{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T00:04:28Z","timestamp":1775174668295,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T00:00:00Z","timestamp":1741824000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Cancers of unknown primary (CUPs) represent a significant diagnostic and therapeutic challenge in the field of oncology. Due to the limitations of current diagnostic tools in these cases, novel approaches must be brought forward to improve treatment outcomes for these patients. The objective of this study was to develop a machine-learning-based software for primary cancer site prediction (OncoOrigin), based on genetic data acquired from tumor DNA sequencing. By design, this was an in silico diagnostic study, conducted using data from the cBioPortal database (accessed on 21 September 2024) and several data processing and machine learning Python libraries. The study involved over 20,000 tumor samples with information on patient age, sex, and the presence of genetic variants in over 600 genes. The main outcome of interest was machine-learning-based discrimination between cancer site classes. Model quality was assessed by training set cross-validation and evaluation on a segregated test set. Finally, the optimal model was incorporated with a graphical user interface into the OncoOrigin software. Feature importance for class discrimination was also determined on the optimal model. Out of the four tested machine learning estimators, the XGBoostClassifier-based model proved superior in test set evaluation, with a top-2 accuracy of 0.91 and ROC-AUC of 0.97. Unlike other machine learning models published in the literature, OncoOrigin stands out as the only one integrated with a graphical user interface, which is crucial for facilitating its use by oncology specialists in everyday clinical practice, where its application and implementation will have the greatest value in the future.<\/jats:p>","DOI":"10.3390\/ijms26062568","type":"journal-article","created":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T04:18:32Z","timestamp":1741839512000},"page":"2568","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["In Silico Validation of OncoOrigin: An Integrative AI Tool for Primary Cancer Site Prediction with Graphical User Interface to Facilitate Clinical Application"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8022-4095","authenticated-orcid":false,"given":"Petar","family":"Brlek","sequence":"first","affiliation":[{"name":"St. Catherine Specialty Hospital, 10000 Zagreb, Croatia"},{"name":"School of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6522-891X","authenticated-orcid":false,"given":"Luka","family":"Buli\u0107","sequence":"additional","affiliation":[{"name":"St. Catherine Specialty Hospital, 10000 Zagreb, Croatia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nidhi","family":"Shah","sequence":"additional","affiliation":[{"name":"Dartmouth Health, Lebanon, NH 03766, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parth","family":"Shah","sequence":"additional","affiliation":[{"name":"Dartmouth Health, Lebanon, NH 03766, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5565-080X","authenticated-orcid":false,"given":"Dragan","family":"Primorac","sequence":"additional","affiliation":[{"name":"St. Catherine Specialty Hospital, 10000 Zagreb, Croatia"},{"name":"School of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"},{"name":"Eberly College of Science, The Pennsylvania State University, State College, PA 16802, USA"},{"name":"School of Medicine, University of Split, 21000 Split, Croatia"},{"name":"The Henry C. Lee College of Criminal Justice and Forensic Sciences, University of New Haven, New Haven, CT 06516, USA"},{"name":"Regiomed Kliniken, 96450 Coburg, Germany"},{"name":"School of Medicine, University of Rijeka, 51000 Rijeka, Croatia"},{"name":"Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia"},{"name":"School of Medicine, University of Mostar, 88000 Mostar, Bosnia and Herzegovina"},{"name":"National Forensic Sciences University, Gandhinagar 382007, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2332","DOI":"10.1158\/2159-8290.CD-24-1476","article-title":"Precision Oncology: 2024 in Review","volume":"14","author":"Repetto","year":"2024","journal-title":"Cancer Discov."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1016\/j.jmoldx.2024.05.013","article-title":"Validation and Implementation of a Somatic-Only Tumor Exome for Routine Clinical Application","volume":"26","author":"Shah","year":"2024","journal-title":"J. Mol. Diagn."