Lysophosphatidic acid receptor 6 regulated by miR-27a-3p attenuates tumor proliferation in breast cancer
TL;DR: In this paper, the LPA receptor 6 (LPAR6) has been reported to have diverse effects in multiple cancers, including breast cancer, its effects and functioning mechanisms are not fully known.
Abstract: Lysophosphatidic acid (LPA) is a bioactive molecule which participates in many physical and pathological processes. Although LPA receptor 6 (LPAR6), the last identified LPA receptor, has been reported to have diverse effects in multiple cancers, including breast cancer, its effects and functioning mechanisms are not fully known. Multiple public databases were used to investigate the mRNA expression of LPAR6, its prognostic value, and potential mechanisms in breast cancer. Western blotting was performed to validate the differential expression of LPAR6 in breast cancer tissues and their adjacent tissues. Furthermore, in vitro experiments were used to explore the effects of LPAR6 on breast cancer. Additionally, TargetScan and miRWalk were used to identify potential upstream regulating miRNAs and validated the relationship between miR-27a-3p and LPAR6 via real-time polymerase chain reaction and an in vitro rescue assay. LPAR6 was significantly downregulated in breast cancer at transcriptional and translational levels. Decreased LPAR6 expression in breast cancer is significantly correlated with poor overall survival, disease-free survival, and distal metastasis-free survival, particularly for hormone receptor-positive patients, regardless of lymph node metastatic status. In vitro gain and loss-of-function assays indicated that LPAR6 attenuated breast cancer cell proliferation. The analyses of TCGA and METABRIC datasets revealed that LPAR6 may regulate the cell cycle signal pathway. Furthermore, the expression of LPAR6 could be positively regulated by miR-27a-3p. The knockdown of miR-27a-3p increased cell proliferation, and ectopic expression of LPAR6 could partly rescue this phenotype. LPAR6 acts as a tumor suppressor in breast cancer and is positively regulated by miR-27a-3p.
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TL;DR: In this paper , the prognosis of E2F transcription factors was determined in four independent pediatric neuroblastoma cohorts from Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO) and European ArrayExpres datasets using Kaplan-Meier and cox regression analysis.
Abstract: Abstract Background Previously, we had analyzed the prognosis of E2F transcription factors across adult tumor types. However, the expressions and prognosis of E2F transcription factors in pediatric neuroblastoma have not yet been fully studied. Methods The prognosis of E2F transcription factors was determined in four independent pediatric neuroblastoma cohorts from Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO) and European ArrayExpres datasets using Kaplan–Meier and cox regression analysis. Results E2F regulated gene set was associated with the event free survival and the overall survival of neuroblastoma. E2F1 and E2F3 were prognostic factors in all four independent pediatric neuroblastoma cohorts. Over-expressions of E2F1 or E2F3 were correlated with the shorted event free survival and overall survival of neuroblastoma. Expression levels of E2F1 and E2F3 were higher in neuroblastoma patients with MYCN amplification or age at diagnosis ≥ 18 months. Moreover, the prognostic significance of E2F1 or E2F3 in neuroblastoma was independent of MYCN amplification and age of diagnosis. Combinations of E2F1 , E2F3 with MYCN amplification or age of diagnosis achieved better prognosis of neuroblastoma. Identification of 234 genes were associated with E2F1 and E2F3 expressions in neuroblastoma and those genes were significantly enriched in cell cycle signaling pathway. Also, higher scores of cell cycle signaling pathway were correlated with the adverse prognosis of neuroblastoma. Conclusions E2F transcription factors E2F1 and E2F3 were prognostic makers of neuroblastoma.
4 citations
02 Sep 2022
TL;DR: In this article , the authors focus on the interactions between neurons and components of the gastrointestinal tract and tumour microenvironment, on the neural signalling pathways involved, and how these factors affect the cancer hallmarks, and discuss the neural signatures in gastrointestinal cancers.
Abstract: Maintenance of gastrointestinal health is challenging as it requires balancing multifaceted processes within the highly complex and dynamic ecosystem of the gastrointestinal tract. Disturbances within this vibrant environment can have detrimental consequences, including the onset of gastrointestinal cancers. Globally, gastrointestinal cancers account for ~19% of all cancer cases and ~22.5% of all cancer-related deaths. Developing new ways to more readily detect and more efficiently target these malignancies are urgently needed. Whereas members of the tumour microenvironment, such as immune cells and fibroblasts, have already been in the spotlight as key players of cancer initiation and progression, the importance of the nervous system in gastrointestinal cancers has only been highlighted in the past few years. Although extrinsic innervations modulate gastrointestinal cancers, cells and signals from the gut's intrinsic innervation also have the ability to do so. Here, we shed light on this thriving field and discuss neural influences during gastrointestinal carcinogenesis. We focus on the interactions between neurons and components of the gastrointestinal tract and tumour microenvironment, on the neural signalling pathways involved, and how these factors affect the cancer hallmarks, and discuss the neural signatures in gastrointestinal cancers. Finally, we highlight neural-related therapies that have potential for the management of gastrointestinal cancers.
