Stage-dependent phosphoproteome remodeling of Parkinson's disease blood cells.

The complexity and heterogeneity of PD necessitate advanced diagnostic and prognostic tools to elucidate its molecular mechanisms accurately. In this study, we addressed this challenge by conducting a pilot phospho-proteomic analysis of peripheral blood mononuclear cells (PBMCs) from idiopathic PD patients at varying disease stages to delineate the functional alterations occurring in these cells throughout the disease course and identify key molecules and pathways contributing to PD progression. By integrating clinical data with phospho-proteomic profiles across various PD stages, we identify potential stage-specific molecular signatures indicative of disease progression. This integrative approach allows for the discernment of distinct disease states and enhances our understanding of PD heterogeneity.

SignalingProfiler 2.0 a network-based approach to bridge multi-omics data to phenotypic hallmarks.

Unraveling how cellular signaling is remodeled upon perturbation is crucial for understanding disease mechanisms and identifying potential drug targets. In this pursuit, computational tools generating mechanistic hypotheses from multi-omics data have invaluable potential. Here, we present a newly implemented version (2.0) of SignalingProfiler, a multi-step pipeline to draw mechanistic hypotheses on the signaling events impacting cellular phenotypes. SignalingProfiler 2.0 derives context-specific signaling networks by integrating proteogenomic data with the prior knowledge-causal network. This is a freely accessible and flexible tool that incorporates statistical, footprint-based, and graph algorithms to accelerate the integration and interpretation of multi-omics data. Through a benchmarking process on three proof-of-concept studies, we demonstrate the tool's ability to generate hierarchical mechanistic networks recapitulating novel and known perturbed signaling and phenotypic outcomes, in both human and mice contexts. In summary, SignalingProfiler 2.0 addresses the emergent need to derive biologically relevant information from complex multi-omics data by extracting interpretable networks.

Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction.

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Phase I Trial of Viral Vector-Based Personalized Vaccination Elicits Robust Neoantigen-Specific Antitumor T-Cell Responses.

PURPOSE: Personalized vaccines targeting multiple neoantigens (nAgs) are a promising strategy for eliciting a diversified antitumor T-cell response to overcome tumor heterogeneity. NOUS-PEV is a vector-based personalized vaccine, expressing 60 nAgs and consists of priming with a nonhuman Great Ape Adenoviral vector (GAd20) followed by boosts with Modified Vaccinia Ankara. Here, we report data of a phase Ib trial of NOUS-PEV in combination with pembrolizumab in treatment-naïve patients with metastatic melanoma (NCT04990479). PATIENTS AND METHODS: The feasibility of this approach was demonstrated by producing, releasing, and administering to 6 patients 11 of 12 vaccines within 8 weeks from biopsy collection to GAd20 administration. RESULTS: The regimen was safe, with no treatment-related serious adverse events observed and mild vaccine-related reactions. Vaccine immunogenicity was demonstrated in all evaluable patients receiving the prime/boost regimen, with detection of robust neoantigen-specific immune responses to multiple neoantigens comprising both CD4 and CD8 T cells. Expansion and diversification of vaccine-induced T-cell receptor (TCR) clonotypes was observed in the posttreatment biopsies of patients with clinical response, providing evidence of tumor infiltration by vaccine-induced neoantigen-specific T cells. CONCLUSIONS: These findings indicate the ability of NOUS-PEV to amplify and broaden the repertoire of tumor-reactive T cells to empower a diverse, potent, and durable antitumor immune response. Finally, a gene signature indicative of the reduced presence of activated T cells together with very poor expression of the antigen-processing machinery genes has been identified in pretreatment biopsies as a potential biomarker of resistance to the treatment.

A key role of the WEE1-CDK1 axis in mediating TKI-therapy resistance in FLT3-ITD positive acute myeloid leukemia patients.

The insertion site of the internal tandem duplications (ITDs) in the FLT3 gene affects the sensitivity to tyrosine kinase inhibitors (TKIs) therapy in acute myeloid leukemia (AML). Patients with the ITD in the tyrosine kinase domain lack effective therapeutic options. Here, to identify genotype-driven strategies increasing the TKI therapy efficacy, we developed SignalingProfiler, a strategy supporting the integration of high-sensitive mass spectrometry-based (phospho)proteomics, RNA sequencing datasets with literature-derived signaling networks. The approach generated FLT3-ITD genotype-specific predictive models and revealed a conserved role of the WEE1-CDK1 axis in TKIs resistance. Remarkably, pharmacological inhibition of the WEE1 kinase synergizes and strengthens the pro-apoptotic effect of TKIs therapy in cell lines and patient-derived primary blasts. Finally, we propose a new molecular mechanism of TKIs resistance in AML and suggest the combination of WEE1 inhibitor and TKI as a therapeutic option to improve patients clinical outcome.