The roles of metallothioneins in carcinogenesis

Si, Manfei; Lang, Jinghe

doi:10.1186/s13045-018-0645-x

Cited by 324 publications

(282 citation statements)

References 208 publications

(194 reference statements)

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“…Metallothionein (MT) is a unique cysteine‐rich small protein, which plays an important role in maintaining steady‐state levels and detoxification of metal ions (Albrecht et al, ; Coyle, Philcox, Carey, & Rofe, ). In addition, recent experimental evidence suggests that MTs play a key role in tumorigenesis, development, drug resistance, and metastasis by participating in a variety of biological processes (Si & Lang, ). As a major member of the MT family, low expression of MT1M is related to poor prognosis in large cell lung cancer, esophageal squamous cancer, and hepatocellular carcinoma (da Motta, De Bastiani, Stapenhorst, & Klamt, ; Ding & Lu, ; Oka et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…Metallothionein (MT) is a unique cysteine-rich small protein, which plays an important role in maintaining steady-state levels and detoxification of metal ions (Albrecht et al, 2008;Coyle, Philcox, Carey, & Rofe, 2002). In addition, recent experimental evidence suggests that MTs play a key role in tumorigenesis, development, drug resistance, and metastasis by participating in a variety of biological processes (Si & Lang, 2018). et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

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Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

Liu

et al. 2019

Journal Cellular Physiology

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The relationship between age and breast cancer is ambiguous. Here, we analyzed the differential expression pattern of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in different age groups to provide an effective association between age and breast cancer risk at the molecular level. We integrated the microarray information from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. The patients were divided into young ( < 50 years) and old ( ≥ 50 years) age groups and evaluated by differential gene expression, weighted gene correlation network analysis (WGCNA), functional enrichment analyses, and coexpression analysis. To determine their potential clinical significance, univariate Cox regression analysis and survival assessment were conducted. We identified two lncRNAs (AL139280.1 and AP000851.1) and three mRNAs (MT1M, HBB, and TFPI2) as the risk markers, and Gene set enrichment analysis (GSEA) focusing on a single gene revealed that "pyrimidine metabolism," "cell cycle," and "P53 signaling pathway"were coenriched. These data demonstrated that age may be a risk factor for breast carcinogenesis and prognosis and provide an in-depth molecular characterization based on the expression patterns of lncRNAs and mRNAs. K E Y W O R D Sage, breast cancer, GEO, lncRNA-mRNA, TCGA

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

Liu

et al. 2019

Journal Cellular Physiology

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“…However, the results were consistent with our previous study (Zhang et al, ), in which no significant lipid accumulation was observed after subchronic Cd exposure, although the mRNA level of genes associated to hepatic lipid metabolism was elevated in adult female mice. Mt, the metal‐binding proteins and the most responsive proteins to Cd exposure, are small cysteine‐rich proteins that play important roles in metal homeostasis and protection against heavy metal toxicity, DNA damage and oxidative stress (Si & Lang, ). In a mouse model of Cd‐induced FGR, Mt1 and Mt2 , two Mt genes, were upregulated in maternal liver.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, transforming growth factor (TGF)-β also plays a crucial role during the cell proliferation (Muraoka et al, 2002;Schiller, rich proteins that play important roles in metal homeostasis and protection against heavy metal toxicity, DNA damage and oxidative stress (Si & Lang, 2018). In a mouse model of Cd-induced FGR, Mt1 and Mt2, two Mt genes, were upregulated in maternal liver.…”

Section: Discussionmentioning

confidence: 99%

Chronic cadmium exposure induced hepatic cellular stress and inflammation in aged female mice

