دورية أكاديمية
Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.
| العنوان: | Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches. |
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| المؤلفون: | Stawiski K; Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland., Fortner RT; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.; Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany., Pestarino L; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.; Department of Gynecological Oncology, Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway., Umu SU; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway., Kaaks R; Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany., Rounge TB; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.; Centre for Bioinformatics, Department of Pharmacy, University of Oslo, Oslo, Norway., Elias KM; Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, MA, United States.; Harvard Medical School, Boston, MA, United States., Fendler W; Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, United States., Langseth H; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom. |
| المصدر: | Frontiers in oncology [Front Oncol] 2024 Jun 25; Vol. 14, pp. 1389066. Date of Electronic Publication: 2024 Jun 25 (Print Publication: 2024). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101568867 Publication Model: eCollection Cited Medium: Print ISSN: 2234-943X (Print) Linking ISSN: 2234943X NLM ISO Abbreviation: Front Oncol Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: [Lausanne : Frontiers Research Foundation] |
| مستخلص: | Introduction: Effective strategies for early detection of epithelial ovarian cancer are lacking. We evaluated whether a panel of 14 previously established circulating microRNAs could discriminate between cases diagnosed <2 years after serum collection and those diagnosed 2-7 years after serum collection. miRNA sequencing data from subsequent ovarian cancer cases were obtained as part of the ongoing multi-cancer JanusRNA project, utilizing pre-diagnostic serum samples from the Janus Serum Bank and linked to the Cancer Registry of Norway for cancer outcomes. Methods: We included a total of 80 ovarian cancer cases contributing 80 serum samples and compared 40 serum samples from cases with samples collected <2 years prior to diagnosis with 40 serum samples from cases with sample collection ≥2 to 7 years. We employed the extreme gradient boosting (XGBoost) algorithm to train a binary classification model using 70% of the available data, while the model was tested on the remaining 30% of the dataset. Results: The performance of the model was evaluated using repeated holdout validation. The previously established set of miRNAs achieved a median area under the receiver operating characteristic curve (AUC) of 0.771 in the test sets. Four out of 14 miRNAs (hsa-miR-200a-3p, hsa-miR-1246, hsa-miR-203a-3p, hsa-miR-23b-3p) exhibited higher expression levels closer to diagnosis, consistent with the previously reported upregulation in cancer cases, with statistical significance observed only for hsa-miR-200a-3p (beta=0.14; p=0.04). Discussion: The discrimination potential of the selected models provides evidence of the robustness of the miRNA signature for ovarian cancer. Competing Interests: K.S., K.E., and W.F.. are co-inventors of patent US201762444085P/EP3565903A1 (title “Circulating microrna signatures for ovarian cancer”), which relates to the use of circulating miRNAs for ovarian cancer diagnosis. The authors remaining declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision. (Copyright © 2024 Stawiski, Fortner, Pestarino, Umu, Kaaks, Rounge, Elias, Fendler and Langseth.) |
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| فهرسة مساهمة: | Keywords: early detection; machine learning; microRNAs; ovarian cancer; sequencing |
| تواريخ الأحداث: | Date Created: 20240710 Latest Revision: 20240711 |
| رمز التحديث: | 20240711 |
| مُعرف محوري في PubMed: | PMC11231195 |
| DOI: | 10.3389/fonc.2024.1389066 |
| PMID: | 38983926 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2234-943X |
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| DOI: | 10.3389/fonc.2024.1389066 |