Skip to main content
eLife logoLink to eLife
. 2015 Jun 18;4:e06938. doi: 10.7554/eLife.06938

Registered report: Interactions between cancer stem cells and their niche govern metastatic colonization

Francesca Incardona 1, M Mehdi Doroudchi 1, Nawfal Ismail 1, Alberto Carreno 1, Erin Griner 2, Minyoung Anna Lim 3; Reproducibility Project: Cancer Biology*
Editor: Gordana Vunjak-Novakovic4
PMCID: PMC4470052  PMID: 26086719

Abstract

The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by replicating selected results from a substantial number of high-profile papers in the field of cancer biology published between 2010 and 2012. This Registered report describes the proposed replication plan of key experiments from ‘Interactions between cancer stem cells and their niche govern metastatic colonization’ by Malanchi and colleagues, published in Nature in 2012 (Malanchi et al., 2012). The key experiments that will be replicated are those reported in Figures 2H, 3A, 3B, and S13. In these experiments, Malanchi and colleagues analyze messenger RNA levels of periostin (POSTN) in pulmonary fibroblasts, endothelial cells, and immune cells isolated from mice with micrometastases to determine which cell type is producing POSTN in the metastatic niche (Figure 2H; Malanchi et al., 2012). Additionally, they examine MMTV-PyMT control or POSTN null mice to test the effect of POSTN on primary tumor growth and metastasis (Figures 3A, 3B, and S13; Malanchi et al., 2012). The Reproducibility Project: Cancer Biology is a collaboration between the Center for Open Science and Science Exchange, and the results of the replications will be published in eLife.

DOI: http://dx.doi.org/10.7554/eLife.06938.001

Research organism: mouse

Introduction

Metastatic colonization is a highly inefficient process that only a small subset of disseminated tumor cells accomplish (Nguyen et al., 2009). A growing body of literature suggests that cancer stem cells (CSC), tumor cells with the ability to self-renew and differentiate, play important roles not only in metastatic colonization but also in establishing the metastatic niche to support metastatic colonization (Visvader and Lindeman, 2012). Using the MMTV-PyMT mouse breast cancer model, which spontaneously metastasizes to the lungs, Malanchi and colleagues reported that only the CSC population, identified as CD24+ CD90+, were capable of initiating lung metastases and secondary metastases (Guy et al., 1992; Lin et al., 2003; Malanchi et al., 2012). Additionally, only a subset of the injected CSC population resulted in metastatic nodules. Periostin (POSTN) was identified by microarray RNA profiling studies as a stromal factor involved in maintaining the normal stem cell niche and demonstrated to be secreted by stromal fibroblasts, but not by infiltrating tumor cells (Malanchi et al., 2012). POSTN is a secreted protein that is incorporated in the extracellular matrix and has been associated with metastasis in several human cancers (Conway et al., 2014). The functional necessity of POSTN was investigated by observing the pulmonary metastatic potential in POSTN-knockout MMTV-PyMT mice, which showed a statistically significant decrease compared to controls (Malanchi et al., 2012). This was further demonstrated by observing a rescue in metastatic efficiency by injecting POSTN-deficient tumor cells into wild-type recipient mice (Malanchi et al., 2012). Investigating the mechanism of POSTN-induced metastasis, Malanchi and colleagues reported a decrease in colony formation in vitro with POSTN-deficient tumor cells or wild-type CSCs co-cultured with POSTN-deficient stromal cells, demonstrating the involvement of POSTN in stem cell maintenance (Malanchi et al., 2012). Furthermore, POSTN was reported to bind to Wnt ligands, leading to an increase in Wnt signaling in CSCs, a known regulator of stem cell maintenance in a variety of tissues (Malanchi et al., 2012). Taken together, these results suggest that CSCs are essential for metastatic colonization and that CSCs induce stromal fibroblasts to secrete POSTN in the metastatic niche to support tumor cell outgrowth by augmenting the Wnt signaling pathway.

Malanchi and colleagues' findings suggest that targeting of POSTN in the metastatic niche could potentially be used to treat metastasis. The key experiments included for replication were selected because they examine the induction of POSTN expression in the pulmonary stromal fibroblasts and test the role of POSTN in primary tumor formation and metastatic efficiency, which are relevant as the role of POSTN as a possible prognostic marker and target for anticancer therapies is explored (Xu et al., 2012; Nuzzo et al., 2014). Indeed, treatment of mice with POSTN specific DNA aptamers, single-stranded DNA oligonucleotides designed to bind and inhibit POSTN, was shown to decrease primary tumor growth and metastasis in a xenograft model of mammary tumorigenesis (Lee et al., 2013). Additionally, treatment of ovarian xenograft models with a neutralizing antibody to POSTN resulted in a reduction of metastatic potential and tumor growth, migration, and invasion (Zhu et al., 2011).

Figures 3A, 3B, and Supplemental Figure S13 examine the role of POSTN in primary tumor formation and metastasis utilizing a MMTV-PyMT mouse model of mammary tumor formation. This mouse model develops primary mammary tumors that spontaneously metastasize to the lung (Guy et al., 1992; Lin et al., 2003). MMTV-PyMT+/tg; Postn−/− mice and their Postn+/+ counterparts were analyzed for primary tumor formation and metastasis. Primary tumor size was measured by weight, and the number of metastases was determined by counting lung metastatic lesions. Malanchi and colleagues reported in Figures 3A and S13A that POSTN does not affect the size of the primary tumors, but MMTV-PyMT+/tg; Postn−/− mice develop significantly fewer metastases than their Postn+/+ counterparts (Malanchi et al., 2012). The importance of stromal POSTN was also demonstrated in another study in which orthotopic inoculation of gastric cancer cells into Rag2−/−; Postn−/− mice reduced tumor size, decreased invasiveness, and decreased growth compared to Rag2−/−; Postn+/+ mice (Kikuchi et al., 2014). Additionally, overexpression of POSTN in human mammary epithelial and breast cancer cells resulted in enhanced tumor growth and metastasis (Wang et al., 2013), which is similar to a colon cancer cell model where overexpression of POSTN resulted in an increase in the number and size of liver metastases (Bao et al., 2004). The experiment reported in Figures 3A, 3B, and Supplemental Figure S13 will be replicated in Protocol 1.

