Supplementary Materials for

MET signaling in keratinocytes activates EGFR and initiates squamous

carcinogenesis

Christophe Cataisson, Aleksandra M. Michalowski, Kelly Shibuya, Andrew Ryscavage,

Mary Klosterman, Lisa Wright, Wendy Dubois, Fan Liu, Anne Zhuang,

Kameron B. Rodrigues, Shelley Hoover, Jennifer Dwyer, Mark R. Simpson,

Glenn Merlino, Stuart H. Yuspa*

*Corresponding author. Email: yuspas@mail.nih.gov

Published 21 June 2016, Sci. Signal. 9, ra62 (2016)

DOI: 10.1126/scisignal.aaf5106

The PDF file includes:

Fig. S1. Malignant conversion rate is increased in MT-HGF compared to DT

animals.

Fig. S2. Ras mutation analysis in DMBA-TPA and MET-generated skin lesions.

Fig. S3. MT-HGF keratinocytes can form squamous papillomas when orthotopically

grafted.

Fig. S4. HGF-MET does not enhance responses to TPA.

Fig. S5. Treatment of MT-HGF keratinocytes with a MET inhibitor (PHA665752)

reverses their phenotype in vitro.

Fig. S6. EGFR dependence of the MET and RAS signatures in keratinocytes.

Fig. S7. Effects of EGFR inhibition on the transcriptional profile of MT-HGF

keratinocytes.

Fig. S8. Activated MET gene signature is not dependent on individual Ras allele

expression.

Fig. S9. TGF and AREG neutralizing antibody activities reduce the activation of

EGFR in MT-HGF keratinocytes.

Fig. S10. Both iRhom1 and iRhom2 contribute to the release of AREG upon MET

activation.

Fig. S11. Gefitinib treatment reduces proliferation and microvessel density in MT-

HGF squamous papillomas.

Fig. S12. MET activation causes EGFR ligand, cytokine, and chemokine mRNA up-

regulation in human keratinocytes.

www.sciencesignaling.org/cgi/content/full/9/433/ra62/DC1

Fig. S13. Quantification for immunoblots represented in Figs. 2 and 3.

Fig. S14. Quantification for immunoblots represented in Figs. 4 and 5.

Fig. S15. Quantification for immunoblots represented in Figs. 6 and 8.

Legends for tables S1 to S3

Table S4. PCR primers.

Other Supplementary Material for this manuscript includes the following:

(available at www.sciencesignaling.org/cgi/content/full/9/433/ra62/DC1)

Table S1 (Microsoft Excel format). The list of 5812 significant genes concordantly

up-regulated or down-regulated in the wild-type RAS and MT-HGF keratinocytes.

Table S2 (Microsoft Excel format). GO functions enriched in the RAS/MET 372-

gene signature.

Table S3 (Microsoft Excel format). Upstream regulators predicted by IPA to be

responsible for expression changes in the RAS/MET 372-gene signature.

Fig. S1: Malignant conversion rate is increased in MT-HGF compared to DT animals. The malignant conversion rate

(% squamous carcinoma among all squamous lesions) was determined at week 20 among the three tumor bearing groups

(50% for K5-PKCa, 73% for MT-HGF, and 23% for DT mice). K5-PKC n=4, MT-HGF n=11 and DT n=30, with n

representing the number of squamous lesions analyzed. A two-sample t-test between proportions was performed to

determine whether there was a significant difference between MT-HGF and DT groups with respect to the % conversion.

The t-statistic was significant, *p= 0.0056.

Fig. S2: Ras mutation analysis in DMBA-TPA and MET-generated skin lesions. (A) Frequency of mutations in Hras

and Kras in mouse skin tumors from DMBA-TPA experiments. (No tumors formed in WT animals). (B) Absence of

mutations in Hras1, Kras and Nras in DT squamous papillomas harvested from study shown in Fig. 1 D-F.

