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  3. Drug response profiles in patient-derived cancer cells across histological subtypes of ovarian cancer: real-time therapy tailoring for a patient with low-grade serous carcinoma

Drug response profiles in patient-derived cancer cells across histological subtypes of ovarian cancer: real-time therapy tailoring for a patient with low-grade serous carcinoma

  • Br J Cancer. 2022 Dec 7. doi: 10.1038/s41416-022-02067-z.
Astrid Murumägi 1,  Daniela Ungureanu 2 3,  Suleiman Khan 4 5,  Mariliina Arjama 4,  Katja Välimäki 4,  Aleksandr Ianevski 4 5,  Philipp Ianevski 4,  Rebecka Bergström 6,  Alice Dini 2 3,  Anna Kanerva 7,  Riitta Koivisto-Korander 7,  Johanna Tapper 7,  Heini Lassus 7,  Mikko Loukovaara 7,  Andrus Mägi 8,  Akira Hirasawa 9,  Daisuke Aoki 10,  Vilja Pietiäinen 4 11,  Teijo Pellinen 4,  Ralf Bützow 12,  Tero Aittokallio 4 5 13 14,  Olli Kallioniemi 15 16 17
Affiliations

Affiliations

  • 1 Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland. [email protected].
  • 2 Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
  • 3 Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland.
  • 4 Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.
  • 5 Helsinki Institute for Information Technology (HIIT), Department of Computer Science, Aalto University, Espoo, Finland.
  • 6 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
  • 7 Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • 8 Tartu University Hospital, Tartu, Estonia.
  • 9 Department of Clinical Genomic Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
  • 10 Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo, Japan.
  • 11 iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland.
  • 12 Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • 13 Institute for Cancer Research, Department of Cancer Genetics, Oslo University Hospital, Oslo, Norway.
  • 14 Centre for Biostatistics and Epidemiology (OCBE), Faculty of Medicine, University of Oslo, Oslo, Norway.
  • 15 Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland. [email protected].
  • 16 iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland. [email protected].
  • 17 Science for Life Laboratory (SciLifeLab), Department of Oncology and Pathology, Karolinska Institutet, Solna, Sweden. [email protected].
PMID: 36476658 DOI: 10.1038/s41416-022-02067-z
Abstract

Many efforts are underway to develop novel therapies against the aggressive high-grade serous ovarian cancers (HGSOCs), while our understanding of treatment options for low-grade (LGSOC) or mucinous (MUCOC) of ovarian malignancies is not developing as well. We describe here a functional precision oncology (fPO) strategy in epithelial ovarian cancers (EOC), which involves high-throughput drug testing of patient-derived ovarian Cancer cells (PDCs) with a library of 526 oncology drugs, combined with genomic and transcriptomic profiling. HGSOC, LGSOC and MUCOC PDCs had statistically different overall drug response profiles, with LGSOCs responding better to targeted inhibitors than HGSOCs. We identified several subtype-specific drug responses, such as LGSOC PDCs showing high sensitivity to MDM2, ERBB2/EGFR inhibitors, MUCOC PDCs to MEK inhibitors, whereas HGSOCs showed strongest effects with Chk1 inhibitors and SMAC mimetics. We also explored several drug combinations and found that the dual inhibition of MEK and SHP2 was synergistic in MAPK-driven EOCs. We describe a clinical case study, where real-time fPO analysis of samples from a patient with metastatic, chemorefractory LGSOC with a CLU-NRG1 fusion guided clinical therapy selection. fPO-tailored therapy with afatinib, followed by trastuzumab and pertuzumab, successfully reduced tumour burden and blocked disease progression over a five-year period. In summary, fPO is a powerful approach for the identification of systematic drug response differences across EOC subtypes, as well as to highlight patient-specific drug regimens that could help to optimise therapies to individual patients in the future.

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