Background Cell adhesion molecules (CAMs) are membrane-bound proteins that mediate cell-cell interactions through trans-cellular protein complexes. In the context of the neuronal synapse, studies of CAMs have revealed their roles from neuronal recognition and neuronal wiring to synaptic plasticity. CAMs form macromolecular complexes via cis- and trans-interactions; however, identifying the specific proteins in these assemblies is challenging. Their interactions are dynamic and transient, making them difficult to capture, and their hydrophobic transmembrane domains complicate extraction from biological samples. New method Here, we present a protocol to pulldown interacting partners of a Teneurin-3-GFP bait protein, as a representative CAM, from minimal mouse brain lysate. Comparison with existing methods Affinity purification of a bait protein from a biological sample, followed by mass spectrometry to identify captured prey proteins is a widely used, unbiased approach, though it usually requires large amounts of material. We show that our refined approach detects known Teneurin interactants while substantially reducing the animal tissue required. We further compared detergents used for lysate preparation and found that the total of CAM species enriched in Teneurin-3 samples relative to control varied considerably. Finally, we evaluated different normalization workflows to aid dataset interpretation. Conclusion This protocol provides an accessible approach for studying CAM interactions with limited animal tissue, enabling refined insights into the complex protein networks underlying synaptic connectivity.

Cholangiocarcinoma (CCA) is a type of liver cancer with an aggressive phenotype and dismal outcome in patients. The metastasis of CCA cancer cells to distant organs, commonly lung and lymph nodes, drastically reduces overall survival. However, mechanistic insight how CCA invades these metastatic sites is still lacking. This is partly because currently available models fail to mimic the complexity of tissue-specific environments for metastatic CCA. To create an in vitro model in which interactions between epithelial tumor cells and their surrounding extracellular matrix (ECM) can be studied in a metastatic setting, we combined patient-derived CCA organoids (CCAOs) (n=3) with decellularized human lung (n=3) and decellularized human lymph node (n=13). Decellularization resulted in removal of cells while preserving ECM structure and retaining important characteristics of the tissue origin. Proteomic analyses showed a tissue-specific ECM protein signature reflecting tissue functioning aspects. The macro and micro-scale mechanical properties, as determined by rheology and micro-indentation, revealed the local heterogeneity of the ECM. When growing CCAOs in decellularized lung and lymph nodes genes related to metastatic processes, including epithelial-to-mesenchymal transition and cancer stem cell plasticity, were significantly influenced by the ECM in an organ-specific manner. Furthermore, CCAOs exhibit significant differences in migration and proliferation dynamics dependent on the original patient tumor and donor of the target organ. In conclusion, CCA metastatic outgrowth is dictated both by the tumor itself as well as by the ECM of the target organ. Convergence of CCAOs with the ECM of its metastatic organs provide a new platform for mechanistic study of cancer metastasis.

Tumor initiation and progression are critically dependent on interaction of cancer cells with their cellular and extracellular microenvironment. Alterations in the composition, integrity, and mechanical properties of the extracellular matrix (ECM) dictate tumor processes including cell proliferation, migration, and invasion. Also in primary liver cancer, consisting of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), the dysregulation of the extracellular environment by liver fibrosis and tumor desmoplasia is pertinent. Yet, the exact changes occurring in liver cancer ECM remain uncharacterized and underlying tumor-promoting mechanisms remain largely unknown. Herein, an integrative molecular and mechanical approach is used to extensively characterize the ECM of HCC and CCA tumors by utilizing an optimized decellularization technique. We identified a myriad of proteins in both tumor and adjacent liver tissue, uncovering distinct malignancy-related ECM signatures. The resolution of this approach unveiled additional ECM-related proteins compared to large liver cancer transcriptomic datasets. The differences in ECM protein composition resulted in divergent mechanical properties on a macro- and micro-scale that are tumor-type specific. Furthermore, the decellularized tumor ECM was employed to create a tumor-specific hydrogel that supports patient-derived tumor organoids, which provides a new avenue for personalized medicine applications. Taken together, this study contributes to a better understanding of alterations to composition, stiffness, and collagen alignment of the tumor ECM that occur during liver cancer development.

Single-cell proteomics has the potential to decipher tumor heterogeneity, and a method like single-cell proteomics by mass spectrometry (SCoPE-MS) allows profiling several tens of single cells for >1,000 proteins per cell. This method, however, cannot link the proteome of individual cells with phenotypes of interest. Here, we developed a microscopy-based functional single-cell proteomic-profiling technology, called FUNpro, to address this. FUNpro enables screening, identification, and isolation of single cells of interest in a real-time fashion, even if the phenotypes are dynamic or the cells of interest are rare. We applied FUNpro to proteomically profile a newly identified small subpopulation of U2OS osteosarcoma cells displaying an abnormal, prolonged DNA damage response (DDR) after ionizing radiation (IR). With this, we identified the PDS5A protein contributing to the abnormal DDR dynamics and helping the cells survive after IR.