The long non‐coding RNA landscape in triple‐negative breast cancer

Zhang, Wenwen; Guan, Xiaoxiang; Tang, Jinhai

doi:10.1111/cpr.12966

Cited by 57 publications

(27 citation statements)

References 151 publications

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“…Hence, SKAI1BC could be a potential target for lncRNA-based therapy in preventing metastatic spread in breast cancer. The approach taken towards inhibiting oncogenic lncRNA in breast cancer, thus far, includes the use of antisense oligonucleotides, treatment with locked nucleic acids (DNA analogues), and nanoparticle-mediated RNA interference (RNAi) technology [103].…”

Section: Epigenetic Drugs For Treatment Of Breast Cancermentioning

confidence: 99%

Targeting CD82/KAI1 for Precision Therapeutics in Surmounting Metastatic Potential in Breast Cancer

Viera

Yip

Shen

et al. 2021

Cancers

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Metastasis is the main cause of mortality in breast cancer patients. There is an unmet need to develop therapies that can impede metastatic spread. Precision oncology has shown great promise for the treatment of cancers, as the therapeutic approach is tailored to a specific group of patients who are likely to benefit from the treatment, rather than the traditional approach of “one size fits all”. CD82, also known as KAI1, a glycoprotein belonging to the tetraspanin family and an established metastasis suppressor, could potentially be exploited to hinder metastases in breast cancer. This review explores the prospect of targeting CD82 as an innovative therapeutic approach in precision medicine for breast cancer patients, with the goal of preventing cancer progression and metastasis. Such an approach would entail the selection of a subset of breast cancer patients with low levels of CD82, and instituting an appropriate treatment scheme tailored towards restoring the levels of CD82 in this group of patients. Proposed precision treatment regimens include current modalities of treating breast cancer, in combination with either clinically approved drugs that could restore the levels of CD82, CD82 peptide mimics or non-coding RNA-based therapeutics.

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Section: Epigenetic Drugs For Treatment Of Breast Cancermentioning

confidence: 99%

Targeting CD82/KAI1 for Precision Therapeutics in Surmounting Metastatic Potential in Breast Cancer

Viera

Yip

Shen

et al. 2021

Cancers

View full text Add to dashboard Cite

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“…On the other side, long noncoding RNAs (lncRNAs) are a class of noncoding RNAs (ncRNAs) with a length of more than 200 nucleotides [ 14 ]. Dysregulation of lncRNAs had been confirmed to be crucial in TNBC progression, including cell proliferation, apoptosis, invasion, metastasis, and regulation of drug resistance [ 15 ]. Although numerous researches have focused on developing novel lncRNA-based therapeutics, there is still a long way to apply it in clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Development of a Prognostic Model Based on the Identification of EMT-Related lncRNAs in Triple-Negative Breast Cancer

Guo

et al. 2021

Journal of Oncology

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Background. Triple-negative breast cancer (TNBC) remains the most incurable subtype of breast cancer owing to high heterogeneity, aggressive nature, and lack of treatment options. It is generally acknowledged that epithelial-mesenchymal transition (EMT) is the key step in tumor metastasis. Methods. With the application of TCGA and GEO databases, we identified EMT-related lncRNAs by the Cox univariate regression analysis. Optimum risk scores were calculated and used to divide TNBC patients into high-/low-risk subgroups by the median value using the Lasso regression analysis. The Kaplan–Meier and ROC curve analyses were applied for model validation. Then, we assessed the risk model from multi-omic aspects including immune infiltration, drug sensitivity, mutability spectrum, signaling pathways, and clinical indicators. We also analyzed the expression pattern of lncRNAs involved in the model using qRT-PCR in TNBC cell lines and constructed the ceRNA network. Results. The risk model was composed of EMT-related long noncoding RNAs (lncRNAs), which seemed to be valuable in the prognostic prediction of TNBC patients. The model could act as an independent prognostic factor of TNBC and showed a robust prognostic ability in the stratification analysis. Further investigation demonstrated that the expression of lncRNAs was different between high aggressive and low aggressive TNBC cell lines, as well as TNBC patients. Conclusions. Together, our study successfully established a risk model with great accuracy and efficacy in the prognostic prediction of TNBC patients.

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“…miR-3960 was highly expressed in H:AD-M, H:BM-M, and H:T-M. The predicted mRNA levels were analyzed for POU class 3 homeobox 3 (POU3F3) [42], protocadherin alpha 2 (Pcdha2) [43], ceramide synthase 1 (CERS1) [44], early growth response (EGR) [45], and macrophage migration inhibitory factor (MIF) [46]. miR-5787 was highly expressed in both H:BM-M and H:T-M cells.…”

Section: Discussionmentioning

confidence: 99%

Alteration of Payload in Extracellular Vesicles by Crosstalk With Mesenchymal Stem Cells From Different Origin

Park

Kong

Seo

2021

Preprint

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BackgroundThe application of extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs) requires customized materials to target disease or cell damage. We hypothesized that EVs exert different inflammatory effects on one recipient cell, although stem cells of different origins in humans have similar payloads.ResultsHere, the payload of EVs released by crosstalk between MSCs and human middle ear epithelial cells (HMEECs) extracted from adipose tissue, bone marrow and tonsils significantly increased the level of anti-inflammatory factors. EVs derived from the co-culture medium decreased TNF-α, COX-2, IL-1β, and IL-6 levels to approximately zero within 3 h in HMEECs. Expression of miR-638 and amyloid-β A4 precursor protein-binding family A member 2 was analyzed using microarrays and gene ontology analysis, respectively.ConclusionsIn conclusion, stem cells of different origins have different payloads through crosstalk with recipient-specific cells. Inducing specific factors in EVs by co-culture with MSCs could be valuable in regenerative medicine.

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The long non‐coding RNA landscape in triple‐negative breast cancer

Cited by 57 publications

References 151 publications

Targeting CD82/KAI1 for Precision Therapeutics in Surmounting Metastatic Potential in Breast Cancer

Targeting CD82/KAI1 for Precision Therapeutics in Surmounting Metastatic Potential in Breast Cancer

Development of a Prognostic Model Based on the Identification of EMT-Related lncRNAs in Triple-Negative Breast Cancer

Alteration of Payload in Extracellular Vesicles by Crosstalk With Mesenchymal Stem Cells From Different Origin

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