Zhang

Wang

et al. 2018

J of Applied Toxicology

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Previous studies have revealed that acute cadmium (Cd) exposure led to inflammation in different organs through an oxidative stress mechanism. However, whether chronic Cd exposure induces inflammation in liver and the mechanistic link between inflammation and cell stress remains unclear. In the present study, we investigated the effects of chronic Cd exposure on hepatic cellular stress and inflammatory responses. Female CD1 mice were administrated with CdCl2 (10 and 100 mg/L) in drinking water for 57 weeks. Our results showed that the mRNA levels of Inos and the protein content of HO‐1, markers of oxidative stress, were markedly increased in Cd‐treated mice. In addition, the protein level of GRP78, the chaperone of endoplasmic reticulum (ER) stress, was significantly increased in Cd‐treated mice. The expression of the proteins CHOP and peIF2α, two proteins downstream of ER stress, was also upregulated in the Cd‐100 mg/L and Cd‐10 mg/L group, respectively. Moreover, there were increased inflammatory cells existing in liver after Cd administration. Besides, there was a significant elevation in the mRNA level of Mip‐2, Il‐10 and Il‐12 in the Cd‐100 mg/L group. The mRNA level of Tgf‐β was also upregulated in Cd‐treated mice. Moreover, we also found that the number of Ki67‐positive hepatic cells was increased in the Cd‐10 mg/L group. Hence, our results indicated that chronic Cd exposure induced oxidative stress, ER stress, inflammatory responses and proliferation in the liver of aged female mice.

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“…9B). Metallothioneins are a family of small proteins that play important roles in metal homeostasis and protection against heavy metal toxicity, DNA damage and oxidative stress (Si and Lang, 2018). Their induction in tumor-associated macrophages (TAMs) has been noted (Ge et al, 2012) but to our knowledge this is the first report of an association with clinical outcome.…”

Section: In-depth Evaluation Of the Sade-feldman Et Al Immunotherapymentioning

confidence: 97%

Non-negative Independent Factor Analysis disentangles discrete and continuous sources of variation in scRNA-seq data

Mao

Pouyan

Kostka

et al. 2020

Preprint

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Motivation: Single cell RNA sequencing (scRNA-seq) enables transcriptional profiling at the level of individual cells. With the emergence of high-throughput platforms datasets comprising tens of thousands or more cells have become routine, and the technology is having an impact across a wide range of biomedical subject areas. However, scRNA-seq data are high-dimensional and affected by noise, so that scalable and robust computational techniques are needed for meaningful analysis, visualization and interpretation. Specifically, a range of matrix factorization techniques have been employed to aid scRNAseq data analysis. In this context we note that sources contributing to biological variability between cells can be discrete (or multi-modal, for instance cell-types), or continuous (e.g. pathway activity). However, no current matrix factorization approach is set up to jointly infer such mixed sources of variability. Results: To address this shortcoming, we present a new probabilistic single-cell factor analysis model, Non-negative Independent Factor Analysis (NIFA), that combines features of complementary approaches like Independent Component Analysis (ICA), Principal Component Analysis (PCA), and Non-negative Matrix Factorization (NMF). NIFA simultaneously models uni-and multi-modal latent factors and can so isolate discrete cell-type identity and continuous pathway-level variations into separate components. Similar to NMF, NIFA constrains factor loadings to be non-negative in order to increase biological interpretability. We apply our approach to a range of data sets where cell-type identity is known, and we show that NIFA-derived factors outperform results from ICA, PCA and NMF in terms of cell-type identification and biological interpretability. Studying an immunotherapy dataset in detail, we show that NIFA identifies biomedically meaningful sources of variation, derive an improved expression signature for regulatory T-cells, and identify a novel myeloid cell subtype associated with treatment response. Overall, NIFA is a general approach advancing scRNA-seq analysis capabilities and it allows researchers to better take

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The roles of metallothioneins in carcinogenesis

Cited by 324 publications

References 208 publications

Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

Chronic cadmium exposure induced hepatic cellular stress and inflammation in aged female mice

Non-negative Independent Factor Analysis disentangles discrete and continuous sources of variation in scRNA-seq data

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