Malanchi and colleagues show that POSTN is expressed primarily in fibroblasts and to a lesser extent in endothelial cells but is not expressed in immune cells at sites of metastasis (Malanchi et al., 2012). This was determined by FACS sorting cells from lungs with macrometastases to isolate CD34+/CD31 pulmonary fibroblasts, CD31+ endothelial cells, and CD45+ immune cells. Quantitative PCR of messenger RNA extracted from each of these cell populations was then used to determine the relative expression of POSTN in each cell type as reported in Figure 2H (Malanchi et al., 2012). RNA in situ hybridization and immunostaining showed similar results (Malanchi et al., 2012). Similarly, another study used immunohistochemistry and immunofluorescence to show that POSTN was localized to stromal fibroblasts in human samples of advanced gastric cancer (Kikuchi et al., 2014). Yet, another study utilized tandem mass spectrometry and immunofluorescence to find POSTN concentrated in the extracellular matrix surrounding sites of neovascularization of micrometastases and within the tips of endothelial cells involved in the neovascularization (Ghajar et al., 2013). The experiment reported in Figure 2H will be replicated in Protocol 2.

Materials and methods

Protocol 1: tumor size and metastases of MMTV-PyMT+/tg; Postn+/+ and MMTV-PyMT+/tg; Postn−/− mice

This experiment examines the requirement of POSTN in metastatic colonization using the MMTV-PyMT mouse model. Female mice carrying the MMTV-PyMT transgene that are either Postn+/+ or Postn−/− will be examined for changes in primary tumor size and the number of spontaneously formed pulmonary macrometastases, which is a replication of the experiment reported in Figures 3A, 3B, and Supplemental Figure 13. This experiment will also generate lung tissue from MMTV-PyMT+/tg; Postn+/+ female mice that are positive with metastatic disease for use in Protocol 2.

Sampling

  • ■ Experiment has 2 cohorts:

    • ◯ Cohort 1: MMTV-PyMT+/tg; Postn+/+ female mice.

    • ◯ Cohort 2: MMTV-PyMT+/tg; Postn−/− female mice.

  • ■ Experiment will use the following number of mice per cohort:

    • ◯ Cohort 1: 14 mice.

    • ◯ Cohort 2: 15 mice.

      • Note: Derive mice from consecutive litters and analyze development of tumors and metastases until the two cohorts reach the indicated numbers.

  • ■ To account for outlier data, as presented in the original publication, 5% and 10% more mice were added to each cohort, respectively, to ensure at least 13 mice survive each cohort for a minimum power of 80%.

    • ◯ See ‘Power calculations’ section for details.

Materials and reagents

Reagent Type Manufacturer Catalog # Comments
MMTV-PyMT+/tg; Postn+/− FVB male mouse Animal model Original lab n/a From original lab
MMTV-PyMT+/tg; Postn−/− FVB male mouse Animal model Original lab n/a From original lab
Postn−/− FVB female mice Animal model Original lab n/a From original lab
Postn+/+ FVB female mice Animal model Charles River Strain code: 207 Original was from France
PureGenome tissue DNA extraction kit Kit EMD Millipore 72635 Original not specified
MMTV-PYVT384 primer Nucleic acid Sequences provided by original authors; specific brand information will be left up to the discretion of the replicating lab and recorded later
MMTV-PYVT385 primer Nucleic acid
Postn-5′ primer Nucleic acid
Postn-3′ primer Nucleic acid
INT-as primer Nucleic acid
dNTPs (10 mM) Chemical Sigma–Aldrich D7295 Included during communication with authors. Original brand not specified
Taq-polymerase (with tubes of 10× PCR buffer and 25 mM MgCl2) Enzyme Sigma–Aldrich D4545 Included during communication with authors. Original brand not specified
PCR system Equipment Applied Biosystems StepOne Original not specified
Isoflurane Chemical Specific brand information will be left up to the discretion of the replicating lab and recorded later
StereoZoom stereomicroscope, zoom range 0.8×–4.0× Instrument Bausch & Lomb n/a Original a Leica M205 FA

Procedure

  1. Breed MMTV-PyMT+/tg; Postn+/− or MMTV-PyMT+/tg; Postn−/− male mice with Postn+/+ and Postn−/− female mice to obtain MMTV-PyMT+/tg; Postn+/+ control and MMTV-PyMT+/tg; Postn−/− experimental female mice, respectively.

    • a. Do not use MMTV-PyMT female mice for breeding as they develop mammary tumors. Additionally, MMTV-PyMT+/tg males cannot be crossed with MMTV-PyMT+/tg females as the progeny will have a double dose of the oncogene and develop extremely aggressive tumors that cannot be used in this study.

    • b. For generation of the MMTV-PyMT+/tg; Postn−/− experimental female mice, male MMTV-PyMT+/tg; Postn−/− male mice will be crossed with Postn−/− female mice.

    • c. For generation of the MMTV-PyMT+/tg; Postn+/+ control female mice, the MMTV-PyMT+/tg; Postn+/− male mouse will be crossed to Postn+/+ female mice to obtain MMTV-PyMT+/tg; Postn+/+ male mice that will then be crossed with Postn+/+ female mice.

    • d. As mice obtained were found to contain agents, cross-foster rederivation of mice will be performed based on the following procedure (Artwohl et al., 2008). Donor dam will be placed with male mice 5 days a week Monday afternoon to Friday morning and plugs will be checked daily. When dam is found plugged, she should be single housed and date of plug will be recorded as a sign of pregnancy. Once the pregnancy is confirmed, a timed pregnant mouse will be ordered to use as a foster recipient. Foster recipients will ideally have a different fur coat color than the donor dam, so the identification of the fostered pups will be easier. Consequently, the donor and recipient dams will be removed from their cages and placed in separate clean cages. The litter to be fostered will gently be picked up and cleaned with alcohol and passed to a clean tech to be mixed with dirty bedding, nestlet, and other pups from the recipient dam's cage. When mixing the pups, they will be gently arranged in the palm of the hand, in contact with nestlet and bedding from the recipient dam's cage to transfer the recipient dam's scent. All pups will be placed back in the nest and the recipient dam will be returned to the cage. The cage will be monitored visually every 15 min for the first hour; if there is evidence of rejection by the dam (agitation, carrying the pups around), the pups will be removed from the cage and humanely euthanized. The cages will be visually assessed at least twice daily and will not be disturbed for the first 72 hr after fostering in order to avoid any potential cannibalism. All experimental animals will not be treated with Ivermectin or Fenbendazole, as these could change a number of immune parameters affecting tumor growth and take rate.

