Receptor Tyrosine Kinases Fall into Distinct Classes Based on Their Inferred Signaling Networks

Abstract

Although many anticancer drugs that target receptor tyrosine kinases (RTKs) provide clinical benefit, their long-term use is limited by resistance that is often attributed to increased abundance or activation of another RTK that compensates for the inhibited receptor. To uncover common and unique features in the signaling networks of RTKs, we measured time-dependent signaling in six isogenic cell lines, each expressing a different RTK as downstream proteins were systematically perturbed by RNA interference. Network models inferred from the data revealed a conserved set of signaling pathways and RTK-specific features that grouped the RTKs into three distinct classes: (i) an EGFR/FGFR1/c-Met class constituting epidermal growth factor receptor, fibroblast growth factor receptor 1, and the hepatocyte growth factor receptor c-Met; (ii) an IGF-1R/NTRK2 class constituting insulin-like growth factor 1 receptor and neurotrophic tyrosine receptor kinase 2; and (iii) a PDGFRβ class constituting platelet-derived growth factor receptor β. Analysis of cancer cell line data showed that many RTKs of the same class were coexpressed and that increased abundance of an RTK or its cognate ligand frequently correlated with resistance to a drug targeting another RTK of the same class. In contrast, abundance of an RTK or ligand of one class generally did not affect sensitivity to a drug targeting an RTK of a different class. Thus, classifying RTKs by their inferred networks and then therapeutically targeting multiple receptors within a class may delay or prevent the onset of resistance.

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“…75,89 For example., models of dynamic changes in signalling networks of receptor tyrosine kinases (RTK) families have facilitated the classification of RTKs and their network activation and led to the identification of points of intervention to delay or overcome drug resistance. 78,90 Furthermore, Komurov et al, 91 used a novel network-based analysis of gene expression and proteomics coupled to ErbB2-positive patient survival data, and showed that in breast tumours with acquired resistance to lapatinib, the drug was still able to block EGFR/ErbB2 signalling, but that upregulation of glucose metabolism, unfolded protein response, and endoplasmic reticulum (ER) stress pathways mitigated the ability of lapatinib to induce cell death, suggesting that coordinated targeting of metabolic networks and signalling networks has the potential to improve patient outcomes. 91,92 Beckman et al .…”

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“…Amplifications of Ras/Raf are present in cancer cells continuously stimulated by growth factors such as HER-soluble ligands, autocrine signaling or constitutively activated mutant receptors. RAS gene mutations have been found in colon (45%), pancreatic (90%), ovarian (30%) and papillary thyroid (60%) carcinomas, and in 15% of melanomas and 35% of non-small-cell lung cancers (NSCLC) (Eccles, 2011;Wagner et al, 2013).…”

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