Proteome-centric cross-omics characterization and integrated network analyses of triple-negative breast cancer

Gong, Tianqi; Jiang, Yi‐Zhou; Shao, Chen; Peng, Weiping; Liu, Mingwei; Li, Da‐Qiang; Zhang, Ben-Yu; Du, Peng; Huang, Yin; Li, Feifei; Li, Muyun; Han, Zhao-Lian; Jin, Xi; Ma, Ding; Xiao, Yi; Yang, Pengyuan; Qin, Jun; Zhu, Weimin

doi:10.1016/j.celrep.2022.110460

Cited by 26 publications

(38 citation statements)

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“…Genes and pathways denoted in red (indicate high expression) while those denoted in green (indicate low expression). Data are aggregated from Lehmann et al[ 57 ], Burstein et al[ 7 ], Jiang et al[ 6 ], Bareche et al[ 35 ], Bareche et al[ 64 ], Lehmann et al[ 58 ], Gong et al[ 76 ] and Asleh et al[ 60 ]. Abbreviations: TNBC, triple negative breast cancer; HRD, …”

Section: Introductionmentioning

confidence: 99%

“…Additionally, LAR tumors are characterized by CDKN2A loss while retaining RB1 and have high phosphorylation of RB protein supporting their sensitivity to CDK4/6 inhibitors [ 58 , 74 , 75 ]. LAR tumors further exhibit low levels of chromosomal instability, HRD and immune-related gene expression [ 6 , 7 , 32 , 33 , 35 , 58 ] and have been associated with lipid metabolism [ 58 , 60 , 64 , 76 ], older age, positive lymph nodes, and apocrine features [ 6 , 57 , 58 ].…”

Section: Introductionmentioning

confidence: 99%

“…The mesenchymal subtype of TNBC is enriched for pathways involved in extracellular matrix, epithelial-mesenchymal-transition and angiogenesis [ 6 , 7 , 58 , 60 , 76 ] expressing EGFR , IGF-1 , osteocyte markers ( OGN ), NOTCH1 and NOTCH3 [ 6 , 35 , 58 ]. Mesenchymal tumors as a group display mixed basal-like and non-basal PAM50 profiles [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…While antigen processing and presentation proteins are low in mesenchymal tumors [ 58 , 60 , 76 ], phospho-proteomic analysis has shown an increased DNA repair signalling in this subtype as demonstrated by high phosphorylation of ATR and ATM [ 58 ]. Mesenchymal tumors have been further reported to display characteristics of breast cancer stem cells and upregulation in JAK1/STAT3 signalling [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

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Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications

Asleh

Riaz

Nielsen

2022

J Exp Clin Cancer Res

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As the field of translational ‘omics has progressed, refined classifiers at both genomic and proteomic levels have emerged to decipher the heterogeneity of breast cancer in a clinically-applicable way. The integration of ‘omics knowledge at the DNA, RNA and protein levels is further expanding biologic understanding of breast cancer and opportunities for customized treatment, a particularly pressing need in clinically triple negative tumors. For this group of aggressive breast cancers, work from multiple groups has now validated at least four major biologically and clinically distinct omics-based subtypes. While to date most clinical trial designs have considered triple negative breast cancers as a single group, with an expanding arsenal of targeted therapies applicable to distinct biological pathways, survival benefits may be best realized by designing and analyzing clinical trials in the context of major molecular subtypes. While RNA-based classifiers are the most developed, proteomic classifiers proposed for triple negative breast cancer based on new technologies have the potential to more directly identify the most clinically-relevant biomarkers and therapeutic targets. Phospho-proteomic data further identify targetable signalling pathways in a unique subtype-specific manner. Single cell profiling of the tumor microenvironment represents a promising way to allow a better characterization of the heterogeneity of triple negative breast cancer which could be integrated in a spatially resolved context to build an ecosystem-based patient classification. Multi-omic data further allows in silico analysis of genetic and pharmacologic screens to map therapeutic vulnerabilities in a subtype-specific context. This review describes current knowledge about molecular subtyping of triple negative breast cancer, recent advances in omics-based genomics and proteomics diagnostics addressing the diversity of this disease, key advances made through single cell analysis approaches, and developments in treatments including targeted therapeutics being tested in major clinical trials.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications

Asleh

Riaz

Nielsen

2022

J Exp Clin Cancer Res

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“…In recent years, researchers have employed a variety of techniques to investigate TNBC hub genes, such as, co-expression network analysis on three proteomic datasets paired with genomic and transcriptome data to uncover critical pathways and regulators of TNBC subtypes (10). Six immune component analysis methods were used to detect, de ne, and validate macrophage-related gene markers in triple-negative breast cancer patients in order to predict overall survival (11).…”

