A fine-needle aspiration-based protein signature discriminates benign from malignant breast lesions Show others and affiliations
2018 (English) In: Molecular Oncology, ISSN 1574-7891, E-ISSN 1878-0261, Vol. 12, no 9, p. 1415-1428Article in journal (Refereed) Published
Abstract [en]
There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and to follow-up personalized cancer therapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissues; however, the minute sample amounts require sensitive multiplex molecular analysis to achieve clinical utility. We have applied proximity extension assays (PEA) and NanoString (NS) technology for analyses of proteins and of RNA, respectively, in FNA samples. Using samples from patients with breast cancer (BC, n=25) or benign lesions (n=33), we demonstrate that these FNA-based molecular analyses (a) can offer high sensitivity and reproducibility, (b) may provide correct diagnosis in shorter time and at a lower cost than current practice, (c) correlate with results from routine analysis (i.e., benchmarking against immunohistochemistry tests for ER, PR, HER2, and Ki67), and (d) may also help identify new markers related to immunotherapy. A specific 11-protein signature, including FGF binding protein 1, decorin, and furin, distinguished all cancer patient samples from all benign lesions in our main cohort and in smaller replication cohort. Due to the minimally traumatic sampling and rich molecular information, this combined proteomics and transcriptomic methodology is promising for diagnostics and evaluation of treatment efficacy in BC.
Place, publisher, year, edition, pages 2018. Vol. 12, no 9, p. 1415-1428
Keywords [en]
breast cancer diagnosis, fine-needle aspiration, protein biomarker, proximity extension assay
National Category
Cancer and Oncology Cell and Molecular Biology
Identifiers URN: urn:nbn:se:uu:diva-364195 DOI: 10.1002/1878-0261.12350 ISI: 000443402000002 PubMedID: 30019538 OAI: oai:DiVA.org:uu-364195 DiVA, id: diva2:1259303
Funder VINNOVA, 201600595 Swedish Research Council EU, FP7, Seventh Framework Programme, 316929 294409 Stockholm County Council, 20151043 The Breast Cancer Foundation Swedish Cancer Society The Cancer Research Funds of Radiumhemmet 2018-10-292018-10-292018-11-16 Bibliographically approved