SNORA71B promotes breast cancer cells across blood–brain barrier by inducing epithelial-mesenchymal transition

Duan, Sijia; Luo, Xuliang; Zeng, Huihui; Zhan, Xiang; Cheng, Yuan

doi:10.1007/s12282-020-01111-1

Cited by 11 publications

(10 citation statements)

References 38 publications

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“…And amongst the top rhythmic snoRNAs are included families with switches across the tissues we considered (3/20 (50% of the snoRNAs) top rhythmic transcripts are snoRNAs (SNORA14B, SNORD115–1 and SNORA71B) from families with switches), suggesting families with capacity for variation in the abundance of members could be used by the cell in processes including the regulation of diurnal rhythms. Interestingly, from these three snoRNAs, SNORD115 members were shown to be involved in the alternative splicing of the serotonin receptor 2C gene [ 56 ] while SNORA71B was shown to promote proliferation, migration and invasion of breast cancer cells [ 57 ]. From that perspective, it is not impossible that switches in expression of family members could be used to modulate the efficiency of non-canonical functions of snoRNAs, while maintaining canonical functions.…”

Section: Discussionmentioning

confidence: 99%

SnoRNA copy regulation affects family size, genomic location and family abundance levels

et al. 2021

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Background Small nucleolar RNAs (snoRNAs) are an abundant class of noncoding RNAs present in all eukaryotes and best known for their involvement in ribosome biogenesis. In mammalian genomes, many snoRNAs exist in multiple copies, resulting from recombination and retrotransposition from an ancestral snoRNA. To gain insight into snoRNA copy regulation, we used Rfam classification and normal human tissue expression datasets generated using low structure bias RNA-seq to characterize snoRNA families. Results We found that although box H/ACA families are on average larger than box C/D families, the number of expressed members is similar for both types. Family members can cover a wide range of average abundance values, but importantly, expression variability of individual members of a family is preferred over the total variability of the family, especially for box H/ACA snoRNAs, suggesting that while members are likely differentially regulated, mechanisms exist to ensure uniformity of the total family abundance across tissues. Box C/D snoRNA family members are mostly embedded in the same host gene while box H/ACA family members tend to be encoded in more than one different host, supporting a model in which box C/D snoRNA duplication occurred mostly by cis recombination while box H/ACA snoRNA families have gained copy members through retrotransposition. And unexpectedly, snoRNAs encoded in the same host gene can be regulated independently, as some snoRNAs within the same family vary in abundance in a divergent way between tissues. Conclusions SnoRNA copy regulation affects family sizes, genomic location of the members and controls simultaneously member and total family abundance to respond to the needs of individual tissues.

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Section: Discussionmentioning

confidence: 99%

SnoRNA copy regulation affects family size, genomic location and family abundance levels

et al. 2021

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“…They can separate from the primary tumour and enter the nearby blood and lymphatic vessels, and then reach the parenchymal tissue to form small cancer cell nodules 47. Accumulating studies show that some sncRNAs can functionally regulate the metastatic ability of cancer cells 64–68. In gastric cancer, tRF-3017A from tRNA-Val-TAC negatively regulates the expression of tumour suppressor gene NELL2 by forming RNA-induced silencing complex with AGO2, so as to enhance the migration and invasion of gastric cancer cells 69.…”

Section: Biological Function Of Sncrnas In Cancermentioning

confidence: 99%

“…Increasing studies have shown the sncRNAs have great potential as a biomarker platform for tumour prognosis 62 65 67 92–95. Gao et al , through univariate COX regression analysis, showed that six snoRNAs (snoRA47, snoRA68, snoRA78, snoRA21, snoRD28 and snoRD66) are highly expressed and are associated with a lower overall survival rate in patients with non-small cell lung cancer 94.…”

Section: Clinical Significance Of Sncrnas In Cancermentioning

confidence: 99%

Disorders and roles of tsRNA, snoRNA, snRNA and piRNA in cancer

Xiao

Wang

et al. 2022

J Med Genet

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Most small non-coding RNAs (sncRNAs) with regulatory functions are encoded by majority sequences in the human genome, and the emergence of high-throughput sequencing technology has greatly expanded our understanding of sncRNAs. sncRNAs are composed of a variety of RNAs, including tRNA-derived small RNA (tsRNA), small nucleolar RNA (snoRNA), small nuclear RNA (snRNA), PIWI-interacting RNA (piRNA), etc. While for some, sncRNAs’ implication in several pathologies is now well established, the potential involvement of tsRNA, snoRNA, snRNA and piRNA in human diseases is only beginning to emerge. Recently, accumulating pieces of evidence demonstrate that tsRNA, snoRNA, snRNA and piRNA play an important role in many biological processes, and their dysregulation is closely related to the progression of cancer. Abnormal expression of tsRNA, snoRNA, snRNA and piRNA participates in the occurrence and development of tumours through different mechanisms, such as transcriptional inhibition and post-transcriptional regulation. In this review, we describe the research progress in the classification, biogenesis and biological function of tsRNA, snoRNA, snRNA and piRNA. Moreover, we emphasised their dysregulation and mechanism of action in cancer and discussed their potential as diagnostic and prognostic biomarkers or therapeutic targets.

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“…Cell adhesion molecule 2 (CADM2) induces BM by activating the EMT pathway in NSCLC [11]. SNORA71B, a type of SnoRNA, promotes the migration of breast cancer cells across the blood-brain barrier by activating the EMT pathway [12]. According to a previous study, the inhibition of EMT by cucurbitacin B, an HER2 target therapeutic substance, results in the inhibition of BM in breast cancer cells [13].…”

Section: Introductionmentioning

confidence: 99%

Tumor Nonimmune-Microenvironment-Related Gene Expression Signature Predicts Brain Metastasis in Lung Adenocarcinoma Patients after Surgery: A Machine Learning Approach Using Gene Expression Profiling

Haam

Han

Lee

et al. 2021

Cancers

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Using a machine learning approach with a gene expression profile, we discovered a tumor nonimmune-microenvironment-related gene expression signature, including extracellular matrix (ECM) remodeling, epithelial–mesenchymal transition (EMT), and angiogenesis, that could predict brain metastasis (BM) after the surgical resection of 64 lung adenocarcinomas (LUAD). Gene expression profiling identified a tumor nonimmune-microenvironment-related 17-gene expression signature that significantly correlated with BM. Of the 17 genes, 11 were ECM-remodeling-related genes. The 17-gene expression signature showed high BM predictive power in four machine learning classifiers (areas under the receiver operating characteristic curve = 0.845 for naïve Bayes, 0.849 for support vector machine, 0.858 for random forest, and 0.839 for neural network). Subgroup analysis revealed that the BM predictive power of the 17-gene signature was higher in the early-stage LUAD than in the late-stage LUAD. Pathway enrichment analysis showed that the upregulated differentially expressed genes were mainly enriched in the ECM–receptor interaction pathway. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. The tumor nonimmune-microenvironment-related gene expression signatures found in this study are important biological markers that can predict BM and provide patient-specific treatment options.

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SNORA71B promotes breast cancer cells across blood–brain barrier by inducing epithelial-mesenchymal transition

Cited by 11 publications

References 38 publications

SnoRNA copy regulation affects family size, genomic location and family abundance levels

SnoRNA copy regulation affects family size, genomic location and family abundance levels

Disorders and roles of tsRNA, snoRNA, snRNA and piRNA in cancer

Tumor Nonimmune-Microenvironment-Related Gene Expression Signature Predicts Brain Metastasis in Lung Adenocarcinoma Patients after Surgery: A Machine Learning Approach Using Gene Expression Profiling

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