{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T18:30:50Z","timestamp":1784140250524,"version":"3.55.0"},"reference-count":56,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:00:00Z","timestamp":1750291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ovarian Cancer Research Foundation (OCRF)"},{"name":"Cancer Council South Australia travel grant"},{"name":"Lin Huddleston Ovarian Cancer Fellowship"},{"name":"Cancer Council South Australia and Adelaide Medical School, The University of Adelaide"},{"name":"Lloyd Cox Research Foundation, The University of Adelaide"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Ovarian cancer is the most lethal gynecological cancer. Up to 75% of cases are high-grade serous ovarian cancer (HGSOC) that have high chemosensitivity to first-line platinum-based therapies. However, 75% of patients will become chemoresistant following relapse. The underlying mechanism for developing resistance to chemotherapy in HGSOC is poorly understood. In this study, we employed Matrix-Assisted Laser Desorption\/Ionization\u2013Mass Spectrometry Imaging (MALDI-MSI) on matching formalin-fixed paraffin-embedded (FFPE) HGSOC tissues at the time of diagnosis and following relapse with chemotherapy-resistant disease (n = 4). We identified m\/z values that were differentially abundant in the matching diagnosis and relapse HGSOC tissues. These were matched to proteins using nano-liquid chromatography tandem mass spectrometry (LC-MS\/MS). We identified upregulated proteins in the HGSOC relapse tissues, including COL12A1, FUBP1, PLEC, SLC4A1, and TKT. These proteins were validated by immunohistochemistry (IHC) and gene expression using online databases. IHC showed COL12A1, FUBP1, PLEC, SLC4A1, and TKT protein abundance were significantly elevated in HGSOC relapse tissues compared to matching tissues at diagnosis. COL12A1, FUBP1, PLEC, and TKT mRNA expression levels were significantly increased in HGSOC compared to normal ovary and associated with poor prognosis in HGSOC. We confirmed that higher protein abundance of both COL12A1 and PLEC correlated with reduced progression-free survival in HGSOC patients. Furthermore, both COL12A1 and PLEC mRNA and protein levels were significantly associated with chemotherapy resistance. In summary, using MALDI-MSI, we have identified proteins, including COL12A1 and PLEC, associated with chemotherapy resistance to be further evaluated as HGSOC biomarkers and\/or therapeutic targets.<\/jats:p>","DOI":"10.3390\/ijms26125893","type":"journal-article","created":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T08:43:58Z","timestamp":1750322638000},"page":"5893","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Identification of Proteins Associated with Ovarian Cancer Chemotherapy Resistance Using MALDI-MSI"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7100-0900","authenticated-orcid":false,"given":"Tannith M.","family":"Noye","sequence":"first","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0139-9757","authenticated-orcid":false,"given":"Parul","family":"Mittal","sequence":"additional","affiliation":[{"name":"Mass Spectrometry and Proteomics Group, Clinical & Health Sciences, Centre for Pharmaceutical Innovation, University of South Australia, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5306-3468","authenticated-orcid":false,"given":"Zoe K.","family":"Price","sequence":"additional","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annie","family":"Fewster","sequence":"additional","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georgia","family":"Williams","sequence":"additional","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7391-1436","authenticated-orcid":false,"given":"Tara L.","family":"Pukala","sequence":"additional","affiliation":[{"name":"Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2165-7813","authenticated-orcid":false,"given":"Manuela","family":"Klingler-Hoffmann","sequence":"additional","affiliation":[{"name":"Mass Spectrometry and Proteomics Group, Clinical & Health Sciences, Centre for Pharmaceutical Innovation, University of South Australia, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Hoffmann","sequence":"additional","affiliation":[{"name":"Mass Spectrometry and Proteomics Group, Clinical & Health Sciences, Centre for Pharmaceutical Innovation, University of South Australia, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin K.","family":"Oehler","sequence":"additional","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"},{"name":"Mass Spectrometry and Proteomics Group, Clinical & Health Sciences, Centre for Pharmaceutical Innovation, University of South Australia, Adelaide, SA 5005, Australia"},{"name":"Department of Gynaecological Oncology, Royal Adelaide Hospital, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2071-5308","authenticated-orcid":false,"given":"Noor A.","family":"Lokman","sequence":"additional","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7415-1854","authenticated-orcid":false,"given":"Carmela","family":"Ricciardelli","sequence":"additional","affiliation":[{"name":"Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"12","DOI":"10.3322\/caac.21820","article-title":"Cancer statistics, 2024","volume":"74","author":"Siegel","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.critrevonc.2013.08.017","article-title":"Sensitivity and resistance to treatment in the primary management of epithelial ovarian cancer","volume":"89","author":"Colombo","year":"2014","journal-title":"Crit. Rev. Oncol. Hematol."