Background: Long noncoding RNAs (lncRNAs) are emerging as critical regulatory elements and play fundamental roles in the biology of various cancers. However, we are still lack of knowledge about their expression patterns and functions in human colorectal cancer (CRC). Methods: Differentially expressed lncRNAs in CRC were identified by bioinformatics screen and the level of MIR22HG in CRC and control tissues were determined by qRT-PCR. Cell viability and migration capacities were examined by MTT and transwell assay. Mouse model was used to examine the function and rational immunotherapy of MIR22HG in vivo. Results: We systematically investigated the expression pattern of lncRNAs and revealed MIR22HG acts as a tumor suppressor in CRC. The expression of MIR22HG was significantly decreased in CRC, which was mainly driven by copy number deletion. Reduced expression of MIR22HG was significantly associated with poor overall survival. Silencing of MIR22HG promoted cell survival, proliferation and tumor metastasis in vitro and in vivo. Mechanistically, MIR22HG exerts its tumor suppressive activity by competitively interacting with SMAD2 and modulating the activity of TGFβ pathway. Decreased MIR22HG promoted the epithelial-mesenchymal transition in CRC. Importantly, we found that MIR22HG expression is significantly correlated with CD8A and overexpression of MIR22HG triggers T cell infiltration, enhancing the clinical benefits of immunotherapy. Conclusion: MIR22HG acts as a tumor suppressor in CRC. Our data provide mechanistic insights into the regulation of MIR22HG in TGFβ pathway and facilitates immunotherapy in cancer.

Long non-coding RNAs (lncRNAs), as important ncRNA regulators, play crucial roles in the regulation of various biological processes, and their aberrant expression is related to the occurrence and development of diseases, which is gradually validated by more and more studies. Alzheimer’s disease (AD) is a chronic neurodegenerative disease that often develops slowly and gradually deteriorates over time. However, which functions the lncRNAs perform in AD are almost unknown. In this study, we performed transcriptome analysis in AD, containing 12,892 known lncRNAs and 19,053 protein-coding genes (PCGs). Further, 14 down-regulated and 39 up-regulated lncRNAs were identified, compared with normal brain samples, which indicated that these lncRNAs might play critical roles in the pathogenesis of AD. In addition, 19 down-regulated and 28 up-regulated PCGs were also detected. Using the differentially expressed lncRNAs and PCGs through the WGCNA method, an lncRNA–mRNA co-expressed network was constructed. The results showed that lncRNAs RP3-522J7, MIR3180-2, and MIR3180-3 were frequently co-expressed with known AD risk PCGs. Interestingly, PCGs in the network are significantly enriched in brain- or AD-related biological functions, including the brain renin–angiotensin system, cell adhesion, neuroprotective role of THOP1 in AD, and so on. Furthermore, it was shown that 18 lncRNAs and 7 PCGs were highly expressed in normal brain tissue relative to other normal tissue types, suggesting their potential as diagnostic markers of AD, especially RP3-522J7, MIR3180-2, MIR3180-3, and CTA-929C8. In total, our study identified a compendium of AD-related dysregulated lncRNAs and characterized the corresponding biological functions of these lncRNAs in AD, which will be helpful to understand the molecular basis and pathogenesis of AD.

LincRNAs enriched with high H3K4me1 and low H3K4me3 signals often have the enhancer-like features which are named as enhancer-associated lincRNAs (elincRNAs). ElincRNAs are considered to be indispensable for target gene transcription, which play important roles in development, signaling events, and even diseases. In this study, we developed a regularized regression model to identify elincRNAs by integrating the genomic, epigenomic, and regulatory data. Application of the proposed method to mouse ESCs reveals that besides the basic well-known epigenetic features H3K4me1 and H3K4me3, more specific epigenetic features, such as high DNA methylation, high H3K122ac, and H3K36me3 were contributed to mark elincRNAs with the best accuracy and precision. Finally, 3729 elincRNAs were identified in mouse ESCs. Furthermore, the elincRNAs and canonical lincRNAs exhibit distinct genomic features, and elincRNAs have the higher CGI enrichment and lower sequence conservation. Through the analysis of transcription regulation, we found that elincRNAs were significantly regulated by NANOG, POU5F1, SOX2 and ESRRB, and were involved in the core transcriptional regulatory circuitry controlling ES cell state Function enrichment analysis further discovered that elincRNAs tended to regulate specific embryonic development biological processes. These results indicated that these two types of lincRNAs had both specific epigenetic and transcriptional regulation mechanism and display distinct functional characters. In conclusion, we presented a credible computational model to prioritize novel elincRNAs, and depicted the atlas of elincRNAs in mouse ESCs, which would help dissect the function roles of lncRNAs during the mammalian development and diseases.

Human papillomavirus (HPV) is a dsDNA virus and its high-risk subtypes increase cancer risks. Yet, the mechanism of HPV infection and pathogenesis still remain unclear. Therefore, understanding the molecular mechanisms, and the pathogenesis of HPV are crucial in the prevention of HPV related cancers. In this study, we analyzed cervix squamous cell carcinoma (CESC) and head and neck carcinoma (HNSC) combined data to investigate various HPV induced cancer common feature. We showed that epidermal growth factor receptor (EGFR) was downregulated in HPV positive (HPV+) cancer, and that HPV+ cancer patients exhibited better prognosis than HPV negative (HPV−) cancer patients. Our study also showed that TP53 mutation rate is lower in HPV+ cancer than in HPV− cancer and that TP53 can be modulated by HPV E7 protein. However, there was no significant difference in the expression of wildtype TP53 in both groups. Subsequently, we constructed HPV-human interaction network and found that EGFR is a critical factor. From the network, we also noticed that EGFR is regulated by HPV E7 protein and hsa-miR-944. Moreover, while phosphorylated EGFR is associated with a worse prognosis, EGFR total express level is not significantly correlated with prognosis. This indicates that EGFR activation will induce a worse outcome in HPV+ cancer patients. Further enrichment analysis showed that EGFR downstream pathway and cancer relative pathway are diversely activated in HPV+ cancer and HPV− cancer. In summary, HPV E7 protein downregulates EGFR that downregulates phosphorylated EGFR and inhibit EGFR related pathways which in turn and consequently induce better prognosis. Importance: Although HPV infection has been studied in various cancer types, there are only limited studies that have focused on the common effect of HPV related cancer. Consequently, this study focused on CESC and HNSC, two cancer types with high HPV infection proportion in cohort, thereby, intending to dig out the common effects and mechanisms of HPV+ cancers. Unlike some virus-human interaction prediction studies, the P-HIPSter database provides virus-human protein interaction based on protein structure prediction. Through this data, our interaction network was able to uncover previously unnoticed protein interactions. Our finding revealed that HPV infection caused various gene expression differences, and a great amount of which interact with EGFR, a cancer related gene. Therefore, since EGFR is associated with HPV+ cancer patients’ survival, some FDA proved EGFR inhibitors would be potential anti-HPV drugs.