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pmid:35686034

Identification and Verification of Key Tumor Genes Associated with Diagnosis and Prognosis of Breast Cancer Based on Bioinformatics Analysis.

Feng Yu · Xian-Jun Pan · Jie Luo

Disease markers · 2022 doi:10.1155/2022/9041466

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:35686034
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science-record
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sha256:e4f23bf5ef84a2168c50099e695c531c67c064a69e5caa11f97ecd2c47048d93
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T18:14:38Z
updated_at
2026-11-01T22:06:44Z
generator object · 2 fields
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corpus-assay-engine
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paper object · 10 fields
state
complete
title
Identification and Verification of Key Tumor Genes Associated with Diagnosis and Prognosis of Breast Cancer Based on Bioinformatics Analysis.
doi
10.1155/2022/9041466
pmid
35686034
authors array · 3 items
[0]
Feng Yu
[1]
Xian-Jun Pan
[2]
Jie Luo
journal
Disease markers
year
2022
abstract
Breast cancer (BC) is the most common cancer and the most frequent cause of cancer death among women worldwide. The aim of the present study was to identify the critical genes for the diagnosis and prognosis of BC. Two mRNA expression data (GSE29431 and GSE42568) were acquired from the GEO database. The determination of differently expressed genes (DEGs) between BC specimens and nontumor specimens was completed via the LIMMA package of R. GO annotation and KEGG pathway enrichment analyses were applied to explore the function of DEGs. Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets. The diagnostic value of the survival-related DGEs were confirmed using ROC assays in two GEO datasets. RT-PCR was used to examine the expression of the critical genes in BC cells and normal breast cells. CCK-8 experiments were applied to explore the function of the critical genes in BC cells. In this study, we identified 31 DEGs between BC specimens and nontumor specimens. KEGG analysis revealed 31 DEGs were involved in PPAR signal path, AMPK signal path, glycerolipid metabolism, adipocytokine signaling pathway, phenylalanine metabolism, tyrosine metabolic process, and glycine, serine, and threonine metabolic process. Four DEGs including CRYAB, DEFB132, MAOA, and RBP4 were observed to be associated with clinical outcome of BC patients. Their diagnostic values were also confirmed in both GSE29431 and GSE42568 datasets. In addition, we analyzed TCGA datasets and confirmed that the results were consistent with GEO datasets. Finally, the results of RT-PCR confirmed that the expression of CRYAB and RBP4 was distinctly downregulated in BC cells. CCK-8 analysis revealed that overexpression of CRYAB and RBP4 distinctly suppressed the proliferation of BC cells. Overall, our findings suggested CRYAB and RBP4 as critical genes for the diagnosis and prognosis of BC patients. They may be used as novel biomarkers for BC patients.
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Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets.
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Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets.
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CRYAB and RBP4 were identified as critical genes for the diagnosis and prognosis of breast cancer patients.
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sections[0] "Abstract" paragraph 1
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Overall, our findings suggested CRYAB and RBP4 as critical genes for the diagnosis and prognosis of BC patients.
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CRYAB and RBP4 were identified as critical genes for the diagnosis and prognosis of breast cancer patients.
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570
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Homo sapiens
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Identifying breast cancer biomarkers
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GSM1045225
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GSM1045233
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GSM1045235
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GSM1045236
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GSM1045246
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GSM1045249
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GSM1045260
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GSM1045262
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121
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570
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Homo sapiens
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Breast Cancer Gene Expression Analysis
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2026-11-01T15:39:54Z
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Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets.
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l genes in BC cells and normal breast cells. CCK-8 experiments were applied to explore the func
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P4 was distinctly downregulated in BC cells. CCK-8 analysis revealed that overexpression of CRY
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Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets.
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assay:3
Complete file
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Two mRNA expression data (GSE29431 and GSE42568) were acquired from the GEO database. The determination of differently expressed genes (DEGs) between BC specimens and nontumor specimens was completed via the LIMMA package of R. GO annotation and KEGG pathway enrichment analyses were applied to explore the function of DEGs. Kaplan-Meier methods were used to determine the prognostic value of DEGs in BC using TCGA datasets. The diagnostic value of the survival-related DGEs were confirmed using ROC assays in two GEO datasets. RT-PCR was used to examine the expression of the critical genes in BC cells and normal breast cells. CCK-8 experiments were applied to explore the function of the critical genes in BC cells. In this study, we identified 31 DEGs between BC specimens and nontumor specimens. KEGG analysis revealed 31 DEGs were involved in PPAR signal path, AMPK signal path, glycerolipid metabolism, adipocytokine signaling pathway, phenylalanine metabolism, tyrosine metabolic process, and glycine, serine, and threonine metabolic process. Four DEGs including CRYAB, DEFB132, MAOA, and RBP4 were observed to be associated with clinical outcome of BC patients. Their diagnostic values were also confirmed in both GSE29431 and GSE42568 datasets. In addition, we analyzed TCGA datasets and confirmed that the results were consistent with GEO datasets. Finally, the results of RT-PCR confirmed that the expression of CRYAB and RBP4 was distinctly downregulated in BC cells. CCK-8 analysis revealed that overexpression of CRYAB and RBP4 distinctly suppressed the proliferation of BC cells. Overall, our findings suggested CRYAB and RBP4 as critical genes for the diagnosis and prognosis of BC patients. 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