Isoforms of MUC16 activate oncogenic signaling through EGF receptors to enhance the progression of pancreatic cancer

Thomas, Divya; Sagar, Satish; Liu, Xiang; Lee, Hye Rim; Grunkemeyer, James A.; Grandgenett, Paul M.; Caffrey, Thomas C.; O’Connell, Kelly A.; Swanson, Benjamin J.; Marcos-Silva, Lara; Steentoft, Catharina; Wandall, Hans H.; Maurer, H. Carlo; Peng, Xianlu L.; Yeh, Jen Jen; Qiu, Fang; Yu, Fang; Madiyalakan, Ragupathy; Olive, Kenneth P.; Mandel, Ulla; Clausen, Henrik; Hollingsworth, Michael A.; Radhakrishnan, Prakash

doi:10.1016/j.ymthe.2020.12.029

Cited by 43 publications

(37 citation statements)

References 29 publications

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“…Motivated by our recent reports detailing the mechanism of action and therapeutic utility of muAR9.6 in mouse models of human pancreatic ductal adenocarcinoma (PDAC), we next embarked upon exploring the theranostic utility of this antibody (10). In vitro binding of S5, S6, S15).…”

Section: Exploring the Theranostic Utility Of Ar96 For Pancreatic Cancermentioning

confidence: 99%

“…Mucin-16 (MUC16) ranks amongst the most widely known mucins due to the utility of its CA125 epitope as a biomarker for serous ovarian cancer (8). Isoforms of MUC16 have also been implicated in the progression and metastasis of pancreatic ductal adenocarcinoma as well as aggressive subtypes of the disease such as squamous and basal-like carcinomas (9,10). Despite its endogenous expression in a few healthy tissues and status as a shed antigen, MUC16 remains a viable therapeutic target for antibody-based and adoptive cell therapies (11)(12)(13)(14)(15)(16)(17)(18)(19).…”

Section: Introductionmentioning

confidence: 99%

“…The vast majority of MUC16-targeted antibodies bind CA125 epitopes in the SEA/tandem repeat region (10,20) or the unshed carboxy-terminus domain (13,21,22). To date, anti-MUC16 antibodies have mostly been harnessed as vectors to deliver toxic payloads, radionuclides, or fluorophores (12,(23)(24)(25)(26).…”

Section: Introductionmentioning

confidence: 99%

“…To date, anti-MUC16 antibodies have mostly been harnessed as vectors to deliver toxic payloads, radionuclides, or fluorophores (12,(23)(24)(25)(26). More recently, a new class of MUC16-targeted antibodies that interact with the N-or O-glycosylation sites on MUC16 have emerged and exert a therapeutic effect by abrogating the downstream pro-oncogenic signaling of cancer cells (10,15). AR9.6 is one such mAb, as it binds to SEA domain 5 on MUC16 and interferes with the interaction of MUC16 with ErbB (EGF) receptors on the cancer cell surface.…”

Section: Introductionmentioning

confidence: 99%

“…AR9.6 is one such mAb, as it binds to SEA domain 5 on MUC16 and interferes with the interaction of MUC16 with ErbB (EGF) receptors on the cancer cell surface. The latter attenuates the subsequent activation of oncogenic AKT and GSK3ß signaling pathways in tumor cells (10).…”

Section: Introductionmentioning

confidence: 99%

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ImmunoPET of Ovarian and Pancreatic Cancer with AR9.6, a Novel MUC16-Targeted Therapeutic Antibody

Sharma

Mack

Piersigilli

et al. 2021

Clinical Cancer Research

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In recent years, proteins with aberrant glycosylation patterns have emerged as therapeutic targets in oncology. Along these lines, MUC16 glycoforms have been implicated in the oncogenesis and metastatic progression of high-grade serous ovarian cancer (HGSOC) and pancreatic ductal adenocarcinoma (PDAC). AR9.6 is a therapeutic mAb that binds to MUC16, interferes with the interaction of MUC16 with ErbB receptors on the surface of cancer cells, and thereby attenuates the activation of downstream oncogenic signaling pathways. Here, we report the in vitro, ex vivo, and in vivo validation of [ 89 Zr]Zr-DFO-muAR9.6 and [ 89 Zr]Zr-DFO-huAR9.6 in murine models of MUC16-positive HGSOC and PDAC. Both radioimmunoconjugates displayed excellent tumor-targeting properties in vivo, ultimatelyResearch.

