Ask about this productRelated genes to: BAIAP2 antibody
- Gene:
- BAIAP2 NIH gene
- Name:
- BAI1 associated protein 2
- Previous symbol:
- -
- Synonyms:
- BAP2, IRSp53
- Chromosome:
- 17q25.3
- Locus Type:
- gene with protein product
- Date approved:
- 1999-02-26
- Date modifiied:
- 2016-02-03
- Gene:
- BAIAP2-DT NIH gene
- Name:
- BAIAP2 divergent transcript
- Previous symbol:
- BAIAP2-AS1
- Synonyms:
- -
- Chromosome:
- 17q25.3
- Locus Type:
- RNA, long non-coding
- Date approved:
- 2012-08-14
- Date modifiied:
- 2018-03-21
Related products to: BAIAP2 antibody
Related articles to: BAIAP2 antibody
- Breast cancer (BRCA) is the most common malignancy among women worldwide. It was widely accepted that autophagy and the tumor immune microenvironment play an important role in the biological process of BRCA. Long non-coding RNAs (lncRNAs), as vital regulatory molecules, are involved in the occurrence and development of BRCA. The aim of this study was to assess the prognosis of BRCA by constructing an autophagy-related lncRNA (ARlncRNA) prognostic model and to provide individualized guidance for the treatment of BRCA. - Source: PubMed
Publication date: 2022/12/15
Chen JiafengLi XinrongYan ShuixinLi JiadiZhou YuxinWu MinhuaDing JinhuaYang JiahuiYuan YijieZhu YeWu Weizhu - Long non-coding RNA (lncRNA) are closely associated with the occurrence and progression of tumors. However, research on N7-methylguanosine (m7G)-related lncRNA in breast cancer is lacking. Therefore, the present study explored the prognostic value, gene expression characteristics, and effects of m7G-related lncRNA on tumor immune cell infiltration and tumor mutational burden (TMB) in breast cancer. lncRNA expression matrices and clinical follow-up data of patients with breast cancer were obtained from The Cancer Genome Atlas, revealing eight significantly differentially expressed and prognostically relevant m7G-related lncRNAs in breast cancer tissues: , , , , , , , and . A breast cancer prognostic signature was created based on these m7G-related lncRNAs according to least absolute shrinkage and selection operator Cox regression. The prognostic signature combined with potential prognostic factors showed independent prognostic value, reliability, and specificity. Meanwhile, we constructed a risk score-based nomogram to assist clinical decision-making. Gene set enrichment analysis revealed that low- and high-risk group were associated with metabolism-related pathways. Our study demonstrated the association between tumor immune cell infiltration based on analyses with the CIBERSORT algorithm and prognostic signature. We also assessed the correlation between prognostic signature and TMB. Lastly, quantitative real-time polymerase chain reaction analysis was performed to validate differentially expressed lncRNAs. The effective prognostic signature based on m7G-related lncRNAs has the potential to predict the survival prognosis of patients with breast cancer. The eight m7G-related lncRNAs identified in this study might represent potential biomarkers and therapeutic targets of breast cancer. - Source: PubMed
Publication date: 2022/10/13
Huang ZhidongLou KaixinLiu Hong - Long non-coding RNAs (lncRNAs) are well known as crucial regulators to breast cancer development and are implicated in controlling autophagy. LncRNAs are also emerging as valuable prognostic factors for breast cancer patients. It is critical to identify autophagy-related lncRNAs with prognostic value in breast cancer. In this study, we identified autophagy-related lncRNAs in breast cancer by constructing a co-expression network of autophagy-related mRNAs-lncRNAs from The Cancer Genome Atlas (TCGA). We evaluated the prognostic value of these autophagy-related lncRNAs by univariate and multivariate Cox proportional hazards analyses and eventually obtained a prognostic risk model consisting of 11 autophagy-related lncRNAs (U62317.4, LINC01016, LINC02166, C6orf99, LINC00992, BAIAP2-DT, AC245297.3, AC090912.1, Z68871.1, LINC00578 and LINC01871). The risk model was further validated as a novel independent prognostic factor for breast cancer patients based on the calculated risk score by Kaplan-Meier analysis, univariate and multivariate Cox regression analyses and time-dependent receiver operating characteristic (ROC) curve analysis. Moreover, based on the risk model, the low-risk and high-risk groups displayed different autophagy and oncogenic statues by principal component analysis (PCA) and Gene Set Enrichment Analysis (GSEA) functional annotation. Taken together, these findings suggested that the risk model of the 11 autophagy-related lncRNAs has significant prognostic value for breast cancer and might be autophagy-related therapeutic targets in clinical practice. - Source: PubMed
Publication date: 2020/11/20
Li XiaoyingJin FengLi Yang