Sensitivity Analysis of the NPM-ALK Signalling Network Reveals Important Pathways for Anaplastic Large Cell Lymphoma Combination Therapy

Abstract

A large subset of anaplastic large cell lymphoma (ALCL) patients harbour a somatic aberration in which anaplastic lymphoma kinase (ALK) is fused to nucleophosmin (NPM) resulting in a constitutively active signalling fusion protein, NPM-ALK. We computationally simulated the signalling network which mediates pathological cell survival and proliferation through NPM-ALK to identify therapeutically targetable nodes through which it may be possible to regain control of the tumourigenic process. The simulations reveal the predominant role of the VAV1-CDC42 (cell division control protein 42) pathway in NPM-ALK-driven cellular proliferation and of the Ras / mitogen-activated ERK kinase (MEK) / extracellular signal-regulated kinase (ERK) cascade in controlling cell survival. Our results also highlight the importance of a group of interleukins together with the Janus kinase 3 (JAK3) / signal transducer and activator of transcription 3 (STAT3) signalling in the development of NPM-ALK derived ALCL. Depending on the activity of JAK3 and STAT3, the system may also be sensitive to activation of protein tyrosine phosphatase-1 (SHP1), which has an inhibitory effect on cell survival and proliferation. The identification of signalling pathways active in tumourigenic processes is of fundamental importance for effective therapies. The prediction of alternative pathways that circumvent classical therapeutic targets opens the way to preventive approaches for countering the emergence of cancer resistance.

Fig 1. NPM-ALK network scheme.

Nodes and links in black represent the core network whose components have been considered in our simulations. The surrounding components (nodes and arrows represented with grey dotted lines) indicate factors that influence the core network in different contexts and are not considered in the simulations. In the core network, the relevance of different nodes for signalling in disease development are linked by activating and inhibiting network’s links, indicated with → and ⊣, respectively. “Interleukins” includes IL-2, IL-4, IL-7, IL-9, IL-15, IL-21 and IL-22 [–36], while “Phosphatases” refers to lipid phosphatases such as the phosphatase and tensin homologue, which converts phosphatidylinositol-3,4,5-triphosphate (PIP3) back to phosphatidylinositol-4,5-bisphosphate (PIP2) [37].

Fig 2. Sensitivity profile of the network.

Sensitivity of the endpoints (“Cell Survival” and “Proliferation”, encircled in the network representation Fig 1 in red and black, respectively) is calculated according to [38, 39] and represented in red and black data points in the central plot. Each point in the central plot corresponds to one of $2^{20}·\frac{20}{2}\approx {10}^7$ states that differ from each other in exactly one node (recall that each node may assume a value of low or high activity). This enables the calculation of the sensitivity of every endpoint with respect to each node by comparing all pairs of states systematically. Following this step, the states that contributed the most to the sensitivity (the top- or bottom-2% regions) were examined to view how often each node is associated with the outcome. The results of this calculation are presented in the bar plots. ε_max (ε_min) indicates the maximum (minimum) sensitivity value corresponding to each bar in the plots on the right and left-hand sides. The bar plots in the middle represent the fractional involvement of the network nodes associated with negligible sensitivity (between ±0.005).

Fig 3. Signal flow in the NPM-ALK network.

Network configurations that predispose NPM-ALK to optimally control proliferation (A) and cell survival (B) are depicted where the size of a node represents its effect on the endpoint—the smaller is the node, the smaller is the effect. The colour represents signal intensity—the darker the node, the more active it is when the control node is highly active.

Fig 4. Sensitivity heat maps of the NPM-ALK network.

Sensitivity maps were calculated in response to variations in JAK3/STAT3, SHP1 and NPM-ALK activities. Independent activity levels of JAK3/STAT3 and SHP1 are represented in the xy-plane, those of NPM-ALK are represented along the z-axis. Sensitivity of proliferation and cell survival calculated with respect to JAK3/STAT3 variations results in positive values (A and B, respectively). Values with respect to SHP1 variations, which only connects other network nodes by inhibiting links, are negative (C and D, respectively). The pink arrow in B highlights a region of increased sensitivity at high NPM-ALK activity. The sensitive areas in C and D (yellow) indicate a variable pattern of sensitive regions of the parameter space as a function of NPM-ALK activity. At intermediate NPM-ALK activity, these regions are larger than at low and high NPM-ALK activity. In addition, a bi-modal sensitivity pattern appears at high levels of NPM-ALK activity.