{"entity": "researcher", "timestamp": "2026-08-20T21:11:23.382Z", "family": "Lehti", "given": "Kaisa", "initials": "K", "orcid": "0000-0001-9110-8719", "affiliations": ["Department of Biomedical Laboratory Science, Norwegian University of Science and Technology NTNU, Trondheim, Norway.", "Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/613d944b4c8c4942b871ba87f580e53e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/613d944b4c8c4942b871ba87f580e53e"}}, "publications": [{"entity": "publication", "iuid": "37e5b61d6d8b4f719da9978e5016e686", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/37e5b61d6d8b4f719da9978e5016e686.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/37e5b61d6d8b4f719da9978e5016e686"}}, "title": "The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients.", "authors": [{"family": "\u00c5kerlund", "given": "Emma", "initials": "E"}, {"family": "Gudoityte", "given": "Greta", "initials": "G"}, {"family": "Moussaud-Lamodi\u00e8re", "given": "Elisabeth", "initials": "E", "orcid": "0000-0002-2359-6519", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5cac5b7c76714c1895a4e31d16616821.json"}}, {"family": "Lind", "given": "Olina", "initials": "O"}, {"family": "Bwanika", "given": "Henri Colyn", "initials": "HC", "orcid": "0000-0002-0834-4153", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/16d34ecedbe74a98831828b46d4e93e4.json"}}, {"family": "Lehti", "given": "Kaisa", "initials": "K", "orcid": "0000-0001-9110-8719", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/613d944b4c8c4942b871ba87f580e53e.json"}}, {"family": "Salehi", "given": "Sahar", "initials": "S"}, {"family": "Carlson", "given": "Joseph", "initials": "J"}, {"family": "Wallin", "given": "Emelie", "initials": "E"}, {"family": "Fernebro", "given": "Josefin", "initials": "J"}, {"family": "\u00d6stling", "given": "P\u00e4ivi", "initials": "P"}, {"family": "Kallioniemi", "given": "Olli", "initials": "O"}, {"family": "Joneborg", "given": "Ulrika", "initials": "U", "orcid": "0000-0002-1922-0738", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d70ae27229fc4723941b2c3ae238ba26.json"}}, {"family": "Seashore-Ludlow", "given": "Brinton", "initials": "B", "orcid": "0000-0001-8658-5967", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8a8ea4c3fdb14de1b651d0367b0a70a4.json"}}], "type": "journal article", "published": "2023-10-31", "journal": {"title": "NPJ Precis Oncol", "issn": "2397-768X", "volume": "7", "issue": "1", "pages": "111", "issn-l": null}, "abstract": "Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DET3Ct (Drug Efficacy Testing in 3D Cultures), where the response of patient cells to drugs and drug combinations are quantified with live-cell imaging. We demonstrate the delivery of individual drug sensitivity profiles in 20 samples from 16 patients with ovarian cancer in both 2D and 3D culture formats, achieving over 90% success rate in providing results six days after operation. In this cohort all patients received carboplatin. The carboplatin sensitivity scores were significantly different for patients with a progression free interval (PFI) less than or equal to 12 months and those with more than 12 months (p < 0.05). We find that the 3D culture format better retains proliferation and characteristics of the in vivo setting. Using the DET3Ct platform we evaluate 27 tailored combinations with results available 10 days after operation. Notably, carboplatin and A-1331852 (Bcl-xL inhibitor) showed an additive effect in four of eight OC samples tested, while afatinib and A-1331852 led to synergy in five of seven OC models. In conclusion, our 3D DET3Ct platform can rapidly define potential, clinically relevant data on efficacy of existing drugs in OC for precision medicine purposes, as well as provide insights on emerging drugs and drug combinations that warrant testing in clinical trials.", "doi": "10.1038/s41698-023-00463-z", "pmid": "37907613", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10618545"}, {"db": "pii", "key": "10.1038/s41698-023-00463-z"}], "notes": [], "created": "2026-08-20T09:24:32.105Z", "modified": "2026-08-20T09:24:32.314Z"}, {"entity": "publication", "iuid": "08aaf14158a140369f042374ecde45a3", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/08aaf14158a140369f042374ecde45a3.