A correlation between BCL-2 modifying factor, p53 and livin gene expressions in cancer colon patients

Badr, Eman; Assar, Mona Ali Mahmoud; El-Torgoman, A. M.; Labeeb, Azza Z.; Breaka, Gehad A.; Elkhouly, E.A.

doi:10.1016/j.bbrep.2020.100747

Cited by 7 publications

(8 citation statements)

References 24 publications

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“…We filled this research gap by constructing a prognosis risk score model based on four mitochondria-related genes. Besides its role in BRCA, BMF is also an important prognostic marker for patients with other cancers, such as colon cancer [ 20 ] and hepatocellular carcinoma [ 21 ]. MRPL36 is a mitochondrial ribosomal protein that has not been studied in BRCA, but MRPL36 has been correlated with poor progression-free survival in ovarian cancer [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

Breast Cancer Prognosis Prediction and Immune Pathway Molecular Analysis Based on Mitochondria-Related Genes

Luo

Han

et al. 2022

Genetics Research

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Background. Mitochondria play an important role in breast cancer (BRCA). We aimed to build a prognostic model based on mitochondria-related genes. Method. Univariate Cox regression analysis, random forest, and the LASSO method were performed in sequence on pretreated TCGA BRCA datasets to screen out genes from a Gene Set Enrichment Analysis, Gene Ontology: biological process gene set to build a prognosis risk score model. Survival analyses and ROC curves were performed to verify the model by using the GSE103091 dataset. The BRCA datasets were equally divided into high- and low-risk score groups. Comparisons between clinical features and immune infiltration related to different risk scores and gene mutation analysis and drug sensitivity prediction were performed for different groups. Result. Four genes, MRPL36, FEZ1, BMF, and AFG1L, were screened to construct our risk score model in which the higher the risk score, the poorer the prognosis. Univariate and multivariate analyses showed that the risk score was significantly associated with age, M stage, and N stage. The gene mutation probability in the high-risk score group was significantly higher than that in the low-risk score group. Patients with higher risk scores were more likely to die. Drug sensitivity prediction in different groups indicated that PF-562271 and AS601245 might be new inhibitors of BRCA. Conclusion. We developed a new workable risk score model based on mitochondria-related genes for BRCA prognosis and identified new targets and drugs for BRCA research.

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Section: Discussionmentioning

confidence: 99%

Breast Cancer Prognosis Prediction and Immune Pathway Molecular Analysis Based on Mitochondria-Related Genes

Luo

Han

et al. 2022

Genetics Research

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“…Badr et al reported that upregulation of livin and downregulation of BMF and p53 expression are signi cantly correlated with more tumor aggressiveness (advanced TNM stage), making metastasis progress more rapidly, and decreasing overall survival in colon cancer patients. Thus, we can apply these genes as crucial prognostic markers related to poor results [37]. Another research showed that STARD13 3′UTR could play as a ceRNA for BMF to enhance apoptosis and be used as a potential therapeutic target in breast cancer cells [38].…”

Section: Discussionmentioning

confidence: 99%

Down regulation of Cathepsin W is associated with poor prognosis in Pancreatic cancer

Khojasteh-Leylakoohi

Mohit

Khalili-Tanha

et al. 2022

Preprint

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Background: Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on the identification of new biomarkers for the early diagnosis of PDAC and prediction of patient survival. Genome-wide RNA and microRNA sequencing were used using bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs) followed by validation in additional cohort of PDAC patients. Methods: genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA) to identify DEGs. We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest, (RF), Max Voting, Adaboost, Gradient boosting machines (GBM) and Extreme Gradient Boosting (XGB) techniques were used and Gradient boosting machines (GBM) were selected with 100 % accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs and a combination of these obtained from machine learning algorithms and survival analysis. Results: Machine learning results showed 23 genes with negative regulation, 5 genes with positive regulation, 7 microRNAs with negative regulation and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of disease. In addition, the survival analysis results showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9 and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Conclusion: Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in pathogenesis of the diseases can be used for detection of patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.

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“…In addition, livin can also induce the production of specific CD4 + T cells and CD8 + T cells [14]. Most of the previous studies on livin focused on the pathogenesis of tumor, such as the relationship between livin expression and the pathogenesis and prognosis of colon cancer and nasopharyngeal carcinoma [24,25]. Recent reports depicted that stronger expression of livin in the pathogenesis of chronic rhinosinusitis with nasal polyps (CRSwNP).…”

Section: Discussionmentioning

confidence: 99%

Livin promotes Th2-type immune response in airway allergic diseases

Wang

Xiang

et al. 2022

Immunol Res

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Objectives To investigate the effects of livin on the Th2 immune response in airway allergic diseases (AAD) and explore the interaction among livin, GATA3, IL-4 in peripheral blood CD4+ T cells of AAD patients. Methods WT mice and livin KO mice were developed for model of AAD. Th2 cell levels in the lung tissues and spleen were assessed by flow cytometry. Also, it was assessed in the culture after exposing to livin inhibitor (Lp-15); the protein and mRNA levels of livin, GATA3 and IL-4 in peripheral blood CD4+ T cells isolated from patients with or without AAD were measured by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting, respectively. Finally, Co-immunoprecipitation (Co-IP) was employed to identify the interaction between livin and GATA3. Results Compared with WT mouse, Th2 cell frequency in lung tissues and spleen was significantly decreased in livin KO mouse; after adding Lp-15, the differentiation from Naive CD4+T cells in spleen to Th2 cells was blocked; the protein and mRNA levels of livin, GATA3 and IL-4 in AAD group were higher than that in control group. The levels of livin were positively correlated with IL-4, and GATA3 was also positively correlated with IL-4 and livin. GATA3 was detected in the protein complex co-precipitated with livin antibody, and livin was also detected in the protein complex co-precipitated by GATA3 antibody. Conclusion Livin increases the expression of IL-4 and facilitates naive CD4+ T cells to differentiate into Th2 cells, which triggers airway allergy.

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A correlation between BCL-2 modifying factor, p53 and livin gene expressions in cancer colon patients

Cited by 7 publications

References 24 publications

Breast Cancer Prognosis Prediction and Immune Pathway Molecular Analysis Based on Mitochondria-Related Genes

Breast Cancer Prognosis Prediction and Immune Pathway Molecular Analysis Based on Mitochondria-Related Genes

Down regulation of Cathepsin W is associated with poor prognosis in Pancreatic cancer

Livin promotes Th2-type immune response in airway allergic diseases

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