TCF1/LEF1 triggers Wnt-dependent chemokine/cytokine-induced inflammation and cadherin pathways to drive T-ALL cell migration

Zhao, Pin; Sun, Lanming; Zhao, Cong

doi:10.1016/j.bbrep.2023.101457

Cited by 3 publications

(3 citation statements)

References 42 publications

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“…2A and 2B). Several well-known metastasis genes were included in the list of DEGs, including TCF7 (Zhao et al 2023 ), MAPK13 (Tan et al 2010 ), RAB17 (Zhou et al 2021 ), CXCL10 (Ka et al 2023 ; Lee et al 2022 ; Shang et al 2022 ), CTSK (Khan et al 2021 ; Li et al 2019 ; Wu et al 2022 ), CCDC80 (Huang et al 2023 ), and ABCC2 (Sensorn et al 2016 ). In line with RNA-seq analysis, our qRT-PCR confirmed the elevated expression of the aforementioned DEGs ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Hao,

Dong,

Bai

et al. 2024

swwlxb

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Tumor metastasis, responsible for approximately 90% of cancer-associated mortality, remains poorly understood. Here in this study, we employed a melanoma lung metastasis model to screen for metastasis-related genes. By sequential tail vein injection of mouse melanoma B16F10 cells and the subsequently derived cells from lung metastasis into BALB/c mice, we successfully obtained highly metastatic B16F15 cells after five rounds of in vivo screening. RNA-sequencing analysis of B16F15 and B16F10 cells revealed a number of differentially expressed genes, some of these genes have previously been associated with tumor metastasis while others are novel discoveries. The identification of these metastasis-related genes not only improves our understanding of the metastasis mechanisms, but also provides potential diagnostic biomarkers and therapeutic targets for metastatic melanoma.

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Section: Resultsmentioning

confidence: 99%

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Hao,

Dong,

Bai

et al. 2024

swwlxb

View full text Add to dashboard Cite

show abstract

“…Among them, 1329 DEGs were significantly up-regulated, and 1581 were remarkably down-regulated in B16F15 cells (Figure 2A-2B). Several well-known metastasis genes were included in the list of DEGs, including TCF7 (Zhao et al 2023), MAPK13 (Tan et al 2010), RAB17 (Zhou et al 2021), CXCL10 (Ka et al 2023;Lee et al 2022;Shang et al 2022), CTSK (Khan et al 2021;Li et al 2019;Wu et al 2022), CCDC80 (Huang et al 2023), and ABCC2 (Sensorn et al 2016). In line with RNA-seq analysis, our qRT-PCR confirmed the elevated expression of the aforementioned DEGs (Figure 2C).…”

Section: Identification Of Differentially Expressed Genes (Degs) and ...mentioning

confidence: 99%

mentioning

confidence: 99%

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Hao,

Shen,

Sang

et al. 2024

Preprint

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Tumor metastasis, responsible for approximately 90% of cancer-associated mortality, remains poorly understood. Here in this study we employed a melanoma lung metastasis model to screen for metastasis-related genes. By sequential tail vein injection of mouse melanoma B16F10 cells and the subsequently derived cells from lung metastasis into BALB/c mice, we successfully obtained highly metastatic B16F15 cells after five rounds of in vivo screening. RNA-sequencing analysis of B16F15 and B16F10 cells revealed a number of differentially expressed genes, some of these genes have previously been associated with tumor metastasis while others are novel discoveries. The identification of these metastasis-related genes not only improve our understanding of the metastasis mechanisms, but also provide potential diagnostic biomarkers and therapeutic targets for metastatic melanoma.

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Identification of candidate biomarkers and signaling pathways associated with Alzheimer’s disease using bioinformatics analysis of next generation sequencing data

Vastrad,

Vastrad

2024

Preprint

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Alzheimer's disease (AD) is the most common cause of dementia, and one of the most common health problems all over the world. However, the specific molecular mechanisms of AD have not been fully investigated. The current investigation aimed to elucidate potential key candidate genes and signaling pathways in AD. Next generation sequencing (NGS) dataset GSE203206 was downloaded from the Gene Expression Omnibus (GEO) database, which included data from 39 AD samples and 8 normal control samples. Differentially expressed genes (DEGs) were identified using t-tests in the limma R bioconductor package. These DEGs were subsequently investigated by Gene ontology (GO) and pathway enrichment analysis, and a protein-protein interaction (PPI) network and modules were constructed and analyzed. The miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis were performed to identify key miRNAs and TFs. The receiver operating characteristic (ROC) curve analysis was performed to estimate the clinical diagnostic value of the hub genes. A total of 958 DEGs, including 479 up regulated genes and 479 down regulated genes, were screened between AD and normal control samples. GO and pathway enrichment analysis results revealed that the up regulated genes were mainly enriched in response to stimulus, cytoplasm, small molecule binding and signal transduction, whereas down regulated genes were mainly enriched in multicellular organism development, cell junction, ion binding and cardiac conduction. The PPI network contained 4886 nodes and 10342 edges. HSP90AA1, FN1, KIT, YAP1, LSM2, SKP1, EIF5A2, TAF9, DDX39B and CDK7 were identified as the top hub genes. The regulatory network analysis revealed that microRNA (miRNA) hsa-mir-545-3p and hsa-miR-548f-5p, and transcription factor (TF) PLAG1 and MEF2A might be involved in the development of AD. These findings provide new insights into the pathogenesis of AD. The hub genes, miRNAs and TFs have the potential to be used as diagnostic and therapeutic markers.

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TCF1/LEF1 triggers Wnt-dependent chemokine/cytokine-induced inflammation and cadherin pathways to drive T-ALL cell migration

Cited by 3 publications

References 42 publications

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Screening for metastasis-related genes in mouse melanoma cells through sequential tail vein injection

Identification of candidate biomarkers and signaling pathways associated with Alzheimer’s disease using bioinformatics analysis of next generation sequencing data

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