  2. Extract genomic DNA from mouse tail snips using DNA extraction kit following manufacturer instructions.

    • a. From manufacturer's instructions follow ‘Solid Tissue’ assay protocol.

  3. Genotype mice by PCR with MMTV-PyMT and Postn primers.

    • a. MMTV-PYVT384 primer: GGA AGC AAG TAC TTC ACA ACG G.

      • i. This primer is one nucleotide different than what is listed on the Jackson Laboratory information for stock number 002374 (FVB/N-Tg(MMTV-PyVT)634Mul/J), but is used successfully by the original lab.

    • b. MMTV-PYVT385 primer: GGA AAG TCA CTA GGA GCA GGG.

    • c. Postn-5′ primer: GGT GCT TCT GTA AGG CCA TC.

    • d. Postn-3′ primer: GTG AGC CAG GAC CTT GTC ATA.

    • e. INT-as primer: AGC ACT GAC TGC GTT AGC AA.

    • f. Genotyping will be determined by examining both amplicon size and presence.

      • i. MMTV-PyMT conditions (oncogene = 556 bp band):
        10× PCR buffer 1.50 µl
        50 mM MgCl2 0.45 µl
        10 mM dNTPs 0.30 µl
        MMTV-PYVT384 primer 0.10 µl
        MMTV-PYVT385 primer 0.10 µl
        Taq-polymerase 0.20 µl
        H2O Bring up to 13 µl
        DNA (1:20 dilution) 2 µl
        • Cycling parameters:

          1. 94°C pause.

          2. 94°C for 3 min.

          3. 12 cycles of:

            • i. 96°C for 20 s.

            • ii. 64°C for 30 s.

            • iii. 72°C for 65 s.

          4. 25 cycles of:

            • i. 94°C for 20 s.

            • ii. 58°C for 30 s.

            • iii. 72°C for 35 s.

          5. 72°C for 2 min.

          6. 20°C pause.

      • ii. Postn conditions (WT = 245 bp band; KO = 182 bp band):
        10× PCR buffer 1.50 µl
        50 mM MgCl2 0.45 µl
        10 mM dNTPs 0.30 µl
        Postn-5′ primer 0.10 µl
        Postn-3′ primer 0.10 µl
        INT-as primer 0.10 µl
        Taq-polymerase 0.20 µl
        H2O Bring up to 13 µl
        DNA (1:20 dilution) 2 µl
        • Cycling parameters:

          1. 94°C pause.

          2. 94°C for 1 min.

          3. 45 cycles of:

            • i. 96°C for 6 s.

            • ii. 59°C for 20 s.

            • iii. 72°C for 30 s.

          4. 20°C pause.

  4. Separate and image amplicons by agarose gel electrophoresis.

  5. Monitor MMTV-PyMT+/tg; Postn+/+ and MMTV-PyMT+/tg; Postn−/− female mice for tumor development and keep until tumor disease is fully developed and the metastatic disease is estimated to occur.

    • a. Record age of mice when palpable tumors are detected.

      • i. Multiple tumors will form and grow until they reach a significant size.

    • b. Monitor health status of mice. If mice have to be euthanized prior to reaching fully developed primary tumors exclude mice from study and record reason for euthanasia.

    • c. Tumor disease is fully developed when primary tumors have developed in all mammary glands with an average weight around 1 g per tumor.

      • i. Both cohorts of mice will develop tumors approximately within 3–4 months of age and up to 6 months.

      • ii. Record mice with tumors that are large and form close to the neck as these may give metastasis more efficiently.

    • d. Record age of mice when sacrificed and determine time gap between detection and fully developed tumor.

      • i. Method of euthanasia is isoflurane overexposure (2–5% at 1 l/min) followed by cervical dislocation.

  6. Dissect primary tumor and lung tissue from mice.

    • a. Weigh primary tumors.

      • i. Record total weight of all primary tumors together for each mouse.

      • ii. Record the number of primary tumors for each mouse.

      • iii. Divide total weight of all primary tumors by number of primary tumors to obtain a reference primary tumor weight for each mouse.

  7. Dissect lungs and blindly count the number of macrometastatic nodules on every side of all separated lobes of the lung using a stereomicroscope.

    • a. Do not fix or stain tissues.

    • b. Quickly count large macrometastatic nodules (≥1 mm in diameter) on all sides.

  8. Immediately after counting macrometastasis, use the first six lungs identified from MMTV-PyMT+/tg;Postn+/+ female mice that are positive with metastatic disease for further analysis (Protocol 2).

    • a. Should be approximately 5–6 months of age.

      • i. Exclude lungs from mice that are euthanized before this age.

    • b. Use mice with detectable metastatic disease and record number of macrometastases in each lung used and the total weight of the primary mammary tumors.

Deliverables
  • ■ Data to be collected:

    • ◯ Mouse health records (age of palatable tumor detection, reason for early euthanasia and exclusion of mice, age of mice with fully developed tumor when sacrificed, mice with large tumors formed close to the neck).

    • ◯ Gel images of PCR genotyping (Compare to Figure S10).

    • ◯ Number of primary tumors formed and total weight of all tumors for each mouse.

    • ◯ Raw numbers and box and whisker plot of weight of primary tumors (total weight divided by number of primary tumors) for each mouse. (Compare to Figure 3A and S13).

    • ◯ Raw numbers of pulmonary macrometastases for each mouse (Compare to Figure 3B and S13).

    • ◯ Box and whisker plot of number of pulmonary macrometastases for each mouse. (Compare to Figure 3B and S13).

  • ■ Sample delivered for further analysis:

    • ◯ Lungs for FACS and qRT-PCR analysis for Protocol 2.

