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. 2020 Feb 21;20:141. doi: 10.1186/s12885-020-6600-6

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© The Author(s). 2020

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 9 — Integrative analysis approach. Raw RNA counts from GDC database were processed in differential expression analysis. Differentially expressed RNAs were further inspected via functional analysis and network analysis (for microRNAs) to confirm that the significant differences are cancer-related. Afterwards, correlation analysis, target analysis and survival analysis were jointly applied to the differentially expressed RNAs to select the best candidates that could affect the difference between BL1 and BL2 subtypes and their outcomes. The candidates were then verified in BL1 and BL2 cell lines