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Phosphoproteomics and ubiquitinomics data-independent acquisition (DIA) mass spectrometry (MS) data is typically analyzed by using a data-dependent acquisition (DDA) spectral library. The performance of various library-free strategies for analyzing phosphoproteomics and ubiquitinomics DIA MS data has not been evaluated. In this study, we systematically compare four commonly used DDA library-free approaches including Spectronaut's directDIA, DIA-Umpire, DIA-MSFragger, and in silico-predicted library for analysis of phosphoproteomics SWATH, DIA, and diaPASEF data as well as ubiquitinomics diaPASEF data. Spectronaut's directDIA shows the highest sensitivity for phosphopeptide detection not only in synthetic phosphopeptide samples but also in phosphoproteomics SWATH-MS and DIA data from real biological samples, when compared to the other three library-free strategies. For phosphoproteomics diaPASEF data, Spectronaut's directDIA and the in silico-predicted library based on DIA-NN identify almost the same number of phosphopeptides as a project-specific DDA spectral library. However, only about 30% of the total phosphopeptides are commonly identified, suggesting that the library-free strategies for phospho-diaPASEF data need further improvement in terms of sensitivity. For ubiquitinomics diaPASEF data, the in silico-predicted library performs the best among the four workflows and detects ∼50% more K-GG peptides than a project-specific DDA spectral library. Our results demonstrate that Spectronaut's directDIA is suitable for the analysis of phosphoproteomics SWATH-MS and DIA MS data, while the in silico-predicted library based on DIA-NN shows substantial advantages for ubiquitinomics diaPASEF MS data.

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Exosomes derived from mesenchymal stem cells (MSCs) have been used for cancer treatment, however, an in-depth analysis of the exosomal proteomes is lacking. In this manuscript, we use the diaPASEF (parallel accumulation serial fragmentation combined with the data-independent acquisition) method to quantify exosomes derived from human umbilical cord mesenchymal stem cells (UCMSCs) and rat bone marrow stem cells (BMSCs), resulting in identification of 4200 human proteins and 5362 rat proteins. Comparison of human exosomal proteins and total cellular proteins reveals that some proteins exist in the exosomes exclusively that can be served as potential markers for exosomes. Quantitative proteomic analysis of exosomes from different passages of BMSCs shows that the proteins involved in TGF-ß signaling pathway are regulated in abundance, which could be markers for the therapeutic ability of BMSC exosomes. Collectively, the data presented by this study can be a resource for further study of exosome research.

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Targeted analysis of data-independent acquisition (DIA) data needs a spectral library, which is generated by data-dependent acquisition (DDA) experiments or directly from DIA data. A comparison of the DDA library and DIA library in analyzing DIA data has been reported. However, the effects of different spectral libraries on the analysis of diaPASEF data have not been investigated. Here, we generate different spectral libraries with varying proteome coverage to analyze parallel accumulation-serial fragmentation (diaPASEF) data. Besides, we also employ the library-free strategy. The library, constructed by extensive fractionation DDA experiments, produces the highest numbers of precursors and proteins but with a high percentage of missing values. The library-free strategy identifies 10-20% fewer proteins than the library-based method but with a high degree of data completeness. A further study shows that the library-free strategy, although it identifies fewer proteins than the library-based method, leads to similar biological conclusions as the library-based method.

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Disassembly of intercellular junctions is a hallmark of epithelial-mesenchymal transition (EMT). However, how the junctions disassemble remains largely unknown. Here, we report that E3 ubiquitin ligase Smurf1 targets p120-catenin, a core component of adherens junction (AJ) complex, for monoubiquitination during transforming growth factor ß (TGFß)-induced EMT, thereby leading to AJ dissociation. Upon TGFß treatment, activated extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylates T900 of p120-catenin to promote its interaction with Smurf1 and subsequent monoubiquitination. Inhibition of T900 phosphorylation or ubiquitination of p120-catenin abrogates TGFß-induced AJ dissociation and consequent tight junction (TJ) dissociation and cytoskeleton rearrangement, hence markedly blocking lung metastasis of murine breast cancer. Moreover, the T900 phosphorylation level of p120-catenin is positively correlated with malignancy of human breast cancer. Hence, our study reveals the underlying mechanism by which TGFß induces dissociation of AJs during EMT and provides a potential strategy to block tumor metastasis.

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The immunosuppressive tumor microenvironment is a key obstacle to hinder a cancer immunotherapy. Myeloid-derived suppressor cells (MDSCs) have been considered as a major player in immunosuppression. In this study, we find that tumor-infiltrating MDSCs (tiMDSCs) are less immunosuppressive than tumor-associated macrophages (TAMs) in multiple murine orthotopic breast tumor models. Compared to TAMs, tiMDSCs produce higher levels of pro-inflammatory factors and lower levels of anti-inflammatory factors. Furthermore, tiMDSCs are preferentially located in hypoxic areas and are more pro-angiogenic than TAMs. Consistent with these functional disparities, a shift from tiMDSCs to TAMs is observed during the progression of breast cancer. Moreover, infiltration of tiMDSCs is also noted in distal colonization of breast cancer cells in the lung. Taken together, our findings indicate that tiMDSCs are more pro-angiogenic and promote tumor initiation, while TAMs are more immunosuppressive and facilitate tumor immune evasion. This study suggests that selectively targeting on TAMs could alleviate the immunosuppressive tumor microenvironment and potentiate cancer immunotherapy.