Confirmatory analysis plan

The original paper reported outliers in each cohort of mice. As these appear to have not been included in the original analysis, we will also remove any outliers from the analysis for comparison. But the analysis will also be performed with all data values. Outliers are determined as 1.5 times the interquartile range.

This replication attempt will perform the following statistical analysis listed below:

  • ■ Statistical analysis:

    • ◯ Primary tumor weight in MMTV-PyMT+/tg;Postn+/+ mice relative to MMTV-PyMT+/tg;Postn−/− mice.

      • Unpaired two-tailed t-test.

    • ◯ Number of pulmonary macrometastases in MMTV-PyMT+/tg;Postn+/+ mice relative to MMTV-PyMT+/tg;Postn−/− mice.

      • Unpaired two-tailed t-test.

    • ◯ The replication attempt will also perform negative binomial regression analysis of the macrometastases count data.

  • ■ Meta-analysis of effect sizes:

    • ◯ Compute the effect sizes of each comparison, compare them against the reported effect size in the original paper, and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.

Known differences from the original study

The mice in the original study were from an 8th generation backcross to the FVB line, thus it was on a mixed background, while the mice used in the replication will be from a pure 10th generation backcross to the FVB line. This may make a difference in the effect size and will be included in the discussion of the results of the replication. Additionally, mice will undergo cross-foster rederivation to attempt to remove agents currently associated with the mice. All known differences of materials and reagents 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

Mice will undergo cross-foster rederivation to attempt to remove agents currently associated with the mice that could alter immune parameters affecting tumor growth and take rate. All data obtained from the experiment—raw data, data analysis, control data, and quality control data—will be made publicly available, either in the published manuscript or as an open access data set available on the Open Science Framework project page for this study (https://osf.io/vseix).

Protocol 2: POSTN expression in lung stroma with macrometastases

This experiment uses quantitative PCR to detect the expression level of POSTN in CD34+/CD31 pulmonary fibroblasts, CD31+ endothelial cells, and CD45+ immune cells isolated from lungs of mice with macrometastases, which is a replication of the experiment reported in Figure 2H.

Sampling

  • ■ Experiment will use six lungs for a minimum power of 82%.

    • ◯ See appendix for detailed power calculations.

  • ■ Each lung will be isolated into 3 cohorts:

    • ◯ Cohort 1: CD34+/CD31 pulmonary fibroblasts from MMTV-PyMT+/tg;Postn+/+ mice.

    • ◯ Cohort 2: CD31+ endothelial cells from MMTV-PyMT+/tg;Postn+/+ mice.

    • ◯ Cohort 3: CD45+ immune cells from MMTV-PyMT+/tg;Postn+/+ mice.

      • Each cohort will be sorted using the following antibodies:

        • ◯ CD45.

        • ◯ CD31.

        • ◯ CD34.

        • ◯ Isotype controls.

        • ◯ Unstained control.

  • ■ Each cohort will be analyzed for the following gene expression levels:

    • ◯ POSTN.

    • ◯ GAPDH.

Materials and reagents

Reagent Type Manufacturer Catalog # Comments
50 ml tubes Labware Sigma–Aldrich CLS430290 Originally not specified
Hank's balanced salt solution (HBSS) Buffer Sigma–Aldrich H6648 Included during communication with authors. Original brand not specified
Liberase TM Enzyme Roche 05401127001
Liberase TH Enzyme Roche 05401151001
DNase Enzyme Sigma–Aldrich DN25
Phosphate buffered saline (PBS) without MgCl2 and CaCl2 Buffer Sigma–Aldrich D8537 Original brand not specified
EDTA Chemical Included during communication with authors. Specific brand information will be left up to the discretion of the replicating lab and recorded later
Bovine serum albumin (BSA) Chemical Sigma–Aldrich A3803 Included during communication with authors. Original brand not specified
100 µm cell strainer Labware Corning 431752 Original brand not specified
2.5 ml syringe Labware Included during communication with authors. Specific brand information will be left up to the discretion of the replicating lab and recorded later
Fetal bovine serum (FBS) Cell culture Sigma–Aldrich F0392 Original brand not specified
Polypropylene (opaque) FACS tubes Labware Specific brand information will be left up to the discretion of the replicating lab and recorded later
CD45 (clone 30-F11) PE-Cy5.5 antibody (rat IgG2b, kappa) Antibodies eBioscience 35-0451-80 Use at 1:300
CD31 (clone 390) Pac.Blue antibody (rat IgG2a, kappa) Antibodies Invitrogen RM5228 Use at 1:200
CD34 (clone RAM34) PE antibody (rat IgG2a, kappa) Antibodies BD Pharmingen 551387 Use at 1:50
Rat IgG2b, kappa isotype control PE-Cy5.5 Antibodies eBioscience 35-4031 Use at 1:300 dilution. Originally not specified
Rat IgG2a, kappa isotype control Pac.Blue Antibodies Invitrogen R2a28 Use at 1:200 dilution. Originally not specified
Rat IgG2a, kappa isotype control PE Antibodies BD Pharmingen 553930 Use at 1:50 dilution. Originally not specified
7AAD Chemical BioLegend 420403 Use at 1:1000. Original brand not specified
Flow cytometric cell sorter Instrument BD Pharmingen FACSAria II Original from Beckman Coulter
FlowJo Software
TRI reagent Chemical Sigma–Aldrich T9424 Replaces RNA extraction kit from Qiagen
Oligo dT (18) Nucleic acid Life Technologies SO132 Included during communication with authors. Original brand not specified
Oligo dT (23), Anchored Nucleic acid Sigma–Aldrich O4387 Included during communication with authors. Original was Oligo dT (24). Original brand not specified
dNTPs (10 mM) Chemical Sigma–Aldrich D7295 Included during communication with authors. Original brand not specified
25 mM MgCl2 Chemical Sigma–Aldrich M8787 (part of Sigma–Aldrich D4545 from Protocol 1) Included during communication with authors. Original brand not specified
Superscript II (with tube of 5× buffer and 100 mM DTT) Enzyme Life Technologies 18064-014 Included during communication with authors
RNase inhibitor Enzyme Sigma–Aldrich R1274 Included during communication with authors. Original was RNasin
POSTN 5′ primer Nucleic acid Sequences provided by original authors; specific brand information will be left up to the discretion of the replicating lab and recorded later
POSTN 3′ primer Nucleic acid
GAPDH 5′ primer Nucleic acid
GAPDH 3′ primer Nucleic acid
Power SYBR green PCR master mix Buffer Life Technologies 4368577
Real-time PCR system Equipment Applied Biosystems StepOne Original was from Roche or a StepOnePlus from Applied Biosystems

Procedure

Note:

  • These metastatic positive lungs from MMTV-PyMT+/tg; Postn+/+ female mice come from Protocol 1.

