مورد إلكتروني
Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging
| العنوان: | Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging |
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| المؤلفون: | Kassuhn, W, Klein, O, Darb-Esfahani, S, Lammert, H, Handzik, S, Taube, ET, Schmitt, WD, Keunecke, C, Horst, D, Dreher, F, George, J, Bowtell, DD, Dorigo, O, Hummel, M, Sehouli, J, Bluthgen, N, Kulbe, H, Braicu, EI |
| بيانات النشر: | MDPI 2021-04-01 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Despite the correlation of clinical outcome and molecular subtypes of high-grade serous ovarian cancer (HGSOC), contemporary gene expression signatures have not been implemented in clinical practice to stratify patients for targeted therapy. Hence, we aimed to examine the potential of unsupervised matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients who might benefit from targeted therapeutic strategies. Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS paired with machine-learning algorithms to identify distinct mass profiles on the same paraffin-embedded tissue sections and distinguish HGSOC subtypes by proteomic signature. Finally, we devised a novel approach to annotate spectra of stromal origin. We elucidated a MALDI-derived proteomic signature (135 peptides) able to classify HGSOC subtypes. Random forest classifiers achieved an area under the curve (AUC) of 0.983. Furthermore, we demonstrated that the exclusion of stroma-associated spectra provides tangible improvements to classification quality (AUC = 0.988). Moreover, novel MALDI-based stroma annotation achieved near-perfect classifications (AUC = 0.999). Here, we present a concept integrating MALDI-IMS with machine-learning algorithms to classify patients according to distinct molecular subtypes of HGSOC. This has great potential to assign patients for personalized treatment. |
| مصطلحات الفهرس: | Journal Article |
| URL: | |
| الإتاحة: | Open access content. Open access content CC BY https://creativecommons.org/licenses/by/4.0 |
| أرقام أخرى: | UMV oai:jupiter.its.unimelb.edu.au:11343/278028 Kassuhn, W., Klein, O., Darb-Esfahani, S., Lammert, H., Handzik, S., Taube, E. T., Schmitt, W. D., Keunecke, C., Horst, D., Dreher, F., George, J., Bowtell, D. D., Dorigo, O., Hummel, M., Sehouli, J., Bluthgen, N., Kulbe, H. & Braicu, E. I. (2021). Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging. CANCERS, 13 (7), https://doi.org/10.3390/cancers13071512. 10.3390/cancers13071512 2072-6694 2072-6694 1315703522 |
| المصدر المساهم: | UNIV OF MELBOURNE From OAIster®, provided by the OCLC Cooperative. |
| رقم الأكسشن: | edsoai.on1315703522 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |