCR machineInstrumentApplied Biosystems7500Replaces Lightcycler 2.0 from Roche used in original study
ReagentTypeManufacturerCatalog #Comments
DU145 cellsCell lineATCCHTB-81–
RPMI 1640 mediumCell cultureSigma–AldrichR8758Replaces Invitrogen brand used in original study
Fetal bovine serum (FBS)Cell cultureSigma–AldrichF2442Replaces Invitrogen brand used in original study
L-glutamineCell cultureSigma–AldrichG7513Original brand not specified
100× Penicillin/streptomycinCell cultureSigma–AldrichP4333Original brand not specified
0.05% trypsin/0.48 mM EDTACell cultureSigma–AldrichT3924Original brand not specified
Phosphate buffered saline (PBS), without MgCl2 and CaCl2Cell cultureSigma–AldrichD8537Original brand not specified
6 well tissue culture dishesLabwareCorning3516Original brand not specified
siGLO RISC-free siRNANucleic acidDharmaconD-001600-01–
siGENOME non-targeting siRNA #2 (siLUC)Nucleic acidDharmaconD-001210-02–
ON-TARGETplus siPTEN SmartpoolNucleic acidDharmaconL-003023-00Composed of: J-003023-09; J-003023-10; J-003023-11; J-003023-12
siPTENNucleic acidDharmaconCustomSee Supplemental Figure 6 of original paper for sequence
siPTENP1Nucleic acidDharmaconCustomSee Supplemental Figure 6 of original paper for sequence
Dharmafect 1Cell cultureDharmaconT-2001-01–
MicroscopeInstrumentOlympusLX81Original brand not specified
Rabbit anti-PTEN (clone 138G6) monoclonal antibodyAntibodiesCell Signaling9559–
Mouse anti-Hsp90 (clone 68) antibodyAntibodiesBecton Dickinson610419Original catalog number not specified
Secondary antibody (anti-rabbit IgG)AntibodiesCell Signaling7074Original brand not specified
Secondary antibody (anti-mouse IgG)AntibodiesCell Signaling7076Original brand not specified
ECL DualVue Western Markers (15–150 kDa)Western blot reagentSigma–AldrichGERPN810Original brand not specified
TrisChemicalSpecific brand information will be left up to the discretion of the replicating lab and recorded later
EDTAChemical
MgCl2Chemical
NaClChemical
NP40Chemical
β-glycerophsphateChemical
NaVO4Chemical
NaFChemical
Protease inhibitor cocktail (mammalian)InhibitorSigma–AldrichP8340Original brand not specified
SonifierInstrumentBranson Digitaln/aOriginal brand not specified
Bradford ReagentReporter assaySigma–AldrichB6916Original brand not specified
TruPAGE LDS sample buffer (4×)BufferSigma–AldrichPCG3009Original brand not specified
TruPAGE DTT sample reducer (10×)BufferSigma–AldrichPCG3005–
XCell SureLOCK Mini-cell systemInstrumentLife Technologiesn/aOriginal brand not specified
4–12% TruPAGE SDS-PAGE gelWestern blot reagentSigma–AldrichPCG2003Replaces NuPage gels
TruPAGE TEA-Tricine SDS running buffer (20×)BufferSigma–AldrichPCG3001Original brand not specified
Xcell II Blot ModuleInstrumentLife Technologiesn/aOriginal brand not specified
Hybond ECL nitrocellulose membraneWestern blot reagentSigma–AldrichGERPN2020DOriginal brand not specified
TruPAGE transfer buffer (20×)BufferSigma–AldrichPCG3011Original brand not specified
Ponceau S solutionBufferSigma–AldrichP7170–
10× Tris buffered saline (TBS)BufferSigma–AldrichT5912Original brand not specified
ECL Prime Western blotting systemDetection assaySigma–AldrichGERPN2232Original brand not specified
Image JSoftwareNIHVersion 10.2–
ReagentTypeManufacturerCatalog #Comments
DU145 cellsCell lineATCCHTB-81–
RPMI 1640 mediumCell cultureSigma–AldrichR8758Replaces Invitrogen brand used in original study