  1. Mince lungs with bended scissors to smooth paste without any clumps and transfer to tube.

    • a. Keep each set of lungs separate (do not pool).

  2. Incubate tissue in 6× volume of digestion solution for 1 hr at 37°C with the tube horizontal and shaking at 100 rpm.

    • a. Digestion solution: HBSS supplemented with 0.4 U/ml liberase TM, 0.4 U/ml liberase TH, and 25 µg/ml DNase.

      • i. Liberase TM: stock solution = 26 U/ml = 5 mg/ml; store at −20°C; use at 1:66 dilution.

      • ii. Liberase TH: stock solution = 26 U/ml = 5 mg/ml; store at −20°C; use at 1:66 dilution.

      • iii. DNase: stock solution = 10 mg/ml in PBS; store at −20°C; use at 1:400 dilution.

  3. Pellet cells at 180×g for 5 min at room temperature.

  4. Resuspend cells in cold MACS buffer and filter through 100-µm cell strainer using a rubber tip of 2.5 ml syringe to smash remaining tissue pieces.

    • a. MACS buffer: 2 mM EDTA in PBS supplemented with 0.5% BSA.

  5. Wash strainer extensively with MACS buffer to collect all cells and pellet cells at 180×g for 5 min.

  6. Wash twice in MACS buffer, pelleting cells at 180×g for 5 min between washes.

  7. Pellet cells at 180×g for 5 min, wash once in FACS buffer and pellet cells at 180×g for 5 min.

    • a. FACS buffer: 3% FBS in PBS.

  8. Resuspend up to 5 × 107 cells total in FACS buffer at 2 × 107 cells/ml in polypropylene (opaque) FACS tubes.

  9. Either add antibodies directly, or add antibody dilution mixes, and incubate on ice for 30 min in the dark (if staining high amount of cells put on roller at 4°C).

    • a. CD45-PE·Cy5.5 (use at 1:300 dilution).

    • b. CD31-Pac.Blue (use at 1:200 dilution).

    • c. CD34-PE (use at 1:50 dilution).

    • d. Include an unstained control for gating.

    • e. Include isotype control antibody stains.

      • i. Rat IgG2b, κ—PE-Cy5.5.

      • ii. Rat IgG2a, κ—Pac.Blue.

      • iii. Rat IgG2a, κ—PE.

  10. Pellet cells at 180×g for 5 min, wash once with 4 ml FACS buffer, and pellet cells at 180×g for 5 min (if staining high amount of cells perform another wash).

  11. Resuspend cells in 500 µl FACS buffer and filter through filter-membrane into polypropylene (opaque) FACS tubes protected from light.

  12. Just before FACS add viability dye.

    • a. 7AAD (use at 1:1000 dilution).

  13. Perform FACS analysis on cells.

    • a. Gate for viability (7-AAD), then gate and collect the different populations to be analyzed:

      • i. CD34+/CD31 cells.

      • ii. CD31+ cells.

      • iii. CD45+ cells.

      • iv. Use negative controls (unstained and isotype control antibodies) to determine gating of populations.

  14. Isolate RNA from each collected cell population using TRI reagent following manufacturer's instructions.

    • a. Quantify RNA concentrations in each sample using a spectrometer.

      • i. Record sample purity (A260/280 and A260/230 ratios).

  15. Reverse transcribe RNA:

    • a. cDNA synthesis:
      Total RNA 1 ng–5 µg
      oligodT(18) 40 pmol
      oligodT(24) 40 pmol
      10 mM dNTPs 1.0 µl
      H2O Bring up to 12.5 µl
    • b. Heat to 70°C for 5 min, chill on ice for 2 min, then add:
      5× superscript II buffer 4.0 µl
      100 mM DTT 2.0 µl
      RNasin 0.5 µl
    • c. Incubate at 45°C for 2 min, then add:
      Superscript II 1.0 µl
    • d. Incubate for 1 hr at 42°C.

    • e. Heat-inactivate at 70°C for 15 min.

  16. Prepare samples in technical duplicates with two dilutions of cDNA (1:25 and 1:125) using POSTN and GAPDH primers and the Power SYBR green PCR Master Mix. Use GAPDH as control.

    • a. Primers:

      • i. POSTN 5′ primer: AAT GCT GCC CTG GCT ATA TG.

      • ii. POSTN 3′ primer: GTA TGA CCC TTT TCC TTC AA.

      • iii. GAPDH 5′ primer: CAA GCT CAT TTC CTG GTA TGA CAA T.

      • iv. GAPDH 3′ primer: GTT GGG ATA GGG CCT CTC TTG.

    • b. Set up SYBR mix (contains 1 mM MgCl2): 10 µl of 1a into 1b (store on ice in the dark).

    • c. Set up PCR master mix (per reaction):
      Forward primer 1.0 µl of 5 µM (5 pmol/µl)
      Reverse primer 1.0 µl of 5 µM (5 pmol/µl)
      MgCl2 0.4 µl (for 2 mM)
      H2O Bring up to 4.0 µl
      SYBR mix 1.0 µl
    • d. Add 5.0 µl of diluted cDNA and 5.0 µl of PCR master mix to Light cycler capillaries, spin down, and run quantitative PCR reaction following manufacturer's instructions.

      • i. Include negative control (no cDNA).

    • e. Analyze and compute ∆∆CT values.

Deliverables
  • ■ Data to be collected:

    • ◯ All FACS plots in gating scheme (including all controls), leading to final population of viable, CD34+/CD31, CD31+, and CD45+ cells.