Fig. S3: MT-HGF keratinocytes can form squamous papillomas when orthotopically grafted. (A) Representative

photographs of syngeneic orthotopic grafts at the interscapular site. Six million wild-type (left) or MT-HGF (right)

keratinocytes were mixed respectively with 6 million wild-type or MT-HGF primary dermal fibroblasts prior to grafting.

The upper panels show grafts forming on either wild-type or MT-HGF recipients. The lower panel shows a tumor forming

from wild-type keratinocytes grafted onto MT-HGF recipients. (B) Representative H&E micrograph of a squamous

papilloma arising from MT-HGF keratinocyte combined with MT-HGF primary dermal fibroblasts grafted onto a MT-

HGF recipient mouse. Scale bar, 25m.

Fig. S4: HGF-MET does not enhance responses to TPA. (A) A single dose of TPA (1 μg) in acetone was applied to the

shaved backs of WT, K5-PKCα, MT-HGF and DT littermates, and samples of treated skin were collected at various times

and stained with H&E. Asterisk marks typical microabcesses. Scale bar, 50m. (B) Neutrophilic infiltration in the

epidermis of the mice treated as in (A) was quantified using leukocyte myeloperoxidase activity (MPO). Bars represent

the mean ± SEM of four independent animals and results are representative of two independent experiments. P-value was

calculated using two-sided student’s t-test. *P < 0.05 vs. WT. **P < 0.01 vs. WT. (C) Epidermal hyperplasia was

quantified in randomly selected regions on H&E stains (presented on panel A) of skin biopsies taken from mice 3 days

after TPA treatment. *P < 0.05 vs. WT. (D and E) Real-time PCR analysis of Cxcl1 (CXCL1 mRNA) and Areg

(amphiregulin mRNA) expression in control (acetone) and TPA treated mice 1 and 3 days after topical treatment. *P <

0.05 vs. WT TPA. **P < 0.01 vs. WT TPA. ***P < 0.01 vs. WT TPA, n=3 mice per genotype for the acetone groups and

n=4 mice per genotype for the TPA groups. (F) Tissue lysates were prepared from full-thickness skin biopsies of all four

genotypes collected 1 day post TPA treatment. Immunoblots were performed for COX-2 and GAPDH for loading control.

Each lane represents an individual animal.

Fig. S5: Treatment of MT-HGF keratinocytes with a MET inhibitor (PHA665752) reverses their phenotype in

vitro. (A) MT-HGF keratinocytes developed a more elongated morphology in the absence of RAS transduction that can

be reverted upon treatment with the MET pharmacological inhibitor PHA-665752. Scale bar, 100m. (B) real-time PCR

analysis of amphiregulin (Areg) mRNA expression in wild-type and MT-HGF keratinocytes treated for 48 hours with the

MET inhibitor PHA665752. Data are mean ± SEM of three biological replicates. #P < 0.001 vs. WT DMSO; ***P <

0.001 vs. MT-HGF DMSO, by a two-sided student’s t-test. (C) MT-HGF primary keratinocytes were cultured in 0.05 mM

Ca++ medium to confluence and treated for 48 hours with the MET inhibitor PHA665752. Total cell extract from primary

keratinocytes was analyzed by immunoblotting for phosphorylated (p-) and total EGFR and HSP90. (D) EGFR inhibition

does not decrease phospho-MET levels in DT keratinocytes. Primary keratinocytes from wild-type (WT) and DT

newborns were cultured in 0.05 mM Ca2+. When confluent, cultures were treated with AG1478 for 24 hours and with a

final concentration of 1µM. Total cell extract from primary keratinocytes were analyzed by immunoblotting for

phosphorylated (p-) and total MET, and HSP90.