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/08aaf14158a140369f042374ecde45a3"}}, "title": "An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation.", "authors": [{"family": "Mobashir", "given": "Mohammad", "initials": "M", "orcid": "0000-0002-5385-4048", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8e961b3a2fe94cb3acc1fa8f718cd97c.json"}}, {"family": "Turunen", "given": "S Pauliina", "initials": "SP", "orcid": "0000-0001-8060-9876", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5ca544f8f7314ccfaf87c365aba0996e.json"}}, {"family": "Izhari", "given": "Mohammad Asrar", "initials": "MA"}, {"family": "Ashankyty", "given": "Ibraheem Mohammed", "initials": "IM", "orcid": "0000-0002-6222-9674", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0731aaa25f51446fbcc5bb5045e5a36f.json"}}, {"family": "Helleday", "given": "Thomas", "initials": "T", "orcid": "0000-0002-7384-092X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/385586c159494955a9a72c3381e3ad47.json"}}, {"family": "Lehti", "given": "Kaisa", "initials": "K", "orcid": "0000-0001-9110-8719", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/613d944b4c8c4942b871ba87f580e53e.json"}}], "type": "journal article", "published": "2022-12-19", "journal": {"title": "Cells", "issn": "2073-4409", "volume": "11", "issue": "24", "issn-l": "2073-4409"}, "abstract": "To understand complex diseases, high-throughput data are generated at large and multiple levels. However, extracting meaningful information from large datasets for comprehensive understanding of cell phenotypes and disease pathophysiology remains a major challenge. Despite tremendous advances in understanding molecular mechanisms of cancer and its progression, current knowledge appears discrete and fragmented. In order to render this wealth of data more integrated and thus informative, we have developed a GECIP toolbox to investigate the crosstalk and the responsible genes'/proteins' connectivity of enriched pathways from gene expression data. To implement this toolbox, we used mainly gene expression datasets of prostate cancer, and the three datasets were GSE17951, GSE8218, and GSE1431. The raw samples were processed for normalization, prediction of differentially expressed genes, and the prediction of enriched pathways for the differentially expressed genes. The enriched pathways have been processed for crosstalk degree calculations for which number connections per gene, the frequency of genes in the pathways, sharing frequency, and the connectivity have been used. For network prediction, protein-protein interaction network database FunCoup2.0 was used, and cytoscape software was used for the network visualization. In our results, we found that there were enriched pathways 27, 45, and 22 for GSE17951, GSE8218, and GSE1431, respectively, and 11 pathways in common between all of them. From the crosstalk results, we observe that focal adhesion and PI3K pathways, both experimentally proven central for cellular output upon perturbation of numerous individual/distinct signaling pathways, displayed highest crosstalk degree. Moreover, we also observe that there were more critical pathways which appear to be highly significant, and these pathways are HIF1a, hippo, AMPK, and Ras. In terms of the pathways' components, GSK3B, YWHAE, HIF1A, ATP1A3, and PRKCA are shared between the aforementioned pathways and have higher connectivity with the pathways and the other pathway components. Finally, we conclude that the focal adhesion and PI3K pathways are the most critical pathways, and since for many other pathways, high-rank enrichment did not translate to high crosstalk degree, the global impact of one pathway on others appears distinct from enrichment.", "doi": "10.3390/cells11244121", "pmid": "36552885", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC9777290"}, {"db": "pii", "key": "cells11244121"}], "notes": [], "created": "2026-08-20T13:40:09.571Z", "modified": "2026-08-20T13:40:09.816Z"}, {"entity": "publication", "iuid": "09a8f68ad91f44feb6bc034920c4fb3f", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/09a8f68ad91f44feb6bc034920c4fb3f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/09a8f68ad91f44feb6bc034920c4fb3f"}}, "title": "Thermal Proteome Profiling Identifies Oxidative-Dependent Inhibition of the Transcription of Major Oncogenes as a New Therapeutic Mechanism for Select Anticancer