    • ◯ Purity (A260/280 and A260/230 ratios) and concentration of isolated total RNA from cells.

    • ◯ Raw CT qRT-PCR values and ∆∆CT (the CT value of POSTN normalized to GAPDH).

    • ◯ Graph of POSTN normalized expression (∆∆CT) for each condition. (Compare to Figure 2H).

Confirmatory analysis plan

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 (q–q) plot to assess the normality of the data and 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.

    • ◯ One-way ANOVA of POSTN RNA expression in CD34+/CD31, CD31+, and CD45+ cells.

      • ◯ Planned comparisons with the Bonferroni correction:

        • CD34+/CD31 vs CD45+.

        • CD31+ vs CD45+.

  • ■ Meta-analysis of effect sizes:

    • ◯ Compute the effect sizes of each comparison, compare them against the reported effect size in the original paper and use a meta-analytic approach to combine the original and replication effects, which will be presented as a forest plot.

Known differences from the original study

All known differences are listed in the materials and reagents section above with the originally used item listed in the comments section. All differences have the same capabilities as the original and are not expected to alter the experimental design.

Provisions for quality control

Negative staining and isotype controls are included to assess antibody staining relative to background during FACS analysis. The sample purity (A260/280 and A260/230 ratios) of the isolated RNA from each sample will be reported. All data obtained from the experiment—raw data, data analysis, control data, and quality control data—will be made publicly available, either in the published manuscript or as an open access data set available on the Open Science Framework project page for this study (https://osf.io/vseix).

Power calculations

Protocol 1

Summary of original data (estimated from Figure S13).

Figure 3B and S13: Number of metastases or size of primary tumor Mean SD N
Number of metastases in MMTV-PyMT; Postn+/+ mice 15.78 17.54 18
Number of metastases in MMTV-PyMT:Postn−/− mice 2.765 5.069 17
Size of primary tumor in MMTV-PyMT; Postn+/+ mice 1.221 0.6023 18
Size of primary tumor in MMTV-PyMT; Postn−/− mice 1.186 0.5901 16

Size of primary tumor

Test family

  • ■ 2-tailed t-test, difference between two independent means, alpha error = 0.05.

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

Group 1 Group 2 Effect size d A priori power Group 1 sample size Group 2 sample size
MMTV-PyMT; Postn+/+ mice MMTV-PyMT; Postn−/− mice 1.145371* 80.0% 13 13
*

This excludes one outlier data point (2.83) from the Postn−/− data.

Number of metastases

Test family

  • ■ 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).

Group 1 Group 2 Effect size d A priori power Group 1 sample size Group 2 sample size
MMTV-PyMT; Postn+/+ mice MMTV-PyMT; Postn−/− mice 1.186517* 82.7% 13 13
*

This excludes one outlier data point (61) from the Postn+/+ data and two outlier data points (18 and 13) from the Postn−/− data.

Test family

  • ■ Negative binomial regression, alpha error = 0.05.

Analysis of original data: performed with R software, version 3.1.2 (R Core Development Team, 2014).

Chi-square goodness of fit test, p-value = 0.2535.

Regression coefficient, Genotype (Postn−/−) = −1.742, incident rate ratio = 0.1752, p-value = 0.000923.

Predicted values from model:

Data set being analyzed Mean SE
Number of metastases in MMTV-PyMT; Postn+/+ mice 15.78 5.594
Number of metastases in MMTV-PyMT:Postn−/− mice 2.765 1.073

Power Calculations performed with R software, version 3.1.2 (R Core Development Team, 2014).

Groups Number of simulations A priori power Sample size
Number of metastases in MMTV-PyMT; Postn+/+ mice and MMTV-PyMT; Postn−/− mice 10,000* 81.2% 12 per group
*

The original data were randomly sampled from, with replacement, to create simulated data sets. For a given n (the number of observations) 10,000 simulations were run and the Chi-square goodness of fit test and regression coefficient (Genotype (Postn−/−)) was calculated for each simulated data set. Any model fit with p < 0.05 was excluded. The power was then calculated by counting the number of times p ≤ 0.05 and dividing by the number of model fits.

Protocol 2

Summary of original data (estimated from Figure 2H).

Figure 2H: qPCR analysis of POSTN expression N Mean SD
CD34+/CD31 pulmonary fibroblasts 3 1.7 0.6
CD31+ endothelial cells 3 0.15 0.1
CD45+ immune cells 3 0.01 0.04

Test family

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

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

ANOVA F test statistic and partial η2 performed with R software, version 3.1.2 (R Core Development Team, 2014).

Groups F test statistic Partial η2 Effect size f A priori power Total sample size
CD34+/CD31, CD31+, and CD45+ F(2,6) = 21.306 0.876574 2.664962 89.8%* 6* (3 groups)
*

A total sample size of 18 will be used based on the planned comparison calculations making the power 99.9%.

Test family

  • ■ 2-tailed t-test, difference between two independent means, Fisher's LSD test: alpha error = 0.05.

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

Group 1 Group 2 Effect size d A priori power Group 1 sample size Group 2 sample size
CD34+/CD31 CD45+ 3.974546 94.6%* 3* 3*
CD31+ CD45+ 1.838290 81.8% 6 6
*

6 tumors will be used per group based on the CD31+ to CD45+ comparison making the power 99.9%.

Acknowledgements

The Reproducibility Project: Cancer Biology core team would like to thank the original authors, in particular Joerg Huelsken and Ilaria Malanchi, for generously sharing critical information as well as reagents to ensure the fidelity and quality of this replication attempt. We thank Courtney Soderberg at the Center for Open Science for assistance with statistical analyses. We would also like to thank the following companies for generously donating reagents to the Reproducibility Project: Cancer Biology; American Type Culture Collection (ATCC), BioLegend, Charles River Laboratories, Corning Incorporated, DDC Medical, EMD Millipore, Harlan Laboratories, LI-COR Biosciences, Mirus Bio, Novus Biologicals, Sigma–Aldrich, and System Biosciences (SBI).

Funding Statement

The Reproducibility Project: Cancer Biology is funded by the Laura and John Arnold Foundation, provided to the Center for Open Science in collaboration with Science Exchange. The funder had no role in study design or the decision to submit the work for publication.

