Proteogenomic characterization of pancreatic ductal adenocarcinoma

Cao, Liwei; Huang, Chen; Zhou, Daniel Cui; Hu, Yingwei; Lih, Tung-Shing Mamie; Savage, Sara R.; Krug, Karsten; Clark, David; Schnaubelt, Michael; Chen, Lijun; Leprevost, Felipe da Veiga; Eguez, Rodrigo Vargas; Yang, Weiming; Pan, Jianbo; Wen, Bo; Dou, Yongchao; Jiang, Wen; Liao, Yuxing; Shi, Zhiao; Terekhanova, Nadezhda V.; Cao, Song; Lu, Rita Jui-Hsien; Li, Yize; Liu, Ruiyang; Zhu, Houxiang; Ronning, Peter; Wu, Yige; Wyczalkowski, Matthew A.; Easwaran, Hariharan; Danilova, Ludmila; Mer, Arvind Singh; Yoo, Seungyeul; Wang, Joshua M.; Liu, Wenke; Haibe‐Kains, Benjamin; Thiagarajan, Mathangi; Jewell, Scott D.; Hostetter, Galen; Newton, Chelsea J.; Li, Qing Kay; Roehrl, Michael H. A.; Fenyö, David; Wang, Pei; Nesvizhskii, Alexey I.; Mani, D. R.; Omenn, Gilbert S.; Boja, Emily S.; Mesri, Mehdi; Robles, Ana I.; Rodriguez, Henry; Bathe, Oliver F.; Chan, Daniel W.; Hruban, Ralph H.; Li, Ding; Zhang, Bing; Zhang, Hui; Amin, Mitual; An, Eunkyung; Ayad, Christina; Bauer, Thomas; Birger, Chet; Birrer, Michael J.; Boca, Simina M.; Bocik, William; Borucki, Melissa; Cai, Shuang; Carr, Steven A.; Cerda, Sandra; Chen, Huan; Chen, Steven; Chesla, David; Chinnaiyan, Arul M.; Colaprico, Antonio; Cottingham, Sandra; Derejska, Magdalena; Dhanasekaran, Saravana M.; Domagalski, Marcin J.; Druker, Brian J.; Duffy, Elizabeth; Dyer, Maureen A.; Edwards, Nathan; Ellis, Matthew J.; Eschbacher, Jennifer; Francis, Alicia; Francis, Jesse; Gabriel, Stacey; Gabrovski, N; Gardner, Johanna; Getz, Gad; Gillette, Michael A.; Goldthwaite, Charles A.; Grady, Pamela; Guo, Shuai; Hariharan, Pushpa; Hiltke, Tara; Hindenach, Barbara; Hoadley, Katherine A.; Huang, Jasmine; Jones, Corbin D.; Ketchum, Karen A.; Kinsinger, Christopher R.; Koziak, Jennifer M.; Kuśnierz, Katarzyna; Liu, Tao; Jiang, Long; Mallery, David; Mareedu, Sailaja; Matteotti, Ronald; Maunganidze, Nicollette; McGarvey, Peter B.; Minoo, Parham; Paklina, Oxana; Paulovich, Amanda G.; Payne, Samuel H.; Potapova, Olga; Pruetz, Barbara L.; Qi, Liqun; Roche, Nancy; Rodland, Karin D.; Rohrer, Daniel C.; Schadt, Eric E.; Шабунин, А. В.; Shelton, Troy; Shutack, Yvonne; Singh, Shilpi; Smith, Michael J.; Smith, Richard; Sokoll, Lori J.; Suh, James; Thangudu, Ratna R.; Tsang, Shirley; Um, Ki Sung; Valley, Dana R.; Vatanian, Negin; Wang, Wenyi; Wilson, George; Wiznerowicz, Maciej; Zhang, Zhen; Zhao, Grace

doi:10.1016/j.cell.2021.08.023

Cited by 323 publications

(280 citation statements)

References 222 publications

(181 reference statements)

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“…It plays vital roles in physiopathological processes, including the progression of various cancers ( Ohtsubo and Marth, 2006 ). Glycoproteomic (glycoprotein, glycosite, glycan, and intact glycopeptide) analysis of clinical samples can reveal tumor biomarkers and therapeutic targets ( Zhang et al, 2020a ; Cao et al, 2021 ). Among them, intact glycopeptide analysis can simultaneously obtain glycoprotein, glycosite, and glycan composition information.…”

Section: Introductionmentioning

confidence: 99%

Comparative N-Glycoproteomics Analysis of Clinical Samples Via Different Mass Spectrometry Dissociation Methods

Zeng

Zheng

et al. 2022

Front. Chem.

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Site-specific N-glycosylation characterization requires intact N-glycopeptide analysis based on suitable tandem mass spectrometry (MS/MS) method. Electron-transfer/higher-energy collisional dissociation (EThcD), stepped collision energy/higher-energy collisional dissociation (sceHCD), higher-energy collisional dissociation-product-dependent electron-transfer dissociation (HCD-pd-ETD), and a hybrid mass spectrometry fragmentation method EThcD-sceHCD have emerged as valuable approaches for glycoprotein analysis. However, each of them incurs some compromise, necessitating the systematic performance comparisons when applied to the analysis of complex clinical samples (e.g., plasma, urine, cells, and tissues). Herein, we compared the performance of EThcD-sceHCD with those previous approaches (EThcD, sceHCD, HCD-pd-ETD, and sceHCD-pd-ETD) in the intact N-glycopeptide analysis, and determined its applicability for clinical N-glycoproteomic study. The intact N-glycopeptides of distinct samples, namely, plasma from prostate cancer (PCa) patients, urine from immunoglobulin A nephropathy (IgAN) patients, human hepatocarcinoma cell line (HepG2), and thyroid tissues from thyroid cancer (TC) patients were analyzed by these methods. We found that EThcD-sceHCD outperformed other methods in the balance of depth and accuracy of intact N-glycopeptide identification, and sceHCD and EThcD-sceHCD have good complementarity. EThcD-sceHCD holds great potential for biomarker discovery from clinical samples.

