Circular RNA mediated gene regulation in human breast cancer: A bioinformatics analysis

PLOS ONE RESEARCH ARTICLE Circular RNA mediated gene regulation in human breast cancer: A bioinformatics analysis Giulia Fiscon ID1,2, Alessio Funari3, Paola Paci ID1,2* a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Fiscon G, Funari A, Paci P (2023) Circular RNA mediated gene regulation in human breast cancer: A bioinformatics analysis. PLoS ONE 18(7): e0289051. https://doi.org/10.1371/journal. pone.0289051 Editor: Divijendra Natha Reddy Sirigiri, BMSCE: BMS College of Engineering, INDIA Received: October 13, 2022 Accepted: July 11, 2023 Published: July 26, 2023 Copyright: © 2023 Fiscon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. The source code developed in R is freely available at https://github.com/giuliafiscon/ CERNOMA.git Funding: This work has been partially funded by BiBiNet project (grant number: H35F21000430002) within the POR-Lazio FESR 2014-2020, by PON Ricerca e Innovazione 2014-2020 – DM 1062/202, by Finalizzata Giovani Ricercatori 2021 (grant n.: GR-2021-12372614, CUP: B83C22007560001), and by Sapienza University of Rome grant - 1 Department of Computer, Control and Management Engineering, Sapienza University of Rome, Roma, Italy, 2 Institute for Systems Analysis and Computer Science “Antonio Ruberti”, National Research Council, Rome, Italy, 3 Department of Translational and Precision Medicine, Sapienza University of Rome, Roma, Italy * Abstract Circular RNAs (circRNAs) are a new acknowledged class of RNAs that has been shown to play a major role in several biological functions both in physiological and pathological conditions, operating as critical part of regulatory processes, like competing endogenous RNA (ceRNA) networks. The ceRNA hypothesis is a recently discovered molecular mechanism that adds a new key layer of post-transcriptional regulation, whereby various types of RNAs can reciprocally influence each other’s expression competing for binding the same pool of microRNAs, even affecting disease development. In this study, we build a network of circRNA-miRNA-mRNA interactions in human breast cancer, called CERNOMA, that is a bipartite graph with one class of nodes corresponding to differentially expressed miRNAs (DEMs) and the other one corresponding to differentially expressed circRNAs (DEC) and mRNAs (DEGs). A link between a DEC (or DEG) and DEM is placed if it is predicted to be a target of the DEM and shows an opposite expression level trend with respect to the DEM. Within the CERNOMA, we highlighted an interesting deregulated circRNA-miRNA-mRNA triplet, including the up-regulated hsa_circRNA_102908 (BRCA1 associated RING domain 1), the down-regulated miR-410-3p, and the up-regulated ESM1, whose overexpression has been already shown to promote tumor dissemination and metastasis in breast cancer. Introduction Circular RNAs (circRNAs) are a special class of non-coding RNAs that are generated by a process of non-canonical splicing that joins a 5’ splice site to an upstream 3’ splice site, resulting in a covalent closed loop [1–3]. CircRNAs are widely observed in both plants [4] and animals [5], and even if their biological functions remain broadly unknown, increasing evidence suggests them as crucial regulators of multiple biological processes, including the development and progression of human diseases such as cancers [6–13]. The high resistance to degradation of circRNAs, which is dependent on their circular structure, makes them different from other linear RNAs. This stability causes tissues such as blood and plasma to be especially enriched with PLOS ONE | https://doi.org/10.1371/journal.pone.0289051 July 26, 2023 1 / 15 PLOS ONE Progetto di ricerca di Ateneo 2022 (grant n: RP12218139131053). Competing interests: The authors have declared that no competing interests exist. Circular RNAs-based ceRNA network in human breast cancer circular RNAs compared to messenger RNAs (mRNAs) and other non-coding RNAs [14]. Thus, when released into the bloodstream by tumoral cells, circRNAs can be more easily detected with respect to other transcripts, revealing them as good potential biomarkers for early diagnosis, metastasis, and prognosis [15]. Several findings reported that circRNAs are aberrantly modulated in human cancer tissues, thus affecting carcinogenesis and metastatization, and can also be useful for predicting and monitoring treatment response [12, 16, 17]. Even though no circRNA have been effectively used as biomarkers in clinical trials yet, the impact of circRNA-mediated regulation on various cell transcriptome showed a great potential to be investigated especially in human diseases [14, 18]. Interestingly, recent studies have been focusing on the possibility that circRNAs can operate as part of competing endogenous RNA (ceRNA) regulatory networks, playing major roles in normal development and in pathologic conditions like human cancer [12, 15, 18–25]. The ceRNA mechanism is a recent discovery providing a possible explanation of fine-tuned post-transcriptional gene regulation orchestrated by the competing endogenous RNAs and microRNAs (miRNAs) [26–30]. microRNAs are small non-coding RNAs (* 20–22 nucleotides long) responsible for RNA silencing and post-transcriptional regulation of gene expression [31]. The ceRNA hypothesis states that various types of RNAs can reciprocally influence each other’s expression competing for binding the same pool of miRNAs, thus preventing mRNAs to be targeted [26]. This RNA-RNA crosstalk can add a new level to the understanding of complex regulatory networks that, when perturbed, could lead to disease development [19, 32–35]. Among several computation tools for ceRNAs discovery, we recently developed SPINNAKER [36], the R-implementation of the well-established model [37] that was acknowledged as the best one in terms of percentage of identified RNAs acting as ceRNA in breast cancer tissues [38]. By exploiting a multivariate statistical analysis, SPINNAKER first searches for highly correlated RNA pairs (i.e., co-expressed) and then evaluates the extent to which this correlation is direct or mediated by miRNAs, via the computation of the sensitivity correlation [37]. Finally, SPINNAKER selects only those RNA pairs whose interaction is mediated by some miRNAs (i.e., highest sensitivity correlation) and builds a ceRNA network where nodes are ceRNAs and links are miRNAs mediating their interactions. The ceRNA network can be optionally refined by considering only those triplets with ceRNAs showing a predicted binding site for the miRNA. To run SPINNAKER and build the ceRNA network, we need as input three matrices of RNA expression levels from the same cohort of tissues/ (...truncated)