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Section: Exploring the Theranostic Utility Of Ar96 For Pancreatic Cancermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

ImmunoPET of Ovarian and Pancreatic Cancer with AR9.6, a Novel MUC16-Targeted Therapeutic Antibody

Sharma

Mack

Piersigilli

et al. 2021

Clinical Cancer Research

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Novel progressive deep learning algorithm for uncovering multiple single nucleotide polymorphism interactions to predict paclitaxel clearance in patients with nonsmall cell lung cancer

Chen,

Zhou,

Zhang

et al. 2024

Cancer Innovation

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BackgroundThe rate at which the anticancer drug paclitaxel is cleared from the body markedly impacts its dosage and chemotherapy effectiveness. Importantly, paclitaxel clearance varies among individuals, primarily because of genetic polymorphisms. This metabolic variability arises from a nonlinear process that is influenced by multiple single nucleotide polymorphisms (SNPs). Conventional bioinformatics methods struggle to accurately analyze this complex process and, currently, there is no established efficient algorithm for investigating SNP interactions.MethodsWe developed a novel machine‐learning approach called GEP‐CSIs data mining algorithm. This algorithm, an advanced version of GEP, uses linear algebra computations to handle discrete variables. The GEP‐CSI algorithm calculates a fitness function score based on paclitaxel clearance data and genetic polymorphisms in patients with nonsmall cell lung cancer. The data were divided into a primary set and a validation set for the analysis.ResultsWe identified and validated 1184 three‐SNP combinations that had the highest fitness function values. Notably, SERPINA1, ATF3 and EGF were found to indirectly influence paclitaxel clearance by coordinating the activity of genes previously reported to be significant in paclitaxel clearance. Particularly intriguing was the discovery of a combination of three SNPs in genes FLT1, EGF and MUC16. These SNPs‐related proteins were confirmed to interact with each other in the protein–protein interaction network, which formed the basis for further exploration of their functional roles and mechanisms.ConclusionWe successfully developed an effective deep‐learning algorithm tailored for the nuanced mining of SNP interactions, leveraging data on paclitaxel clearance and individual genetic polymorphisms.

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Crystal structure of a human MUC16 SEA domain reveals insight into the nature of the CA125 tumor marker

et al. 2022

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MUC16 is a membrane bound glycoprotein involved in the progression and metastasis of pancreatic and ovarian cancer. The protein is shed into the serum and the resulting cancer antigen 125 (CA125) can be detected by immunoassays. The CA125 epitope is used for monitoring ovarian cancer treatment progression, and has emerged as a potential target for antibody mediated immunotherapy. The extracellular tandem repeat domain of the protein is composed of repeating segments of heavily glycosylated sequence intermixed with homologous SEA (Sperm protein, Enterokinase and Agrin) domains. Here we report the purification and the first X-ray structure of a human MUC16 SEA domain. The structure was solved by molecular replacement using a Rosetta generated structure as a search model. The SEA domain reacted with three different MUC16 therapeutic antibodies, confirming that the CA125 epitope is localized to the SEA domain. The structure revealed a canonical ferredoxin-like fold, and contained a conserved disulfide bond. Analysis of the relative solvent accessibility of side chains within the SEA domain clarified the assignment of N-linked and O-linked glycosylation sites within the domain. A model of the glycosylated SEA domain revealed two major accessible faces, which likely represent the binding sites of CA125 specific antibodies. The results presented here will serve to accelerate future work to understand the functional role of MUC16 SEA domains and antibody recognition of the CA125 epitope.

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Isoforms of MUC16 activate oncogenic signaling through EGF receptors to enhance the progression of pancreatic cancer

Cited by 43 publications

References 29 publications

ImmunoPET of Ovarian and Pancreatic Cancer with AR9.6, a Novel MUC16-Targeted Therapeutic Antibody

ImmunoPET of Ovarian and Pancreatic Cancer with AR9.6, a Novel MUC16-Targeted Therapeutic Antibody

Novel progressive deep learning algorithm for uncovering multiple single nucleotide polymorphism interactions to predict paclitaxel clearance in patients with nonsmall cell lung cancer

Crystal structure of a human MUC16 SEA domain reveals insight into the nature of the CA125 tumor marker

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