Section: Introductionmentioning

confidence: 99%

Identification of hub genes affecting triple-negative breast cancer using bioinformatics analysis strategies

Liu

Kan

Wang

et al. 2022

Preprint

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BackgroundBreast cancer is one of the most serious malignancies in women throughout the world, with an increasing number of people being diagnosed and dying from it. Triple-negative breast cancer (TNBC), which has a dismal prognosis, the estrogen receptor (ER), progesterone receptor (PR), and human growth factor receptor type 2 (Her2) immunohistochemistry test results are all negative. MethodsTo find differentially expressed genes (DEGs), two datasets from the Gene Expression Omnibus (GEO) were used to search for TNBC and not triple-negative breast cancer (not-TNBC) differentially expressed genes. Using weighted gene co-expression network analysis (WGCNA), the breast cancer data from the Cancer Genome Atlas (TCGA) was utilized to study the relationship between genes and TNBC features and to identify the hub genes in the most important linked modules. The Gene Ontology (GO) and Kyoto Encyclopedia of the Genes and Genomes (KEGG) enrichment analyses were performed on the differential genes in the GEO dataset and the hub genes in the TCGA dataset to study the nature of genes and to find gene enrichment pathways. A protein-protein interaction network (PPI) was created for each of the genes considered. To discover the most important genes in PPI networks, utilize the cytoHubba plugin in Cytoscape. Following that, the gene expression profiling interaction analysis (GEPIA) was used to confirm the hub gene's expression. Finally, data sets from the cBioPortal database were utilized for survival analysis. ResultsWe detected 7 genes that were up-regulated and 2 genes that were down-regulated by combining the GEO and TCGA databases.PGR, ELF5, AGR2, and GATA3 prolong life expectancy, while ESR1, TFF1, FOXA1, and AR shorten life expectancy.ConclusionOur study confirmed that PGR, ELF5, AGR2, GATA3, ESR1, TFF1, FOXA1, and AR may be potential therapeutic targets and biomarkers for TNBC.

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C9orf142 transcriptionally activates MTBP to drive progression and resistance to CDK4/6 inhibitor in triple‐negative breast cancer

Liao,

Deng,

Zhang

et al. 2023

Clinical & Translational Med

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BackgroundTriple‐negative breast cancer (TNBC) presents the most challenging subtype of all breast cancers because of its aggressive clinical phenotypes and absence of viable therapy targets. In order to identify effective molecular targets for treating patients with TNBC, we conducted an integration analysis of our recently published TNBC dataset of quantitative proteomics and RNA‐Sequencing, and found the abnormal upregulation of chromosome 9 open reading frame 142 (C9orf142) in TNBC. However, the functional roles of C9orf142 in TNBC are unclear.MethodsIn vitro and in vivo functional experiments were performed to assess potential roles of C9orf142 in TNBC. Immunoblotting, real‐time quantitative polymerase chain reaction (RT‐qPCR), and immunofluorescent staining were used to investigate the expression levels of C9orf142 and its downstream molecules. The molecular mechanisms underlying C9orf142‐regulated mouse double minute 2 (MDM2)‐binding protein (MTBP) were determined by chromatin immunoprecipitation (ChIP) and dual‐luciferase reporter assays.ResultsIn TNBC tissues and metastatic lymph nodes, we observed that C9orf142 exhibited abnormal up‐regulation, and its elevated expression was indicative of unfavorable prognosis for TNBC patients. Both in vitro and in vivo functional experiments demonstrated that C9orf142 accelerated TNBC growth and metastasis. Further mechanism exploration revealed that C9orf142 transcriptionally activated MTBP, thereby regulating its downstream MDM2/p53/p21 signaling axis and the transition of cell cycle from G1 to S phase. Functional rescue experiment demonstrated that knockdown of MTBP attenuated C9orf142‐mediated tumour growth and metastasis. Furthermore, depletion of C9orf142 remarkably increased the responsiveness of TNBC cells to CDK4/6 inhibitor abemaciclib.ConclusionsTogether, these findings unveil a previously unrecognized effect of C9orf142 in TNBC progression and responsiveness to CDK4/6 inhibitor, and emphasize C9orf142 as a promising intervention target for TNBC treatment.

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Proteome-centric cross-omics characterization and integrated network analyses of triple-negative breast cancer

Cited by 26 publications

References 72 publications

Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications

Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications

Identification of hub genes affecting triple-negative breast cancer using bioinformatics analysis strategies

C9orf142 transcriptionally activates MTBP to drive progression and resistance to CDK4/6 inhibitor in triple‐negative breast cancer

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