Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis

Wang, Zhanwei; Katsaros, Dionyssios; Yi, Siyan; Fu, Yuanyuan; Canuto, Emilie Marion; Benedetto, Chiara; Lu, Lingeng; Chen, Wen-Ming; Risch, Harvey A.; Yu, Herbert

doi:10.1371/journal.pone.0136246

Cited by 72 publications

(61 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There were reports suggesting that microarray data from different platforms did not correlate well [22, 23]. We had the same impression when we compared gene expression signatures generated by different microarray platforms for breast cancer prognosis and found little overlap in genes across different signatures [24]. This phenomenon led us to think that our previous results need to be validated by other microarray platforms.…”

Section: Discussionmentioning

confidence: 70%

LINC00472 expression is regulated by promoter methylation and associated with disease-free survival in patients with grade 2 breast cancer

Wang

Loo

et al. 2015

Breast Cancer Res Treat

Self Cite

View full text Add to dashboard Cite

Long non-coding RNAs (lncRNAs) are a class of newly recognized DNA transcripts that have diverse biological activities. Dysregulation of lncRNAs may be involved in many pathogenic processes including cancer. Recently, we found an intergenic lncRNA, LINC00472, whose expression was correlated with breast cancer progression and patient survival. Our findings were consistent across multiple clinical datasets and supported by results from in vitro experiments. To evaluate further the role of LINC00472 in breast cancer, we used various online databases to investigate possible mechanisms that might affect LINC00472 expression in breast cancer. We also analyzed associations of LINC00472 with estrogen receptor, tumor grade, and molecular subtypes in additional online datasets generated by microarray platforms different from the one we investigated previously. We found that LINC00472 expression in breast cancer was regulated more possibly by promoter methylation than by the alteration of gene copy number. Analysis of additional datasets confirmed our previous findings of high expression of LINC00472 associated with ER-positive and low-grade tumors and favorable molecular subtypes. Finally, in nine datasets, we examined the association of LINC00472 expression with disease-free survival in patients with grade 2 tumors. Meta-analysis of the datasets showed that LINC00472 expression in breast tumors predicted the recurrence of breast cancer in patients with grade 2 tumors. In summary, our analyses confirm that LINC00472 is functionally a tumor suppressor, and that assessing its expression in breast tumors may have clinical implications in breast cancer management.

show abstract

Section: Discussionmentioning

confidence: 70%

LINC00472 expression is regulated by promoter methylation and associated with disease-free survival in patients with grade 2 breast cancer

Wang

Loo

et al. 2015

Breast Cancer Res Treat

Self Cite

View full text Add to dashboard Cite

show abstract

“…MAD2L1 protein is a component of the mitotic spindle assembly checkpoint and inhibits the onset of the anaphase by sequestering CDC20 until all chromosomes are aligned at the metaphase plate (41). It has been reported that MAD2L1 is highly expressed in patients with lung cancer (42), and furthermore, MAD2L1 may have the potential to be used as a diagnostic marker and therapeutic target in breast cancer (41). In addition, high intratumoral MAD2L1 levels may lead to reduced recurrence-free survival rates of patients with cancer (41).…”

Section: Discussionmentioning

confidence: 99%

“…It has been reported that MAD2L1 is highly expressed in patients with lung cancer (42), and furthermore, MAD2L1 may have the potential to be used as a diagnostic marker and therapeutic target in breast cancer (41). In addition, high intratumoral MAD2L1 levels may lead to reduced recurrence-free survival rates of patients with cancer (41).…”

Section: Discussionmentioning

confidence: 99%

Identification of differentially expressed protein‑coding genes in lung adenocarcinomas

