Introduction of mutant TP53 related genes in metabolic pathways and evaluation their correlation with immune cells, drug resistance and sensitivity

Motlagh, Ali Valipour; Mahdevar, Mohammad; Mirzaei, Sepideh; Entezari, Maliheh; Hashemi, Mehrdad; Hushmandi, Kiavash; Peymani, Maryam

doi:10.1016/j.lfs.2022.120650

Cited by 7 publications

(4 citation statements)

References 40 publications

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“…Among its related pathways are signaling by GPCR and Metabolism of fat-soluble vitamins[ 45 , 46 ]. PKM encoded proteins involved in glycolysis participate in many malignant tumors, especially in TP53 mutation hepatocytic cell carcinoma[ 47 – 49 ]. Additionally, Pyruvate Kinase Deficiency Of Red Cells is a disease usually associated with PKM [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

Genomic characteristics of two breast malignant phyllodes tumors during pregnancy and lactation identified through whole-exome sequencing

Lei

Shen

Deng

et al. 2022

Orphanet J Rare Dis

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Background The genomic landscape of breast malignant phyllodes tumors (PTs) is not well defined, especially pregnancy-related malignant PTs. To clarify this topic, whole-exome next-generation sequencing (NGS) was performed on tumor samples and paired normal breast tissues from two pregnancy-related malignant PTs, followed by a functional analysis of the genetic alterations. Methods DNA from malignant PT samples and matched normal breast tissues of both patients were subjected to molecular profiling. NGS of the whole-exome was performed in a commercial molecular pathology laboratory. Predictive tools were used to estimate genetic variation in somatic and germline genes. Results In total, 29 somatic genomic alterations and 18 germline alterations were found in both patients. In Patient 1, 12 aberrations were identified in the tumor tissue, and 9 alterations were identified in matched normal breast tissue. One pathogenic variant in tumor suppressor genes (TP53) was detected in patient 1. In Patient 2, 18 and 10 variants were found in the tumor and matched normal breast tissue, respectively. In Patient 2, pathogenic alterations were identified in two tumor suppressor genes (PTEN and TP53). PTEN and TP53 may be potential drug targets. The functional predictive tools showed that genes of unknown significance for PTs, including FCHO1 in Patient 1, and LRP12 and PKM in Patient 2, were pathogenic. Several genes, including FCHO1, LRP12 and PKM, were shown for the first time to be altered in malignant PTs. A potentially pathogenic germline variant in PRF1, was detected in Patient 1. Conclusion Our study first demonstrated somatic and germline gene alterations in two malignant PTs during pregnancy and lactation. These two PTs shared major genetic events, including TP53 mutation, which commonly occurs in malignant PTs; additionally, we identified two potential genes for targeted therapy, TP53 and PTEN. One germline mutation in PRF1 was also detected. These results provide clues regarding tumor pathogenesis and precision therapy development.

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Section: Discussionmentioning

confidence: 99%

Genomic characteristics of two breast malignant phyllodes tumors during pregnancy and lactation identified through whole-exome sequencing

Lei

Shen

Deng

et al. 2022

Orphanet J Rare Dis

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“… 81 Additionally, a previous analysis involving 12 types of cancer found a strong association between TP53 mutations and PKM expression. 82 Moreover, TTN expression has been shown to be related to CTSH, 83 while Hu et al demonstrated that mice with ALDH2 mutations had higher levels of phosphorylated RYR2 protein than wild-type mice. 84 …”