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Havasi, A., Cainap, S.S., Havasi, A.T., and Cainap, C. (2023). Ovarian Cancer\u2014Insights into Platinum Resistance and Overcoming It. Medicina, 59.","DOI":"10.3390\/medicina59030544"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1097\/GCO.0000000000000931","article-title":"Maintenance therapy for newly and recurrent epithelial ovarian cancer: Current therapies and future perspectives","volume":"36","author":"Salutari","year":"2024","journal-title":"Curr. Opin. Obstet. Gynecol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e1800029","DOI":"10.1002\/prca.201800029","article-title":"Site-to-Site Reproducibility and Spatial Resolution in MALDI-MSI of Peptides from Formalin-Fixed Paraffin-Embedded Samples","volume":"13","author":"Ly","year":"2019","journal-title":"Proteom. Clin. Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1021\/pr300996x","article-title":"Tryptic peptide reference data sets for MALDI imaging mass spectrometry on formalin-fixed ovarian cancer tissues","volume":"12","author":"Meding","year":"2013","journal-title":"J. Proteome Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"205","DOI":"10.2183\/pjab.83.205","article-title":"A novel method for analyzing formalin-fixed paraffin embedded (FFPE) tissue sections by mass spectrometry imaging","volume":"83","author":"Aoki","year":"2007","journal-title":"Proc. Jpn. Acad. Ser. B Phys. Biol. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.ebiom.2017.06.001","article-title":"Combined Mass Spectrometry Imaging and Top-down Microproteomics Reveals Evidence of a Hidden Proteome in Ovarian Cancer","volume":"21","author":"Delcourt","year":"2017","journal-title":"eBioMedicine"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e1800064","DOI":"10.1002\/prca.201800064","article-title":"Discerning the Primary Carcinoma in Malignant Peritoneal and Pleural Effusions Using Imaging Mass Spectrometry-A Feasibility Study","volume":"13","author":"Schwamborn","year":"2019","journal-title":"Proteom. Clin. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1002\/prca.201200079","article-title":"Proteomic analyses of serous and endometrioid epithelial ovarian cancers\u2014Cases studies\u2014Molecular insights of a possible histological etiology of serous ovarian cancer","volume":"7","author":"Gagnon","year":"2013","journal-title":"Proteom. Clin. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e1700181","DOI":"10.1002\/prca.201700181","article-title":"MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods","volume":"13","author":"Klein","year":"2019","journal-title":"Proteom. Clin. Appl."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kassuhn, W., Klein, O., Darb-Esfahani, S., Lammert, H., Handzik, S., Taube, E.T., Schmitt, W.D., Keunecke, C., Horst, D., and Dreher, F. (2021). Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging. Cancers, 13.","DOI":"10.3390\/cancers13071512"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kulbe, H., Klein, O., Wu, Z., Taube, E.T., Kassuhn, W., Horst, D., Darb-Esfahani, S., Jank, P., Abobaker, S., and Ringel, F. (2020). Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging. Cancers, 12.","DOI":"10.1055\/s-0040-1718157"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ma, X., Botros, A., Yun, S.R., Park, E.Y., Kim, O., Park, S., Pham, T.H., Chen, R., Palaniappan, M., and Matzuk, M.M. (2023). Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models. Front. Chem., 11.","DOI":"10.3389\/fchem.2023.1332816"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3003","DOI":"10.1074\/mcp.M116.059816","article-title":"N-glycan MALDI Imaging Mass Spectrometry on Formalin-Fixed Paraffin-Embedded Tissue Enables the Delineation of Ovarian Cancer Tissues","volume":"15","author":"Briggs","year":"2016","journal-title":"Mol. Cell. Proteom."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e1800482","DOI":"10.1002\/pmic.201800482","article-title":"MALDI Mass Spectrometry Imaging of Early- and Late-Stage Serous Ovarian Cancer Tissue Reveals Stage-Specific N-Glycans","volume":"19","author":"Briggs","year":"2019","journal-title":"Proteomics"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1793","DOI":"10.1002\/pmic.201500455","article-title":"Lymph node metastasis of primary endometrial cancers: Associated proteins revealed by MALDI imaging","volume":"16","author":"Mittal","year":"2016","journal-title":"Proteomics"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1186\/s12920-019-0514-7","article-title":"GENT2: An updated gene expression database for normal and tumor tissues","volume":"12","author":"Park","year":"2019","journal-title":"BMC Med. Genom."