Identification of Breast Cancer Subtype-Specific Biomarkers by Integrating Copy Number Alterations and Gene Expression Profiles

Cava, Claudia; Pisati, Mirko; Frasca, Marco; Castiglioni, Isabella

doi:10.3390/medicina57030261

Cited by 14 publications

(6 citation statements)

References 57 publications

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“…On the one hand, our proposed method only worked at the gene expression level. Multiple omics data, e.g., DNA methylation [ 52 ], copy number variation [ 58 ], protein complexes [ 57 ] and metabolite information [ 59 ] will provide integrative and comprehensive information for biomarker discovery. The integration of multi-omics data is an important approach for discovering more accurate BRCA biomarkers.…”

Section: Discussionmentioning

confidence: 99%

Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models

Liu

2021

J Transl Med

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Background The successful identification of breast cancer (BRCA) prognostic biomarkers is essential for the strategic interference of BRCA patients. Recently, various methods have been proposed for exploring a small prognostic gene set that can distinguish the high-risk group from the low-risk group. Methods Regularized Cox proportional hazards (RCPH) models were proposed to discover prognostic biomarkers of BRCA from gene expression data. Firstly, the maximum connected network with 1142 genes by mapping 956 differentially expressed genes (DEGs) and 677 previously BRCA-related genes into the gene regulatory network (GRN) was constructed. Then, the 72 union genes of the four feature gene sets identified by Lasso-RCPH, Enet-RCPH, $$L_{0}$$ L 0 -RCPH and SCAD-RCPH models were recognized as the robust prognostic biomarkers. These biomarkers were validated by literature checks, BRCA-specific GRN and functional enrichment analysis. Finally, an index of prognostic risk score (PRS) for BRCA was established based on univariate and multivariate Cox regression analysis. Survival analysis was performed to investigate the PRS on 1080 BRCA patients from the internal validation. Particularly, the nomogram was constructed to express the relationship between PRS and other clinical information on the discovery dataset. The PRS was also verified on 1848 BRCA patients of ten external validation datasets or collected cohorts. Results The nomogram highlighted that the importance of PRS in guiding significance for the prognosis of BRCA patients. In addition, the PRS of 301 normal samples and 306 tumor samples from five independent datasets showed that it is significantly higher in tumors than in normal tissues ($$P<0.05$$ P < 0.05 ). The protein expression profiles of the three genes, i.e., ADRB1, SAV1 and TSPAN14, involved in the PRS model demonstrated that the latter two genes are more strongly stained in tumor specimens. More importantly, external validation illustrated that the high-risk group has worse survival than the low-risk group ($$P<0.05$$ P < 0.05 ) in both internal and external validations. Conclusions The proposed pipelines of detecting and validating prognostic biomarker genes for BRCA are effective and efficient. Moreover, the proposed PRS is very promising as an important indicator for judging the prognosis of BRCA patients.

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Section: Discussionmentioning

confidence: 99%

Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models

Liu

2021

J Transl Med

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“…Importantly MCPH1/BRIT1 was an independent predictor of overall survival (42). Furthermore, previous studies found MCPH1/BRIT1 to be associated in all subtypes (48). Another study identified low MCPH1/BRIT1 nuclear expression in 52.4% (43/82) of breast cancers which was associated with the presence of allele T in the MCPH1/BRIT1 polymorphisms (rs2912010 and rs1057090).…”

Section: Discussion Mcph1/brit1 In Breast Cancermentioning

confidence: 89%

The emerging role of MCPH1/BRIT1 in carcinogenesis

Alsolami

Aboalola²,

Malibari³

et al. 2023

Front. Oncol.

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The MCPH1 gene, also known as BRCT-repeat inhibitor of hTERT expression (BRIT1), has three BRCA1 carboxyl-terminal domains which is an important regulator of DNA repair, cell cycle checkpoints and chromosome condensation. MCPH1/BRIT1 is also known as a tumour suppressor in different types of human cancer. The expression level of the MCPH1/BRIT1 gene is decreased at the DNA, RNA or protein level in a number of types of cancers including breast cancer, lung cancer, cervical cancer, prostate cancer and ovarian cancer compared to normal tissue. This review also showed that deregulation of MCPH1/BRIT1 is significantly associated with reduced overall survival in 57% (12/21) and relapsed free survival in 33% (7/21) of cancer types especially in oesophageal squamous cell carcinoma and renal clear cell carcinoma. A common finding of this study is that the loss of MCPH1/BRIT1 gene expression plays a key role in promoting genome instability and mutations supporting its function as a tumour suppressor gene.