Fig. S6: EGFR dependence of the MET and RAS signature in keratinocytes. (A and B) Real-time PCR analysis of

CXCL1 (Cxcl1), IL-1a (Il1a), keratin1 (Krt1), keratin10 (Krt10), amphiregulin (Areg), betacellulin (Btc), heparin-binding

EGF-like growth factor (Hbegf) and transforming growth factor α (Tgfa) mRNA expression in (A) wild-type and EGFR-

deficient primary keratinocytes were cultured in 0.05 mM Ca2+ medium to confluence and treated for 18 hours with

recombinant HGF (40ng/ml) or (B) control or v-rasHa transduced wild-type and EGFR-/- keratinocytes. (C) Real-time PCR

analysis of IL-1a (Il1a), K1 (Krt1), K10 (Krt10) and CXCL1 (Cxcl1) mRNA expression in wild-type and MT-HGF

keratinocytes treated for 24 hours with the EGFR inhibitor AG1478 or PD168393. Data are means ± SEM of three

biological replicates. P-values were calculated using two-sided student’s t-test. A, *P < 0.05 vs WT-HGF, **P < 0.01 vs

WT-HGF. B, **P < 0.01 vs WT-RAS, ***P < 0.001 vs. WT-RAS, ****P < 0.0001 vs WT-RAS. C, **P < 0.01 vs. MT-

HGF DMSO ***P < 0.001 vs. MT-HGF DMSO, #P < 0.001 vs.WT DMSO.

Fig. S7: Effects of EGFR inhibition on the transcriptional profile of MT-HGF keratinocytes. Heatmap visualization

of relative expression of 372 genes selected for the model RAS/MET signature in untreated keratinocytes (MT-HGF) and

treated with the EGFR inhibitor AG1478 (MT-HGF-AG); genes (columns) and samples (rows) are ordered by hierarchical

clustering using Euclidean distance and complete linkage; expression levels are mean centered by columns (genes); 329

genes are significantly affected by AG1478 and their names on the right side of the heatmap are proceeded by an asterisk;

in addition grey bars on the left side of the heatmap indicate genes that do not reach significance; see table S1 for

estimates of statistical significance of gene expression changes upon administration of AG1478.

Fig. S8: Activated MET gene signature is not dependent on individual Ras allele expression. Primary keratinocytes

from wild-type or MT-HGF mice were cultured in 0.05 mM Ca2+ medium to confluence and transduced with siRNA

against Hras, Kras or Nras. Cultures were harvested 48 and 72 hours after transduction and analyzed for (A) HRAS,

KRAS and HSP90 expression by immunoblot or (B) for NRAS (Nras), IL-1a (Il1a), keratin1 (Krt1) and CXCL1 (Cxcl1)

mRNA expression by real-time PCR analysis at the same time points. Data are means ± SEM of three biological

replicates. P-values were calculated using two-sided student’s t-test: *P < 0.05 vs MT-HGF control, **P < 0.01 vs. MT-

HGF control.

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Fig. S9: TGF and AREG neutralizing antibody activities reduce the activation of EGFR in MT-HGF

keratinocytes. (A) Wild-type primary keratinocytes were cultured in 0.05 mM Ca2+ medium to confluence and treated for

30 min with recombinant TGFα (10ng/ml) or AREG (100ng/ml) in the presence of control IgG or TGF or AREG

antibodies to confirm neutralizing activity. (B) Primary keratinocytes from MT-HGF mice were cultured in 0.05 mM Ca2+

medium to confluence and treated for 24 hours in the presence of neutralizing antibodies against TGFα and Amphiregulin.

Total cell extract from primary keratinocytes were analyzed by immunoblotting for phosphorylated (p-) and total EGFR

and HSP90. Values below the p-EGFR blot are representative p-EGFR:total EGFR ratios after normalization with HSP90

expression for input relative to control set as 1; n=3 experiments.

Fig. S10: Both iRhom1 and iRhom2 contribute to the release of AREG upon MET activation. (A to D) Primary

keratinocytes were cultured in 0.05 mM Ca2+ medium to confluence and treated for 6 hours with HGF in the presence of

siRNAs targeting the mRNA encoding iRhom1 (Rhbdf1; A and B) or iRhom2 (Rhbdf2; C and D). Cells were harvested

and mRNAs were quantified by real-time PCR (A and C) and AREG concentrations in the culture supernatants were

determined by ELISA (B and D). Data are means ± SEM of four biological replicates. **P < 0.01, ***P < 0.001, ****P <

0.0001 vs control siRNA treated with HGF, by a two-sided student’s t-test.

