Activity-based protein profiling reveals active serine proteases that drive malignancy of human ovarian clear cell carcinoma

Mehner, Christine; Hockla, Alexandra; Coban, Matt; Madden, Benjamin J.; Estrada, Rosendo; Radisky, Derek C.; Radisky, Evette S.

doi:10.1016/j.jbc.2022.102146

Cited by 7 publications

(5 citation statements)

References 89 publications

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“…Isolation of labeled enzymes from tissue lysates revealed increased activities of cathepsins B, C, L, and Z during tumor progression ( 397 ). A recent study used an activity-based probe designed to broadly label serine proteases with tryptic-like specificity (those cleaving after lysine or arginine), identifying uPA and tPA as active serine proteases that promote malignant properties of ovarian clear cell carcinoma cells ( 398 ). Sometimes research needs to answer more specific questions, such as identifying the protease responsible for cleaving a specific substrate in a particular setting.…”

Section: Identifying the Villains And Their Modus Operandi—an Evolvin...mentioning

confidence: 99%

Extracellular proteolysis in cancer: Proteases, substrates, and mechanisms in tumor progression and metastasis

Radisky

2024

Journal of Biological Chemistry

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Section: Identifying the Villains And Their Modus Operandi—an Evolvin...mentioning

confidence: 99%

Extracellular proteolysis in cancer: Proteases, substrates, and mechanisms in tumor progression and metastasis

Radisky

2024

Journal of Biological Chemistry

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“…With proper optimization, DPPs are excellent tools to profile enzyme activity across varied disease states. Radisky and coworkers recently developed arginine DPP probes equipped with a biotin handle for detection of active trypsin‐like serine proteases implicated in ovarian clear cell carcinoma progression [8b] . Using their probe, tissue plasminogen activator and urokinase‐type plasminogen activator were identified as catalytically active proteases, significant drivers of malignancy, and potential therapeutic targets for difficult‐to‐treat ovarian cancers.…”

Section: Current Serine Hydrolase‐targeting Chemotypesmentioning

confidence: 99%

“…Aberrant SH activities often lead to disease progression, highlighting the need for chemical tools to further characterize and modulate SHs for human health [8] . Unsurprisingly, SHs have already been targeted by numerous small molecule therapeutics for treatment of widespread diseases including microbial infections, [3] cancer, [8b] obesity, [9] and neurological diseases, [10] and many of these SH inhibitors directly stem from ABPP [1–2] . While many key contributions will be further discussed below, ABPP and SH probes have provided a strong foundation for both drug discovery and discovery biology efforts by enabling screening campaigns and elucidating the functions of uncharacterized SH members across diseases.…”

Section: Introductionmentioning

confidence: 99%

Serine Hydrolase Activity‐Based Probes for Use in Chemical Proteomics

Racioppo

Qiu

Adibekian

2023

Israel Journal of Chemistry

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Serine hydrolases (SHs) comprise a large superfamily of enzymes that play critical roles in many biological processes. Despite their importance, many SHs remain uncharacterized and the vast majority of SHs lack selective inhibitors. In response, activity-based protein profiling (ABPP) and activity-based probes (ABPs) have been leveraged to construct a more comprehensive picture of the SH proteome. Since the utility of ABPP is largely dictated by the reactivity profile of the ABPs deployed, novel scaffolds and chemotypes are needed to expand the breadth and selectivity of SH-targeting ABPs. In this review, we highlight recent innovations in SH probe development, covering both established and emerging electrophilic warheads. We then discuss how strategic implementation of SH-targeting ABPs has yielded selective, potent inhibitors and imaging agents with broad use. Finally, we present methods for ABP diversification and explore cutting-edge applications in therapeutics development and discovery biology.

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“…Moreover, proteomics analyses can complement transcriptomic and genomic analyses, providing insights into the underlying mechanisms and potentially serving as objective biomarkers of disease. Scholars have gained a better understanding of the functions of proteins in the proteome of ovarian cancer and their impact on prognosis, providing new avenues for developing more effective diagnostics and therapies [ 10 , 11 ]. In the process of tumor development and metastasis, communication between tumor cells and their microenvironment is critical.…”

Section: Introductionmentioning

confidence: 99%

Screening and Identification of a Prognostic Model of Ovarian Cancer by Combination of Transcriptomic and Proteomic Data

et al. 2023

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The integration of transcriptome and proteome analysis can lead to the discovery of a myriad of biological insights into ovarian cancer. Proteome, clinical, and transcriptome data about ovarian cancer were downloaded from TCGA’s database. A LASSO–Cox regression was used to uncover prognostic-related proteins and develop a new protein prognostic signature for patients with ovarian cancer to predict their prognosis. Patients were brought together in subgroups using a consensus clustering analysis of prognostic-related proteins. To further investigate the role of proteins and protein-coding genes in ovarian cancer, additional analyses were performed using multiple online databases (HPA, Sangerbox, TIMER, cBioPortal, TISCH, and CancerSEA). The final resulting prognosis factors consisted of seven protective factors (P38MAPK, RAB11, FOXO3A, AR, BETACATENIN, Sox2, and IGFRb) and two risk factors (AKT_pS473 and ERCC5), which can be used to construct a prognosis-related protein model. A significant difference in overall survival (OS), disease-free interval (DFI), disease-specific survival (DSS), and progression-free interval (PFI) curves were found in the training, testing, and whole sets when analyzing the protein-based risk score (p < 0.05). We also illustrated a wide range of functions, immune checkpoints, and tumor-infiltrating immune cells in prognosis-related protein signatures. Additionally, the protein-coding genes were significantly correlated with each other. EMTAB8107 and GSE154600 single-cell data revealed that the genes were highly expressed. Furthermore, the genes were related to tumor functional states (angiogenesis, invasion, and quiescence). We reported and validated a survivability prediction model for ovarian cancer based on prognostic-related protein signatures. A strong correlation was found between the signatures, tumor-infiltrating immune cells, and immune checkpoints. The protein-coding genes were highly expressed in single-cell RNA and bulk RNA sequencing, correlating with both each other and tumor functional states.

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Activity-based protein profiling reveals active serine proteases that drive malignancy of human ovarian clear cell carcinoma

Cited by 7 publications

References 89 publications

Extracellular proteolysis in cancer: Proteases, substrates, and mechanisms in tumor progression and metastasis

Extracellular proteolysis in cancer: Proteases, substrates, and mechanisms in tumor progression and metastasis

Serine Hydrolase Activity‐Based Probes for Use in Chemical Proteomics

Screening and Identification of a Prognostic Model of Ovarian Cancer by Combination of Transcriptomic and Proteomic Data

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