Fetal bovine serum (FBS)Cell cultureSigma–AldrichF2442Replaces Invitrogen brand used in original study
L-glutamineCell cultureSigma–AldrichG7513Original brand not specified
100× Penicillin/streptomycinCell cultureSigma–AldrichP4333Original brand not specified
0.05% trypsin/0.48 mM EDTACell cultureSigma–AldrichT3924Original brand not specified
Phosphate buffered saline (PBS), without MgCl2 and CaCl2Cell cultureSigma–AldrichD8537Original brand not specified
60 mm tissue culture dishesLabwareCorning430166Original brand not specified
Endo-free maxiprep kitKitSigma–AldrichNA0400–
pCMV (empty vector)DNA constructOriginal labn/aFrom original lab
pCMV/PTEN 3′ UTRDNA constructOriginal labn/aFrom original lab
EffecteneCell cultureQiagen301425Original brand not specified
PTENP1 forward and reverse primersNucleic acidSpecific brand information will be left up to the discretion of the replicating lab and recorded later
ACTIN forward and reverse primersNucleic acid
36B4 forward and reverse primersNucleic acid
TRI reagentChemicalSigma–AldrichT9424Replaces Trizol reagent from Invitrogen
1-bromo-3-chloropropaseChemicalSigma–AldrichB9673Reagent needed from TRI reagent protocol
Nuclease free waterChemicalSigma–AldrichW4502Reagent needed from TRI reagent protocol
DNAse I amplification gradeChemicalSigma–AldrichAMPD1Replaces Invitrogen brand used in original study
First-strand cDNA synthesis kit (includes pd(N)6 random hexamers and NotI-(dT)18 primers)KitSigma–AldrichGE27-9261-01Replaces SuperScript II reverse transcriptase from Invitrogen used in original study
QuantiTect Sybr Green PCR kitKitQiagen204141–
Real-time PCR systemInstrumentApplied Biosystems7500 FastReplaces Roche Lightcycler 2.0 used in original study
ReagentTypeManufacturerCatalog #Comments
DU145 cellsCell lineATCCHTB-81–
RPMI 1640 mediumCell cultureSigma–AldrichR8758Replaces Invitrogen brand used in original study
Fetal bovine serum (FBS)Cell cultureSigma–AldrichF2442Replaces Invitrogen brand used in original study
L-glutamineCell cultureSigma–AldrichG7513Original brand not specified
100× Penicillin/streptomycinCell cultureSigma–AldrichP4333Original brand not specified
0.05% trypsin/0.48 mM EDTACell cultureSigma–AldrichT3924Original brand not specified
Phosphate buffered saline (PBS), without MgCl2 and CaCl2Cell cultureSigma–AldrichD8537Original brand not specified
60 mm tissue culture dishesLabwareCorning430166Original brand not specified
pCMV (empty vector)DNA constructOriginal labn/aFrom original lab
pCMV/PTEN 3′ UTRDNA constructOriginal labn/aFrom original lab
EffecteneCell cultureQiagen301425Original brand not specified
12 well tissue culture dishesLabwareCorning3513Original brand not specified
Crystal violetDyeSigma–AldrichC0775Original brand not specified
FormalinChemicalSpecific brand information will be left up to the discretion of the replicating lab and recorded later
Acetic acidChemical
MethanolChemical
Spectrophotometer capable of reading at 590 nm (or 595 nm)InstrumentAlamolabsOriginal brand not specified
siRNAmRNAMeanStdevN
siLUCPTEN1.000.2393
PTENP11.000.3863
19bPTEN0.2860.0853
PTENP10.2340.0653
20aPTEN0.4580.1673
PTENP10.2500.0803
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLuc PTEN mRNA19b PTEN mRNA3.9855591.9%*4*4*
siLuc PTEN mRNA20a PTEN mRNA2.6299988.3%66
siLuc PTENP1 mRNA19b PTENP1 mRNA2.7653280.7%†5†5†
siLuc PTENP1 mRNA20a PTENP1 mRNA2.6890889.8%66

