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Article ; Online: Targeting cancer stem cells for reversing therapy resistance

He-Ming Zhou / Ji-Gang Zhang / Xue Zhang / Qin Li

Signal Transduction and Targeted Therapy, Vol 6, Iss 1, Pp 1-

mechanism, signaling, and prospective agents

2021 Volume 17

Abstract: Abstract Cancer stem cells (CSCs) show a self-renewal capacity and differentiation potential that contribute to tumor progression and therapy resistance. However, the underlying processes are still unclear. Elucidation of the key hallmarks and resistance ...

Abstract	Abstract Cancer stem cells (CSCs) show a self-renewal capacity and differentiation potential that contribute to tumor progression and therapy resistance. However, the underlying processes are still unclear. Elucidation of the key hallmarks and resistance mechanisms of CSCs may help improve patient outcomes and reduce relapse by altering therapeutic regimens. Here, we reviewed the identification of CSCs, the intrinsic and extrinsic mechanisms of therapy resistance in CSCs, the signaling pathways of CSCs that mediate treatment failure, and potential CSC-targeting agents in various tumors from the clinical perspective. Targeting the mechanisms and pathways described here might contribute to further drug discovery and therapy.
Keywords	Medicine ; R ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Global and tissue-specific aging effects on murine proteomes

Gregory R. Keele / Ji-Gang Zhang / John Szpyt / Ron Korstanje / Steven P. Gygi / Gary A. Churchill / Devin K. Schweppe

Cell Reports, Vol 42, Iss 7, Pp 112715- (2023)

2023

Abstract: Summary: Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we ... ...

Abstract	Summary: Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we perform discovery-based proteomics in 10 tissues from 20 C57BL/6J mice, representing both sexes at adult and late midlife ages (8 and 18 months). Consistent with previous studies, age-related changes in protein abundance often have no corresponding transcriptional change. Aging results in increases in immune proteins across all tissues, consistent with a global pattern of immune infiltration with age. Our protein-centric data reveal tissue-specific aging changes with functional consequences, including altered endoplasmic reticulum and protein trafficking in the spleen. We further observe changes in the stoichiometry of protein complexes with important roles in protein homeostasis, including the CCT/TriC complex and large ribosomal subunit. These data provide a foundation for understanding how proteins contribute to systemic aging across tissues.
Keywords	CP: Metabolism ; CP: Genomics ; Biology (General) ; QH301-705.5
Subject code	612
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Non-Coding RNA m6A Modification in Cancer

Da-Hong Chen / Ji-Gang Zhang / Chuan-Xing Wu / Qin Li

Frontiers in Cell and Developmental Biology, Vol

Mechanisms and Therapeutic Targets

2021 Volume 9

Abstract: Recently, N6-methyl-adenosine (m6A) ribonucleic acid (RNA) modification, a critical and common internal RNA modification in higher eukaryotes, has generated considerable research interests. Extensive studies have revealed that non-coding RNA m6A ... ...

Abstract	Recently, N6-methyl-adenosine (m6A) ribonucleic acid (RNA) modification, a critical and common internal RNA modification in higher eukaryotes, has generated considerable research interests. Extensive studies have revealed that non-coding RNA m6A modifications (e.g. microRNAs, long non-coding RNAs, and circular RNAs) are associated with tumorigenesis, metastasis, and other tumour characteristics; in addition, they are crucial molecular regulators of cancer progression. In this review, we discuss the relationship between non-coding RNA m6A modification and cancer progression from the perspective of various cancers. In particular, we focus on important mechanisms in tumour progression such as proliferation, apoptosis, invasion and metastasis, tumour angiogenesis. In addition, we introduce clinical applications to illustrate more vividly that non-coding RNA m6A modification has broad research prospects. With this review, we aim to summarize the latest insights and ideas into non-coding RNA m6A modification in cancer progression and targeted therapy, facilitating further research.
Keywords	m6A RNA modification ; non-coding RNA ; tumorigenesis mechanism ; cancer therapy ; epigenetics ; Biology (General) ; QH301-705.5
Subject code	610 ; 612
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: MicroRNA‐425‐5p promotes breast cancer cell growth by inducing PI3K/AKT signaling

Li‐Feng Zhang / Ji‐Gang Zhang / Hao Zhou / Tian‐Tian Dai / Feng‐Bao Guo / Shao‐Yong Xu / Yan Chen

Kaohsiung Journal of Medical Sciences, Vol 36, Iss 4, Pp 250-

2020 Volume 256

Abstract: Abstract MicroRNA‐425‐5p (miR‐425‐5p) has been reported to be involved in the tumorigenesis of several tumors, but its function in breast cancer is still unknown. In this study, miR‐425‐5p was found significantly upregulated in breast cancer cells, and ... ...

Abstract	Abstract MicroRNA‐425‐5p (miR‐425‐5p) has been reported to be involved in the tumorigenesis of several tumors, but its function in breast cancer is still unknown. In this study, miR‐425‐5p was found significantly upregulated in breast cancer cells, and predicted a poor prognosis for breast cancer patients. Overexpression of miR‐425‐5p could significantly promote breast cancer cell growth. Further studies showed that overexpression of miR‐425‐5p upregulated the protein levels of Cyclin D1, Cyclin D3, CDK4, and CDK6. However, inhibiting miR‐425‐5p downregulated their expression and induced cell cycle arrest at G0/G1 phase. In mechanism, overexpression of miR‐425‐5p increased the phosphorylation of PI3K p85 and AKT, but inhibiting miR‐425‐5p displayed opposite effects. Moreover, miR‐425‐5p bound to the 3'UTR of PTEN mRNA, and downregulated the expression levels of PTEN in both mRNA and protein levels in breast cancer cells. Collectively, the results above demonstrated that miR‐425‐5p was involved in the tumorigenesis of breast cancer by inducing PI3K/AKT signaling and indicated that miR‐425‐5p could be as a potential target for breast cancer therapy in the future.
Keywords	AKT ; breast cancer ; microRNA‐425‐5p ; PI3K ; PTEN ; Medicine (General) ; R5-920
Subject code	616
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Statistical Test for Differential Network Analysis Based on Inference of Gaussian Graphical Model

