Systems Modeling Identifies Divergent Receptor Tyrosine Kinase Reprogramming to MAPK Pathway Inhibition

Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways

The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and targeted therapies for related diseases. Recent advances in single-cell proteomic technologies have provided unprecedented opportunities to investigate the heterogeneity and noise within complex, multi-signaling networks across diverse cells and cell types. Mathematical modeling has become a powerful interdisciplinary tool that bridges mathematics and experimental biology, providing valuable insights into these intricate cellular processes. In addition, statistical methods have been developed to infer pathway topologies and estimate unknown parameters within dynamic models. This review presents a comprehensive analysis of how mathematical modeling of the MAPK pathway deepens our understanding of its regulatory mechanisms, enhances the prediction of system behavior, and informs experimental research, with a particular focus on recent advances in modeling and inference using single-cell proteomic data.

An integrated mechanistic and data-driven computational model predicts cell responses to high- and low-affinity EGFR ligands

The biophysical properties of ligand binding heavily influence the ability of receptors to specify cell fates. Understanding the rules by which ligand binding kinetics impact cell phenotype is challenging, however, because of the coupled information transfers that occur from receptors to downstream signaling effectors and from effectors to phenotypes. Here, we address that issue by developing an integrated mechanistic and data-driven computational modeling platform to predict cell responses to different ligands for the epidermal growth factor receptor (EGFR). Experimental data for model training and validation were generated using MCF7 human breast cancer cells treated with the high- and low-affinity ligands epidermal growth factor (EGF) and epiregulin (EREG), respectively. The integrated model captures the unintuitive, concentration-dependent abilities of EGF and EREG to drive signals and phenotypes differently, even at similar levels of receptor occupancy. For example, the model correctly predicts the dominance of EREG over EGF in driving a cell differentiation phenotype through AKT signaling at intermediate and saturating ligand concentrations and the ability of EGF and EREG to drive a broadly concentration-sensitive migration phenotype through cooperative ERK and AKT signaling. Parameter sensitivity analysis identifies EGFR endocytosis, which is differentially regulated by EGF and EREG, as one of the most important determinants of the alternative phenotypes driven by different ligands. The integrated model provides a new platform to predict how phenotypes are controlled by the earliest biophysical rate processes in signal transduction and may eventually be leveraged to understand receptor signaling system performance depends on cell context.

One-sentence summary

Integrated kinetic and data-driven EGFR signaling model identifies the specific signaling mechanisms that dictate cell responses to EGFR activation by different ligands.

Concurrent inhibition of FAK/SRC and MEK overcomes MEK inhibitor resistance in Neurofibromatosis Type I related malignant peripheral nerve sheath tumors

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft-tissue sarcomas which lack effective drugs. Loss of the RAS GTPase-activating protein NF1 and subsequent overactivation of mitogen-activated protein kinase kinase (MAPK) signaling exist nearly uniformly in MPNST, making MAPK inhibition a promising therapeutic intervention. However, the efficacy of MEK inhibitor (MEKi) monotherapy was limited in MPNST and the relative mechanisms remained largely unexplored. In this study, we generated three MEKi-resistant cell models and investigated the mechanisms of MEKi resistance using high-throughput transcriptomic sequencing. We discovered that cell apoptosis and cell cycle arrest induced by MEKi were rescued in MEKi-resistant cells and the upregulation of LAMA4/ITGB1/FAK/SRC signaling conferred resistance to MEKi. In addition, concurrent inhibition of MAPK signaling and FAK/SRC cascade could sensitize MPNST cells to MEKi. Our findings provide potential solutions to overcome MEKi resistance and effective combination therapeutic strategies for treating MPNSTs.

MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY

A full understanding of cell signaling processes requires knowledge of protein structure/function relationships, protein-protein interactions, and the abilities of pathways to control phenotypes. Computational models offer a valuable framework for integrating that knowledge to predict the effects of system perturbations and interventions in health and disease. Whereas mechanistic models are well suited for understanding the biophysical basis for signal transduction and principles of therapeutic design, data-driven models are particularly suited to distill complex signaling relationships among samples and between multivariate signaling changes and phenotypes. Both approaches have limitations and provide incomplete representations of signaling biology, but their careful implementation and integration can provide new understanding for how manipulating system variables impacts cellular decisions.

