AI Article Synopsis

  • Breast cancer is a complex disease with varying genomic and transcriptomic profiles, making it the second leading cause of cancer death in women.
  • This study focuses on long non-coding RNAs (lncRNAs) in breast cancer, analyzing samples from 26 tumors and 5 normal tissues to identify over 19,000 regions with significant expression differences, half of which were non-coding.
  • The research highlighted the structural characteristics of lncRNAs, revealing their presence in various genomic locations and suggesting a regulatory role in tumorigenesis and the expression of nearby protein-coding genes.

Article Abstract

Breast cancer, the second leading cause of cancer death in women, is a highly heterogeneous disease, characterized by distinct genomic and transcriptomic profiles. Transcriptome analyses prevalently assessed protein-coding genes; however, the majority of the mammalian genome is expressed in numerous non-coding transcripts. Emerging evidence supports that many of these non-coding RNAs are specifically expressed during development, tumorigenesis, and metastasis. The focus of this study was to investigate the expression features and molecular characteristics of long non-coding RNAs (lncRNAs) in breast cancer. We investigated 26 breast tumor and 5 normal tissue samples utilizing a custom expression microarray enclosing probes for mRNAs as well as novel and previously identified lncRNAs. We identified more than 19,000 unique regions significantly differentially expressed between normal versus breast tumor tissue, half of these regions were non-coding without any evidence for functional open reading frames or sequence similarity to known proteins. The identified non-coding regions were primarily located in introns (53%) or in the intergenic space (33%), frequently orientated in antisense-direction of protein-coding genes (14%), and commonly distributed at promoter-, transcription factor binding-, or enhancer-sites. Analyzing the most diverse mRNA breast cancer subtypes Basal-like versus Luminal A and B resulted in 3,025 significantly differentially expressed unique loci, including 682 (23%) for non-coding transcripts. A notable number of differentially expressed protein-coding genes displayed non-synonymous expression changes compared to their nearest differentially expressed lncRNA, including an antisense lncRNA strongly anticorrelated to the mRNA coding for histone deacetylase 3 (HDAC3), which was investigated in more detail. Previously identified chromatin-associated lncRNAs (CARs) were predominantly downregulated in breast tumor samples, including CARs located in the protein-coding genes for CALD1, FTX, and HNRNPH1. In conclusion, a number of differentially expressed lncRNAs have been identified with relation to cancer-related protein-coding genes.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4180073PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0106076PLOS

Publication Analysis

Top Keywords

differentially expressed
24
protein-coding genes
24
breast tumor
16
non-coding rnas
12
breast cancer
12
long non-coding
8
expressed
8
expressed normal
8
normal versus
8
breast
8

Similar Publications

Background: Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.

Aim: In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).

Methods And Results: Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes.

View Article and Find Full Text PDF

The study by Cao aimed to identify early second-trimester biomarkers that could predict gestational diabetes mellitus (GDM) development using advanced proteomic techniques, such as Isobaric tags for relative and absolute quantitation isobaric tags for relative and absolute quantitation and liquid chromatography-mass spectrometry liquid chromatography-mass spectrometry. Their analysis revealed 47 differentially expressed proteins in the GDM group, with retinol-binding protein 4 and angiopoietin-like 8 showing significantly elevated serum levels compared to controls. Although these findings are promising, the study is limited by its small sample size ( = 4 per group) and lacks essential details on the reproducibility and reliability of the protein quantification methods used.

View Article and Find Full Text PDF

Oil palm () yield is impacted by abiotic stresses, leading to significant economic losses. To understand the core abiotic stress transcriptome (CAST) of oil palm, we performed RNA-Seq analyses of oil palm leaves subjected to drought, salinity, waterlogging, heat, and cold stresses. A total of 19,834 differentially expressed genes (DEGs) were identified.

View Article and Find Full Text PDF

Glaucoma is a leading cause of irreversible blindness, often associated with elevated intraocular pressure (IOP) due to trabecular meshwork (TM) dysfunction. Diabetes mellitus (DM) is recognized as a significant risk factor for glaucoma; however, the molecular mechanisms through which hyperglycemia affects TM function remain unclear. This study investigated the impact of high glucose on gene expression in human TM (HTM) cells to uncover pathways that contribute to TM dysfunction and glaucoma pathogenesis under diabetic conditions.

View Article and Find Full Text PDF

Long non-coding RNAs (lncRNAs) and RNA N⁶-methyladenosine (m A) have been linked to leukemia drug resistance. However, whether and how lncRNAs and m A coordinately regulate resistance remain elusive. Here, we show that many differentially expressed lncRNAs enrich m A, and more lncRNAs tend to have higher m A content in CML cells resistant to tyrosine kinase inhibitors (TKIs).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!