A Metabolic Gene Signature to Predict Breast Cancer Prognosis

Lu, Jun; Liu, Pinbo; Zhang, Ran

doi:10.3389/fmolb.2022.900433

Cited by 6 publications

(8 citation statements)

References 30 publications

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“…To further explore the predictive ability of our signature, a comparison was performed among several significant molecular signatures employed for predicting OS in patients with BC. Compared with the other signature, such as ferroptosis, necroptosis, pyroptosis, and immune-related ( Lin et al, 2020 ; Zhong et al, 2020 ; Wang et al, 2021a ; Wu et al, 2021a ; Zhu et al, 2021b ; Ding et al, 2021 ; Ye et al, 2021 ; Lu et al, 2022a ; Lu et al, 2022b ; Chen et al, 2022 ; Chu et al, 2022 ; Yu et al, 2022 ; Zou et al, 2022 ), our signature indicated much higher AUCs, which indicated a better predictive ability, especially in predicting the long-term survival status. Furthermore, we constructed a prognostic nomogram that could simplify treatment decision-making for patients with BC.…”

Section: Discussionmentioning

confidence: 79%

“…We also listed the other signatures that focus more on short-term survival, such as 1-year, 2-year, 3-year, and 5-year survival. We found our signature have similar short-term survival (3-year) prognostic value compared with them, such as the ferroptosis-related gene signature ( Wang et al, 2021a ; Wu et al, 2021a ; Zhu et al, 2021b ), pyroptosis-related gene signature ( Chen et al, 2022 ), necroptosis-related gene signature ( Yu et al, 2022 ), apoptosis-related gene signature ( Zou et al, 2022 ), zinc finger protein-related gene signature ( Ye et al, 2021 ), autophagy-related gene signature ( Lin et al, 2020 ), and metabolic-related gene signatures ( Lu et al, 2022b ). In addition, our model only involves four genes, while other models (11/13) tend to have more, which is more convenient to use to a certain extent.…”

Section: Resultsmentioning

confidence: 99%

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The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Jia

et al. 2022

Front. Genet.

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Breast cancer (BC) is the most diagnosed cancer in women. Cuproptosis is new regulated cell death, distinct from known death mechanisms and dependent on copper and mitochondrial respiration. However, the comprehensive relationship between cuproptosis and BC is still blank until now. In the present study, we acquired 13 cuproptosis-related regulators (CRRs) from the previous research and downloaded the RNA sequencing data of TCGA-BRCA from the UCSC XENA database. The 13 CRRs were all differently expressed between BC and normal samples. Using consensus clustering based on the five prognostic CRRs, BC patients were classified into two cuproptosis-clusters (C1 and C2). C2 had a significant survival advantage and higher immune infiltration levels than C1. According to the Cox and LASSO regression analyses, a novel cuproptosis-related prognostic signature was developed to predict the prognosis of BC effectively. The high- and low-risk groups were divided based on the risk scores. Kaplan-Meier survival analysis indicated that the high-risk group had shorter overall survival (OS) than the low-risk group in the training, test and entire cohorts. GSEA indicated that the immune-related pathways were significantly enriched in the low-risk group. According to the CIBERSORT and ESTIMATE analyses, patients in the high-risk group had higher infiltrating levels of antitumor lymphocyte cell subpopulations and higher immune score than the low-risk group. The typical immune checkpoints were all elevated in the high-risk group. Furthermore, the high-risk group showed a better immunotherapy response than the low-risk group based on the Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS). In conclusion, we identified two cuproptosis-clusters with different prognoses using consensus clustering in BC. We also developed a cuproptosis-related prognostic signature and nomogram, which could indicate the outcome, the tumor immune microenvironment, as well as the response to immunotherapy.

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Section: Discussionmentioning

confidence: 79%

Section: Resultsmentioning

confidence: 99%

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Jia

et al. 2022

Front. Genet.

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“…Breast cancer is an out-of-control proliferation of mammary gland epithelial cells due to a variety of carcinogenic factors [12,13]. The early stage of the disease is often manifested as breast lumps, nipple discharge, axillary lymph node enlargement and other symptoms, and the late stage can be manifested as the distant metastasis of cancer cells, multiple organ lesions and the direct threat to the patient's life [14,15].…”

Section: Discussionmentioning

confidence: 99%

Sini San inhibits breast cancer cell migration and angiogenesis via the HIF 1 /VEGF pathway