Section: Discussionmentioning

confidence: 99%

Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma

Mi,

Zeng,

Chen

et al. 2023

IJGM

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Background Lung adenocarcinoma (LUAD) is a group of cancers with poor prognosis. The combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) can identify important genes involved in cancer development and progression from a broader perspective. Methods The scRNA-seq data and bulk RNA-seq data of LUAD were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Analyzing scRNA-seq for core cells in the GSE131907 dataset, and the uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Macrophage polarization-associated subtypes were acquired from the TCGA-LUAD dataset after analysis, followed by further identification of differentially expressed genes (DEGs) in the TCGA-LUAD dataset (normal/LUAD tissue samples, two subtypes). Venn diagrams were utilized to visualize differentially expressed and highly variable macrophage polarization-related genes. Subsequently, a prognostic risk model for LUAD patients was constructed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO), and the model was investigated for stability in the external data GSE72094. After analyzing the correlation between the trait genes and significantly mutated genes, the immune infiltration between the high/low-risk groups was then examined. The Monocle package was applied to analyze the pseudo-temporal trajectory analysis of different cell clusters in macrophage clusters. Subsequently, cell clusters of data macrophages were selected as key cell clusters to explore the role of characteristic genes in different cell populations and to identify transcription factors (TFs) that affect signature genes. Finally, qPCR were employed to validate the expression levels of prognosis signature genes in LUAD. Results 424 macrophage highly variable genes, 3920 DEGs, and 9561 DEGs were obtained from macrophage clusters, the macrophage polarization-related subtypes, and normal/LUAD tissue samples, respectively. Twenty-eight differentially expressed and highly mutated MPRGs were obtained. A prognostic risk model with 7 DE-MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) was constructed. This prognostic model still has a good prediction effect in the GSE72094 dataset. ZNF536 and DNAH9 were mutated in the low-risk group, while COL11A1 was mutated in the high-risk group, and they were highly correlated with the characteristic genes. A total of 11 immune cells were significantly different in the high/low-risk groups. Five cell types were again identified in the macrophage cluster, and then NK cells: CD56hiCD62L+ differentiated earlier and were present mainly on 2 branches. While macrophages were present on 2 branches and differentiated later. It was found that the expression levels of BCLAF1 and MAX were higher in cluster 1, which might be the TFs affecting the expression of the characteristic genes. Moreover, qPCR confi...

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“…3A-D). 11,14 . Utilizing the median Risk Score (RS) as the cut-off value, the RS was divided into high-risk and low-risk groups [17][18][19] .…”

Section: Construction Ppi Network and Survivalmentioning

confidence: 99%

“…Bioinformatics tools like genomic technologies have been widely utilized for gene expression pro les analysis 9,10 . Furthermore, transcriptomics analysis is a useful method for differential gene expression analysis, which able the researchers to discover quantitative changes in expression levels between experimental groups and control groups 11 . Moreover, the correlation between the expression level of genes with prognosis and survival could be obtained by using the tumor pro ling 12 .…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics molecular analysis of prognostic-related genes and drug sensitivity and resistance in head and neck squamous cell carcinomas

Saleh

Mustafa

Abdullaev

et al. 2022

Preprint

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One of the most heterogeneous collections of malignancies probably is head and neck cancers that in this study, we focus on the head and neck squamous cell carcinomas (HNSCCs). The aim of this study was to recognize the prognosis-related genes and their pathways related to HNSCC and to further analyze its molecular mechanism and drug sensitivity and resistance. Furthermore, the correlation between the expression of candidate genes with immune infiltration and IC50 of some drugs was evaluated. The cancer genome atlas (TCGA) HNSCC was utilized for differential expression analyzing. Differentially expressed genes (DEGs) were indicated by R software. By applying univariate and multivariate Cox regression analysis, and using prognostic risk model, we identified the key prognostic genes in HNSCC based on PPI network, and enrichment analysis of DEGs was performed by Gene Set Enrichment Analysis (GSEA) and Enrichr database. The Tumor Immune Estimation Resource (TIMER) was used to assess the relationship between selected genes and immune infiltration in cancer. Finally, the CCLE and GDSC were used to assess the correlation between the level of selected genes with drug resistance and sensitivity. Our results indicated that four hub genes including NUF2, BUB1, TPX2, and DLGAP5 were selected as poor prognostic genes in HNSCC. Our findings revealed that drugs like Glucosamine, Ribavirin and Tocetrapib could lower the expression of selected genes in HNSCC. In doing so, NUF2, BUB1, DLGAP5, TPX2 were identified as hub-related prognostic genes associated with patients’ survival, drug resistance and sensitivity, and could be effective in the cancer progression.

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Introduction of mutant TP53 related genes in metabolic pathways and evaluation their correlation with immune cells, drug resistance and sensitivity

Cited by 7 publications

References 40 publications

Genomic characteristics of two breast malignant phyllodes tumors during pregnancy and lactation identified through whole-exome sequencing

Genomic characteristics of two breast malignant phyllodes tumors during pregnancy and lactation identified through whole-exome sequencing

Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma

Bioinformatics molecular analysis of prognostic-related genes and drug sensitivity and resistance in head and neck squamous cell carcinomas

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