4 citations
TL;DR: It is found that ADCY 6 is expressed at low levels in breast cancer and leads to increases in the proliferation, invasion and migration of breast cancer cells, and bioinformatics analysis showed that TET1 is regulated by miR-27a-3p and regulates the methylation of ADCY6 to affect the EMT process of breastcancer cells, thereby affecting the malignant biological behaviour of breast cancers.
Abstract: Introduction Adenylyl cyclase isoform 6 (ADCY6) is a member of membrane-bound adenylate cyclase family that converts adenosine triphosphate (ATP) into cAMP and pyrophosphate. An increasing number of researchers have studied the role of ADCY6 in cancer. However, its specific role in breast cancer remains unknown. Methods Bioinformatics and clinical data were used to analyse the expression of ADCY6 in breast cancer. ADCY6 DNA methylation was analysed using DNA methylation-specific PCR and Bisulfite Sanger sequencing. Using lentiviral stable miRNA transfection together with cell biology functional assays and gene expression/target analysis, we investigated the interaction between miR-27a-3p, TET1 and ADCY6 in breast cancer. Results We found that ADCY6 is expressed at low levels in breast cancer and leads to increases in the proliferation, invasion and migration of breast cancer cells. The low expression of ADCY6 is due to the lower demethylation of ten-eleven translocation methylcytosine dioxygenase 1 (TET1), and the methylation of ADCY6 can be altered by TET1. More importantly, bioinformatics analysis showed that TET1 is regulated by miR-27a-3p and regulates the methylation of ADCY6 to affect the EMT process of breast cancer cells, thereby affecting the malignant biological behaviour of breast cancer. Conclusions Our study demonstrates that the methylation modification of ADCY6 is regulated by TET1 and leads to ADCY6 activation. miR-27a-3p negatively regulates the expression of TET1 and affects the EMT process of breast cancer through ADCY6, thereby promoting the malignant biological behaviour of breast cancer. Our results may provide new research ideas and directions for DNA methylation and EMT changes in breast cancer.
3 citations
TL;DR: In this paper , the authors investigated the association between the selected gene variants by predicting them as possible target genes and concluded that a strong association was reported between the PI3K-AKT signaling pathway genes and KLF 14-AA, MDM4-GA, miR27a-GG and miR-196a-CT gene variants.
Abstract: Simple Summary The genomic landscape of breast cancer (BC) is complex. Previous research studies have not extensively elucidated the correlation of genotypes and allele variations of the PI3K, AKT-1, KLF-14, MDM4 and miRNAs 27a, miR-196a genes with the predisposition of Breast cancer in Saudi Arabia. Therefore, to cover this area of research, we conducted a case-control study on 230 subjects (115 cases and 115 controls). Genotyping was studied by using the ARMS-PCR and results were confirmed by Sanger sequencing. The novel and known gene variants were studied by Whole-exome sequencing using Illumina NovaSeq 6000 platform. Strong association was reported between the PI3K-AKT signaling pathway genes and KLF 14-AA, MDM4-GA, miR27a-GG and miR-196a-CT gene variants with the breast cancer susceptibility and progression. The results could help to classify and identify those at risk for Breast cancer in the future. WES for provide insight toward disease mechanisms for the development of more effective therapies. Abstract Genome-wide association studies have reported link between SNPs and risk of breast cancer. This study investigated the association of the selected gene variants by predicting them as possible target genes. Molecular technique advances with the availability of whole-exome sequencing (WES), now offer opportunities for simultaneous investigations of many genes. The experimental protocol for PI3K, AKT-1, KLF-14, MDM4, miRNAs 27a, and miR-196a genotyping was done by ARMS-PCR and sanger sequencing. The novel and known gene variants were studied by Whole-exome sequencing using Illumina NovaSeq 6000 platform. This case control study reports significant association between BC patients, healthy controls with the polymorphic variants of PI3K C > T, AKT-1 G > A KLF 14 C > T, MDM4 A > G, miR-27a A > G, miR-196a-2 C > T genes (p < 0.05). MDM4 A > G genotypes were strongly associated with BC predisposition with OR 2.08 & 2.15, p < 0.05) in codominant and dominant models respectively. MDM4 A allele show the same effective (OR1.76, p < 0.05) whereas it remains protective in recessive model for BC risk. AKT1G > A genotypes were strongly associated with the BC susceptibility in all genetic models whereas PI3K C > T genotypes were associated with breast cancer predisposition in recessive model OR 6.96. Polymorphic variants of KLF-14 A > G, MDM4G > A, MiR-27aA >G, miR-196a-C > T were strongly associated with stage, tamoxifen treatment. Risk variants have been reported by whole exome sequencing in our BC patients. It was concluded that a strong association between the PI3K-AKT signaling pathway gene variants with the breast cancer susceptibility and progression. Similarly, KLF 14-AA, MDM4-GA, miR27a-GG and miR-196a-CT gene variants were associated with the higher risk probability of BC and were strongly correlated with staging of the BC patients. This study also reported Low, novel, and intermediate-genetic-risk variants of PI3K, AKT-1, MDM4G & KLF-14 by utilizing whole-exome sequencing. These variants should be further investigated in larger cohorts’ studies.
