Dr. Oliver Klein:
"When Virchow Meets Mass Spectrometry-how Molecular Signatures May Aid Predict Disease Progression and Therapy Outcome"
Intra-tissue heterogeneity and its evolution over disease course have assisted an expansion of tissue sample collection accompanying patient treatment and trials worldwide. In-depth analysis and further interpretation with respect to potential clinical implications will achieve a better grasp of the extent of intra tissue heterogeneity in several disease to improve personalized patient treatment. In disease progression, in general, is known to be affected by cellular interplay and the surrounding microenvironment. Taken together, there is unmet need for reliable disease risk classification that takes the microenvironment and spatial heterogeneity into account. Mass spectrometry imaging (MSI) innovative technology combines the comprehensive mass spectrometric technique with a conventional histological evaluation. It allows unlabeled as well targeted analysis of molecules (e.g., metabolites, proteins, peptide, lipids and glycans) directly on a single tissue section, preserving their spatial coordinates and generating a molecular intensity map displaying the spatial relative molecule abundance. Consequently, BIH's Mass Spectrometry Imaging unit helps discover biomarkers for therapy stratification and decipher tissue heterogeneities by advancing MSI technology and combining it with machine-learning algorithms.
Dr. Hagen Kulbe:
"In Silico Prediction of Novel Therapeutic Approaches To Distinct Molecular Subtypes of HGSOC"
Tumor heterogeneity in high-grade serous ovarian cancer (HGSOC) is a proposed cause of acquired resistance to treatment and high rates of relapse. The failure to effectively treat the distinct molecular subtypes to lower mortality highlights the need for effective targeted therapeutic strategies for personalized medicine (PM). Here, we integrated in silico, gene expression and in vivo murine patient-derived xenograft (PDX) drug response data to elucidate potential actionable targets within the distinct molecular phenotypes of mesenchymal HGSOC. Our results revealed a complex tumor microenvironment-mediated cytokine signaling network implicating TNF-α, IL-6 and TGF-β in constitutive activation of the PI3K/AKT pathway as a principal driver of mesenchymal HGSOC. The in silico predictions were corroborated by phospho-proteomics data revealing hyperactivation of PIK3CA and PAK4. Accordingly, PI3K inhibition achieved the highest efficacy in PDX models. Thus, our work suggests treatment strategies involving inhibition of PI3K, CK2 and SRC, or PAK4/p38 for the PM of mesenchymal HGSOC.
