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Background Patients with triple‐negative breast cancer (TNBC) face a major challenge of the poor prognosis, and N6‐methyladenosine‐(m6A) mediated regulation in cancer has been proposed. Therefore, this study aimed to explore the prognostic roles of m6A‐related long non‐coding RNAs (LncRNAs) in TNBC. Methods Clinical information and expression data of TNBC samples were collected from TCGA and GEO databases. Pearson correlation, univariate, and multivariate Cox regression analysis were employed to identify independent prognostic m6A‐related LncRNAs to construct the prognostic score (PS) risk model. Receiver operating characteristic (ROC) curve was used to evaluate the performance of PS risk model. A competing endogenous RNA (ceRNA) network was established for the functional analysis on targeted mRNAs. Results We identified 10 independent prognostic m6A‐related LncRNAs ( SAMD12 ‐ AS1 , BVES ‐ AS1 , LINC00593 , MIR205HG , LINC00571 , ANKRD10 ‐ IT1 , CIRBP ‐ AS1 , SUCLG2 ‐ AS1 , BLACAT1 , and HOXB ‐ AS1 ) and established a PS risk model accordingly. Relevant results suggested that TNBC patients with lower PS had better overall survival status, and ROC curves proved that the PS model had better prognostic abilities with the AUC of 0.997 and 0.864 in TCGA and GSE76250 datasets, respectively. Recurrence and PS model status were defined as independent prognostic factors of TNBC. These ten LncRNAs were all differentially expressed in high‐risk TNBC compared with controls. The ceRNA network revealed the regulatory axes for nine key LncRNAs, and mRNAs in the network were identified to function in pathways of cell communication, signaling transduction and cancer. Conclusion Our findings proposed a ten‐m6A‐related LncRNAs as potential biomarkers to predict the prognostic risk of TNBC.

A coupled intravascular-transvascular-interstitial fluid flow model is developed to study the distributions of blood flow and interstitial fluid pressure in solid tumor microcirculation based on a tumor-induced microvascular network. This is generated from a 2D nine-point discrete mathematical model of tumor angiogenesis and contains two parent vessels. Blood flow through the microvascular network and interstitial fluid flow in tumor tissues are performed by the extended Poiseuille's law and Darcy's law, respectively, transvascular flow is described by Starling's law; effects of the vascular permeability and the interstitial hydraulic conductivity are also considered. The simulation results predict the heterogeneous blood supply, interstitial hypertension and low convection on the inside of the tumor, which are consistent with physiological observed facts. These results may provide beneficial information for anti-angiogenesis treatment of tumor and further clinical research.

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IntroductionThis study aimed to explore the effect of activated T cells on breast cancer (BC) cells and provide a theoretical basis for the interaction mechanism studies between BC and immune cells.MethodsThe microarray dataset GSE73527 was downloaded from the Gene Expression Omnibus database. The common differentially expressed mRNAs (co-DEMs) and the common differentially expressed long non-coding RNAs (co-DElncRNAs) were identified between MDA-MB-231 cells and MCF7 activated human T cells, respectively. The RNA–miRNA–lncRNA (ceRNA) network was constructed. Furthermore, the Kyoto encyclopedia of genes and genomes pathway and the gene ontology function analyses were performed on co-DEMs. The protein–protein interaction networks and modules were investigated.ResultsA total of 639 co-DEMs (such as interleukin-6 [IL6] and signal transducer and activator of transcription 1 [STAT1]) were detected in this study. Defense response to other organisms and herpes simplex infection were the most outstanding function and pathway assembled with co-DEMs, respectively. One protein–protein interaction network and three modules were further constructed. A total of 88 mRNA–miRNA–lncRNA relationships such as BTN3A1-has-mir-20-b-5p-HCP5 were explored in the ceRNA network.ConclusionActivated T cells may play a crucial role in the defense response to other organism functions and herpes simplex infection pathways by upregulating IL6 and STAT1, which further affected the progression of BC. The BTN3A1-has-miR-20b-5p-HCP5 relationship may be the potential interaction mechanism between BC and immune cells.