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Molecular & Cellular Proteomics

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      • Checklist (PDF)
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      • Checklist (PDF)
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      • Checklist (PDF)
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Cancer Biology*

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    Interaction proteomics identifies estrogen receptor beta association with multiple chromatin repressive complexes to inhibit cholesterol biosynthesis and exert an oncosuppressive role in triple-negative breast cancer
    Elena Alexandrova, Giorgio Giurato, Pasquale Saggese, Giovanni Pecoraro, Jessica Lamberti, Maria Ravo, Francesca Rizzo, Domenico Rocco, Roberta Tarallo, Tuula A. Nyman, Francesca Collina, Monica Cantile, Maurizio Di Bonito, Gerardo Botti, Giovanni Nassa and Alessandro Weisz
    Molecular & Cellular Proteomics December 2, 2019, mcp.RA119.001817; https://doi.org/10.1074/mcp.RA119.001817
  • You have access
    Profiling the surfaceome identifies therapeutic targets for cells with hyperactive mTORC1 signaling
    Junnian Wei, Kevin Leung, Charles Truillet, Davide Ruggero, James Wells and Michael J. Evans
    Molecular & Cellular Proteomics December 2, 2019, mcp.RA119.001785; https://doi.org/10.1074/mcp.RA119.001785
  • You have access
    Combined EGFR and ROCK inhibition in TNBC leads to cell death via impaired autophagic flux
    Stamatia Rontogianni, Sedef Iskit, Sander van Doorn, Daniel S. Peeper and Maarten Altelaar
    Molecular & Cellular Proteomics November 26, 2019, mcp.RA119.001800; https://doi.org/10.1074/mcp.RA119.001800
  • You have access
    Mitochondrial oxidative phosphorylation complex regulates NLRP3 inflammasome activation and predicts patient survival in nasopharyngeal carcinoma
    I-Che Chung, Lih-Chyang Chen, Ngan-Ming Tsang, Wen-Yu Chuang, Tzu-Chieh Liao, Sheng-Ning Yuan, Chun-Nan OuYang, David M. Ojcius, Chih-Ching Wu and Yu-Sun Chang
    Molecular & Cellular Proteomics November 13, 2019, mcp.RA119.001808; https://doi.org/10.1074/mcp.RA119.001808
  • Graph Algorithms for Condensing and Consolidating Gene Set Analysis Results
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    Graph Algorithms for Condensing and Consolidating Gene Set Analysis Results
    Sara R. Savage, Zhiao Shi, Yuxing Liao and Bing Zhang
    Molecular & Cellular Proteomics August 9, 2019, First published on May 29, 2019, 18 (8 suppl 1) S141-S152; https://doi.org/10.1074/mcp.TIR118.001263

    Weighted set cover and affinity propagation algorithms are used to combine results from multiple enrichment analyses. Weighted set cover first condenses enriched gene sets to use the fewest number of gene sets that cover all relevant genes. Affinity propagation then clusters the enriched pathways and selects the most representative set. Together they facilitate interpretation of multiple enrichment analysis results. A demonstration of its utility highlights both general and unique pathways associated with cancer survival across seven cancer types.

  • An Advanced Strategy for Comprehensive Profiling of ADP-ribosylation Sites Using Mass Spectrometry-based Proteomics
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    An Advanced Strategy for Comprehensive Profiling of ADP-ribosylation Sites Using Mass Spectrometry-based Proteomics
    Ivo A. Hendriks, Sara C. Larsen and Michael L. Nielsen
    Molecular & Cellular Proteomics May 1, 2019, First published on February 23, 2019, 18 (5) 1010-1026; https://doi.org/10.1074/mcp.TIR119.001315

    We augmented our MS-based proteomics strategy for the purification and identification of ADP-ribosylated peptides, through side-by-side comparison of complementary proteolytic digestions by trypsin or Lys-C, and ETD and EThcD fragmentation of precursors. This allowed us to identify an unprecedented number of ADP-ribosylated peptides (>11,000) and sites (>7000), gain insight into crosstalk between phosphorylation and ADP-ribosylation, and elucidate a spatial regulatory component in the targeting of ADP-ribosylation to distinct amino acid residue types.