Wang

et al. 2019

Exp Ther Med

View full text Add to dashboard Cite

Lung adenocarcinoma accounts for a high proportion of lung cancers. Though efforts have been made to develop new and effective treatments for this disease, the mortality rate remains high. Gene expression microarrays facilitate the study of lung cancer at the molecular level. The present study aimed to detect differentially expressed protein-coding genes to identify novel biomarkers and therapeutic targets for lung adenocarcinoma. Aberrations in gene expression in lung adenocarcinoma were determined by analysis of mRNA microarray datasets from the Gene Expression Omnibus database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) networks and statistical analysis were used to identify the biological functions of the differentially expressed genes (DEGs). The results of the bioinformatics analysis were subsequently validated using reverse transcription-quantitative PCR. A total of 303 DEGs were identified in lung adenocarcinomas, and they were enriched in a number of cancer-associated GO terms and KEGG pathways. DNA topoisomerase 2α (TOP2A), cell division cycle protein homolog 20 (CDC20), mitotic checkpoint serine/threonine protein kinase BUB1 (BUB1) and mitotic spindle assembly checkpoint protein MAD2A (MAD2L1) exhibited the highest degree of interaction in the PPI network. Survival analysis performed using Kaplan-Meier curves and Cox regression indicated that these four genes were all significantly associated with the survival of patients with lung adenocarcinomas. In conclusion, TOP2A, CDC20, BUB1 and MAD2L1 may be key protein-coding genes that may serve as biomarkers and therapeutic targets in lung adenocarcinomas.

show abstract

“…In a study conducted by Abal et al 50 , they mentioned that APC inactivation is associated with abnormal mitosis and concomitant BUB1B/MAD2L1 up-regulation. However, the overexpression of these two genes was correlated with tumor metastasis and poor prognosis of patients with breast cancer 51 . Its expression is amplified in colon cancer as well.…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Components in Colon Adenocarcinoma Using Transcriptome to Interactome Multilayer Framework

Pournoor

Mousavian

Dalini

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Complexity of cascading interrelations between molecular cell components at different levels fromgenome to metabolome ordains a massive difficulty in comprehending biological happenings. However, considering these complications in the systematic modelings will result in realistic and reliable outputs. The multilayer networks approach is a relatively innovative concept that could be applied for multiple omics datasets as an integrative methodology to overcome heterogeneity difficulties. Herein, we employed the multilayer framework to rehabilitate colon adenocarcinoma network by observing co-expression correlations, regulatory relations, and physical binding interactions. Hub nodes in this three-layer network were selected using a heterogeneous random walk with random jump procedure. We exploited local composite modules around the hub nodes having high overlay with cancer-specific pathways, and investigated their genes showing a different expressional pattern in the tumor progression. These genes were examined for survival effects on the patient's lifespan, and those with significant impacts were selected as potential candidate biomarkers. Results suggest that identified genes indicate noteworthy importance in the carcinogenesis of the colon. open Scientific RepoRtS | (2020) 10:4991 | https://doi.org/10.1038/s41598-020-59605-z www.nature.com/scientificreports www.nature.com/scientificreports/ to explore it. Second, Ensemble (Consensus) approaches, in which each layer is individually evaluated; then, the results are combined to create the final consequence. Third, methods extended for multilayer networks (briefly called extended approaches), in which the analysis process is simultaneously conducted on all layers. Didier et al. 13 compared these three approaches in terms of community detection and found that the extended modularity function has superiority over the other two methods.The extension of topological attributes from monolayer to multilayer is a critical and challenging topic in this area 12,14-16 . Hmimida et al. 12 have defined metrics (such as degree, shortest-path, neighbor set) for multiplex networks using an entropy-like aggregate function. Domenico et al. 16 proposed reducibility methods for multilayer networks to eliminate redundant interactions and layers. In this context, community detection for multilayer networks is considered one of the most challenging topics. Given the topological perspective, a community is a cluster of densely connected nodes, which are far from other clusters. Communities may be either local or global and may have overlap with each other. Recently, various extended multilayer community detection algorithms have been proposed to seek modules in layers simultaneously [17][18][19][20][21] . A specific type of community detection method is based on seed-centric approach, in which communities are localized around predefined (manual or computational) seed nodes 12,22 .Extended approaches for multilayer networks were recently used in biological and medical sciences. Berenstein et...

show abstract

Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis

Cited by 72 publications

References 53 publications

LINC00472 expression is regulated by promoter methylation and associated with disease-free survival in patients with grade 2 breast cancer

LINC00472 expression is regulated by promoter methylation and associated with disease-free survival in patients with grade 2 breast cancer

Identification of differentially expressed protein‑coding genes in lung adenocarcinomas

Identification of Key Components in Colon Adenocarcinoma Using Transcriptome to Interactome Multilayer Framework

Contact Info

Product

Resources

About