Synergistic effects of extracellular vesicle phenotyping and AFP in hepatobiliary cancer differentiation

Urban, Sabine; Sänger, Hanna; Krawczyk, Marcin; Julich-Haertel, Henrike; Willms, Arnulf; Ligocka, Joanna; Azkargorta, Mikel; Mocan, Tudor; Kahlert, Christoph; Kruk, Beata; Jankowski, Krzysztof; Patkowski, Waldemar; Krawczyk, Marek; Zieniewicz, Krzysztof; Hołówko, Wacław; Krupa, Łukasz; Rzucidło, Mateusz; Gutkowski, Krzysztof; Wystrychowski, Wojciech; Król, Robert; Raszeja‐Wyszomirska, Joanna; Słomka, Artur; Schwab, Robert; Wöhler, Aliona; Gonzalez‐Carmona, Maria A.; Gehlert, Sebastian; Spârchez, Zeno; Strassburg, Christian P.; Lammert, Frank; Milkiewicz, Piotr; Kornek, Miroslaw

doi:10.1111/liv.14585

Cited by 21 publications

(21 citation statements)

References 49 publications

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“…Here, analysis of the protein cargo on or in sEVs could potentially allow the detection of resistant tumor parts during treatment early on [ 1 , 2 , 3 ]. Indeed, methods like antibody arrays [ 21 ], fluorescence-activated cell sorting (FACS) surface profiling [ 22 ], and proteomic profiling via mass spectrometry (MS) [ 23 ] have already been employed for the analysis of NSCLC-derived sEVs. However, some of these analyses are not easily transferred into clinical applicable methods as they require specialized equipment and trained personnel or are time-consuming and expensive [ 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR

Stiller

Viktorsson

Gomero

et al. 2021

Cancers

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Precision cancer medicine for non-small-cell lung cancer (NSCLC) has increased patient survival. Nevertheless, targeted agents towards tumor-associated membrane receptors only result in partial remission for a limited time, calling for approaches which allow longitudinal treatment monitoring. Rebiopsy of tumors in the lung is challenging, and metastatic lesions may have heterogeneous signaling. One way ahead is to use liquid biopsies such as circulating tumor DNA or small extracellular vesicles (sEVs) secreted by the tumor into blood or other body fluids. Herein, an immuno-PCR-based detection of the tumor-associated membrane receptors EGFR, HER2, and IGF-1R on CD9-positive sEVs from NSCLC cells and pleural effusion fluid (PE) of NSCLC patients is developed utilizing DNA conjugates of antibody mimetics and affibodies, as detection agents. Results on sEVs purified from culture media of NSCLC cells treated with anti-EGFR siRNA, showed that the reduction of EGFR expression can be detected via immuno-PCR. Protein profiling of sEVs from NSCLC patient PE samples revealed the capacity to monitor EGFR, HER2, and IGF-1R with the immuno-PCR method. We detected a significantly higher EGFR level in sEVs derived from a PE sample of a patient with an EGFR-driven NSCLC adenocarcinoma than in sEVs from PE samples of non-EGFR driven adenocarcinoma patients or in samples from patients with benign lung disease. In summary, we have developed a diagnostic method for sEVs in liquid biopsies of cancer patients which may be used for longitudinal treatment monitoring to detect emerging bypassing resistance mechanisms in a noninvasive way.

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Section: Introductionmentioning

confidence: 99%

Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR

Stiller

Viktorsson

Gomero

et al. 2021

Cancers

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show abstract

“…Unlike conventional tissue biopsy, liquid biopsy is a non-invasive approach, which allows repeated analysis to enable monitoring tumor progression, metastasis, and recurrence, as well as treatment response. This enables identification and accounting novel biomarker candidates circulating in the bloodstream with sensitivity, specificity, positive, and negative predictive values reaching up to 100% [ 36 ].…”

