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Analysis of the Regulation of Metastasis-associated Lung Adenocarcinoma Transcript 1 on the Biological Behavior of Breast Cancer

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Specialty Oncology
Date 2022 Feb 4
PMID 35116487
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Abstract

Background: Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a class of long non-coding RNA (lncRNA) that has been proved to be closely related to many cancers.

Methods: The relevant research on MALAT1 in cancers published in recent years were collected and integrated. CiteSpace was employed to draw a knowledge map of MALAT1 in breast cancer, to evaluate the research front-burner issues. Then, multiple microarray data sets were searched from online data for meta-analysis to evaluate the relationship between MALAT1 and breast cancer survival rate.

Results: The results showed that MALAT1 had been widely studied in the proliferation and differentiation of cancer cells, and MALAT1 might regulate breast cancer through the PI3K/AKT/mTOR signaling pathway. In addition, high expression of MALAT1 had a significant correlation with relapse-free survival (HR: 1.51, 95% CI: 0.79-2.29), while there was no significant correlation between MALAT1 expression and overall survival (HR: 1.09, 95% CI: 0.63-1.72).

Conclusions: The expression level of lncRNA MALAT1 was closely related to cancer progression and prognosis of cancer patients. Moreover, the expression of MALAT1 was strongly associated with the survival rate of recurrence-free breast cancer. However, since the present study only adopted the existing literature for visual analysis, subsequent experiments are needed to be done to verify this conclusion. It is hoped that this work could provide a theoretical foundation for promoting the clinical adoption of MALAT1 in the prediction, diagnosis, and treatment of breast cancer, and point out a new direction for the in-depth exploration of the function of MALAT1.

Citing Articles

Prognostic and diagnostic values of non-coding RNAs as biomarkers for breast cancer: An umbrella review and pan-cancer analysis.

Bahramy A, Zafari N, Rajabi F, Aghakhani A, Jayedi A, Khaboushan A Front Mol Biosci. 2023; 10:1096524.

PMID: 36726376 PMC: 9885171. DOI: 10.3389/fmolb.2023.1096524.

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