Integration of orthogonal data sets allows construction of an EGFR-centered signaling network for targeted RNAi screening
To construct a network-based library, genes encoding proteins with evidence of functional interactions with EGFR were collected from multiple databases (, and Materials and Methods). We used two members of the EGFR family, EGFR (also known as ERBB1) and HER2 (also known as ERBB2), as seed nodes to select first- and second-order binary protein-protein interactions (PPIs). We mined non-PPI functional linkages relevant to the EGFR pathway from five pathway databases. From BOND (8
) and EBI (9
), we identified proteins that associated with the seed proteins in purified complexes. We included genes that were transcriptionally responsive to inhibition or stimulation of EGFR that we identified from the NIH GEO resource (10
). We added human orthologs for genes identified in other species (predominantly Drosophila
) that genetically interacted with evolutionarily conserved EGFR orthologs. Together, these data nominated 2689 genes encoding proteins linked by at least one criterion to the initial seed list. We chose 638 genes to target in the siRNA library (Table S1
) predominantly on the basis of representation in at least two overlapping orthogonal sources. Also included in the 638 genes were those of the 2689 genes that exhibited a physical interaction with the EGFR adaptor protein SHC, or close signaling connections to the nonreceptor tyrosine kinase SRC and transforming growth factor β (TGF-β) pathways that interact with ERBB family proteins to promote tumor aggressiveness (11
Design and screening of a targeted library
siRNA screening defines subsets of genes that sensitize cells to EGFR inhibition
The A431 cervical adenocarcinoma cell line is dependent on EGFR signaling for proliferation and survival. We reiteratively screened this cell line with the targeted siRNA library in combination with DMSO (vehicle), or small molecule inhibitors of EGFR, or function-blocking EGFR antibodies, or with the non-EGFR-targeted cytotoxic and DNA-damaging agent camptothecin (CPT11) applied at IC25
concentrations (fig. S1A
). Viability was measured with Alamar blue, a metabolic indicator of the number of viable cells. Primary hits were defined as genes that when targeted with siRNAs reduced negative control-normalized viability by at least 15% in the presence of a drug compared to the viability in the presence of DMSO [defined as the Sensitization Index (SI) <0.85], with a false discovery rate (FDR) < 20% (fig. S1B
). (In the absence of drug treatment, knockdown of (247/638) of genes in the library reduced the viability of DMSO-treated A431 cells by at least 15%, including 45 that reduced viability more than 30%. The distribution of primary hits was independent of the tendency of a siRNA to affect cell viability in the absence of drug treatment (), indicating the action of hits was not merely a reflection of accumulated injury to hit-depleted cells. The majority of hits obtained by treating the cells with the EGFR-targeted antibody panitumumab were included within the larger set of genes identified as hits in the cells exposed to the EGFR-targeted small molecule inhibitor erlotinib (). Knockdown of 212 primary hits, including 95 hits with an SI <0.7, sensitized to cells to one or both EGFR-targeting agents. In contrast, knockdown of only 83 primary hits, including 30 hits with an SI <0.7, sensitized cells to CPT11 ().
Performance of additional validation testing (fig. S2
) identified a set of 61 genes () for which 2 or more independent gene-targeted siRNAs both efficiently knocked down their target gene and sensitized cells to EGFR-targeting agents. The majority of the sensitizing genes (48/61) encoded proteins that were connected in a physically interacting network (). The remaining 13 encoded proteins that are not known to interact physically with EGFR or its direct partners, but instead are linked to EGFR on the basis of rapid changes in the abundance of their mRNA transcripts in response to pathway activation, inhibition, or both.