Compounds.", "authors": [{"family": "Peuget", "given": "Sylvain", "initials": "S"}, {"family": "Zhu", "given": "Jiawei", "initials": "J"}, {"family": "Sanz", "given": "Gema", "initials": "G", "orcid": "0000-0002-6227-0431", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a47391ae48b44959b1d95d9372ecfa7f.json"}}, {"family": "Singh", "given": "Madhurendra", "initials": "M"}, {"family": "Gaetani", "given": "Massimiliano", "initials": "M", "orcid": "0000-0001-5610-0797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/a402c63fbe4f478daa286177f031b923.json"}}, {"family": "Chen", "given": "Xinsong", "initials": "X"}, {"family": "Shi", "given": "Yao", "initials": "Y"}, {"family": "Saei", "given": "Amir Ata", "initials": "AA", "orcid": "0000-0002-2639-6328", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ebf703f0f2d44b14846ea1d9811b6e0d.json"}}, {"family": "Visnes", "given": "Torkild", "initials": "T", "orcid": "0000-0003-1047-988X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9fef10d6a8604971a6ad1849b9f8b029.json"}}, {"family": "Lindstr\u00f6m", "given": "Mikael S", "initials": "MS", "orcid": "0000-0003-1148-8497", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/069306b8ab85484db417a144c0a7d325.json"}}, {"family": "Rihani", "given": "Ali", "initials": "A", "orcid": "0000-0002-6176-0519", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/473d1074db314fcc968f37871d5b5271.json"}}, {"family": "Moyano-Galceran", "given": "Lidia", "initials": "L", "orcid": "0000-0001-9219-6394", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/84dfd710b5884f46a17ec259e18546b0.json"}}, {"family": "Carlson", "given": "Joseph W", "initials": "JW", "orcid": "0000-0002-3006-4107", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/33ec4d8cf5e54b4b918f081683bd08ba.json"}}, {"family": "Hjerpe", "given": "Elisabet", "initials": "E"}, {"family": "Joneborg", "given": "Ulrika", "initials": "U"}, {"family": "Lehti", "given": "Kaisa", "initials": "K", "orcid": "0000-0001-9110-8719", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/613d944b4c8c4942b871ba87f580e53e.json"}}, {"family": "Hartman", "given": "Johan", "initials": "J", "orcid": "0000-0002-6500-8527", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d62d622200d443b7b5be34ff3c0945be.json"}}, {"family": "Helleday", "given": "Thomas", "initials": "T"}, {"family": "Zubarev", "given": "Roman", "initials": "R"}, {"family": "Selivanova", "given": "Galina", "initials": "G"}], "type": "journal article", "published": "2020-04-01", "journal": {"title": "Cancer Res.", "issn": "1538-7445", "volume": "80", "issue": "7", "pages": "1538-1550", "issn-l": "0008-5472"}, "abstract": "Identification of the molecular mechanism of action (MoA) of bioactive compounds is a crucial step for drug development but remains a challenging task despite recent advances in technology. In this study, we applied multidimensional proteomics, sensitivity correlation analysis, and transcriptomics to identify a common MoA for the anticancer compounds RITA, aminoflavone (AF), and oncrasin-1 (Onc-1). Global thermal proteome profiling revealed that the three compounds target mRNA processing and transcription, thereby attacking a cancer vulnerability, transcriptional addiction. This led to the preferential loss of expression of oncogenes involved in PDGF, EGFR, VEGF, insulin/IGF/MAPKK, FGF, Hedgehog, TGF\u03b2, and PI3K signaling pathways. Increased reactive oxygen species level in cancer cells was a prerequisite for targeting the mRNA transcription machinery, thus conferring cancer selectivity to these compounds. Furthermore, DNA repair factors involved in homologous recombination were among the most prominently repressed proteins. In cancer patient samples, RITA, AF, and Onc-1 sensitized to poly(ADP-ribose) polymerase inhibitors both in vitro and ex vivo These findings might pave a way for new synthetic lethal combination therapies.Significance: These findings highlight agents that target transcriptional addiction in cancer cells and suggest combination treatments that target RNA processing and DNA repair pathways simultaneously as effective cancer therapies.", "doi": "10.1158/0008-5472.CAN-19-2069", "pmid": "32019870", "labels": [], "xrefs": [{"db": "pii", "key": "0008-5472.CAN-19-2069"}], "notes": [], "created": "2026-08-20T12:10:57.167Z", "modified": "2026-08-20T12:10:57.525Z"}]}