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TL;DR: An R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters and can be easily extended to other species and ontologies is presented.
Abstract: Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters The analysis module and visualization module were combined into a reusable workflow Currently, clusterProfiler supports three species, including humans, mice, and yeast Methods provided in this package can be easily extended to other species and ontologies The clusterProfiler package is released under Artistic-20 License within Bioconductor project The source code and vignette are freely available at http://bioconductororg/packages/release/bioc/html/clusterProfilerhtml
16,644 citations
TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
10,947 citations
TL;DR: In the United States, the cancer death rate has dropped continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment as mentioned in this paper.
Abstract: Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2017) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2018) were collected by the National Center for Health Statistics. In 2021, 1,898,160 new cancer cases and 608,570 cancer deaths are projected to occur in the United States. After increasing for most of the 20th century, the cancer death rate has fallen continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment. This translates to 3.2 million fewer cancer deaths than would have occurred if peak rates had persisted. Long-term declines in mortality for the 4 leading cancers have halted for prostate cancer and slowed for breast and colorectal cancers, but accelerated for lung cancer, which accounted for almost one-half of the total mortality decline from 2014 to 2018. The pace of the annual decline in lung cancer mortality doubled from 3.1% during 2009 through 2013 to 5.5% during 2014 through 2018 in men, from 1.8% to 4.4% in women, and from 2.4% to 5% overall. This trend coincides with steady declines in incidence (2.2%-2.3%) but rapid gains in survival specifically for nonsmall cell lung cancer (NSCLC). For example, NSCLC 2-year relative survival increased from 34% for persons diagnosed during 2009 through 2010 to 42% during 2015 through 2016, including absolute increases of 5% to 6% for every stage of diagnosis; survival for small cell lung cancer remained at 14% to 15%. Improved treatment accelerated progress against lung cancer and drove a record drop in overall cancer mortality, despite slowing momentum for other common cancers.
9,661 citations
TL;DR: It is shown that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical.
Abstract: Proteins are built by using the information contained in molecules of messenger RNA (mRNA). Cells have several ways of controlling the amounts of different proteins they make. For example, a so-called ‘microRNA’ molecule can bind to an mRNA molecule to cause it to be more rapidly degraded and less efficiently used, thereby reducing the amount of protein built from that mRNA. Indeed, microRNAs are thought to help control the amount of protein made from most human genes, and biologists are working to predict the amount of control imparted by each microRNA on each of its mRNA targets. All RNA molecules are made up of a sequence of bases, each commonly known by a single letter—‘A’, ‘U’, ‘C’ or ‘G’. These bases can each pair up with one specific other base—‘A’ pairs with ‘U’, and ‘C’ pairs with ‘G’. To direct the repression of an mRNA molecule, a region of the microRNA known as a ‘seed’ binds to a complementary sequence in the target mRNA. ‘Canonical sites’ are regions in the mRNA that contain the exact sequence of partner bases for the bases in the microRNA seed. Some canonical sites are more effective at mRNA control than others. ‘Non-canonical sites’ also exist in which the pairing between the microRNA seed and mRNA does not completely match. Previous work has suggested that many non-canonical sites can also control mRNA degradation and usage. Agarwal et al. first used large experimental datasets from many sources to investigate microRNA activity in more detail. As expected, when mRNAs had canonical sites that matched the microRNA, mRNA levels and usage tended to drop. However, no effect was observed when the mRNAs only had recently identified non-canonical sites. This suggests that microRNAs primarily bind to canonical sites to control protein production. Based on these results, Agarwal et al. further developed a statistical model that predicts the effects of microRNAs binding to canonical sites. The updated model considers 14 different features of the microRNA, microRNA site, or mRNA—including the mRNA sequence around the site—to predict which sites within mRNAs are most effectively targeted by microRNAs. Tests showed that Agarwal et al.'s model was as good as experimental approaches at identifying the effective target sites, and was better than existing computational models. The model has been used to power the latest version of a freely available resource called TargetScan, and so could prove a valuable resource for researchers investigating the many important roles of microRNAs in controlling protein production.
5,365 citations
TL;DR: UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data, serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers.
3,546 citations