Validated EGFR-sensitizing genes
Relative to the overall properties of the 638-gene library, the erlotinib-sensitizing hits were significantly enriched for genes that were first-order PPIs of the seeds and were also present in the pathway maps (). When examined within the context of the EGFR-centered network, the erlotinib-sensitizing hits encoded proteins that exhibited topology parameters distinct from those of the overall network, such as increased degree, which reflected the number of edges linked to it; topological coefficient, which provided an estimate for the trend of nodes in the network to have shared neighbors; stress, which reflected how frequently a node was in the shortest path connecting other nodes; and neighborhood connectivity, which represented the average number of neighbors for each direct interactor of the node. Together these properties suggest that these genes encode proteins that serve as network “hubs” and connect with many other proteins in the network (). On the basis of their Gene Ontology (GO) function, erlotinib-sensitizing hits encoded proteins that were significantly enriched for involvement in phosphate metabolism (kinases or phosphatases) and signaling (represented by several GO categories) relative to the overall composition of the siRNA library (). We observed a weak trend for hits to be evolutionarily conserved, as reflected by the increased number of orthologs in lower eukaryotes among hits relative to the overall library ().
Network properties of hits
A subgroup of validated genes is active in multiple cell lines and promotes drug-induced apoptosis
To assess if the genes that sensitized A431 cells to EGFR inhibitors or non-EGFR-targeted cytotoxic agents also influenced the sensitivity of other cancer cell lines to these drugs, we profiled the efficacy of siRNAs targeting 45 of these genes in sensitizing 7 other cell lines to erlotinib, cetuximab (an EGFR function-blocking antibody), or CPT11. These lines included A431, the colorectal adenocarcinoma cell lines HCT116, DLD-1, DKS-8, and LoVo, the head and neck squamous cell carcinoma cell line SCC61, and the pancreatic adenocarcinoma cell lines PANC-1 and MIA PaCa-2 (). Cell lines with mutations in genes encoding proteins that are known to produce drug resistance (for example, in K-Ras or p53, or both) had more noise in their sensitization responses, with the result that lines containing such mutations (DLD-1, DKS-8, LoVo, MIA PaCa-2) yielded many fewer sensitizing hits than we found in the A431 cells, as judged by a strict FDR-based statistical criteria. One contributing factor to the reduced number of hits was an increase in the stochastic “noise”, which caused greater standard deviation in experimental repetitions. To compensate for this factor, we analyzed the data in two ways-- not only by statistically stringent conventional threshold analysis (, left) but also by assessing the rank order of sensitization phenotype, using relaxed statistical criteria (compare to , right; see Materials and Methods). This analysis indicated a subset of sensitizing genes were consistently most sensitizing among the group analyzed.
Sensitization profile of hits
None of the 45 genes when knocked down sensitized all tested cell lines to erlotinib. On the basis of the threshold analysis (, left), knockdown of the 45 genes originally identified in the A431 cells, most consistently sensitized this cell line to erlotinib, with many in this group also sensitizing A431 cells to cetuximab (). Knockdown of a subset of these genes (including those targeting RPS6KA5, FLNA, DUSP7, PRKCE, PRKACB, SC4MOL, and ASCL2) sensitized cells to erlotinib, CPT11, or both, in 3 to 5 cell lines, suggesting a broader action in resistance, but less specificity for EGFR-targeting agents. This overlap in CPT11 sensitizing genes with erlotinib sensitizing genes may indicate general roles for some of the genes in general cell survival pathways, or alternatively, reflect the important role of genes closely linked to EGFR in supporting general cell survival. Surprisingly, we also observed that a small number of genes originally identified as sensitizing in A431 cells treated with erlotinib actually antagonized the effects of this or other drugs in other cell lines (for example, PPIAP19 and INPPL1).
Reanalyzing the same set of 45 genes on the basis of sensitization ranking (, right), all genes detected on the basis of strict thresholds were again identified, but additional genes of interest were now detected (). For example, in the ranking analysis, PRKCE was one of the most sensitizing genes in 11/16 conditions assessed, whereas in the threshold analysis it only scored as significantly sensitizing in 6/16 conditions.
Table 2 Genes that when knocked down sensitized multiple cell lines to drugs. Threshold analysis provides a set of target genes based on strict statistical criteria. Rank order analysis provides a different view of the target gene set by compensating for stochastic (more ...)