  • Metabolic, Anti-apoptotic and Immune Evasion Strategies of Primary Human Myeloma Cells Indicate Adaptations to Hypoxia
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    Metabolic, Anti-apoptotic and Immune Evasion Strategies of Primary Human Myeloma Cells Indicate Adaptations to Hypoxia
    Lukas Janker, Rupert L. Mayer, Andrea Bileck, Dominique Kreutz, Johanna C. Mader, Kirsten Utpatel, Daniel Heudobler, Hermine Agis, Christopher Gerner and Astrid Slany
    Molecular & Cellular Proteomics May 1, 2019, First published on February 21, 2019, 18 (5) 936-953; https://doi.org/10.1074/mcp.RA119.001390

    In-depth proteome profiling of primary human CD138-positive plasma cells, derived from bone marrow biopsies from patients with different stages of multiple myeloma, have been performed on a Q Exactive orbitrap. Analysis of the 6218 identified proteins using label-free quantification with the MaxQuant software revealed strategies adopted by myeloma cells to overcome limitations imposed by hypoxic conditions in the bone marrow microenvironment, including specific immune evasion mechanisms and metabolic adaptations.

  • Quantitative Mass Spectrometry to Interrogate Proteomic Heterogeneity in Metastatic Lung Adenocarcinoma and Validate a Novel Somatic Mutation CDK12-G879V
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    Quantitative Mass Spectrometry to Interrogate Proteomic Heterogeneity in Metastatic Lung Adenocarcinoma and Validate a Novel Somatic Mutation CDK12-G879V
    Xu Zhang, Khoa Dang Nguyen, Paul A. Rudnick, Nitin Roper, Emily Kawaler, Tapan K. Maity, Shivangi Awasthi, Shaojian Gao, Romi Biswas, Abhilash Venugopalan, Constance M. Cultraro, David Fenyƶ and Udayan Guha
    Molecular & Cellular Proteomics April 1, 2019, First published on January 7, 2019, 18 (4) 622-641; https://doi.org/10.1074/mcp.RA118.001266

    Global quantitative mass spectrometry characterized tumor heterogeneity of lung metastatic site and eight different serially collected progressive metastatic lymph nodes over seven years from an exceptional responder lung adenocarcinoma patient. Specific signaling networks were enriched in lung compared with the lymph node metastatic sites. Fifty-five germline and 6 somatic variant peptides were identified and validated. MRM assays were developed for two novel somatic variant peptides. CDK12-G879V mutant specific to lung metastatic sites resulted in increased chemotherapy sensitivity of lung tumors.

  • Dynamic Phosphoproteomics Uncovers Signaling Pathways Modulated by Anti-oncogenic Sphingolipid Analogs
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    Dynamic Phosphoproteomics Uncovers Signaling Pathways Modulated by Anti-oncogenic Sphingolipid Analogs
    Peter Kubiniok, Brendan T. Finicle, Fanny Piffaretti, Alison N. McCracken, Michael Perryman, Stephen Hanessian, Aimee L. Edinger and Pierre Thibault
    Molecular & Cellular Proteomics March 1, 2019, First published on November 27, 2018, 18 (3) 408-422; https://doi.org/10.1074/mcp.RA118.001053

    The anti-neoplastic sphingolipid analog SH-BC-893 starves cancer cells to death by down-regulating cell surface nutrient transporters and blocking lysosomal trafficking events. However, the actual mechanism of action giving rise to these phenotypes remains unclear. Here, dynamic phosphoproteomics was used to further understand how the activity of PP2A is affected following cell treatment with SH-BC-893. These analyses combined with functional assays identified the differential regulation of Akt and Gsk3b by SH-BC-893 and C2-ceramide as responsible for the vacuolation of cells by SH-BC-893 but not C2-ceramide.

  • Integrated Genomic and Proteomic Analyses Reveal Novel Mechanisms of the Methyltransferase SETD2 in Renal Cell Carcinoma Development
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    Integrated Genomic and Proteomic Analyses Reveal Novel Mechanisms of the Methyltransferase SETD2 in Renal Cell Carcinoma Development
    Lin Li, Weili Miao, Ming Huang, Preston Williams and Yinsheng Wang
    Molecular & Cellular Proteomics March 1, 2019, First published on November 28, 2018, 18 (3) 437-447; https://doi.org/10.1074/mcp.RA118.000957

    SETD2 is commonly mutated in clear cell renal cell carcinoma (ccRCC), and exploring the underlying mechanism is urgent for developing targeted therapies for ccRCC. Here, we systematically analyzed the alterations in histone epigenetic marks (H3K36me3 and H4K16ac), mRNA transcriptome and chromatin-bound proteins evoked by SETD2 depletion. This work provided a robust foundation for understanding SETD2's role in ccRCC.

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