Functional protein pathway activation mapping of the progression of normal skin to squamous cell carcinoma

Abstract

Reverse phase protein microarray analysis was used to identify cell signaling derangements in squamous cell carcinoma (SCC) compared with actinic keratosis (AK) and upper inner arm (UIA). We analyzed two independent tissue sets with isolation and enrichment of epithelial cells by laser capture microdissection. Set 1 served as a pilot and a means to identify protein pathway activation alterations that could be further validated in a second independent set. Set 1 was comprised of 4 AK, 13 SCC, and 20 UIA. Set 2 included 15 AK, 9 SCCs, and 20 UIAs. Activation of 51 signaling proteins, known to be involved in tumorigenesis, were assessed for set 1 and showed that the MEK-ERK [mitogen-activated protein (MAP)/extracellular signal-regulated (ERK; MEK)] pathway was activated in SCC compared with AK and UIA, and that epidermal growth factor receptor (EGFR) and mTOR pathways were aberrantly activated in SCC. Unsupervised two-way hierarchical clustering revealed that AK and UIA shared a common signaling network activation architecture while SCC was dramatically different. Statistical analysis found that prosurvival signaling through phosphorylation of ASK and 4EBP1 as well as increased Bax and Bak expression was higher in AK compared with UIA. We expanded pathway network activation mapping in set 2 to 101 key signaling proteins, which corroborated activation of MEK-ERK, EGFR, and mTOR pathways through discovery of a number of upstream and downstream signaling molecules within these pathways to conclude that SCC is indeed a pathway activation-driven disease. Pathway activation mapping of SCC compared with AK revealed several interconnected networks that could be targeted with drug therapy for potential chemoprevention and therapeutic applications.

Figure 1

RPMA analysis of human skin biopsy samples containing AK or advanced SCC showing an unsupervised two-way hierarchical clustering heatmap. Samples with the highest relative level of phosphorylation are shown as red and lowest levels as green. Median values are black.

Figure 2

RPMA analysis of human skin biopsy samples containing advanced SCC or non-advanced SCC (in situ and lower risk SCCs) showing an unsupervised two-way hierarchical clustering heatmap. Samples with the highest relative level of phosphorylation are shown as red and lowest levels as green. Median values are black.

Figure 3

Unsupervised clustering of RPMA pathway activation data from study set 2 showing AK, UIA, non-advanced SCC and advanced SCC samples. Samples with the highest relative level of phosphorylation are shown as red and lowest levels as green. Median values are black.

Figure 4

Protein Pathway Activation Map of SCC. A Cancer Landscape (CScape) Protein Pathway Activation Map (4 Top left) is shown using population averages of RPMA data from patients with AK and SCC. Higher fold differences in the SCC group are shown in increasing shades of red while higher fold differences in signaling in the AK group are shown in green. Each balloon pin is placed over the protein measured. Magnified views of the AMPK-mTOR pathway (green box, middle top) and RAS-RAF-ERK pathway (red box, middle bottom) are shown to reveal pathway detail. Linked pathway members from each pathway are numbered and the individual protein data are plotted as scatter plots for the statistically significant endpoints.