Section: Proteomic Profiling Technologies and Big Datamentioning

confidence: 99%

Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine

et al. 2021

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Hepatocellular carcinoma (HCC) is the most common primary cancer of the liver with high morbidity and mortality rates worldwide. Since 1963, when alpha-fetoprotein (AFP) was discovered as a first HCC serum biomarker, several other protein biomarkers have been identified and introduced into clinical practice. However, insufficient specificity and sensitivity of these biomarkers dictate the necessity of novel biomarker discovery. Remarkable advancements in integrated multiomics technologies for the identification of gene expression and protein or metabolite distribution patterns can facilitate rising to this challenge. Current multiomics technologies lead to the accumulation of a huge amount of data, which requires clustering and finding correlations between various datasets and developing predictive models for data filtering, pre-processing, and reducing dimensionality. Artificial intelligence (AI) technologies have an enormous potential to overcome accelerated data growth, complexity, and heterogeneity within and across data sources. Our review focuses on the recent progress in integrative proteomic profiling strategies and their usage in combination with machine learning and deep learning technologies for the discovery of novel biomarker candidates for HCC early diagnosis and prognosis. We discuss conventional and promising proteomic biomarkers of HCC such as AFP, lens culinaris agglutinin (LCA)-reactive L3 glycoform of AFP (AFP-L3), des-gamma-carboxyprothrombin (DCP), osteopontin (OPN), glypican-3 (GPC3), dickkopf-1 (DKK1), midkine (MDK), and squamous cell carcinoma antigen (SCCA) and highlight their functional significance including the involvement in cell signaling such as Wnt/β-catenin, PI3K/Akt, integrin αvβ3/NF-κB/HIF-1α, JAK/STAT3 and MAPK/ERK-mediated pathways dysregulated in HCC. We show that currently available computational platforms for big data analysis and AI technologies can both enhance proteomic profiling and improve imaging techniques to enhance the translational application of proteomics data into precision medicine.

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“…EVs collected from saliva may be useful for the diagnosis of lung cancer [ 192 , 193 , 194 ]. It has been reported that the contents of EVs collected from serum, such as miR-200, lipocalin-2 [ 86 ], miR-505-5p [ 91 ], ubiquitin C-terminal hydrolase-L1 (UCHL1) [ 88 ], cell-free DNA [ 82 , 83 ], and proteins [ 195 , 196 , 197 , 198 , 199 ], are useful for the diagnosis of lung cancer. MiR-193a-5p, and miR-551b-5p have been suggested as biomarkers of malignant pleural mesothelioma.…”

Section: Potential Of Evs For Liquid Biopsymentioning

confidence: 99%

Anti-Cancer Role and Therapeutic Potential of Extracellular Vesicles

Tominaga

2021

Cancers

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Cell–cell communication is an important mechanism in biological processes. Extracellular vesicles (EVs), also referred to as exosomes, microvesicles, and prostasomes, are microvesicles secreted by a variety of cells. EVs are nanometer-scale vesicles composed of a lipid bilayer and contain biological functional molecules, such as microRNAs (miRNAs), mRNAs, and proteins. In this review, “EVs” is used as a comprehensive term for vesicles that are secreted from cells. EV research has been developing over the last four decades. Many studies have suggested that EVs play a crucial role in cell–cell communication. Importantly, EVs contribute to cancer malignancy mechanisms such as carcinogenesis, proliferation, angiogenesis, metastasis, and escape from the immune system. EVs derived from cancer cells and their microenvironments are diverse, change in nature depending on the condition. As EVs are thought to be secreted into body fluids, they have the potential to serve as diagnostic markers for liquid biopsy. In addition, cells can encapsulate functional molecules in EVs. Hence, the characteristics of EVs make them suitable for use in drug delivery systems and novel cancer treatments. In this review, the potential of EVs as anti-cancer therapeutics is discussed.

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Synergistic effects of extracellular vesicle phenotyping and AFP in hepatobiliary cancer differentiation

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 21 publications

References 49 publications

Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR

Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR

Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine

Anti-Cancer Role and Therapeutic Potential of Extracellular Vesicles

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