Fig. S11: Gefitinib treatment reduces proliferation and microvessel density in MT-HGF squamous papillomas. Six

million MT-HGF keratinocytes were mixed respectively with 6 million MT-HGF primary dermal fibroblasts prior to

grafting to a skin graft site in the interscapular region of syngeneic hosts. Once squamous papillomas were clearly

established mice were orally treated by gavage daily with vehicle control or Gefitinib at 100mg/kg for two weeks. (A)

Ki67-labeled nuclei in tumors were counted in five to seven randomly selected regions. Columns, mean; bars, SEM. **, P

< 0.01 compared with Control. (B) Quantification of the number of stromal CD31-positive vessels used the Aperio

software ImageScope according to treatment group. Microvessel density was calculated by dividing the number of vessels

counted by the surface area analyzed (squamous portion of papilloma was not included in surface area determination).

Columns, mean; bars, SEM. P-values were calculated using two-sided student’s t-test. * P < 0.05 compared with Control.

Control, n=5; gefitinib, n=6 squamous papillomas analyzed.

Fig. S12: MET activation causes EGFR ligand, cytokine, and chemokine mRNA up-regulation in human

keratinocytes. Human primary keratinocytes were grown to sub-confluence in Epilife media with S7 supplement

(Invitrogen) and starved overnight prior to treatment with recombinant HGF (40 ng/ml) or PBS for 3 hours. AREG

(amphiregulin), TGFA, IL1A and CXCL8 mRNA expression were analyzed by real-time PCR. Data are means ± SEM of

three biological replicates. *P < 0.05, **P < 0.01, ***P < 0.001 vs control by a two-sided student’s t-test.

Fig. S13: Quantification for immunoblots represented in Figs. 2 and 3. (A) Quantification of p-EGFR, p-ERK and p-

MET. Data are means ± SEM of five biological replicates. *P < 0.05 vs wild-type control. (B) Quantification of cyclin

D1. Data are means ± SEM of four biological replicates. *P < 0.05, **P < 0.01, ***P < 0.001 vs respective wild-type

control. (C) Quantification of K8, K1 and K10. Data are means ± SEM of four biological replicates*P < 0.05, **P < 0.01,

****P < 0.0001 vs wild-type control. P-values were calculated using two-sided student’s t-test.

Fig. S14: Quantification for immunoblots represented in Figs. 4 and 5. (A) Quantification of phosphorylated (p-)

EGFR represented in Fig.4B. Data are means ± SEM of three biological replicates. *P < 0.05 vs untreated control by a

two-sided student’s t-test. (B) Quantification of ADAM17 and p-EGFR represented in Fig.4C, Data are means ± SEM of

three biological replicates. ***P < 0.001 vs control siRNA. (C) Quantification of ADAM17 represented in Fig.4D insert.

Data are means ± SEM of three biological replicates. *P < 0.05 vs control treated with HGF. (D) Quantification of p-

EGFR and ADAM17 represented in Fig.4E. Data are means ± SEM of three biological replicates. *P < 0.05 vs control

adenovirus. (E) Quantification of p-EGFR and ADAM17 represented in Fig.4F. Data are means ± SEM of four biological

replicates. *P < 0.05, **P < 0.01 vs RAS treated with control siRNA. (F) Quantification of p-SRC represented in Fig.5A.

Data are means ± SEM of four biological replicates. *P < 0.05, **P < 0.01 vs control. (G) Quantification of SRC

represented in Fig.5B insert. Data are means ± SEM of three biological replicates *P < 0.05, **P < 0.01. P-values were

calculated using two-sided student’s t-tests.

Fig. S15: Quantification for immunoblots represented in Figs. 6 and 8. (A) Quantification of phosphorylated (p-)

EGFR and ERK represented in Fig.6B. Data are means ± SEM, n=7 for squamous papilloma and n=4 for skin. *P < 0.05

pap vs skin. (B) Quantification of MET represented in Fig.8D. Data are means ± SEM of three to four biological

replicates. *P < 0.05 vs DMSO. P-values were calculated using two-sided student’s t-test.