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“…Numerous genetic analysis studies have shown the molecular components of several pathways, and the discovery of genes linked to particular tissues has helped elucidate their biological role and put disease states like breast cancer, and subtypes like BRCA-Basal, BRCA-Her2, BRCA-LumA, and BRCA-LumB, into context [33][34][35]. The statistical significance is annotated via the number of stars (*: p < 0.05; **: p < 0.01; ***: p < 0.001); 3, 4: clinical stage factor; N.S.…”

Section: Disease Stage Factor Analysis Of Gene Expression Across Vari...mentioning

confidence: 99%

Gene Signature Associated with Nervous System in an Experimental Radiation- and Estrogen-Induced Breast Cancer Model

Calaf,

Roy,

Jara

et al. 2023

Biomedicines

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Breast cancer is frequently the most diagnosed female cancer in the world. The experimental studies on cancer seldom focus on the relationship between the central nervous system and cancer. Despite extensive research into the treatment of breast cancer, chemotherapy resistance is an important issue limiting the efficacy of treatment. Novel biomarkers to predict prognosis or sensitivity to chemotherapy are urgently needed. This study examined nervous-system-related genes. The profiling of differentially expressed genes indicated that high-LET radiation, such as that emitted by radon progeny, in the presence of estrogen, induced a cascade of events indicative of tumorigenicity in human breast epithelial cells. Bioinformatic tools allowed us to analyze the genes involved in breast cancer and associated with the nervous system. The results indicated that the gene expression of the Ephrin A1 gene (EFNA1), the roundabout guidance receptor 1 (ROBO1), and the kallikrein-related peptidase 6 (KLK6) was greater in T2 and A5 than in the A3 cell line; the LIM domain kinase 2 gene (LIMK2) was greater in T2 than A3 and A5; the kallikrein-related peptidase 7 (KLK7), the neuroligin 4 X-linked gene (NLGN4X), and myelin basic protein (MBP) were greater than A3 only in T2; and the neural precursor cell expressed, developmentally down-regulated 9 gene (NEDD9) was greater in A5 than in the A3 and E cell lines. Concerning the correlation, it was found a positive correlation between ESR1 and EFNA1 in BRCA-LumA patients; with ROBO1 in BRCA-Basal patients, but this correlation was negative with the kallikrein-related peptidase 6 (KLK6) in BRCA-LumA and –LumB, as well as with LIMK2 and ROBO1 in all BRCA. It was also positive with neuroligin 4 X-linked (NLGN4X) in BRCA-Her2 and BRCA-LumB, and with MBP in BRCA-LumA and –LumB, but negative with KLK7 in all BRCA and BRCA-LumA and NEDD9 in BRCA-Her2. The differential gene expression levels between the tumor and adjacent tissue indicated that the ROBO1, KLK6, LIMK2, KLK7, NLGN4X, MBP, and NEDD9 gene expression levels were higher in normal tissues than in tumors; however, EFNA1 was higher in the tumor than the normal ones. EFNA1, LIMK2, ROBO1, KLK6, KLK7, and MBP gene expression had a negative ER status, whereas NEDD9 and NLGN4X were not significant concerning ER status. In conclusion, important markers have been analyzed concerning genes related to the nervous system, opening up a new avenue of studies in breast cancer therapy.

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Identification of Breast Cancer Subtype-Specific Biomarkers by Integrating Copy Number Alterations and Gene Expression Profiles

Cited by 14 publications

References 57 publications

Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models

Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models

The emerging role of MCPH1/BRIT1 in carcinogenesis

Gene Signature Associated with Nervous System in an Experimental Radiation- and Estrogen-Induced Breast Cancer Model

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