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Section: Introductionmentioning

confidence: 99%

Comparative N-Glycoproteomics Analysis of Clinical Samples Via Different Mass Spectrometry Dissociation Methods

Zeng

Zheng

et al. 2022

Front. Chem.

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“…However, our results provide additional evidence of the utilities of these serum biomarkers and their complementary values as panels in the early detection of PDAC, which also serves as a cross-validation study via parallel analyses in a large, independent sample cohort in a multiplex immunoassay format. The development and application of multiple high-throughput screening technologies have made it possible that a large number of ‘-omic’ data, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, that may be combined as diagnostic or prognostic indices [ 40 , 41 , 42 ]. The selection of optimal panels through stepwise multivariate logistic regression allowed us to identify markers that are complementary in detecting specific disease conditions.…”

Section: Discussionmentioning

confidence: 99%

Validation of Serum Biomarkers That Complement CA19-9 in Detecting Early Pancreatic Cancer Using Electrochemiluminescent-Based Multiplex Immunoassays

et al. 2021

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Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy; its early detection is critical for improving prognosis. Electrochemiluminescent-based multiplex immunoassays were developed with high analytical performance. All proteins were analyzed in sera of patients diagnosed with PDAC (n = 138), benign pancreatic conditions (111), and healthy controls (70). The clinical performance of these markers was evaluated individually or in combination for their complementarity to CA19-9 in detecting early PDAC. Logistic regression modeling including sex and age as cofactors identified a two-marker panel of CA19-9 and CA-125 that significantly improved the performance of CA19-9 alone in discriminating PDAC (AUC: 0.857 vs. 0.766), as well as early stage PDAC (0.805 vs. 0.702) from intraductal papillary mucinous neoplasm (IPMN). At a fixed specificity of 80%, the panel significantly improved sensitivities (78% vs. 41% or 72% vs. 59%). A two-marker panel of HE4 and CEA significantly outperformed CA19-9 in separating IPMN from chronic pancreatitis (0.841 vs. 0.501). The biomarker panels evaluated by assays demonstrated potential complementarity to CA19-9 in detecting early PDAC, warranting additional clinical validation to determine their role in the early detection of pancreatic cancer.

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“…With recent advancements in cancer cohort datasets and experimental toolkits, functional proteogenomic analysis has been used to discover synthetic lethality driven by loss-of-function tumor suppressors (Xiao et al, 2020;Lei and Zhang, 2021). This strategy has been applied in cancers with high level of CDKN2A deficiency, but further analyses and functional validations will be needed to delineate synthetic lethality associated specifically with ARF deficiency, as most efforts to identify therapeutic opportunities associated with CDKN2A deficiency begin and end at p16-CDK4/6-RB pathway intervention (Oh et al, 2020;Cao et al, 2021;Satpathy et al, 2021). Using a similar approach, Zhu et al found that breast cancer cells with CDKN2A mutations are more sensitive to a TTK/CLK2 inhibitor, CC-671.…”

Section: Development Of Arf-based Therapeutic Strategies-functional Antagonists Against Arf Deficiencymentioning

confidence: 99%

It’s Getting Complicated—A Fresh Look at p53-MDM2-ARF Triangle in Tumorigenesis and Cancer Therapy

Kung

Weber

2022

Front. Cell Dev. Biol.

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Anti-tumorigenic mechanisms mediated by the tumor suppressor p53, upon oncogenic stresses, are our bodies’ greatest weapons to battle against cancer onset and development. Consequently, factors that possess significant p53-regulating activities have been subjects of serious interest from the cancer research community. Among them, MDM2 and ARF are considered the most influential p53 regulators due to their abilities to inhibit and activate p53 functions, respectively. MDM2 inhibits p53 by promoting ubiquitination and proteasome-mediated degradation of p53, while ARF activates p53 by physically interacting with MDM2 to block its access to p53. This conventional understanding of p53-MDM2-ARF functional triangle have guided the direction of p53 research, as well as the development of p53-based therapeutic strategies for the last 30 years. Our increasing knowledge of this triangle during this time, especially through identification of p53-independent functions of MDM2 and ARF, have uncovered many under-appreciated molecular mechanisms connecting these three proteins. Through recognizing both antagonizing and synergizing relationships among them, our consideration for harnessing these relationships to develop effective cancer therapies needs an update accordingly. In this review, we will re-visit the conventional wisdom regarding p53-MDM2-ARF tumor-regulating mechanisms, highlight impactful studies contributing to the modern look of their relationships, and summarize ongoing efforts to target this pathway for effective cancer treatments. A refreshed appreciation of p53-MDM2-ARF network can bring innovative approaches to develop new generations of genetically-informed and clinically-effective cancer therapies.

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Proteogenomic characterization of pancreatic ductal adenocarcinoma

Cited by 323 publications

References 222 publications

Comparative N-Glycoproteomics Analysis of Clinical Samples Via Different Mass Spectrometry Dissociation Methods

Comparative N-Glycoproteomics Analysis of Clinical Samples Via Different Mass Spectrometry Dissociation Methods

Validation of Serum Biomarkers That Complement CA19-9 in Detecting Early Pancreatic Cancer Using Electrochemiluminescent-Based Multiplex Immunoassays

It’s Getting Complicated—A Fresh Look at p53-MDM2-ARF Triangle in Tumorigenesis and Cancer Therapy

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