MicroRNAs (miRNAs) are crucial regulators of gene expression at the post-transcriptional level in eukaryotes via targeting gene 3'-untranslated regions. Transposable elements (TEs) are considered as natural origins of some miRNAs. However, what miRNAs are and how these miRNAs originate and evolve from TEs remain unclear. We identified 409 TE-derived miRNAs (386 overlapped with TEs and 23 un-overlapped with TEs) which are derived from TEs in human. This indicates that the TEs play important roles in origin of miRNAs in human. In addition, we found that the proportions of miRNAs derived from TEs (MDTEs) in human are more than other vertebrates especially non-mammal vertebrates. Furthermore, we classified MDTEs into three types and found that TE head or tail sequences along with adjacent genomic sequences contribute to generation of human miRNAs. Our current study will improve the understanding of origin and evolution of human miRNAs.

Background: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. Methods: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. Results: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor–ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. Conclusions: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

Genes carry out their biological functions through pathways in complex networks consisting of many interacting molecules. Studies on the effect of network architecture on the evolution of individual proteins will provide valuable information for understanding the origin and evolution as well as functional conservation of signaling pathways. However, the relationship between the network architecture and the individual protein sequence evolution is yet little known. In current study, we carried out network-level molecular evolution analysis on TLR (Toll-like receptor ) signaling pathway, which plays an important role in innate immunity in insects and mammals, and we found that: 1) The selection constraint of genes was negatively correlated with its position along TLR signaling pathway; 2) all genes in TLR signaling pathway were highly conserved and underwent strong purifying selection; 3) the distribution of selective pressure along the pathway was driven by differential nonsynonymous substitution levels; 4) The TLR signaling pathway might present in a common ancestor of sponges and eumetazoa, and evolve via the TLR, IKK, IκB and NF-κB genes underwent duplication events as well as adaptor molecular enlargement, and gene structure and conservation motif of NF-κB genes shifted in their evolutionary history. Our results will improve our understanding on the evolutionary history of animal TLR signaling pathway as well as the relationship between the network architecture and the sequences evolution of individual protein.

Clear cell renal cell carcinoma (ccRCC) still remains a higher mortality rate in worldwide. Obtaining promising biomakers is very crucial for improving the diagnosis and prognosis of ccRCC patients. Herein, we firstly identified eight potentially prognostic miRNAs (hsa-miR-144-5p, hsa-miR-223-3p, hsa-miR-365b-3p, hsa-miR-3613-5p, hsa-miR-9-5p, hsa-miR-183-5p, hsa-miR-335-3p, hsa-miR-1269a). Secondly, we found that a signature containing these eight miRNAs showed obviously superior to a single miRNA in the prognostic effect and credibility for predicting the survival of ccRCC patients. Thirdly, we discovered that twenty-two transcription factors (TFs) interact with these eight miRNAs, and a signature combining nine TFs (TFAP2A, KLF5, IRF1, RUNX1, RARA, GATA3, IKZF1, POU2F2, and FOXM1) could promote the prognosis of ccRCC patients. Finally, we further identified eleven genes (hsa-miR-365b-3p, hsa-miR-223-3p, hsa-miR-1269a, hsa-miR-144-5p, hsa-miR-183-5p, hsa-miR-335-3p, TFAP2A, KLF5, IRF1, MYC, IKZF1) that could combine as a signature to improve the prognosis effect of ccRCC patients, which distinctly outperformed the eight-miRNA signature and the nine-TF signature. Overall, we identified several new prognosis factors for ccRCC, and revealed a potential mechanism that TFs and miRNAs interplay cooperatively or oppositely regulate a certain number of tumor suppressors, driver genes, and oncogenes to facilitate the survival of ccRCC patients.