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                "content": " that seeks to address 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 (Errington et al., 2014). For each of these papers a Registered Report detailing the proposed experimental designs and protocols for the replications was peer reviewed and published prior to data collection. The present paper is a Replication Study that reports the results of the replication experiments detailed in the Registered Report (Blum et al., 2015) for a 2012 paper by Lin et al., and uses a number of approaches to compare the outcomes of the original experiments and the replications.\n",
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                "content": "In 2012, Lin et al. reported results that the c-Myc transcription factor, a potent oncogene that is frequently overexpressed in a large percentage of cancers, globally amplifies the expression of actively transcribed genes, opposed to regulating specific target genes. Using the P493-6 cell line, a model for ",
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                "content": " activation in Burkitt\u2019s lymphoma, total levels of RNA per cell were reported to increase when c-Myc was highly expressed compared to conditions where c-Myc expression was low. Additionally, active genes in cells with low c-Myc levels were reported to increase in expression upon c-Myc induction, in contrast to genes that were silent under low c-Myc conditions that did not change.\n",
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                "content": "The Registered Report for the 2012 paper by Lin et al. described the experiments to be replicated\u00a0(Figure\u00a01B and 3E\u2013F), and summarized the current evidence for these findings (Blum et al., 2015). Since that publication there have been additional studies investigating the ability c-Myc to influence the global gene expression output of cells. Similar to Lin et al. other studies have reported c-Myc dependent amplification of cellular RNA (Hart et al., 2014; Hsu et al., 2015; Nie et al., 2012; Sab\u00f2 et al., 2014), although this observation was not reported in all biological systems (Fagnocchi et al., 2016; Sab\u00f2 et al., 2014; Walz et al., 2014). It has been suggested c-Myc regulates specific genes that indirectly lead to RNA amplification (Sab\u00f2 et al., 2014; Sab\u00f2 & Amati, 2014; Walz et al., 2014). This has also been suggested of MYCN (Duffy et al., 2015). The reported differences could be a result of the intrinsic variation between cell lines in maintaining the transcriptome (Trakhtenberg et al., 2016). Indeed, a recent study reported that distinct transcriptional regulation can be accounted for by differences in promoter affinity under different c-Myc expression levels (Lorenzin et al., 2016).\n",
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                "content": " transgene (Pajic et al., 2000; Schuhmacher et al., 1999) as the original study. We performed Western blot analysis to confirm c-Myc expression could be reduced to very low levels and then reactivated after removal of tetracycline. This is comparable to what was reported in Figure 1B of (Lin et al., 2012) and described in Protocol 1 in the Registered Report (Blum et al., 2015). Since proliferation of P493-6 cells depend on c-Myc expression and the presence of serum (Pajic et al., 2000; Schuhmacher et al., 1999), with serum reported to stimulate a majority of genes independent of c-Myc (Schlosser et al., 2005), we maintained these cells in separate lots of serum to assess whether the results differed. For cells maintained in both lots of serum, treatment with tetracycline resulted in a strong decrease in c-Myc protein levels\u00a0(",
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                "content": ") Quantification of total RNA levels (ng of total RNA per 1,000 cells) for cells at 0, 1, and 24 hr after release from Tet. Means reported and error bars represent s.e.m. from three independent biological repeats. For serum lot one, one-way ANOVA on total RNA levels of all groups; F(2, 6)=1.25, p=0.353. Planned contrast between 0 hr and 24 hr; t(6) = 1.02, p=0.347 with a priori alpha level\u00a0=\u00a00.05. For serum lot two, one-way ANOVA on total RNA levels of all groups; F(2, 6)=21.87, p=0.00176. Planned contrast between 0 hr and 24 hr; t(6) = 5.03, p=0.0024 with a priori alpha level\u00a0=\u00a00.05. Additional details for this experiment can be found at ",
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                "content": "=0.0024). This compares to the original study, which reported a mean of 4.25 ng/1 k cells at 0 hr, which increased to 5.47 ng/1 k cells at 24 hr, a 1.29 times increase in total RNA levels. In both studies there was a minor decrease at 1 hr after tetracycline release when c-Myc levels begin to become detectable. Total RNA per 1,000 cells at 0 hr were much lower in this replication attempt than those reported in the original study, although changes in total RNA levels were in the same direction following c-Myc expression. Similarly, another independent study that measured total RNA from P493-6 cells reported a different level at 0 hr (~3 ng/1 k cells), while also reporting increased levels following c-Myc expression (Sab\u00f2 et al., 2014). There are multiple possible explanations for these differences, such as variation in RNA expression during cell culture passage (Hiorns et al., 2004), low yield of the RNA isolation procedure (e.g. incomplete homogenization), or the high variance associated with manual cell counts using a hemacytometer (Biggs & Macmillan, 1948; Nielson et al., 1991). To summarize, for this experiment we found results that were in the same direction as the original study and not statistically significant for serum lot one, while statistically significant for serum lot two.\n",