The effects of inhibiting a selected target gene reflect not only drug-related sensitizing activity, but also an intrinsic effect on cell growth due to loss of the gene product, which may cumulatively result in an altered rank order of target genes in influencing cell viability. We therefore also established the baseline intrinsic activity of the validated siRNAs in reducing cell viability in DMSO-treated cells (). In multiple cell lines in the presence of vehicle alone, targeting of some genes, such as RPS6KA5 and SHC1, significantly reduced cell viability; whereas targeting of others, including DUSP7 and DLG4, had relatively little effect on cell viability in the absence of drug treatment ().
On the basis of the combination of intrinsic and sensitizing effects, knock down of many genes (including PRKCE, DUSP7, SH2D3C, SHC1, SC4MOL, FLNA, and NEDD9) strongly reduced the viability of multiple tumor cell lines treated with EGFR-targeting agents. Further, depletion of 30 of the hits showed statistically significant drug-gene interactions by selectively enhancing apoptosis in the presence of erlotinib versus GL2-targeted control siRNA A431 cells, including 9 of the hits that selectively enhanced apoptosis >2-fold in erlotinib- versus DMSO-treated cells ().) These genes may be particularly useful targets for cancer therapy, because of their ability to induce cell death rather than only cytostasis.
siRNA hits enhance apoptosis in the presence of EGFR inhibitor
Many strongly sensitizing hits populate a protein network connected to EGFR
These findings support the idea that a cogently designed network focused around a core cancer target, such as EGFR, would provide a rich source of genes that modulate resistance to EGFR pathway-targeted agents. In general, we observed a greater effect on the core viability of cell lines containing wild-type versus mutant RAS (for example, SCC61 and DKS8 in A431 cells), although the stronger hits (SI <0.7) were typically active in both (, ); in contrast, no meaningful correlation was detected between sensitization profile and RAS mutational status, suggesting that sensitizing activity occurred downstream or independently from core RAS signaling outputs. We investigated the relative interactions of the stronger hits within the overall topology of the EGFR signaling network (). We could place the majority of hits in a connected subnetwork defined by direct physical interactions. We identified genes encoding 2 members of the protein kinase C (PRKC) family as sensitizing in multiple cell lines (PRKCD and PRKCE), with a third PRKC encoding gene PRKCE also directly connecting to another sensitizer, PRKACB (encoding the catalytic subunit of cAMP-dependent protein kinase). A second cluster included SH2D3C, BCAR1, and NEDD9 (in each case encoding a scaffolding protein involved in integrin-dependent signaling), which on the basis of rank-order analysis () sensitized cells preferentially to erlotinib and cetuximab relative to non-EGFR targeted agents, and were all connected by direct physical interactions. Many of these most sensitizing hits were directly connected to MAPK1 (encoding mitogen-activated protein kinase 1, also known as extracellular signal-regulated protein kinase ERK2), PIK3R (encoding the regulatory subunit of phosphoinositide 3-kinase), STAT3 (encoding signal transducer and activator of transcription 3), SHC1 (encoding a scaffolding protein intermediate between receptor tyrosine kinases and RAS), and EGFR itself, supporting the idea that these proteins modulated core outputs of the central EGFR signaling pathway.
Functional classification of hits
We next tested the ability of a number of the hits in this network to directly modulate both basal and EGF-stimulated activation of the core pathway effectors MAPK1 and AKT, which is activated by PI3K ( and fig. S4
). Knockdown of ERBB3, ANXA6 (encoding annexin VI), PRKCD, NEDD9, BCAR1, or SH2D3C reduced basal activation of MAPK1 or AKT, or both, implying the encoded proteins could influence activity of these canonical effectors of EGFR-RAS signaling. However, knockdown of none of these genes reduced EGF-stimulated activation of AKT or MAPK1, indicating that EGF signaling to MAPK1 and AKT does not require these components of the network.