Zhang¹,

Chen²,

Lv³

et al. 2023

Trop. J. Pharm Res

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Purpose: To investigate the effects of Sini San (SNS) on breast cancer (BC), and the mechanism of action.Methods: MDA-MB-231 and SK-BR-3 cells were used as breast cancer cell models. Cell viability, migration, and invasion were determined by CCK-8, Transwell and wound healing assays, respectively. SNS mechanism of action and its anti-cancer effect were investigated by network pharmacological analysis, and further verified by Immunoblot.Results: Sini San inhibited the proliferation of the breast cancer (BC) cells., and also suppressed the migration as well as the invasion of BC cells, and also restrained the angiogenesis of BC cells. In performing the network pharmacological analysis of Sini Powder in the treatment of BC, 337 drugdisease targets were obtained. PPI network was established through String, and GO and KEGG enrichment analysis was performed on the target sites. KEGG analysis showed that genes were enriched in HIF-1 and VEGF pathways.Conclusion: Sini San suppressed cell migration as well as angiogenesis via the HIF-1 /VEGF pathway

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“…Because of the limits of clinicopathologic characteristics, predicting the potential therapeutic genes of cancer is still difficult for many malignancies, which is important for cancer management. Identification of gene expression profiles can aid in the improvement of patient care by offering directions for individualized treatment strategies (48). Twenty-seven apoptosis-regulated genes were included for statistical comparison in the current study.…”

Section: Discussionmentioning

confidence: 99%

The Role of Apoptotic Genes and Protein-Protein Interactions in Triple-negative Breast Cancer

Adinew¹,

Messeha²,

Taka³

et al. 2023

Cancer Genomics Proteomics

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Background/Aim: Compared to other breast cancer types, triple-negative breast cancer (TNBC) has historically had few treatment alternatives. Therefore, exploring and pinpointing potentially implicated genes could be used for treating and managing TNBC. By doing this, we will provide essential data to comprehend how the genes are involved in the apoptotic pathways of the cancer cells to identify potential therapeutic targets. Analysis of a single genetic alteration may not reveal the pathogenicity driving TNBC due to the high genomic complexity and heterogeneity of TNBC. Therefore, searching through a large variety of gene interactions enabled the identification of molecular therapeutic genes. Materials and Methods: This study used integrated bioinformatics methods such as UALCAN, TNM plotter, PANTHER, GO-KEEG and PPIs to assess the gene expression, protein-protein interaction (PPI), and transcription factor interaction of apoptosis-regulated genes. Results: Compared to normal breast tissue, gene expressions of BNIP3, TNFRSF10B, MCL1, and CASP4 were downregulated in UALCAN. At the same time, BIK, AKT1, BAD, FADD, DIABLO, and CASP9 was down-regulated in bc-GeneExMiner v4.5 mRNA expression (BCGM) databases. Based on GO term enrichment analysis, the cellular process (GO:0009987), which has about 21 apoptosis-regulated genes, is the top category in the biological processes (BP), followed by biological regulation (GO:0065007). We identified 29 differentially regulated pathways, including the p53 pathway, angiogenesis, apoptosis signaling pathway, and the Alzheimer's disease presenilin pathway. We examined the PPIs between the genes that regulate apoptosis; CASP3 and CASP9 interact with FADD, MCL1, TNF, TNFRSRF10A, and TNFRSF10; additionally, CASP3 significantly forms PPIs with CASP9, DFFA, and TP53, and CASP9 with DIABLO. In the top 10 transcription factors, the androgen receptor (AR) interacts with five apoptosisregulated genes (p<0.0001; q<0.01), followed by retinoic acid receptor alpha (RARA) (p<0.0001; q<0.01) and ring finger protein (RNF2) (p<0.0001; q<0.01). Overall, the gene expression profile, PPIs, and the apoptosis-TF interaction findings suggest that the 27 apoptosis-regulated genes might be used as promising targets in treating and managing TNBC. Furthermore, from a total of 27 key genes, CASP2, CASP3, DAPK1, TNF, TRAF2, and TRAF3 were significantly correlated with poor overall survival in TNBC (p-value <0.05); they could play important roles in the progression of TNBC and provide attractive therapeutic targets that may offer new candidate molecules for targeted therapy. Conclusion: Our findings demonstrate that CASP2, CASP3, DAPK1, TNF, TRAF2, and TRAF3 were substantially associated with the overall survival rate (OS) difference of TNBC patients out of a total of 27 specific genes used in this study, which may play crucial roles in the development of TNBC and offer promising therapeutic interventions.Breast cancer (BC) is the most common malignant tumor in women and the biggest threat to the health of wome...

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A Metabolic Gene Signature to Predict Breast Cancer Prognosis

Cited by 6 publications

References 30 publications

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Sini San inhibits breast cancer cell migration and angiogenesis via the HIF 1 /VEGF pathway

The Role of Apoptotic Genes and Protein-Protein Interactions in Triple-negative Breast Cancer

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