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                "content": "To test whether c-Myc expression amplifies the existing gene expression program, digital gene expression analysis using the NanoString nCounter platform was performed on a set of genes from multiple functional categories. This experiment is similar to what was reported in Figure 3F and Table S1\u00a0of (Lin et al., 2012) and described in Protocols 3\u20134 in the Registered Report (Blum et al., 2015). We quantified mRNA levels/cell of 1369 genes, of which 1212 were the same genes as the 1338 genes interrogated in the original study. We used the same criteria as the original study to classify a gene as silent (expression was less than 0.5 transcript/cell at time 0 hr) or active (more than one transcript/cell at time 0 hr). In cells with low levels of c-Myc (0 hr) there were 708 active genes with a median expression of 4.70, and 580 silent genes with a median expression of 0.032, for serum lot one. For active genes, 75% of the genes increased from 0 hr to 1 hr, 68% increased from 0 hr to 24 hr, and 59% increased from 1 hr to 24 hr upon c-Myc induction. This corresponds to a 1.11, 1.50, and 1.36 times increase in median expression, respectively (",
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                "content": "). For silent genes, 74% of the genes increased from 0 hr to 1 hr, 66% increased from 0 hr to 24 hr, and 50% increased from 1 hr to 24 hr, corresponding to a 1.19 and 1.13 times increase, and a 0.05 times decrease in median expression, respectively (",
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                "content": " cells were collected (number determined with a C-chip disposable hemocytometer) and lysed directly in 100 \u00b5l Buffer RLT (Qiagen, Hilden,\u00a0Germany,\u00a0cat# 79216) supplemented with \u00df-mercaptoethanol to yield a concentration of 10,000 cells per \u00b5l. This was performed four independent times. Multiple 4 \u00b5l aliquots were stored and shipped at \u221280\u00b0C with temperature monitored during shipping to avoid freeze/thaw cycles. Lysates were processed according to the Cell Lysate Protocol (nCounter Gene Expression Assay Manual, NanoString Technologies, Seattle, Washington) according to the manufacturer\u2019s instructions and as described in the Registered Report (Blum et al., 2015). Three nCounter Reporter CodeSets (nCounter GX Human Immunology Kit, nCounter GX Human Kinase Kit, nCounter Custom CodeSet) encompassing 1369 genes across multiple functional categories were used. Following hybridization, samples were immediately processed with the nCounter Analysis System (NanoString Technologies, NCT-PREP-120). The count data was collected using the nCounter RCC Collector Worksheet (NanoString Technologies), version 1.6.0 and then positive-, negative-, and housekeeping gene-normalized per nCounter guidelines. Expression for each gene was averaged across the four independent replicate samples. Additionally, for genes that appeared on multiple CodeSets, expression values were averaged together to generate a single value for each gene. A gene was defined as transcriptionally active if its average expression was above one transcript/cell at 0 hr and transcriptionally silent if below 0.5 transcript/cell. A list of all Reporter CodeSets and their expression values (transcripts/cell) are available at ",
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                "content": "The number of flasks, and thus cells, was increased when tetracycline was added to P493-6 cells to account for the cells not proliferating during this period (i.e. there were two Flask B\u2019s as described in the Registered Report, which were pooled prior to seeding). The proposed statistical analysis for the western blot analysis (Protocol 1) described in the Registered Report was not performed since the levels of normalized c-Myc at time 0 hr was at the limit of detection. The number of genes analyzed in the original study, and thus listed in the Registered Report, was reported incorrectly as 1388 instead of 1338 (data shared by original authors). NanoString analysis was conducted using the nCounter RCC Collector Worksheet instead of nSolver Analysis software. Additionally, the statistical tests reported in\u00a0Figure\u00a03F of the original study incorrectly described the comparisons as between 0 hr and 1 hr instead of between 0 hr and 24 hr (scripts shared by original authors). The corrected values are described above for comparisons and used in the meta-analysis. Additional materials and instrumentation not listed in the Registered Report, but needed during experimentation are also listed.\n",
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