6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 99.9%.

6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 91.6%.

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, 19b, 20a (PTEN and PTENP1 mRNA for all)F(2,12) = 23.1978 (main effect: siRNA)0.794511.9662996.3%*9* (6 groups)

36 total samples (6 per group) will be used based on the planned comparisons making the power 99.9%.

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLuc PTEN mRNA19b PTEN mRNA3.9855594.2%*4*4*
siLuc PTEN mRNA20a PTEN mRNA2.6299990.6%66
siLuc PTENP1 mRNA19b PTENP1 mRNA2.7653284.0%†5†5†
siLuc PTENP1 mRNA20a PTENP1 mRNA2.6890881.6%‡5‡5‡

6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 99.9%.

6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 93.4%.

6 samples per group will be used based on the siLuc to 20a PTEN comparison making the power 91.9%.

siRNADayMeanStdevN
siLuc01.00003
10.9550.1083
20.9280.1083
31.2520.1083
41.3150.1083
51.6040.1083
siPTEN01.00003
11.1980.1083
21.3060.1083
32.0450.1083
42.4140.1083
54.1530.2343
siPTENP101.00003
11.1620.1083
21.0990.1083
31.6130.1083
41.7750.1083
52.6130.1083
siPTEN/PTENP101.00003
11.1980.1083
21.3870.1083
32.3960.1083
43.0990.1083
55.4140.1713
siRNADaysMeanStdevN
siLuc0, 1, 2, 3, 4, 55.7520.4863
siPTEN0, 1, 2, 3, 4, 59.5410.5503
siPTENP10, 1, 2, 3, 4, 57.4550.4863
siPTEN/PTENP10, 1, 2, 3, 4, 511.2880.5183
GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1F(1,8) = 798.9603 (main effect: siPTEN)0.990099.9933792.0%*5* (4 groups)
F(1,8) = 143.7867 (main effect: siPTENP1)0.947294.2394899.5%*6* (4 groups)

16 total samples (4 per group) will be used based on the planned comparisons making the power 99.9%.

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1F(1,8) = 166.9731 (main effect: siPTEN)0.954284.5685799.8%*6* (4 groups)
F(1,8) = 34.2219 (main effect: siPTENP1)0.810532.0682793.9%*7* (4 groups)

16 total samples (4 per group) will be used based on the planned comparisons making the power 99.9%.

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLucsiPTEN15.5499491.1%*2*2*
siLucsiPTENP16.1540491.1%*3*3*
siLucsiPTEN/PTENP123.2424999.9%*2*2*
siPTEN/PTENP1siPTEN7.6925599.4%*3*3*
siPTEN/PTENP1siPTENP117.0884594.6%*2*2*

5 samples per group will be used based on the AUC calculation planned comparisons making the power 99.9%.

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLucsiPTEN7.4163699.1%*3*3*
siLucsiPTENP13.3333993.8%55*
siLucsiPTEN/PTENP110.8379499.9%*3*3*
siPTEN/PTENP1siPTEN3.4215881.3%†4†4†
siPTEN/PTENP1siPTENP17.5045499.3%*3*3*

5 samples per group will be used based on the siLuc to siPTENP1 comparison making the power 99.9%.

5 samples per group will be used based on the siLuc to siPTENP1 comparison making the power 95.0%.

siRNAmRNAMeanStdevN
siLUCPTEN1.0000.2493
PTENP11.0000.1553
siPTENPTEN0.1160.0653
PTENP10.5430.0993
siPTENP1PTEN0.3810.0863
PTENP10.2690.0943
siPTEN/PTENP1PTEN0.1930.0673
PTENP10.4820.1613
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLuc PTEN mRNAsiPTEN PTEN mRNA4.8588496.8%*4*4*
siLuc PTENP1 mRNAsiPTEN PTENP1 mRNA3.5253793.1%55
siLuc PTEN mRNAsiPTENP1 PTEN mRNA3.3226789.7%55
siLuc PTENP1 mRNAsiPTENP1 PTENP1 mRNA5.7074583.9%†3†3†
siLuc PTEN mRNAsiPTEN/PTENP1 PTEN mRNA4.4265893.2%‡4‡4‡
siLuc PTENP1 mRNAsiPTEN/PTENP1 PTENP1 mRNA3.2758588.7%55

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.8%.

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.9%.

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.3%.

GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1 (PTEN and PTENP1 mRNA for all)F(3,16) = 36.6570 (main effect: siRNA)0.872992.6216894.9%*11* (8 groups)

40 total samples (5 per group) will be used based on the planned comparisons making the power 99.9%.

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLuc PTEN mRNAsiPTEN PTEN mRNA4.8588498.1%*4*4*
siLuc PTENP1 mRNAsiPTEN PTENP1 mRNA3.5253780.8%†4†4†
siLuc PTEN mRNAsiPTENP1 PTEN mRNA3.3226792.2%55
siLuc PTENP1 mRNAsiPTENP1 PTENP1 mRNA5.7074589.1%‡3‡3‡
siLuc PTEN mRNAsiPTEN/PTENP1 PTEN mRNA4.4265895.4%§4§4§
siLuc PTENP1 mRNAsiPTEN/PTENP1 PTENP1 mRNA3.2758591.4%55

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.9%.

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 95.1%.

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.9%.