Footnotes

Malanchi I, Santamaria-Martinez A, Susanto E, Peng H, Lehr HA, Delaloye JF, Huelsken J. 2012. Interactions between cancer stem cells and their niche govern metastatic colonization. Nature 4:85–89. doi: 10.1038/nature10694.

Contributor Information

Gordana Vunjak-Novakovic, Columbia University, United States.

Reproducibility Project: Cancer Biology:

Elizabeth Iorns, William Gunn, Fraser Tan, Joelle Lomax, Nicole Perfito, and Timothy Errington

Funding Information

This paper was supported by the following grant:

  • Laura and John Arnold Foundation to .

Additional information

Competing interests

FI: This is a Science Exchange associated lab.

MMD: This is a Science Exchange associated lab.

NI: This is a Science Exchange associated lab.

AC: This is a Science Exchange associated lab.

RP:CB: EI, FT, JL, and NP are employed by and hold shares in Science Exchange Inc.

The other authors declare that no competing interests exist.

Author contributions

FI, Drafting or revising the article.

MMD, Drafting or revising the article.

NI, Drafting or revising the article.

AC, Drafting or revising the article.

EG, Drafting or revising the article.

MAL, Drafting or revising the article.

RP:CB, Conception and design, Drafting or revising the article.

References

  1. Artwohl JE, Purcell JE, Fortman JD. The use of cross-foster rederivation to eliminate murine norovirus, Helicobacter spp., and murine hepatitis virus from a mouse colony. Journal of the American Association for Laboratory Animal Science. 2008;47:19–24. [PMC free article] [PubMed] [Google Scholar]
  2. Bao S, Ouyang G, Bai X, Huang Z, Ma C, Liu M, Shao R, Anderson RM, Rich JN, Wang XF. Periostin potently promotes metastatic growth of colon cancer by augmenting cell survival via the Akt/PKB pathway. Cancer Cell. 2004;5:329–339. doi: 10.1016/S1535-6108(04)00081-9. [DOI] [PubMed] [Google Scholar]
  3. Conway SJ, Izuhara K, Kudo Y, Litvin J, Markwald R, Ouyang G, Arron JR, Holweg CT, Kudo A. The role of periostin in tissue remodeling across health and disease. Cellular and Molecular Life Sciences. 2014;71:1279–1288. doi: 10.1007/s00018-013-1494-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods. 2007;39:175–191. doi: 10.3758/BF03193146. [DOI] [PubMed] [Google Scholar]
  5. Ghajar CM, Peinado H, Mori H, Matei IR, Evason KJ, Brazier H, Almeida D, Koller A, Hajjar KA, Stainier DY, Chen EI, Lyden D, Bissell MJ. The perivascular niche regulates breast tumour dormancy. Nature Cell Biology. 2013;15:807–817. doi: 10.1038/ncb2767. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Guy CT, Cardiff RD, Muller WJ. Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease. Molecular and Cellular Biology. 1992;12:954–961. doi: 10.1128/mcb.12.3.954. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Kikuchi Y, Kunita A, Iwata C, Komura D, Nishiyama T, Shimazu K, Takeshita K, Shibahara J, Kii I, Morishita Y, Yashiro M, Hirakawa K, Miyazono K, Kudo A, Fukayama M, Kashima TG. The niche component periostin is produced by cancer-associated fibroblasts, supporting growth of gastric cancer through ERK activation. The American Journal of Pathology. 2014;184:859–870. doi: 10.1016/j.ajpath.2013.11.012. [DOI] [PubMed] [Google Scholar]
  8. Lee YJ, Kim IS, Park SA, Kim Y, Lee JE, Noh DY, Kim KT, Ryu SH, Suh PG. Periostin-binding DNA aptamer inhibits breast cancer growth and metastasis. Molecular Therapy. 2013;21:1004–1013. doi: 10.1038/mt.2013.30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Lin EY, Jones JG, Li P, Zhu L, Whitney KD, Muller WJ, Pollard JW. Progression to malignancy in the polyoma middle T oncoprotein mouse breast cancer model provides a reliable model for human diseases. The American Journal of Pathology. 2003;163:2113–2126. doi: 10.1016/S0002-9440(10)63568-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Malanchi I, Santamaria-Martinez A, Susanto E, Peng H, Lehr HA, Delaloye JF, Huelsken J. Interactions between cancer stem cells and their niche govern metastatic colonization. Nature. 2012;481:85–89. doi: 10.1038/nature10694. [DOI] [PubMed] [Google Scholar]
  11. Nguyen DX, Bos PD, Massague J. Metastasis: from dissemination to organ-specific colonization. Nature Reviews. Cancer. 2009;9:274–284. doi: 10.1038/nrc2622. [DOI] [PubMed] [Google Scholar]
  12. Nuzzo PV, Buzzatti G, Ricci F, Rubagotti A, Argellati F, Zinoli L, Boccardo F. Periostin: a novel prognostic and therapeutic target for genitourinary cancer? Clinical Genitourinary Cancer. 2014;12:301–311. doi: 10.1016/j.clgc.2014.02.005. [DOI] [PubMed] [Google Scholar]
  13. R Core Development Team . R: A language and environment for statistical computing. R Foundation for Statistical Computing; 2014. http://www.R-project.org/ [Google Scholar]
  14. Visvader JE, Lindeman GJ. Cancer stem cells: current status and evolving complexities. Cell Stem Cell. 2012;10:717–728. doi: 10.1016/j.stem.2012.05.007. [DOI] [PubMed] [Google Scholar]
  15. Wang X, Liu J, Wang Z, Huang Y, Liu W, Zhu X, Cai Y, Fang X, Lin S, Yuan L, Ouyang G. Periostin contributes to the acquisition of multipotent stem cell-like properties in human mammary epithelial cells and breast cancer cells. PLOS ONE. 2013;8:e72962. doi: 10.1371/journal.pone.0072962. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Xu D, Xu H, Ren Y, Liu C, Wang X, Zhang H, Lu P. Cancer stem cell-related gene periostin: a novel prognostic marker for breast cancer. PLOS ONE. 2012;7:e46670. doi: 10.1371/journal.pone.0046670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Zhu M, Saxton RE, Ramos L, Chang DD, Karlan BY, Gasson JC, Slamon DJ. Neutralizing monoclonal antibody to periostin inhibits ovarian tumor growth and metastasis. Molecular Cancer Therapeutics. 2011;10:1500–1508. doi: 10.1158/1535-7163.MCT-11-0046. [DOI] [PubMed] [Google Scholar]
eLife. 2015 Jun 18;4:e06938. doi: 10.7554/eLife.06938.002

