MDN1 Mutation Is Associated With High Tumor Mutation Burden and Unfavorable Prognosis in Breast Cancer

Hao, Shuai; Hao, Miao; Xu, Xiaofan; Wang, Xulin; Huo, Liqun; Wang, Lu; Gu, Jun

doi:10.3389/fgene.2022.857836

Cited by 4 publications

(3 citation statements)

References 45 publications

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“…Tumor‐infiltrating immune cells, such as T cells, B cells, neutrophils, and regulatory T cells, are crucial elements in the tumor microenvironment and are critical in the antitumor response and cancer therapy. [ 24,25 ] Herein, we demonstrated, for the first time, a significant correlation between MYH16 expression and T, B, CD8 T, and other cells. In our study, tumor‐infiltrating B cells captured tumor antigens and triggered immune cells, thereby mediating tumor elimination by producing antibodies such as CCL2 and CXCR4, which activated CD4 and CD8 T cells.…”

Section: Discussionmentioning

confidence: 69%

“…Tumor-infiltrating immune cells, such as T cells, B cells, neutrophils, and regulatory T cells, are crucial elements in the tumor microenvironment and are critical in the antitumor response and cancer therapy. [24,25] Herein, we demonstrated, for the first time, a significant correlation between MYH16 expression and T, B, CD8 T, and other cells.…”

Section: Gsea Of Myh16-related Pathways In Patients With Luadmentioning

confidence: 62%

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MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration

Zhang,

Liu,

Wang

et al. 2023

J Biochem & Molecular Tox

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Myosin heavy chain 16 (MYH16) may significantly affect cell cycle progression. Nevertheless, there is a lack of evidence about the clinical relevance of MYH16 upregulation in pan cancers, including lung adenocarcinoma (LUAD). MYH16 expression patterns were evaluated in various bioinformatics databases using The Cancer Genome Atlas data set. Clinical and pathological factor data were employed to risk‐stratify patients. The Kaplan–Meier plotter approach was used to estimate survival rates. Tumor immune infiltration was explored via the TIMER tool, and gene set enrichment analysis (GSEA) was used to identify the pathways involved in MYH16 upregulation. The results showed that MYH16 was abnormally upregulated in pan cancers, including LUAD. MYH16 expression induction in LUAD was found to be related to the tumor stage. Furthermore, MYH16 upregulation was correlated with LUAD development and worse overall survival, particularly in women. Notably, MYH16 overexpression in LUAD tissues corresponded to the amount of immune infiltration in the tumor. Additionally, univariate Cox hazard regression analysis revealed that MYH16 may be an independent prognostic indicator for LUAD. Furthermore, a nomogram was constructed according to MYH16 expression and clinical characteristics. BMP6 expression deficiency may be a key factor contributing to MYH16 upregulation in LUAD. Finally, GSEA demonstrated that MYH16 might mediate meiosis and gene silencing through RNA signaling pathways. This study, for the first time, showed that MYH16 upregulation in LUAD is associated with various risk factors, increased cancer aggressiveness, enhanced infiltration of tumor immune cells, and reduced survival rates.

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Section: Discussionmentioning

confidence: 69%

Section: Gsea Of Myh16-related Pathways In Patients With Luadmentioning

confidence: 62%

MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration

Zhang,

Liu,

Wang

et al. 2023

J Biochem & Molecular Tox

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“…In previous studies, a gene coefficient was often obtained from a Cox regression analysis or other method in the training set ( 24 - 26 ). However, due to the limitations of the sample size and the heterogeneity of the tumor, we may never know the true coefficient of a gene.…”

Section: Discussionmentioning

confidence: 99%

Identification and evaluation of a risk model predicting the prognosis of breast cancer based on characteristic signatures

