Recent reports showed that haematological and neurological expressed 1-like (HN1L) gene participated in tumorigenesis and tumour invasion. However, the expression and role of HN1L in breast cancer remain to be investigated. Here, bioinformatics, western blot and immunohistochemistry were used to detect the expression of HN1L in breast cancer. Wound healing, transwell assay, immunofluorescence assay and mass spectrum were used to explore the role and mechanism of HN1L on the migration and invasion of breast cancer, which was confirmed in vivo using a nude mice model. Results showed that HN1L was significantly over-expressed in breast cancer tissues, which was positively correlated with M metastasis of breast cancer patients. Silencing HN1L significantly inhibited the invasion and metastasis of breast cancer cells in vitro and lung metastasis in nude mice metastasis model of breast cancer. Mechanistically, HN1L interacted with HSPA9 and affected the expression of HMGB1, playing a key role in promoting the invasion and metastasis of breast cancer cell. These results suggested that HN1L was an appealing drug target for breast cancer. 相似文献
The ADP-ribosylation factor-like proteins (ARLs) have been proved to regulate the malignant phenotypes of several cancers. However, the exact role of ARLs in gastric cancer (GC) remains elusive. In this study, we systematically investigate the expression status, interactive relations, potential pathways, genetic variations and clinical values of ARLs in GC. We find that ARLs are significantly dysregulated in GC and involved in various cancer-related pathways. Subsequently, machine learning models identify ARL4C as one of the two most significant clinical indicators among ARLs for GC. Furthermore, ARL4C silencing remarkably inhibits the growth and metastasis of GC cells both in vitro and in vivo. Moreover, enrichment analysis indicates that ARL4C is highly correlated with TGF-β1 signalling. Correspondingly, TGF-β1 treatment dramatically increases ARL4C expression and ARL4C knockdown inhibits the phosphorylation level of Smads, downstream factors of TGF-β1. Meanwhile, the coexpression of ARL4C and TGF-β1 worsens the prognosis of GC patients. Our work comprehensively demonstrates the crucial role of ARLs in the carcinogenesis of GC and the specific mechanisms underlying the GC-promoting effects of TGF-β1. More importantly, we uncover the great promise of ARL4C-targeted therapy in improving the efficacy of TGF-β1 inhibitors for GC patients. 相似文献
Long non-coding RNA (lncRNA) represents a new direction to identify expression profiles and regulatory mechanisms in various organisms. Here, we report the first dataset of lncRNAs of the golden snub-nosed monkey (GSM), including 12,557 putative lncRNAs identified from seven organs. Compared with mRNA, GSM lncRNA had fewer exons and isoforms, and longer length. LncRNA showed more obvious tissue-specific expression than mRNA. However, for the top ten most abundant genes in each organ, mRNAs expression was more tissue-specific than lncRNAs. By identification of specifically expressed lncRNAs and mRNAs in each organ, it indicates that the expression of SEG-lncRNA (specifically expressed lncRNA) and SEG-mRNA (specifically expressed mRNA) had high correlation. In particular, combined our lncRNA and mRNA data, we identified 92 heart SEG-lncRNAs targeted ten mRNA genes in the oxidative phosphorylation pathway and upregulated the expression of these target genes such as ND4, ATP6, and ATP8. These may contribute to GSM adaption to its high-elevation environment. We also identified 171 liver SEG-lncRNAs, which targeted 27 genes associated with the metabolism of xenobiotics and leaded to high expression of these target genes in liver. These lncRNAs may play important roles in GSM adaptation to a folivory diet.
We propose a dynamically tunable surface plasmon polaritons (SPPs) waveguide system based on bulk Dirac semimetals (BDS) containing only a side-coupled T-shaped cavity. Plasmon-induced transparency (PIT) is achieved in the terahertz band by introducing a position offset. We have analytically investigated the spectral characteristics of PIT in this system, indicating that the larger the position offset, the higher the peak of the PIT window. The spectrum responses of PIT system can be flexibly regulated via transforming the geometric parameters of the structure. At the same time, it is particularly sensitive to the refractive index of the surrounding medium, which is promising for sensing devices. In addition, the resonance frequency and peak transmission can be actively adjusted by controlling the Fermi energy of the BDS without reconstructing the geometric structure. Moreover, the optical delay time near the PIT peak reaches 11.001 ps, which has good slow-light characteristics and is a candidate in the field of slow-light equipment. The structure we designed may have potential application value in the design of SPPs light-guide devices.
BackgroundMachine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.MethodsWe retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.ResultsThis study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.ConclusionML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies. 相似文献
The 37-kDa laminin receptor precursor/67-kDa laminin receptor (LRP/LR, also known as ribosomal protein SA, RPSA) has been reported to be involved in cancer development and prion internalization. Previous studies have shown that the LRP/LR is expressed in a wide variety of tissues. In particular, expression of LRP/LR mRNA may be closely related to the degree of PrPSc propagation. This study presents a detailed investigation of the LRP/LR mRNA expression levels in eleven normal ovine tissues. Using real-time quantitative PCR, the highest LRP/LR expression was found in neocortex (p < 0.05). Slightly lower levels were found in the heart and obex. Intermediate levels were seen in hippocampus, cerebellum, spleen, thalamus, mesenteric lymph node, and the lowest levels were present in liver, kidney, and lung. In general, the LRP/LR mRNA levels were much higher in neuronal tissues than in peripheral tissues. The observation that differences in LRP/LR mRNA expression levels are consistent with the corresponding variation in PrPSc accumulation suggests that the 37-kDa/67-kDa laminin receptor may be involved in the regulation of PrPSc propagation. 相似文献