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1186\/s13045-022-01351-y","article-title":"Liquid biopsy: Current technology and clinical applications","volume":"15","author":"Nikanjam","year":"2022","journal-title":"J. Hematol. Oncol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"104297","DOI":"10.1016\/j.critrevonc.2024.104297","article-title":"Cancer of unknown primary and the \u00abseed and soil\u00bb hypothesis","volume":"196","author":"Zolotykh","year":"2024","journal-title":"Crit. Rev. Oncol. Hematol."},{"key":"ref_5","unstructured":"Cancer of Unknown Primary Statistics (2024, September 09). Cancer Research UK. Available online: https:\/\/www.cancerresearchuk.org\/health-professional\/cancer-statistics\/statistics-by-cancer-type\/cancer-of-unknown-primary."},{"key":"ref_6","unstructured":"Board, P.A. (2024). Cancer of Unknown Primary (CUP) Treatment (PDQ\u00ae). PDQ Cancer Information Summaries, National Cancer Institute (US)."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Brlek, P., Buli\u0107, L., Bra\u010di\u0107, M., Proji\u0107, P., \u0160karo, V., Shah, N., Shah, P., and Primorac, D. (2024). Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives. Cells, 13.","DOI":"10.3390\/cells13060504"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.ccell.2023.12.012","article-title":"Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer","volume":"42","author":"Shiao","year":"2024","journal-title":"Cancer Cell"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1158\/0008-5472.CAN-23-2042","article-title":"Targeting Tumor Heterogeneity with Neoantigen-Based Cancer Vaccines","volume":"84","author":"Pounraj","year":"2024","journal-title":"Cancer Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"91","DOI":"10.11622\/smedj.2021054","article-title":"Machine learning in medicine: What clinicians should know","volume":"64","author":"Fong","year":"2023","journal-title":"Singap. Med. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2057","DOI":"10.1038\/s41591-023-02482-6","article-title":"Machine learning for genetics-based classification and treatment response prediction in cancer of unknown primary","volume":"29","author":"Moon","year":"2023","journal-title":"Nat. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1038\/s41392-022-01270-x","article-title":"Neoantigens: Promising targets for cancer therapy","volume":"8","author":"Xie","year":"2023","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Xiong, Z., Raphael, I., Olin, M., Okada, H., Li, X., and Kohanbash, G. (2024). Glioblastoma vaccines: Past, present, and opportunities. EBioMedicine, 100.","DOI":"10.1016\/j.ebiom.2023.104963"},{"key":"ref_14","first-page":"337","article-title":"Diagnostic and prognostic value of F-18 FDG PET\/CT in patients with carcinoma of unknown primary","volume":"9","author":"Bicakci","year":"2022","journal-title":"North. Clin. Istanb."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1038\/s41586-021-03512-4","article-title":"AI-based pathology predicts origins for cancers of unknown primary","volume":"594","author":"Lu","year":"2021","journal-title":"Nature"},{"key":"ref_16","first-page":"100066","article-title":"Bridging the divide between data scientists and clinicians","volume":"6","author":"Bastian","year":"2022","journal-title":"Intell.-Based Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1270","DOI":"10.4143\/crt.2023.415","article-title":"Specific Mutations in APC, with Prognostic Implications in Metastatic Colorectal Cancer","volume":"55","author":"Peng","year":"2023","journal-title":"Cancer Res. Treat."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1038\/s41392-021-00780-4","article-title":"KRAS mutation: From undruggable to druggable in cancer","volume":"6","author":"Huang","year":"2021","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s00018-023-05099-7","article-title":"Wnt\/\u03b2-catenin-driven EMT regulation in human cancers","volume":"81","author":"Xue","year":"2024","journal-title":"Cell Mol. Life Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Bukovac, A., Kafka, A., Ragu\u017e, M., Brlek, P., Dragi\u010devi\u0107, K., M\u00fcller, D., and Pe\u0107ina-\u0160laus, N. (2021). Are We Benign? What Can Wnt Signaling Pathway and Epithelial to Mesenchymal Transition Tell Us about Intracranial Meningioma