Multi-Omic Regulation of the PAM50 Gene Signature in Breast Cancer Molecular Subtypes

Ochoa, Soledad; Anda-Jáuregui, Guillermo de; Hernández‐Lemus, Enrique

doi:10.3389/fonc.2020.00845

Cited by 17 publications

(14 citation statements)

References 63 publications

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“…BC is generally regarded as a heterogeneous disease in terms of its molecular features, histological composition, and clinical characteristics (McCart Reed et al, 2021;Sadeghalvad et al, 2021). With the evolution of high-throughput technologies, we tend to subtype the disease into clinically relevant molecular subtypes, including normal-like, luminal A and B, HER2-enriched, and basallike or more intrinsic subtypes (Ochoa et al, 2020;Morgan et al, 2021). The five clinically molecular subtypes have drastically different treatment selection, prognosis, and tumor biology (Zubair et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Dissecting the Role of N6-Methylandenosine-Related Long Non-coding RNAs Signature in Prognosis and Immune Microenvironment of Breast Cancer

Zhang

Shan

Lin

et al. 2021

Front. Cell Dev. Biol.

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Breast cancer (BC) represents a molecularly and clinically heterogeneous disease. Recent progress in immunotherapy has provided a glimmer of hope for several BC subtypes. The relationship between N6-methyladenosine (m6A) modification and long non-coding RNAs (LncRNAs) is still largely unexplored in BC. Here, with the intention to dissect the landscape of m6A-related lncRNAs and explore the immunotherapeutic value of the m6A-related lncRNA signature, we identified m6A-related lncRNAs by co-expression analysis from The Cancer Genome Atlas (TCGA) and stratified BC patients into different subgroups. Furthermore, we generated an m6A-related lncRNA prognostic signature. Four molecular subtypes were identified by consensus clustering. Cluster 3 preferentially had favorable prognosis, upregulated immune checkpoint expression, and high level of immune cell infiltration. Twenty-one m6A-related lncRNAs were applied to construct the m6A-related lncRNA model (m6A-LncRM). Survival analysis and receiver operating characteristic (ROC) curves further confirmed the prognostic value and prediction performance of m6A-LncRM. Finally, high- and low-risk BC subgroups displayed significantly different clinical features and immune cell infiltration status. Overall, our study systematically explored the prognostic value of the m6A-related LncRNAs and identified a high immunogenicity BC subtype. The proposed m6A-related LncRNA model might serve as a robust prognostic signature and attractive immunotherapeutic targets for BC treatment.

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Section: Introductionmentioning

confidence: 99%

Dissecting the Role of N6-Methylandenosine-Related Long Non-coding RNAs Signature in Prognosis and Immune Microenvironment of Breast Cancer

Zhang

Shan

Lin

et al. 2021

Front. Cell Dev. Biol.

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“…A 50 gene signature, PAM50, was used to analyze the biological subtype of BC within the clinical setting. 37 …”

Section: Methodsmentioning

confidence: 99%

Kinectin 1 promotes the growth of triple-negative breast cancer via directly co-activating NF-kappaB/p65 and enhancing its transcriptional activity

Gao

Chen

Hong

et al. 2021

Sig Transduct Target Ther

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Triple-negative breast cancer (TNBC) is the most challenging subtype of breast cancer. Various endeavor has been made to explore the molecular biology basis of TNBC. Herein, we reported a novel function of factor Kinectin 1 (KTN1) as a carcinogenic promoter in TNBC. KTN1 expression in TNBC was increased compared with adjacent tissues or luminal or Her2 subtypes of breast cancer, and TNBC patients with high KTN1 expression have poor prognosis. In functional studies, knockdown of KTN1 inhibited the proliferation and invasiveness of TNBC both in vitro and in vivo, while overexpression of KTN1 promoted cancer cell proliferation and invasiveness. RNA-seq analysis revealed that the interaction of cytokine-cytokine receptor, particularly CXCL8 gene, was upregulated by KTN1, which was supported by the further experiments. CXCL8 depletion inhibited the tumorigenesis and progression of TNBC. Additionally, rescue experiments validated that KTN1-mediated cell growth acceleration in TNBC was dependent on CXCL8 both in vitro and in vivo. Furthermore, it was found that KTN1 enhanced the phosphorylation of NF-κB/p65 protein at Ser536 site, and specifically bound to NF-κB/p65 protein in the nucleus and cytoplasm of cells. Moreover, the transcription of CXCL8 gene was directly upregulated by the complex of KTN1 and NF-κB/p65 protein. Taken together, our results elucidated a novel mechanism of KTN1 gene in TNBC tumorigenesis and progression. KTN1 may be a potential molecular target for the development of TNBC treatment.

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“…In previous studies, the TFs, such as p53, and the non-coding RNAs (ncRNAs), such as microRNA (miR)-21, miR-10b, and NEAT 1, could regulate different target genes in different subpopulations or subtypes of cancers. 35 , 36 , 37 In this study, we found that ETV 6 could play diversified roles through regulating different genes in the five molecular subtypes, which might be associated with intratumoral heterogeneity. To explore the potential drugs related to the ETV 6 gene, we used the ChEMBL database to scrutinize the candidate compounds.…”

Section: Discussionmentioning

confidence: 73%

Single-cell RNA-seq dissects the intratumoral heterogeneity of triple-negative breast cancer based on gene regulatory networks

Zhou

Huang

Liu

et al. 2021

Molecular Therapy - Nucleic Acids

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Triple-negative breast cancer (TNBC) is a subtype of breast cancer with high intratumoral heterogeneity. Recent studies revealed that TNBC patients might comprise cells with distinct molecular subtypes. In addition, gene regulatory networks (GRNs) constructed based on single-cell RNA sequencing (scRNA-seq) data have demonstrated the significance for decoding the key regulators. We performed a comprehensive analysis of the GRNs for the intrinsic subtypes of TNBC patients using scRNA-seq. The copy number variations (CNVs) were inferred from scRNA-seq data and identified 545 malignant cells. The subtypes of the malignant cells were assigned based on the PAM50 model. The cell-cell communication analysis revealed that the macrophage plays a dominant role in the tumor microenvironment. Next, the GRN for each subtype was constructed through integrating gene co-expression and enrichment of transcription-binding motifs. Then, we identified the critical genes based on the centrality metrics of genes. Importantly, the critical gene ETV 6 was ubiquitously upregulated in all subtypes, but it exerted diverse roles in each subtype through regulating different target genes. In conclusion, the construction of GRNs based on scRNA-seq data could help us to dissect the intratumoral heterogeneity and identify the critical genes of TNBC.

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Multi-Omic Regulation of the PAM50 Gene Signature in Breast Cancer Molecular Subtypes

Cited by 17 publications

References 63 publications

Dissecting the Role of N6-Methylandenosine-Related Long Non-coding RNAs Signature in Prognosis and Immune Microenvironment of Breast Cancer

Dissecting the Role of N6-Methylandenosine-Related Long Non-coding RNAs Signature in Prognosis and Immune Microenvironment of Breast Cancer

Kinectin 1 promotes the growth of triple-negative breast cancer via directly co-activating NF-kappaB/p65 and enhancing its transcriptional activity

Single-cell RNA-seq dissects the intratumoral heterogeneity of triple-negative breast cancer based on gene regulatory networks

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