scholarly journals Analysis of subtype-specific and common Gene/MiRNA expression profiles of four main breast cancer subtypes using bioinformatic approach; Characterization of four genes, and two MicroRNAs with possible diagnostic and prognostic values

2020 ◽  
Vol 20 ◽  
pp. 100425
Author(s):  
Amir Mehrgou ◽  
Shima Ebadollahi ◽  
Behnam Jameie ◽  
Shahram Teimourian
2009 ◽  
Vol 62 (5) ◽  
pp. 422-428 ◽  
Author(s):  
S M Khoshnaw ◽  
A R Green ◽  
D G Powe ◽  
I O Ellis

MicroRNAs (miRNAs) are a highly abundant class of endogenous small non-coding RNAs (18–25 nucleotides in length) that regulate gene expression by targeting protein-coding mRNAs post-transcriptionally. miRNAs have been implicated in cancer development and progression. As miRNAs and their regulatory functions are further revealed, the more the importance of miRNA-directed gene regulation is emphasised. In the human genome, 695 mature miRNAs have been identified, although computational calculation predicts that this may increase to >1000. Deregulation of miRNA expression profiles is thought to be implicated in the pathogenesis of many human cancers including breast tumours. Breast cancer subtypes are observed to have deranged miRNA expression signatures, which makes miRNAs important targets for developing a novel molecular classification of breast cancer and opening avenues for more individualised treatment strategies for patients with breast cancer.


2019 ◽  
Author(s):  
Kyuri Jo ◽  
Beatriz Santos Buitrago ◽  
Minsu Kim ◽  
Sungmin Rhee ◽  
Carolyn Talcott ◽  
...  

AbstractFor breast cancer, clinically important subtypes are well characterised at the molecular level in terms of gene expression profiles. In addition, signaling pathways in breast cancer have been extensively studied as therapeutic targets due to their roles in tumor growth and metastasis. However, it is challenging to put signaling pathways and gene expression profiles together to characterise biological mechanisms of breast cancer subtypes since many signaling events result from post-translational modifications, rather than gene expression differences.We present a logic-based approach to explain the differences in gene expression profiles among breast cancer subtypes using Pathway Logic and transcriptional network information. Pathway Logic is a rewriting-logic-based formal system for modeling biological pathways including post-translational modifications. Proposed method demonstrated its utility by constructing subtype-specific path from key receptors (TNFR, TGFBR1 and EGFR) to key transcription factor (TF) regulators (RELA, ATF2, SMAD3 and ELK1) and identifying potential pathway crosstalk via TFs in basal-specific paths, which could provide a novel insight on aggressive breast cancer subtypes.AvailabilityAnalysis result is available at http://epigenomics.snu.ac.kr/PL/


Gene ◽  
2021 ◽  
Vol 769 ◽  
pp. 145206
Author(s):  
Chengdong Wang ◽  
Feng Li ◽  
Linhua Deng ◽  
Mingzhou Li ◽  
Ming Wei ◽  
...  

2020 ◽  
Vol 21 (20) ◽  
pp. 7691
Author(s):  
Erik Kudela ◽  
Marek Samec ◽  
Lenka Koklesova ◽  
Alena Liskova ◽  
Peter Kubatka ◽  
...  

Breast cancer, which is the most common malignancy in women, does not form a uniform nosological unit but represents a group of malignant diseases with specific clinical, histopathological, and molecular characteristics. The increasing knowledge of the complex pathophysiological web of processes connected with breast cancercarcinogenesis allows the development of predictive and prognostic gene expressionand molecular classification systems with improved risk assessment, which could be used for individualized treatment. In our review article, we present the up-to-date knowledge about the role of miRNAs and their prognostic and predictive value in luminal A breast cancer. Indeed, an altered expression profile of miRNAs can distinguish not only between cancer and healthy samples, but they can classify specific molecular subtypes of breast cancer including HER2, Luminal A, Luminal B, and TNBC. Early identification and classification of breast cancer subtypes using miRNA expression profilescharacterize a promising approach in the field of personalized medicine. A detection of sensitive and specific biomarkers to distinguish between healthy and early breast cancer patients can be achieved by an evaluation of the different expression of several miRNAs. Consequently, miRNAs represent a potential as good diagnostic, prognostic, predictive, and therapeutic biomarkers for patients with luminal A in the early stage of BC.


2019 ◽  
Vol 93 ◽  
pp. 103157 ◽  
Author(s):  
Juan C. Rodriguez ◽  
Gabriela A. Merino ◽  
Andrea S. Llera ◽  
Elmer A. Fernández

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