Yang¹,

Chen²,

Yao³

et al. 2023

Transl Cancer Res

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Background Breast cancer (BC) is one of the most common fatal cancers in women. Identifying new biomarkers is thus of great significance for the diagnosis and prognosis of BC. Methods In this study, 1,030 BC cases from The Cancer Genome Atlas (TCGA) were obtained for differential expression analysis and Short Time-series Expression Miner (STEM) analysis to identify characteristic BC development genes, which were further divided into upregulated and downregulated genes. Two predictive prognosis models were both defined by Least Absolute Shrinkage and Selection Operator (LASSO). Survival analysis and receiver operating characteristic (ROC) curve analysis were used to determine the diagnostic and prognostic capabilities of the two gene set model scores, respectively. Results Our findings from this study suggested that both the unfavorable (BC1) and favorable (BC2) gene sets are reliable biomarkers for the diagnosis and prognosis of BC, although the BC1 model presents better diagnostic and prognostic value. Associations between the models and M2 macrophages and sensitivity to Bortezomib were also found, indicating that unfavorable BC genes are significantly involved in the tumor immune microenvironment. Conclusions We successfully established one predictive prognosis model (BC1) based on characteristic gene sets of BC to diagnose and predict the survival time of BC patients using a cluster of 12 differentially expressed genes (DEGs).

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Molecular characterization of human HSPCs with different cell fates in vivo using single‐cell transcriptome analysis and lentiviral barcoding technology

Hua,

Wang,

Chen

et al. 2024

Clinical & Translational Med

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Hematopoietic stem and progenitor cells (HSPCs) possess the potential to produce all types of blood cells throughout their lives. It is well recognized that HSPCs are heterogeneous, which is of great significance for their clinical applications and the treatment of diseases associated with HSPCs. This study presents a novel technology called Single‐Cell transcriptome Analysis and Lentiviral Barcoding (SCALeBa) to investigate the molecular mechanisms underlying the heterogeneity of human HSPCs in vivo. The SCALeBa incorporates a transcribed barcoding library and algorithm to analyze the individual cell fates and their gene expression profiles simultaneously. Our findings using SCALeBa reveal that HSPCs subset with stronger stemness highly expressed MYL6B, ATP2A2, MYO19, MDN1, ING3, and so on. The high expression of COA3, RIF1, RAB14, and GOLGA4 may contribute to the pluripotent‐lineage differentiation of HSPCs. Moreover, the roles of the representative genes revealed in this study regarding the stemness of HPSCs were confirmed with biological experiments. HSPCs expressing MRPL23 and RBM4 genes may contribute to differentiation bias into myeloid and lymphoid lineage, respectively. In addition, transcription factor (TF) characteristics of lymphoid and myeloid differentiation bias HSPCs subsets were identified and linked to previously identified genes. Furthermore, the stemness, pluripotency, and differentiation‐bias genes identified with SCALeBa were verified in another independent HSPCs dataset. Finally, this study proposes using the SCALeBa‐generated tracking trajectory to improve the accuracy of pseudo‐time analysis results. In summary, our study provides valuable insights for understanding the heterogeneity of human HSPCs in vivo and introduces a novel technology, SCALeBa, which holds promise for broader applications.Key points SCALeBa and its algorithm are developed to study the molecular mechanism underlying human HSPCs identity and function. The human HSPCs expressing MYL6B, MYO19, ATP2A2, MDN1, ING3, and PHF20 may have the capability for high stemness. The human HSPCs expressing COA3, RIF1, RAB14, and GOLGA4 may have the capability for pluripotent‐lineage differentiation. The human HSPCs expressing MRPL23 and RBM4 genes may have the capability to differentiate into myeloid and lymphoid lineage respectively in vivo. The legitimacy of the identified genes with SCALeBa was validated using biological experiments and a public human HSPCs dataset. SCALeBa improves the accuracy of differentiation trajectories in monocle2‐based pseudo‐time analysis.

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MDN1 Mutation Is Associated With High Tumor Mutation Burden and Unfavorable Prognosis in Breast Cancer

Cited by 4 publications

References 45 publications

MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration

MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration

Identification and evaluation of a risk model predicting the prognosis of breast cancer based on characteristic signatures

Molecular characterization of human HSPCs with different cell fates in vivo using single‐cell transcriptome analysis and lentiviral barcoding technology

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