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1007\/s10585-015-9718-1","article-title":"Transketolase is upregulated in metastatic peritoneal implants and promotes ovarian cancer cell proliferation","volume":"32","author":"Ricciardelli","year":"2015","journal-title":"Clin. Exp. Metastasis"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.7150\/jca.15371","article-title":"Increased Expression of Several Collagen Genes is Associated with Drug Resistance in Ovarian Cancer Cell Lines","volume":"7","author":"Januchowski","year":"2016","journal-title":"J. Cancer"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e230012","DOI":"10.1530\/ERC-23-0012","article-title":"COL12A1 as a prognostic biomarker links immunotherapy response in breast cancer","volume":"30","author":"Yan","year":"2023","journal-title":"Endocr. Relat. Cancer"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1002\/jcb.22413","article-title":"Quantitative proteome analysis of multidrug resistance in human ovarian cancer cell line","volume":"109","author":"Li","year":"2010","journal-title":"J. Cell. Biochem."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1093\/carcin\/bgx122","article-title":"Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): A novel role of RAD51AP1 for ovarian and lung cancers","volume":"39","author":"Chudasama","year":"2018","journal-title":"Carcinogenesis"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1007\/s10238-024-01431-y","article-title":"Type XII collagen is elevated in serum from patients with solid tumors: A non-invasive biomarker of activated fibroblasts","volume":"24","author":"Hettich","year":"2024","journal-title":"Clin. Exp. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4587","DOI":"10.1038\/s41467-022-32255-7","article-title":"Temporal profiling of the breast tumour microenvironment reveals collagen XII as a driver of metastasis","volume":"13","author":"Papanicolaou","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1186\/s13046-019-1318-5","article-title":"A positive feedback between IDO1 metabolite and COL12A1 via MAPK pathway to promote gastric cancer metastasis","volume":"38","author":"Xiang","year":"2019","journal-title":"J. Exp. Clin. Cancer Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"BSR20221002","DOI":"10.1042\/BSR20221002","article-title":"FBP1 knockdown decreases ovarian cancer formation and cisplatin resistance through EZH2-mediated H3K27me3","volume":"42","author":"Xiong","year":"2022","journal-title":"Biosci. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"794715","DOI":"10.3389\/fmolb.2022.794715","article-title":"Pan-Cancer Transcriptome and Immune Infiltration Analyses Reveal the Oncogenic Role of Far Upstream Element-Binding Protein 1 (FUBP1)","volume":"9","author":"Wang","year":"2022","journal-title":"Front. Mol. Biosci."},{"key":"ref_29","first-page":"1682","article-title":"FBP1 promotes ovarian cancer development through the acceleration of cell cycle transition and metastasis","volume":"16","author":"Xiong","year":"2018","journal-title":"Oncol. Lett."},{"key":"ref_30","first-page":"5819","article-title":"Knockdown of FUSE binding protein 1 enhances the sensitivity of epithelial ovarian cancer cells to carboplatin","volume":"14","author":"Zhang","year":"2017","journal-title":"Oncol. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"102066","DOI":"10.1016\/j.tranon.2024.102066","article-title":"FUBP1 in human cancer: Characteristics, functions, and potential applications","volume":"48","author":"Zhang","year":"2024","journal-title":"Transl. Oncol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Perez, S.M., Brinton, L.T., and Kelly, K.A. (2021). Plectin in Cancer: From Biomarker to Therapeutic Target. Cells, 10.","DOI":"10.3390\/cells10092246"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wang, Z., Wang, W., Luo, Q., and Song, G. (2024). Plectin: Dual Participation in Tumor Progression. Biomolecules, 14.","DOI":"10.3390\/biom14091050"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1186\/s12964-021-00726-x","article-title":"The attributes of plakins in cancer and disease: Perspectives on ovarian cancer progression, chemoresistance and recurrence","volume":"19","author":"Wesley","year":"2021","journal-title":"Cell Commun. Signal."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"30061","DOI":"10.1038\/srep30061","article-title":"Unique proteome signature of post-chemotherapy ovarian cancer ascites-derived tumor cells","volume":"6","author":"Ahmed","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wesley, T., Escalona, R.M., Kannourakis, G., and Ahmed, N. (2024). Plakin Expression in Serous Epithelial Ovarian Cancer Has the Potential to Impede Metastatic Spread and Epithelial\u2013Mesenchymal Transition: A Comparative Expression Analysis of Immunohistochemical and In Silico Datasets. Cancers, 16.","DOI":"10.3390\/cancers16234087"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Perez, S.M., Dimastromatteo, J., Landen, C.N., and Kelly, K.A. (2021). A Novel Monoclonal Antibody Targeting Cancer-Specific Plectin Has Potent Antitumor Activity in Ovarian Cancer. Cells, 10.","DOI":"10.3390\/cells10092218"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2782","DOI":"10.7150\/thno.23050","article-title":"Plectin-targeted liposomes enhance the therapeutic efficacy of a PARP inhibitor in the treatment of ovarian