Shotgun proteomics of thyroid carcinoma exosomes – Insight into the role of exosomal proteins in carcinogenesis and thyroid homeostasis

Surman, Magdalena; Wilczak, Magdalena; Jankowska, Urszula; Skupień-Rabian, Bożena; Przybyło, Małgorzata

doi:10.1016/j.bbagen.2024.130672

Biochimica et Biophysica Acta (BBA) - General Subjects

2024

DOI: 10.1016/j.bbagen.2024.130672

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Shotgun proteomics of thyroid carcinoma exosomes – Insight into the role of exosomal proteins in carcinogenesis and thyroid homeostasis

Magdalena Surman,

Magdalena Wilczak,

Urszula Jankowska

et al.

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2024

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Cited by 2 publications

References 89 publications

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Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases

Che,

Zhao,

Gao

et al. 2024

Front. Mol. Biosci.

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Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people’s health. Therefore, a timely and accurate diagnosis is necessary. Mass spectrometry (MS) based multi-omics has become an effective strategy to reveal the complex biological mechanisms of thyroid diseases. The exponential growth of biomedical data has promoted the applications of machine learning (ML) techniques to address new challenges in biology and clinical research. In this review, we presented the detailed review of applications of ML for MS-based multi-omics in thyroid disease. It is primarily divided into two sections. In the first section, MS-based multi-omics, primarily proteomics and metabolomics, and their applications in clinical diseases are briefly discussed. In the second section, several commonly used unsupervised learning and supervised algorithms, such as principal component analysis, hierarchical clustering, random forest, and support vector machines are addressed, and the integration of ML techniques with MS-based multi-omics data and its application in thyroid disease diagnosis is explored.

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Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases

Che,

Zhao,

Gao

et al. 2024

Front. Mol. Biosci.

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Exploring exosomes: novel diagnostic and therapeutic frontiers in thyroid cancer

Zhang,

Yang,

Wang

et al. 2024

Front. Pharmacol.

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In recent years, the incidence of thyroid cancer has surged globally, posing significant challenges in its diagnosis, treatment, and prognosis. Exosomes, as a class of extracellular vesicles, are secreted by nearly all cell types and encapsulate a variety of nucleic acids and proteins reflective of their cell of origin, thereby facilitating critical intercellular communication. Recent advancements in understanding these exosomes have catalyzed their application in oncology, particularly through uncovering their roles in the pathogenesis, diagnosis, and therapy of cancers. Notably, the latest literature highlights the integral role of exosomes in refining diagnostic techniques, enhancing targeted therapies, optimizing radiotherapy outcomes, and advancing immunotherapeutic approaches in thyroid cancer management. This review provides a current synthesis of the implications of exosomes in thyroid cancer tumorigenesis and progression, as well as their emerging applications in diagnosis and treatment strategies. Furthermore, we discuss the profound clinical potential of exosome-based interventions in managing thyroid cancer, serving as a foundational reference for future therapeutic developments.

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Shotgun proteomics of thyroid carcinoma exosomes – Insight into the role of exosomal proteins in carcinogenesis and thyroid homeostasis

Cited by 2 publications

References 89 publications

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases

Exploring exosomes: novel diagnostic and therapeutic frontiers in thyroid cancer

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