Table S1: The list of 5812 significant genes concordantly up-regulated or down-regulated in the wild-type RAS and

MT-HGF keratinocytes. Statistical significance was determined with the one-way ANOVA specific contrasts (treatment

versus control) and the false discovery rate threshold of 1%. The gene list is divided into two parts, that is ‘Model’

signature (at least 2-fold change in both MT-HGF and WT-RAS) and ‘Concordant’ signature (the rest of the differentially

expressed genes). The signatures are ordered by the magnitude of differences in WT-RAS keratinocytes. The magnitude

of tested differences is color coded with shades of red and blue, which indicate the level of up-regulation and down-

regulation of gene expression, respectively. Gene expression estimates are given for WT-Control-, WT-RAS-, MT-HGF-,

and in addition for MT-HGF-AG1478- keratinocytes. Gene annotations are imported from the NCI mAdb database

(https://madb.nci.nih.gov/).

Table S2: Gene Ontology (GO) functions enriched in the RAS/MET 372-gene signature.

The table includes the DAVID GO_FAT terms (Biological Process, Molecular Function, and Cellular Component)

identified with the Gene Set Enrichment Analysis (GSEA) at the 5% false discovery rate. Positive (red) and negative

(blue) enrichment scores indicate up- and down-regulation of the enriched gene sets, respectively. The GSEA core genes

(‘leading edge’) are listed for each GO function and members of the top RAS/MET signature are annotated with an

asterisk (*). In addition, the representative terms are shown for GO functions classified as semantically redundant with the

REVIGO’s elimination algorithm.

Table S3: Upstream regulators predicted by IPA to be responsible for expression changes in the RAS/MET 372-

gene signature. The list of transcriptional regulators was determined with two metrics, namely the overlap P-value

(Fisher’s exact test) less than 0.01 and the bias corrected activation z-score ± 1.96. The bias correction of a z-score

accounts for unbalanced number of up- and down-regulated target genes. Positive (red) and negative (blue) z-scores

indicate the likely activated and inhibited state of an upstream regulator, respectively.

Gene Primer Sequence

Kras (Codon 12+13) External-Forward* ACACACAAAGGTGAGTGTTAAA

External-Reverse GCAGCGTTACCTCTATCGTA

Internal-Forward TTATTGTAAGGCCTGCTGAA

Internal-Reverse TCATACTCATCCACAAAGTG

Kras (Codon 61) External-Forward TTCTCAGGACTCCTACAGGA

External-Reverse ACCCACCTATAATGGTGAAT

Internal-Forward TACAGGAAACAAGTAGTAATTGATGGAGA

Internal-Reverse ATAATGGTGAATATCTTCAAATGATTTAGT

Hras1 (Codon 12+13) External-Forward* GGTGATCAACTGGGCCACTG

External-Reverse CCTCTGGCAGGTAGGCAGAG

Internal-Forward CTAAGTGTGCTTCTCATTGGCAGGT

Internal-Reverse CTCTATAGTGGGATCATACTCGTCC

Hras1 (Codon 61) External-Forward CCACTAAGCCGTGTTGTTTTGCA

External-Reverse CTGTACTGATGGATGTCCTCGAAGGA

Internal-Forward GGACTCCTACCGGAAACAGG

Internal-Reverse GGTGTTGTTGATGGCAAATACA

Nras (Codon 12+13) Forward GACTGAGTACAAACTGGTGG

Reverse GGGCCTCACCTCTATGGTG

Nras (Codon 61) Forward GGTGAGACCTGCCTGCTGGA

Reverse ATACACAGAGGAACCCTTCG

Table S4: PCR primers. Primers specific for mouse Kras, Hras1, and Nras were purchased from Invitrogen and are

listed in the table. Primers marked with * were designed for this experiment, all non-marked primers were previously

reported (54).