5 samples per group will be used based on the siLuc to siPTENP1 PTEN comparison making the power 99.6%.

siRNARelative PTEN signal
siLuc1.00
siPTEN0.50
siPTENP10.60
siPTEN/PTENP10.10
GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1F(1,8) = 4629.6 (main effect: siPTEN)0.9982824.056499.9%8 (4 groups)
F(1,8) = 2963.0 (main effect: siPTENP1)0.9973119.2440499.9%8 (4 groups)
GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1F(1,8) = 82.3050 (main effect: siPTEN)0.911413.2075099.9%8 (4 groups)
F(1,8) = 52.6750 (main effect: siPTENP1)0.868152.5660099.9%8 (4 groups)
GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1F(1,8) = 23.6210 (main effect: siPTEN)0.747001.7183094.5%8 (4 groups)
F(1,8) = 15.1170 (main effect: siPTENP1)0.653941.3746482.4%8 (4 groups)
GroupsF test statisticPartial η2Effect size fA priori powerTotal sample size
siLUC, siPTEN, siPTENP1, siPTEN/PTENP1F(1,8) = 11.5741 (main effect: siPTEN)0.591301.2028195.3%12 (4 groups)
F(1,8) = 7.4074 (main effect: siPTENP1)0.480770.9622583.0%12 (4 groups)
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLucsiPTEN39.2839999.9%22
siLucsiPTENP131.4271999.9%22
siLucsiPTEN/PTENP170.7111899.9%22
siPTEN/PTENP1siPTEN31.4271999.9%22
siPTEN/PTENP1siPTENP139.2839999.9%22
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLucsiPTEN5.2378286.6%33
siLucsiPTENP14.1902686.6%44
siLucsiPTEN/PTENP19.4280899.9%33
siPTEN/PTENP1siPTEN4.1902694.6%44
siPTEN/PTENP1siPTENP15.2378286.6%33
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLucsiPTEN2.8060382.0%55
siLucsiPTENP12.2448284.8%77
siLucsiPTEN/PTENP15.0508584.0%33
siPTEN/PTENP1siPTEN2.2448284.8%77
siPTEN/PTENP1siPTENP12.8060382.0%55
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
siLucsiPTEN1.9641986.9%88
siLucsiPTENP11.5713584.7%1212
siLucsiPTEN/PTENP13.5355491.0%44
siPTEN/PTENP1siPTEN1.5713583.6%1212
siPTEN/PTENP1siPTENP11.9641981.0%88
PlasmidMeanStdevN
pCMV1.0000.5413
pCMV/PTEN 3′ UTR3.8800.7073
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
pCMVpCMV/PTEN 3′ UTR4.5744698.2%33
PlasmidDayMeanStdevN
pCMV01.00003
11.0000.1193
21.2380.1193
31.9170.1193
45.7260.1193
57.1670.1193
pCMV/PTEN 3′ UTR01.00003
11.0000.1193
21.1430.1193
31.9170.1193
44.1550.2143
55.2380.1193
PlasmidDaysMeanStdevN
pCMV0, 1, 2, 3, 4, 513.9640.5363
pCMV/PTEN 3′ UTR0, 1, 2, 3, 4, 511.3330.6313
Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
pCMVpCMV/PTEN 3′ UTR16.2000099.9%2*2*

3 samples per group will be used based on the AUC calculation.

Group 1Group 2Effect size dA priori powerGroup 1 sample sizeGroup 2 sample size
pCMVpCMV/PTEN 3′ UTR4.4952697.9%33
  41 in total

1.  Restoration of wild-type PTEN expression leads to apoptosis, induces differentiation, and reduces telomerase activity in human glioma cells.

Authors:  X X Tian; J C Pang; S S To; H K Ng
Journal:  J Neuropathol Exp Neurol       Date:  1999-05       Impact factor: 3.685

2.  PTEN restoration and PIK3CB knockdown synergistically suppress glioblastoma growth in vitro and in xenografts.

Authors:  Hongbo Chen; Lin Mei; Lanzhen Zhou; Xiaomeng Shen; Caiping Guo; Yi Zheng; Huijun Zhu; Yongqiang Zhu; Laiqiang Huang
Journal:  J Neurooncol       Date:  2010-12-29       Impact factor: 4.130

3.  The PTEN/MMAC1 tumor suppressor induces cell death that is rescued by the AKT/protein kinase B oncogene.

Authors:  J Li; L Simpson; M Takahashi; C Miliaresis; M P Myers; N Tonks; R Parsons
Journal:  Cancer Res       Date:  1998-12-15       Impact factor: 12.701

Review 4.  The functions and regulation of the PTEN tumour suppressor.

