Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

Lv, Zhenyi; Wang, Qiang; Liu, Xuxu; Du, Zhiwei; Liang, Wenping; Liu, Tianming; Zheng, Yi; Ma, Biao; Xue, Dongbo

doi:10.3389/fgene.2022.926984

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…Recent research [39] has shown that LINC00675 overexpression can inhibit breast cancer cell proliferation, migration, and invasion, while depletion of LINC00675 has the opposite effect. Additionally, literature [40] predict LDAs was further substantiated through these case studies involving these three cancers.…”

Section: Cases Studiesmentioning

confidence: 86%

“…Recent research [39] has shown that LINC00675 overexpression can inhibit breast cancer cell proliferation, migration, and invasion, while depletion of LINC00675 has the opposite effect. Additionally, literature [40] has demonstrated that GACAT2 is associated with breast cancer. Only one lncRNA candidate is labeled as 'Unknown', indicating a temporary lack of evidence supporting its association with breast cancer.…”

Section: Cases Studiesmentioning

confidence: 99%

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AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron

Yao,

Zhang,

Zhan

2024

Preprint

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Increased evidence suggests that long non-coding RNA (lncRNA) holds a vital position in intricate human diseases. Nonetheless, the current pool of identified lncRNA linked to diseases remains restricted. Hence, the scientific community emphasizes the need for a reliable and cost-effective computational approach to predict the probable correlations between lncRNA and diseases. It would facilitate the exploration of the underlying mechanisms of lncRNA in ailments and the development of novel disease treatments. In this study, we propose a novel approach for predicting the associations between lncRNAs and diseases, which relies on the adaptive meta-path generation (AMPGLDA). Firstly, we integrate information about lncRNA, diseases, and miRNAs to construct a heterogeneous graph. Then, we utilize principal component analysis to extract global features from nodes. Based on this heterogeneous graph, AMPGLDA adaptively generates multiple meta-path graph structures and uses a graph convolutional neural network to learn the semantic feature representations of lncRNA and disease from the meta-path. Ultimately, AMPGLDA utilizes a deep neural network classifier to accurately predict the association between lncRNA and disease. The AMPGLDA model achieves impressive results, with AUC and AUPR scores of 99.66% and 99.66%, respectively, under the independent test set. Furthermore, three case studies demonstrate its accuracy in discovering new lncRNA-disease associations.

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Section: Cases Studiesmentioning

confidence: 86%

“…Recent research [39] has shown that LINC00675 overexpression can inhibit breast cancer cell proliferation, migration, and invasion, while depletion of LINC00675 has the opposite effect. Additionally, literature [40] has demonstrated that GACAT2 is associated with breast cancer. Only one lncRNA candidate is labeled as 'Unknown', indicating a temporary lack of evidence supporting its association with breast cancer.…”

Section: Cases Studiesmentioning

confidence: 99%

AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron

Yao,

Zhang,

Zhan

2024

Preprint

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The prognostic and biological importance of chromatin regulation-related genes for lung cancer is examined using bioinformatics and experimentally confirmed

Ren

2023

Pathology - Research and Practice

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Age-Related Alterations in Mesenchymal Stem Cell Function: Understanding Mechanisms and Seeking Opportunities to Bypass the Cellular Aging

Rasouli

Naeimzadeh

Hashemi

et al. 2024

CSCR

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Undoubtedly, mesenchymal stem cells (MSCs) are the most common cell therapy candidates in clinical research and therapy. They not only exert considerable therapeutic effects to alleviate inflammation and promote regeneration, but also show low-immunogenicity properties, which ensure their safety following allogeneic transplantation. Thanks to the necessity of providing a sufficient number of MSCs to achieve clinically efficient outcomes, prolonged in vitro cultivation is indisputable. However, either following long-term in vitro expansion or aging in elderly individuals, MSCs face cellular senescence. Senescent MSCs undergo an impairment in their function and therapeutic capacities and secrete degenerative factors which negatively affect young MSCs. To this end, designing novel investigations to further elucidate cellular senescence and to pave the way toward finding new strategies to reverse senescence is highly demanded. In this review, we will concisely discuss current progress on the detailed mechanisms of MSC senescence and various inflicted changes following aging in MSC. We will also shed light on the examined strategies underlying monitoring and reversing senescence in MSCs to bypass the comprised therapeutic efficacy of the senescent MSCs.

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Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

Cited by 4 publications

References 39 publications

AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron

AMPGLDA: Predicting LncRNA-Disease Associations Based on Adaptive Meta-Path Generation and Multi-Layer Perceptron

The prognostic and biological importance of chromatin regulation-related genes for lung cancer is examined using bioinformatics and experimentally confirmed

Age-Related Alterations in Mesenchymal Stem Cell Function: Understanding Mechanisms and Seeking Opportunities to Bypass the Cellular Aging

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