By contrast, a small number of the hits, including TBL1Y [encoding transducin (beta)-like, an adaptor protein], PIN1 (encoding peptidyl-prolyl cis/trans isomerase), NIMA-interacting 1 protein), SC4MOL (encoding sterol-C4-methyl oxidase-like protein, involved in sterol biosynthesis), and ASCL2 (encoding achaete-scute complex homolog 2, a transcription factor), were not connected by direct protein-protein interactions to the core network (), suggesting either a different mode of action or previously undetected connections.
Direct testing of knockdown of ASCL2 showed that a reduction of the encoded protein failed to statistically significantly affect MAPK1 or AKT activation under basal or EGF-stimulated conditions, although it potently sensitized erlotinib-treated cells to apoptosis (). ASCL2 is a target of Wnt signaling that is increased in abundance in a subset of colon carcinomas (13
), and that also controls the expansion of epithelial stem cells (14
). Together, these observations suggest that inhibition of ASCL2 may be promising as a direction for therapeutic development.
Chemical inhibition of proteins encoded by or associated with hit genes synergizes with erlotinib in reducing cell viability and tumor growth
We wanted to gain insights that could be rapidly translated into the clinic. Although the clinical use of RNAi is a topic of intense current research, small molecules and monoclonal antibodies remain the most broadly applicable therapy platforms. Further, given that siRNA rarely depletes targeted genes more than 90%, whereas small molecule inhibitors can completely block the functions of targeted gene products, they may produce more robust effects relative to RNAi. For some sensitizing hits, targeted small molecules exist, including Stattic [a small molecule inhibitor of STAT3 activation and dimerization (15
)], enzastaurin and Ro-318220 [both targeting the PRKC family (16
), including members represented among the hits].
Stattic synergized with erlotinib in inhibiting the viability of both A431 and HCT116 cells ( and fig. S5A
) in keeping with the reported dependency of EGFR-driven autocrine growth on STAT3 activation in cancer (17
), but showed no statistically significant synergy in reducing cell motility (, left panel). Both Ro-318220 and enzastaurin synergized with erlotinib in A431 and HCT116 cells ( and fig. S5B
), at multiple ratios of drug combination. Combined application of erlotinib and Ro-318220 also significantly reduced tumor cell motility (, right panel), and reduced tumor growth in a xenograft assay (). We analyzed the effect of drug combinations on the activation state of a series of benchmark signaling proteins relevant to proliferation and apoptosis, including AKT, ERK, MDM2 (an E3 ubiquitin ligase), and p53 (Fig. S6
). Erlotinib used as a single drug reduced basal ERK activation, and basal and EGF-stimulated AKT signaling, but did not affect MDM2 or p53. None of these proteins exhibited changes in amount of phosphorylated (active) species as a consequence of combined application of two drugs, with the exception of AKT, which consistently trended towards reduced phosphorylation on S473
in cells treated with erlotinib in combination with either stattic or enzastaurin. S473
phosphorylation of AKT has been described as dependent on integrated signaling by PRKC, EGFR, and mTOR (19
), which may be a pathway by which the enzastaurin-erlotinib combination reduced cell viability.
