LncRNA polymorphisms and breast cancer risk

Abdi, Esmat; Latifi‐Navid, Saeid; Latifi-Navid, Hamid

doi:10.1016/j.prp.2021.153729

Cited by 16 publications

(10 citation statements)

References 62 publications

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“…The significance of long noncoding RNAs (lncRNAs) in EC is increasingly recognized. LncRNA transcripts, consisting of over 200 nucleotides, are involved in various biological processes, including tumor cell apoptosis, cell cycle regulation, migration, differentiation, and proliferation [25]. Importantly, aberrant expression of certain lncRNAs has been observed in EC tissues compared to normal endometrial tissues.…”

Section: Discussionmentioning

confidence: 99%

Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial Cancer

Zhang,

Wang,

et al. 2024

IJCEMR

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Background: Recently, a novel form of cell death called disulfidptosis was identified. It is characterized by rapid cell death caused by disulfide stress resulting from excessive cystine accumulation within cells. Disulfidptosis holds promise as a potential target for intervention in tumor treatment. However, the roles and prognostic value of disulfidptosis-related lncRNAs (DRLs) in EC remain largely unknown. Therefore, the objective of this study is to develop a prediction model based on DRLs to forecast the prognosis and assess the immunotherapy response in EC patients, as well as identify potential chemotherapy drugs for treatment. Methods: We constructed a model by screening DRLs associated with EC prognosis through bioinformatics methods and validated it. Furthermore, enrichment analysis was conducted to explore functional differences between different risk populations. Additionally, we examined the associations between the risk score and tumor mutational burden (TMB), tumor microenvironment (TME), tumor immune dysfunction and exclusion (TIDE), and drug sensitivity. Finally, we validated this using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results: We identified 8 DRLs (Z69733.1, AL158071.4, AC022960.1 AC005034.2, AC003086.1, AC024230.1, AL499602.1, RAB11B-AS1) and constructed a robust risk model. Further analysis revealed that the low-risk group had superior overall survival (OS), immunotherapy response, and drug sensitivity compared to the high-risk group. Conclusion: Our risk model provides an accurate prediction of prognosis and immunotherapy response in EC patients, offering significant clinical implications and novel insights for clinicians in the treatment of EC.

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Section: Discussionmentioning

confidence: 99%

Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial Cancer

Zhang,

Wang,

et al. 2024

IJCEMR

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“…Values of both mRNAs and lncRNAs were clustered simultaneously according to their expression trajectories across the time points using fuzzy c-means clustering implemented in the e1071 (v1. [7][8][9][10][11][12][13] [63] R package. Helper functions [64] were used to define optimal hyper-parameters.…”

Section: Differential Expression and Expression Variation Analysismentioning

confidence: 99%

“…The diversity of mechanisms by which lncRNAs can function is mirrored by the number of biological processes in which they intervene. In humans, many lncRNAs are differentially expressed in cancerous tissues, indicating their importance for DNA damage repair, genome stability and the regulation of autophagy [7][8][9]. A notable example is MALAT1 with an unusual up-regulation in cancer cells serving as a robust biomarker for several types of cancer including in breast and lung tissue [10,11].…”

Section: Introductionmentioning

confidence: 99%

The expression landscape and pangenome of long non-coding RNA in the fungal wheat pathogen Zymoseptoria tritici

Glad,

Tralamazza,

Croll

2023

Microbial Genomics

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Long non-coding RNAs (lncRNAs) are regulatory molecules interacting in a wide array of biological processes. lncRNAs in fungal pathogens can be responsive to stress and play roles in regulating growth and nutrient acquisition. Recent evidence suggests that lncRNAs may also play roles in virulence, such as regulating pathogenicity-associated enzymes and on-host reproductive cycles. Despite the importance of lncRNAs, only a few model fungi have well-documented inventories of lncRNA. In this study, we apply a recent computational pipeline to predict high-confidence lncRNA candidates in Zymoseptoria tritici, an important global pathogen of wheat impacting global food production. We analyse genomic features of lncRNAs and the most likely associated processes through analyses of expression over a host infection cycle. We find that lncRNAs are frequently expressed during early infection, before the switch to necrotrophic growth. They are mostly located in facultative heterochromatic regions, which are known to contain many genes associated with pathogenicity. Furthermore, we find that lncRNAs are frequently co-expressed with genes that may be involved in responding to host defence signals, such as oxidative stress. Finally, we assess pangenome features of lncRNAs using four additional reference-quality genomes. We find evidence that the repertoire of expressed lncRNAs varies substantially between individuals, even though lncRNA loci tend to be shared at the genomic level. Overall, this study provides a repertoire and putative functions of lncRNAs in Z. tritici enabling future molecular genetics and functional analyses in an important pathogen.

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“…and many others. Polymorphisms associated with a higher rate of BC were also identified in miRNA and lncRNAs [ 84 , 85 ]. Importantly, increased risk for BC is associated with SNPs (single nucleotide polymorphisms) in virtually all DNA repair mechanisms after genotoxic damage [ 86 ].…”

Section: Novel Specific Molecular Biomarkers In Current Use and Futur...mentioning

confidence: 99%

Classic and New Markers in Diagnostics and Classification of Breast Cancer

Benacka

Szabóová

Guľašová

et al. 2022

Cancers

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Breast cancer remains the most frequently diagnosed form of female’s cancer, and in recent years it has become the most common cause of cancer death in women worldwide. Like many other tumours, breast cancer is a histologically and biologically heterogeneous disease. In recent years, considerable progress has been made in diagnosis, subtyping, and complex treatment of breast cancer with the aim of providing best suited tumour-specific personalized therapy. Traditional methods for breast cancer diagnosis include mammography, MRI, biopsy and histological analysis of tumour tissue in order to determine classical markers such as estrogen and progesterone receptors (ER, PR), cytokeratins (CK5/6, CK14, C19), proliferation index (Ki67) and human epidermal growth factor type 2 receptor (HER2). In recent years, these methods have been supplemented by modern molecular methodologies such as next-generation sequencing, microRNA, in situ hybridization, and RT-qPCR to identify novel molecular biomarkers. MicroRNAs (miR-10b, miR-125b, miR145, miR-21, miR-155, mir-30, let-7, miR-25-3p), altered DNA methylation and mutations of specific genes (p16, BRCA1, RASSF1A, APC, GSTP1), circular RNA (hsa_circ_0072309, hsa_circRNA_0001785), circulating DNA and tumour cells, altered levels of specific proteins (apolipoprotein C-I), lipids, gene polymorphisms or nanoparticle enhanced imaging, all these are promising diagnostic and prognostic tools to disclose any specific features from the multifaceted nature of breast cancer to prepare best suited individualized therapy.

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LncRNA polymorphisms and breast cancer risk

Cited by 16 publications

References 62 publications

Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial Cancer

Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial Cancer

The expression landscape and pangenome of long non-coding RNA in the fungal wheat pathogen Zymoseptoria tritici

Classic and New Markers in Diagnostics and Classification of Breast Cancer

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