AXL Receptor in Breast Cancer: Molecular Involvement and Therapeutic Limitations

Breast cancer was one of the first malignancies to benefit from targeted therapy, i.e., treatments directed against specific markers. Inhibitors against HER2 are a significant example and they improved the life expectancy of a large cohort of patients. Research on new biomarkers, therefore, is always current and important. AXL, a member of the TYRO-3, AXL and MER (TAM) subfamily, is, today, considered a predictive and prognostic biomarker in many tumor contexts, primarily breast cancer. Its oncogenic implications make it an ideal target for the development of new pharmacological agents; moreover, its recent role as immune-modulator makes AXL particularly attractive to researchers involved in the study of interactions between cancer and the tumor microenvironment (TME). All these peculiarities characterize AXL as compared to other members of the TAM family. In this review, we will illustrate the biological role played by AXL in breast tumor cells, highlighting its molecular and biological features, its involvement in tumor progression and its implication as a target in ongoing clinical trials.

Receptor-Driven ERK Pulses Reconfigure MAPK Signaling and Enable Persistence of Drug-Adapted BRAF-Mutant Melanoma Cells

Targeted inhibition of oncogenic pathways can be highly effective in halting the rapid growth of tumors but often leads to the emergence of slowly dividing persister cells, which constitute a reservoir for the selection of drug-resistant clones. In BRAF^V600E melanomas, RAF and MEK inhibitors efficiently block oncogenic signaling, but persister cells emerge. Here, we show that persister cells escape drug-induced cell-cycle arrest via brief, sporadic ERK pulses generated by transmembrane receptors and growth factors operating in an autocrine/paracrine manner. Quantitative proteomics and computational modeling show that ERK pulsing is enabled by rewiring of mitogen-activated protein kinase (MAPK) signaling: from an oncogenic BRAF^V600E monomer-driven configuration that is drug sensitive to a receptor-driven configuration that involves Ras-GTP and RAF dimers and is highly resistant to RAF and MEK inhibitors. Altogether, this work shows that pulsatile MAPK activation by factors in the microenvironment generates a persistent population of melanoma cells that rewires MAPK signaling to sustain non-genetic drug resistance.

A census of pathway maps in cancer systems biology

A key goal of cancer systems biology is to use big data to elucidate the molecular networks by which cancer develops. However, to date there has been no systematic evaluation of how far these efforts have progressed. In this Analysis, we survey six major systems biology approaches for mapping and modelling cancer pathways with attention to how well their resulting network maps cover and enhance current knowledge. Our sample of 2,070 systems biology maps captures all literature-curated cancer pathways with significant enrichment, although the strong tendency is for these maps to recover isolated mechanisms rather than entire integrated processes. Systems biology maps also identify previously underappreciated functions, such as a potential role for human papillomavirus-induced chromosomal alterations in ovarian tumorigenesis, and they add new genes to known cancer pathways, such as those related to metabolism, Hippo signalling and immunity. Notably, we find that many cancer networks have been provided only in journal figures and not for programmatic access, underscoring the need to deposit network maps in community databases to ensure they can be readily accessed. Finally, few of these findings have yet been clinically translated, leaving ample opportunity for future translational studies. Periodic surveys of cancer pathway maps, such as the one reported here, are critical to assess progress in the field and identify underserved areas of methodology and cancer biology.

AXL as a Target in Breast Cancer Therapy

AXL is a receptor tyrosine kinase (RTK) that has been implicated in diverse tumor-promoting processes such as proliferation, migration, invasion, survival, and apoptosis. AXL therefore plays a role in cancer progression, and AXL has been implicated in a wide variety of malignancies from solid tumors to hematopoietic cancers where it is often associated with poor prognosis. In cancer, AXL has been shown to promote epithelial to mesenchymal transition (EMT), metastasis formation, drug resistance, and a role for AXL in modulation of the tumor microenvironment and immune response has been identified. In light of these activities multiple AXL inhibitors have been developed, and several of these have entered clinical trials in the U.S. In breast cancer, high levels of AXL expression have been observed. The role of AXL in cancer with a focus on therapeutic implications for breast cancer is discussed.