The proteins of the sensitizing BCAR1-SH3D2C-NEDD9 cluster have been linked to control of cell survival in the context of integrin-mediated signaling cascades that are frequently active in advanced and metastatic tumors (20
), suggesting this cluster may be of particular interest for therapeutic exploitation. However, these proteins are scaffolding proteins and not catalytic, and in contrast to STAT3, have not been targeted by existing small molecule agents. Given the results suggesting the enrichment of sensitizing genes among gene encoding proteins closely linked to core hits, we hypothesized that small molecules targeting kinases closely linked to this cluster by physical interactions might similarly provide a source of synergizing agents for combination with erlotinib. We identified more than 20 kinases as direct interaction neighbors around BCAR1, SH3D3C, and NEDD9 (). Ten of these kinases (either uniquely, or as one member of a protein family) are targeted by drugs that are in pre-clinical or clinical development, or approved agents, and some of these drugs have indeed been combined productively with EGFR-directed therapeutics, for example dasatinib, targeting Src family kinases (25
). Among these, the NEDD9-interacting (26
) kinase AURKA (known as Aurora A kinase or STK6) also stimulates the EGFR effector RALA (a guanosine trisphosphatase) (27
), and when overexpressed in tumors is associated with increased amounts of phosphorylated AKT (28
). Moreover, drugs targeting AURKA are currently undergoing clinical evaluation (29
Synergy between inhibitors of AURKA and inhibitors of EGFR
Analysis on the basis of the Chou-Talalay coefficient of interaction showed that the small molecule AURKA inhibitor PHA-680632 (29
) synergized with erlotinib in reducing cell viability of both A431 and HCT116 cells (). In HCT116 cells, we found strong synergy (coefficient of interaction values <0.5) between cetuximab and either PHA-680632 or another AURKA inhibitor C1368 (32
) (). Erlotinib exhibited strong synergy with PHA-680832 (combination index <0.5) and a slightly less strong interaction with C1368. Combination of AURKA and EGFR-targeting agents did not merely produce cytostasis, but resulted in cell death, increasing the frequency of apoptosis nearly two-fold (). In addition, combination of these drugs significantly reduced cell motility (), colony growth in soft agar (), and the growth of tumor xenografts implanted in SCID mice ().
Co-inhibition of EGFR and AURKA reduces SRC family kinase activity
We explored the signaling changes underlying the synergy between EGFR inhibition with erlotinib and the AURKA inhibitor PHA-680632. Treatment of cells with PHA-680632 alone did not reduce the abundance of EGFR or alter EGFR autophosphorylation, and activation when compared to DMSO-treated cells (fig. S7
). Furthermore, inhibition of AURKA alone with PHA-680632 had little effect on ERK1/2 or AKT phosphorylation in response to transient EGF stimulation ( and fig. S7
). However, in combination with erlotinib treatment, PHA-680632 significantly reduced Ser473
-AKT phosphorylation below the amounts seen in cells treated with either agent alone (), which is consistent with the reduced survival of cells treated with the drug combination, despite not significantly influencing other EGFR-dependent signaling benchmarks (fig. S7
To explore signaling consequences of co-inhibition of AURKA and EGFR in greater depth, we performed a more comprehensive phosphoproteomic analysis of 46 signaling proteins linked to cell proliferation or survival responses, or both, following treatment of A431 cells with erlotinib, PHA-680632, or both. Analysis of two independently performed Western-based screens with phosphorylation-directed antibodies () established that erlotinib blocked EGF-induced activation of multiple signaling pathways (reducing AKT and ERK phosphorylation below the amount in unstimulated cells), and PHA-680632 had little effect on EGF-mediated phosphorylation events when used as single agent. In contrast, the combination of drugs led to specific inhibition of a subset of proteins, including greater inhibition of ERK and AKT, as well as inhibition of GSK3β (glycogen synthase kinase 3β, a known functional partner of AUKRA (33
)), JNK (c-Jun-N-terminal kinase), and the SRC family kinase FGR.
Dual inhibition of Aurora-A and EGFR suppresses activation of multiple signaling nodes
We performed similar experiments to analyze signaling changes under the steady-state growth conditions in the presence of serum (when the activation state of pathways was not strictly dependent on EGF), which we used to assess synergistic killing of cells (). Strikingly, this analysis re-identified the same targets for the drug combination as those seen with EGF-dependent signaling (), but in addition showed significant reduction in the phosphorylation of STAT3 and a group of SRC kinases, including FGR, HCK, LYN, SRC, and LCK. These last hits in particular are intriguing, because the BCAR1-NEDD9-SH2D3C proteins that led us to consider AURKA are direct activators and substrates of these same kinases of SRC family () (34
). AURKA inhibitors may weaken this resistance cluster in the network.