Identification of long non-coding RNAs and RNA binding proteins in breast cancer subtypes

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  • dc.contributor.author Cava, Claudia
  • dc.contributor.author Armaos, Alexandros, 1989-
  • dc.contributor.author Lang, Benjamin
  • dc.contributor.author Tartaglia, Gian Gaetano
  • dc.contributor.author Castiglioni, Isabella
  • dc.date.accessioned 2022-04-20T06:30:32Z
  • dc.date.available 2022-04-20T06:30:32Z
  • dc.date.issued 2022
  • dc.description.abstract Breast cancer is a heterogeneous disease classified into four main subtypes with different clinical outcomes, such as patient survival, prognosis, and relapse. Current genetic tests for the differential diagnosis of BC subtypes showed a poor reproducibility. Therefore, an early and correct diagnosis of molecular subtypes is one of the challenges in the clinic. In the present study, we identified differentially expressed genes, long non-coding RNAs and RNA binding proteins for each BC subtype from a public dataset applying bioinformatics algorithms. In addition, we investigated their interactions and we proposed interacting biomarkers as potential signature specific for each BC subtype. We found a network of only 2 RBPs (RBM20 and PCDH20) and 2 genes (HOXB3 and RASSF7) for luminal A, a network of 21 RBPs and 53 genes for luminal B, a HER2-specific network of 14 RBPs and 30 genes, and a network of 54 RBPs and 302 genes for basal BC. We validated the signature considering their expression levels on an independent dataset evaluating their ability to classify the different molecular subtypes with a machine learning approach. Overall, we achieved good performances of classification with an accuracy >0.80. In addition, we found some interesting novel prognostic biomarkers such as RASSF7 for luminal A, DCTPP1 for luminal B, DHRS11, KLC3, NAGS, and TMEM98 for HER2, and ABHD14A and ADSSL1 for basal. The findings could provide preliminary evidence to identify putative new prognostic biomarkers and therapeutic targets for individual breast cancer subtypes.
  • dc.description.sponsorship The research leading to these results has been supported by European Research Council grant agreements RIBOMYLOME (309545) and ASTRA (855923), and the European Union’s Horizon 2020 research and innovation programme grant agreements IASIS (727658), DeepRNA (793135), and INFORE (825080). We would like to thank for the financial support the project Grant SysBioNet, Italian Roadmap Research Infrastructures 2012.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Cava C, Armaos A, Lang B, Tartaglia GG, Castiglioni I. Identification of long non-coding RNAs and RNA binding proteins in breast cancer subtypes. Sci Rep. 2022 Jan 13;12(1):693. DOI: 10.1038/s41598-021-04664-z
  • dc.identifier.doi http://dx.doi.org/10.1038/s41598-021-04664-z
  • dc.identifier.issn 2045-2322
  • dc.identifier.uri http://hdl.handle.net/10230/52855
  • dc.language.iso eng
  • dc.publisher Nature Research
  • dc.relation.ispartof Sci Rep. 2022 Jan 13;12(1):693
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/309545
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/855923
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/727658
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/793135
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825070
  • dc.rights © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Computational biology and bioinformatics
  • dc.subject.keyword Molecular biology
  • dc.title Identification of long non-coding RNAs and RNA binding proteins in breast cancer subtypes
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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