Decision letter

Editor: Gordana Vunjak-Novakovic1

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 sending your work entitled “Registered report: Interactions between cancer stem cells and their niche govern metastatic colonization” for consideration at eLife. Your article has been evaluated by Janet Rossant (Senior editor), Gordana Vunjak-Novakovic°(Reviewing editor), and three reviewers, one of whom, M Dawn Teare, has agreed to share her identity.

The Reviewing editor and the reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.°

This Registered report is part of a bigger project named Reproducibility Project: Cancer Biology, which aims to address concerns about reproducibility of scientific data published in the field of cancer research between 2010 and 2012. Within this project, parts of the experiments from 50 selected publications will be reproduced by an independent laboratory.°

The report describes the plan for the reproduction of two selected experiments from the original article “Interactions between cancer stem cells and their niche govern metastatic colonization” by Malanchi et al. in Nature in 2012 (Malanchi et al., 2012). The first experiment is to measure metastatic lung cancer in MMTV-PyMT transgenic mice crossed with the POSTN Knock out mice, and controls, with focus on the role of periostin in metastatic progression.°

The second experiment is to isolate various cell types from lungs harboring metastasis to confirm the cellular source of periostin in response to metastatic growth. We find the data of high quality and possibly of interest to the scientific community. However, the reviewers also made some comments that we would like you to address.°

1) The key finding that periostin acts as a fundamental stromal factor for metastatic progression has been meanwhile experimentally validated in several independent labs by using other models. In light of this, it would be helpful to explain in more detail what exactly is your reproducibility project providing in terms of scientific and technical validation.°

2) The two repeated experiments analyze the source of POSTN expression in the lung and whether it affects the number/size of primary and secondary tumor formation in a spontaneous mouse model of breast cancer (MMTV-PyMT). Please provide justification for these particular choices of experiments. The reviewers suggest starting the manuscript by an overview of the original results and experimental designs, and the reasoning for repeating the two selected experiments. This would help the reader, who may not be familiar with the original work, to better evaluate the scope and focus of this repetition.°

3) Discussing the results of the original study, reproduced here, in the context of other work published over the last few years, would also be very helpful.°

4) Finally, the use of statistics requires some explanation. For protocol 1, the authors should discuss their treatment of outliers: why such outliers have arisen and how they can be best handled in the analysis. For protocol 2, very small numbers in each group are planned and this is due to assuming the data is normally distributed. The normality of data should be addressed in the analysis and if data is not clearly normally distributed it would be fair to relax the normality assumption and check that conclusions are not changed if a non-parametric comparison is used.°

eLife. 2015 Jun 18;4:e06938. doi: 10.7554/eLife.06938.003

Author response


1) The key finding that periostin acts as a fundamental stromal factor for metastatic progression has been meanwhile experimentally validated in several independent labs by using other models. In light of this, it would be helpful to explain in more detail what exactly is your reproducibility project providing in terms of scientific and technical validation.°

This project aims to evaluate the predictors of directly reproducing a subset of the published literature. Thus, the focus is on a collection of experimental outcomes, and the factors associated with them, and not the conclusions from any given paper, which are based on multiple experiments and models.

Additionally, the project is focused on direct replications (same methodology/system) compared to conceptual replications (similar experiment, but different techniques/models). Conceptual replication is as vital for gaining understanding of an effect as direct replication is for increasing confidence that the effect occurs. The focus on understanding if the effects drawn from a single model can be reproduced will provide a means to understand the challenges and predictors of reproducing any given experiment based on current research and reporting practices. While this does not speak to the robustness of the effect, such as can be inferred through multiple models/approaches, it does provide a mechanism to examine the extent to which an effect with a given model can be observed again. We will also limit the conclusions that can be drawn to only this model.

2) The two repeated experiments analyze the source of POSTN expression in the lung and whether it affects the number/size of primary and secondary tumor formation in a spontaneous mouse model of breast cancer (MMTV-PyMT). Please provide justification for these particular choices of experiments. The reviewers suggest starting the manuscript by an overview of the original results and experimental designs, and the reasoning for repeating the two selected experiments. This would help the reader, who may not be familiar with the original work, to better evaluate the scope and focus of this repetition.°

Thank you for the suggestion. We have included an additional paragraph to describe the original work and the rational for the two selected experiments included.

3) Discussing the results of the original study, reproduced here, in the context of other work published over the last few years, would also be very helpful.°

We have expanded the Introduction to include other published studies in the context of the original study.

4) Finally, the use of statistics requires some explanation. For protocol 1, the authors should discuss their treatment of outliers: why such outliers have arisen and how they can be best handled in the analysis. For protocol 2, very small numbers in each group are planned and this is due to assuming the data is normally distributed. The normality of data should be addressed in the analysis and if data is not clearly normally distributed it would be fair to relax the normality assumption and check that conclusions are not changed if a non-parametric comparison is used.°

For protocol 1, we’ve included language to discuss the detection of outliers and plan to perform the test with and without the outliers to ascertain if a difference occurs in the analysis. The original analysis appears to have excluded the outliers in the statistical test they used. Additionally, we have further explored the original estimated data and the metastatic foci counts violate the normality and homoscedasticity assumption of the test used, as determined by the Shapiro–Wilk test (and Q–Q plots) and Levene’s test. So, in addition to a Student’s t-test (which was originally performed) we plan to analyze the data using negative binomial regression. The power calculations were also performed again to ensure the sample size was still adequate for this test.

For protocol 2, we have added language to the manuscript to clarify that we will perform tests for normality and homoscedasticity.


Articles from eLife are provided here courtesy of eLife Sciences Publications, Ltd

RESOURCES