Our results demonstrate that cells with oncogenic K-RAS, oncogenic N-RAS, or no RAS mutations differentially affect multiple pathways to impact cell fate. These perturbations to the cell network influence the ERK pathway by convoluting positive and negative feedback circuits, as well as additional pathways that together direct cell behavior. Importantly, despite the clear differences in ERK, prediction of the RAS impact on apoptosis and chemokine levels requires incorporation of both ERK and additional pathways which provide a context for the ERK variations.
Similar to previous reports in HT-29 cells (23
) and mammary epithelial cells (24
), TNFα treatment led to transactivation of the EGFR by TGFα in the RAS-variant cells. TACE has been implicated as the enzyme responsible for cleaving TGFα from the cell surface (25
). Interestingly, activation of ERK has been linked to phosphorylation of TACE, which results in trafficking of TACE to the cell surface (32
). Despite their constitutively active K-RAS allele, DLD-1 cells exhibit lower levels of basal pERK, which is mitigated by DUSP6 (5
). The reduced levels of basal pERK combined with the lower levels of TACE (Supplementary Fig. S5C
) likely explain the reduced TGFα release and subsequent lower activation of pERK in DLD-1.
Differences in pERK at later times among the RAS-variants appear to be mediated by a transcriptionally-induced protein, DUSP5. Induction of the negative-feedback DUSP genes was recently shown to be pathway-specific process (21
). DUSP5 is a nuclear-localized phosphatase with ERK-specificity (22
) that is induced by growth factors and stress (33
). In the DKs8-N cells, normalized DUSP5 levels are lower, and induction is delayed, correlating with the extended duration of pERK in these cells with oncogenic N-RAS (). DUSP6, a cytoplasmic ERK-specific phosphatase, has been previously shown to impact basal pERK in K-RAS mutant cells (5
) and is induced during cellular transformation by oncogenic RAS (34
). To our knowledge, this is the first report of RAS-dependent differential activation of DUSP5.
The TNFα-induced TGFα autocrine loop was previously shown to initiate a pro-death IL-1 loop in HT-29 colon carcinoma cells (23
). In the RAS mutant cell lines, we found no evidence for the IL-1 loop, and instead, our results suggest that TGFα initiated a pro-death loop as well as a pro-survival CXCL1 and/or CXCL8 cascade (). CXCL1 has been reported to be elevated in colon cancer (35
) and associated with greater proliferation and invasiveness in colon carcinoma cells (36
), while CXCL8 constitutes a pro-proliferative autocrine loop in HCT-116 (37
). Recent reports have begun to highlight unexpected autocrine roles for chemokines, including CXCR2/p53-dependent senescence (38
), which were not observed in this panel of p53-mutant cell lines (13
). It will be important in future studies to examine the relative importance of the paracrine and autocrine effects of chemokine production on tumor development.
To interpret the broader effects of the RAS variations on the cellular signaling network, and how these changes are integrated into decisions, we utilized a large phosphoproteomic data set and PLSR (). PLSR has been previously used to provide evidence for induced autocrine cascades, demonstrate common effector processing for cell specific responses, and predict production of interleukins (23
). In these studies, we demonstrate that the same compendium of signals can predict diverse outcomes (apoptosis and CXCL1/8). The two models have different components (Supplemental Tables S2-S8
), indicating that parts of the signaling network are more responsible for one outcome versus another. We also demonstrate that models built without the ‘dominant’ signals are still predictive. This observation is important as it [a] suggests that the data and model allow us to observe how a change in one signal is propagated throughout a network and [b] indicates that even by only collecting information about a few molecules, we can still capture important network behavior. The separate PLSR models show time-dependence, suggesting that the ‘early’ signals result in the production of chemokines for the CXCL1/8 autocrine loop. The ‘late’ signals, which may represent the effects of these chemokine loops, then determine the apoptotic decision.
In conclusion, we have demonstrated multiple differences that result from changes in the form of mutant RAS expressed by cells. While pERK signals in response to TNFα are clearly different through changes to both positive and negative feedback circuits, only with the inclusion of additional pathway context can we predict the differences seen in apoptosis between the RAS variants. Combined, our data suggests that multi-pathway models can interpret the influence of the oncogenic RAS proteins by including both direct effects (pERK) and contextual effects such as how the TGFα-chemokine autocrine cascade impact other signaling pathways.