Abstract
Long non-coding RNAs (lncRNAs) play key regulatory roles in breast cancer. However, population-level differential expression analysis methods disregard the heterogeneous expression of lncRNAs in individual patients. Therefore, we individualized lncRNA expression profiles for breast invasive carcinoma (BRCA) using the method of LncRNA Individualization (LncRIndiv). After evaluating the robustness of LncRIndiv, we constructed an individualized differentially expressed lncRNA (IDElncRNA) profile for BRCA and investigated the subtype-specific IDElncRNAs. The breast cancer subtype-specific IDElncRNA showed frequent co-occurrence with alterations of protein-coding genes, including mutations, copy number variation and differential methylation. We performed hierarchical clustering to subdivide TNBC and revealed mesenchymal subtype and immune subtype for TNBC. The TNBC immune subtype showed a better prognosis than the TNBC mesenchymal subtype. LncRNA PTOV1-AS1 was the top differentially expressed lncRNA in the mesenchymal subtype. And biological experiments validated that the upregulation of PTOV1-AS1 could downregulate TJP1 (ZO-1) and E-Cadherin, and upregulate Vimentin, which suggests PTOV1-AS1 may promote epithelial-mesenchymal transition and lead to migration and invasion of TNBC cells. The mesenchymal subtype showed a higher fraction of M2 macrophages, whereas the immune subtype was more associated with CD4 + T cells. The immune subtype is characterized by genomic instability and upregulation of immune checkpoint genes, thereby suggesting a potential response to immunosuppressive drugs. Last, drug response analysis revealed lncRNA ENSG00000230082 (PRRT3-AS1) is a potential resistance biomarker for paclitaxel in BRCA treatment. Our analysis highlights that IDElncRNAs can characterize inter-tumor heterogeneity in BRCA and the new TNBC subtypes indicate novel insights into TNBC immunotherapy.
Highlights
Long non-coding RNAs are involved in carcinogenesis through epigenetics, chromatin regulation, and transcriptional as well as post-transcriptional regulation [1, 2]
Analytic pipeline of IDElncRNA profile for breast invasive carcinoma (BRCA) We employed the LncRIndiv method to construct an IDElncRNA profile for BRCA using the Long non-coding RNAs (lncRNAs) expression profile from The Cancer Genome Atlas (TCGA) (Fig. S1A)
We investigated the co-occurrence between differential expression of lncRNAs and alterations of protein-coding genes, including mutations, copy number variation (CNV), and differential methylation in BRCA (Fig. S1C)
Summary
Long non-coding RNAs (lncRNAs) are involved in carcinogenesis through epigenetics, chromatin regulation, and transcriptional as well as post-transcriptional regulation [1, 2]. Population-level lncRNA differential expression analysis has been used to identify differentially expressed lncRNAs in breast cancer. Methods such as T-test are sensitive to technical factors, including different platforms and batch effects [5]. The fold-change (FC) method for pairwise comparison of disease and control samples is usually used to detect individual differentially expressed genes. RankComp can directly utilize data from different datasets to identify differentially expressed genes in individual samples. Our previous study proposed a LncRNA Individualization (LncRIndiv) method, which detects individualized differentially expressed lncRNAs (IDElncRNAs), to develop a prognostic signature for lung adenocarcinoma [7]. Identifying IDElncRNA may provide novel insights into the mechanism of known breast cancer subtypes and reveal new malignant breast cancer classification
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