Authors:  Min Sup Song; Leonardo Salmena; Pier Paolo Pandolfi
Journal:  Nat Rev Mol Cell Biol       Date:  2012-04-04       Impact factor: 94.444

5.  Competitive endogenous RNAs cannot alter microRNA function in vivo.

Authors:  Jennifer A Broderick; Phillip D Zamore
Journal:  Mol Cell       Date:  2014-06-05       Impact factor: 17.970

6.  Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance.

Authors:  Rémy Denzler; Vikram Agarwal; Joanna Stefano; David P Bartel; Markus Stoffel
Journal:  Mol Cell       Date:  2014-05-01       Impact factor: 17.970

7.  Negative regulation of PKB/Akt-dependent cell survival by the tumor suppressor PTEN.

Authors:  V Stambolic; A Suzuki; J L de la Pompa; G M Brothers; C Mirtsos; T Sasaki; J Ruland; J M Penninger; D P Siderovski; T W Mak
Journal:  Cell       Date:  1998-10-02       Impact factor: 41.582

8.  A microRNA expression signature of human solid tumors defines cancer gene targets.

Authors:  Stefano Volinia; George A Calin; Chang-Gong Liu; Stefan Ambs; Amelia Cimmino; Fabio Petrocca; Rosa Visone; Marilena Iorio; Claudia Roldo; Manuela Ferracin; Robyn L Prueitt; Nozumu Yanaihara; Giovanni Lanza; Aldo Scarpa; Andrea Vecchione; Massimo Negrini; Curtis C Harris; Carlo M Croce
Journal:  Proc Natl Acad Sci U S A       Date:  2006-02-03       Impact factor: 11.205

Review 9.  Genomic Rearrangements of PTEN in Prostate Cancer.

Authors:  Sopheap Phin; Mathew W Moore; Philip D Cotter
Journal:  Front Oncol       Date:  2013-09-17       Impact factor: 6.244

10.  Pten dose dictates cancer progression in the prostate.

Authors:  Lloyd C Trotman; Masaru Niki; Zohar A Dotan; Jason A Koutcher; Antonio Di Cristofano; Andrew Xiao; Alan S Khoo; Pradip Roy-Burman; Norman M Greenberg; Terry Van Dyke; Carlos Cordon-Cardo; Pier Paolo Pandolfi
Journal:  PLoS Biol       Date:  2003-10-27       Impact factor: 8.029
View more
  6 in total

1.  [Role of lncRNA PTENP1 in tumorigenesis and progression of bladder cancer and the molecular mechanism].

Authors:  Gan Yu; Zheng-Yue Ou; Qi-Ye Tao; Guo-Yue Wan; Zong-Hao Lu; Bin Lang
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2017-11-20

Review 2.  Inflamma-miRs in Aging and Breast Cancer: Are They Reliable Players?

Authors:  Cristina Sorina Cătană; George A Calin; Ioana Berindan-Neagoe
Journal:  Front Med (Lausanne)       Date:  2015-12-15

3.  Downregulated lncRNA HOXA11-AS Affects Trophoblast Cell Proliferation and Migration by Regulating RND3 and HOXA7 Expression in PE.

Authors:  Yetao Xu; Dan Wu; Jie Liu; Shiyun Huang; Qing Zuo; Xi Xia; Ying Jiang; Sailan Wang; Yanzi Chen; Tianjun Wang; Lizhou Sun
Journal:  Mol Ther Nucleic Acids       Date:  2018-05-29       Impact factor: 8.886

4.  Pseudogenes, RNAs and new reproducibility norms.

Authors:  George A Calin
Journal:  Elife       Date:  2020-04-21       Impact factor: 8.140

5.  Single nucleotide polymorphisms in the MYLKP1 pseudogene are associated with increased colon cancer risk in African Americans.

Authors:  Heather Lynn; Xiaoguang Sun; Djanybek Ayshiev; Jessica H Siegler; Alicia N Rizzo; Jason H Karnes; Manuel Gonzales Garay; Ting Wang; Nancy Casanova; Sara M Camp; Nathan A Ellis; Joe G N Garcia
Journal:  PLoS One       Date:  2018-08-30       Impact factor: 3.240

6.  Challenges for assessing replicability in preclinical cancer biology.

Authors:  Timothy M Errington; Alexandria Denis; Nicole Perfito; Elizabeth Iorns; Brian A Nosek
Journal:  Elife       Date:  2021-12-07       Impact factor: 8.140
  6 in total

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