Progression. Cancers, 13.","DOI":"10.3390\/cancers13071633"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Kafka, A., Bukovac, A., Brglez, E., Jarmek, A.M., Poljak, K., Brlek, P., \u017darkovi\u0107, K., Njiri\u0107, N., and Pe\u0107ina-\u0160laus, N. (2021). Methylation Patterns of DKK1, DKK3 and GSK3\u03b2 Are Accompanied with Different Expression Levels in Human Astrocytoma. Cancers, 13.","DOI":"10.3390\/cancers13112530"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1016\/j.ccell.2022.08.011","article-title":"Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future","volume":"40","author":"Akhoundova","year":"2022","journal-title":"Cancer Cell"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/s12943-022-01505-z","article-title":"Liquid biopsy in lung cancer: Significance in diagnostics, prediction, and treatment monitoring","volume":"21","author":"Li","year":"2022","journal-title":"Mol. Cancer"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1111\/1759-7714.15284","article-title":"Considerations for multidisciplinary management of synchronous primary breast cancer and primary lung cancer\u2014Analysis of thirty-one patients","volume":"15","author":"Chen","year":"2024","journal-title":"Thorac. Cancer"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1158\/2159-8290.CD-12-0095","article-title":"The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data","volume":"2","author":"Cerami","year":"2012","journal-title":"Cancer Discov."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"pl1","DOI":"10.1126\/scisignal.2004088","article-title":"Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal","volume":"6","author":"Gao","year":"2013","journal-title":"Sci. Signal."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Brlek, P., Kafka, A., Bukovac, A., and Pe\u0107ina-\u0160laus, N. (2021). Integrative cBioPortal Analysis Revealed Molecular Mechanisms That Regulate EGFR-PI3K-AKT-mTOR Pathway in Diffuse Gliomas of the Brain. Cancers, 13.","DOI":"10.3390\/cancers13133247"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3861","DOI":"10.1158\/0008-5472.CAN-23-0816","article-title":"Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal","volume":"83","author":"Kundra","year":"2023","journal-title":"Cancer Res."},{"key":"ref_29","unstructured":"Van Rossum, G., and Drake, F.L. (2009). Python 3 Reference Manual, CreateSpace."},{"key":"ref_30","unstructured":"McKinney, W. (July, January 28). Data structures for statistical computing in python. Proceedings of the 9th Python in Science Conference, Austin, TX, USA."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1038\/s41586-020-2649-2","article-title":"Array programming with NumPy","volume":"585","author":"Harris","year":"2020","journal-title":"Nature"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nat. Methods"},{"key":"ref_33","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/MCSE.2007.55","article-title":"Matplotlib: A 2D Graphics Environment","volume":"9","author":"Hunter","year":"2007","journal-title":"Comp. Sci. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.21105\/joss.03021","article-title":"seaborn: Statistical data visualization","volume":"6","author":"Waskom","year":"2021","journal-title":"J. Open Source Softw."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v036.i11","article-title":"Feature Selection with the Boruta Package","volume":"36","author":"Kursa","year":"2010","journal-title":"J. Stat. Soft."},{"key":"ref_38","unstructured":"Dorogush, A.V., Ershov, V., and Gulin, A. (2018). CatBoost: Gradient boosting with categorical features support. arXiv."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M. (2019). Optuna: A Next-generation Hyperparameter Optimization Framework. arXiv.","DOI":"10.1145\/3292500.3330701"},{"key":"ref_40","unstructured":"Lundh, F. (2024, September 21). An Introduction to Tkinter. Available online: https:\/\/ftp.math.utah.edu\/u\/ma\/hohn\/linux\/tcl\/an-introduction-to-tkinter.pdf."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/6\/2568\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:52:46Z","timestamp":1760028766000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/6\/2568"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,13]]},"references-count":40,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["ijms26062568"],"URL":"https:\/\/doi.org\/10.3390\/ijms26062568","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,13]]}}}