cancer","volume":"8","author":"Dasa","year":"2018","journal-title":"Theranostics"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"130","DOI":"10.3389\/fphys.2014.00130","article-title":"Regulation and roles of bicarbonate transport in cancer","volume":"5","author":"Gorbatenko","year":"2014","journal-title":"Front. Physiol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1593\/neo.07403","article-title":"Expression of anion exchanger 1 sequestrates p16 in the cytoplasm in gastric and colonic adenocarcinoma","volume":"9","author":"Shen","year":"2007","journal-title":"Neoplasia"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Schilling, V., Beyerlein, P., and Chien, J. (2023). A Bioinformatics Analysis of Ovarian Cancer Data Using Machine Learning. Algorithms, 16.","DOI":"10.20944\/preprints202305.0413.v1"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"113607","DOI":"10.1016\/j.biopha.2022.113607","article-title":"The role of transketolase in human cancer progression and therapy","volume":"154","author":"Hao","year":"2022","journal-title":"Biomed. Pharmacother."},{"key":"ref_43","first-page":"4845","article-title":"Prognostic values of transketolase family genes in ovarian cancer","volume":"18","author":"Zhao","year":"2019","journal-title":"Oncol. Lett."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/1559-0275-11-13","article-title":"Deciphering the ovarian cancer ascites fluid peptidome","volume":"11","author":"Bery","year":"2014","journal-title":"Clin. Proteom."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.jprot.2019.01.017","article-title":"Univariate and classification analysis reveals potential diagnostic biomarkers for early stage ovarian cancer Type 1 and Type 2","volume":"196","author":"Ulfenborg","year":"2019","journal-title":"J. Proteom."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Giacomini, I., Ragazzi, E., Pasut, G., and Montopoli, M. (2020). The Pentose Phosphate Pathway and Its Involvement in Cisplatin Resistance. Int. J. Mol. Sci., 21.","DOI":"10.3390\/ijms21030937"},{"key":"ref_47","first-page":"15719","article-title":"Exosomes mediated pentose phosphate pathway in ovarian cancer metastasis: A proteomics analysis","volume":"8","author":"Yi","year":"2015","journal-title":"Int. J. Clin. Exp. Pathol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5093","DOI":"10.1016\/j.jprot.2012.04.054","article-title":"Internal calibrants allow high accuracy peptide matching between MALDI imaging MS and LC-MS\/MS","volume":"75","author":"Gustafsson","year":"2012","journal-title":"J. Proteom."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Acland, M., Mittal, P., Arentz, G., Whitehead, F., Hoffmann, P., Klingler-Hoffmann, M., and Oehler, M.K. (2022). A Protocol for the Acquisition of Comprehensive Proteomics Data from Single Cases Using Formalin-Fixed Paraffin Embedded Sections. Methods Protoc., 5.","DOI":"10.3390\/mps5040057"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1016\/j.cell.2016.05.069","article-title":"Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer","volume":"166","author":"Zhang","year":"2016","journal-title":"Cell"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.bbapap.2013.01.040","article-title":"2D and 3D MALDI-imaging: Conceptual strategies for visualization and data mining","volume":"1844","author":"Thiele","year":"2014","journal-title":"Biochim. Biophys. Acta"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Price, Z.K., Lokman, N.A., Yoshihara, M., Kajiyama, H., Oehler, M.K., and Ricciardelli, C. (2022). Disabled-2 (DAB2): A Key Regulator of Anti- and Pro-Tumorigenic Pathways. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24010696"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3140","DOI":"10.1002\/ijc.32369","article-title":"ROCplot.org: Validating predictive biomarkers of chemotherapy\/hormonal therapy\/anti-HER2 therapy using transcriptomic data of 3,104 breast cancer patients","volume":"145","author":"Fekete","year":"2019","journal-title":"Int. J. Cancer"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1889","DOI":"10.1007\/s11357-023-00742-4","article-title":"Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer","volume":"45","year":"2023","journal-title":"Geroscience"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.18632\/oncotarget.1122","article-title":"Annexin A2 is regulated by ovarian cancer-peritoneal cell interactions and promotes metastasis","volume":"4","author":"Lokman","year":"2013","journal-title":"Oncotarget"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"16878","DOI":"10.1038\/s41598-017-17204-5","article-title":"QuPath: Open source software for digital pathology image analysis","volume":"7","author":"Bankhead","year":"2017","journal-title":"Sci. Rep."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/12\/5893\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:55:00Z","timestamp":1760032500000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/12\/5893"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,19]]},"references-count":56,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["ijms26125893"],"URL":"https:\/\/doi.org\/10.3390\/ijms26125893","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,19]]}}}