Hao He / Shaolong Cao / Ji-gang Zhang / Hui Shen / Yu-Ping Wang / Hong-wen Deng

Scientific Reports, Vol 9, Iss 1, Pp 1-

2019 Volume 8

Abstract: Abstract Differential network analysis investigates how the network of connected genes changes from one condition to another and has become a prevalent tool to provide a deeper and more comprehensive understanding of the molecular etiology of complex ... ...

Abstract	Abstract Differential network analysis investigates how the network of connected genes changes from one condition to another and has become a prevalent tool to provide a deeper and more comprehensive understanding of the molecular etiology of complex diseases. Based on the asymptotically normal estimation of large Gaussian graphical model (GGM) in the high-dimensional setting, we developed a computationally efficient test for differential network analysis through testing the equality of two precision matrices, which summarize the conditional dependence network structures of the genes. Additionally, we applied a multiple testing procedure to infer the differential network structure with false discovery rate (FDR) control. Through extensive simulation studies with different combinations of parameters including sample size, number of vertices, level of heterogeneity and graph structure, we demonstrated that our method performed much better than the current available methods in terms of accuracy and computational time. In real data analysis on lung adenocarcinoma, we revealed a differential network with 3503 nodes and 2550 edges, which consisted of 50 clusters with an FDR threshold at 0.05. Many of the top gene pairs in the differential network have been reported relevant to human cancers. Our method represents a powerful tool of network analysis for high-dimensional biological data.
Keywords	Medicine ; R ; Science ; Q
Subject code	000
Language	English
Publishing date	2019-07-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identifying Mechanisms of Normal Cognitive Aging Using a Novel Mouse Genetic Reference Panel

Amy R. Dunn / Niran Hadad / Sarah M. Neuner / Ji-Gang Zhang / Vivek M. Philip / Logan Dumitrescu / Timothy J. Hohman / Jeremy H. Herskowitz / Kristen M. S. O’Connell / Catherine C. Kaczorowski

Frontiers in Cell and Developmental Biology, Vol

2020 Volume 8

Abstract: Developing strategies to maintain cognitive health is critical to quality of life during aging. The basis of healthy cognitive aging is poorly understood; thus, it is difficult to predict who will have normal cognition later in life. Individuals may have ...

Abstract	Developing strategies to maintain cognitive health is critical to quality of life during aging. The basis of healthy cognitive aging is poorly understood; thus, it is difficult to predict who will have normal cognition later in life. Individuals may have higher baseline functioning (cognitive reserve) and others may maintain or even improve with age (cognitive resilience). Understanding the mechanisms underlying cognitive reserve and resilience may hold the key to new therapeutic strategies for maintaining cognitive health. However, reserve and resilience have been inconsistently defined in human studies. Additionally, our understanding of the molecular and cellular bases of these phenomena is poor, compounded by a lack of longitudinal molecular and cognitive data that fully capture the dynamic trajectories of cognitive aging. Here, we used a genetically diverse mouse population (B6-BXDs) to characterize individual differences in cognitive abilities in adulthood and investigate evidence of cognitive reserve and/or resilience in middle-aged mice. We tested cognitive function at two ages (6 months and 14 months) using y-maze and contextual fear conditioning. We observed heritable variation in performance on these traits (h2RIx̄ = 0.51–0.74), suggesting moderate to strong genetic control depending on the cognitive domain. Due to the polygenetic nature of cognitive function, we did not find QTLs significantly associated with y-maze, contextual fear acquisition (CFA) or memory, or decline in cognitive function at the genome-wide level. To more precisely interrogate the molecular regulation of variation in these traits, we employed RNA-seq and identified gene networks related to transcription/translation, cellular metabolism, and neuronal function that were associated with working memory, contextual fear memory, and cognitive decline. Using this method, we nominate the Trio gene as a modulator of working memory ability. Finally, we propose a conceptual framework for identifying strains exhibiting cognitive reserve ...
Keywords	cognitive aging ; cognitive reserve ; cognitive resilience ; Weighted Gene Co-expression Network Analysis ; quantitative trait locus mapping ; Y-maze ; Biology (General) ; QH301-705.5
Subject code	120 ; 401
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Genetic risk factors identified in populations of European descent do not improve the prediction of osteoporotic fracture and bone mineral density in Chinese populations

Yu-Mei Li / Cheng Peng / Ji-Gang Zhang / Wei Zhu / Chao Xu / Yong Lin / Xiao-Ying Fu / Qing Tian / Lei Zhang / Yang Xiang / Victor Sheng / Hong-Wen Deng

Scientific Reports, Vol 9, Iss 1, Pp 1-

2019 Volume 9

Abstract: Abstract Aiming to investigate whether genetic risk factors (GRFs) for fracture and bone mineral density (BMD) identified from people of European descent can help improve the prediction of osteoporotic fracture (OF) risk and BMD in Chinese populations, ... ...

Abstract	Abstract Aiming to investigate whether genetic risk factors (GRFs) for fracture and bone mineral density (BMD) identified from people of European descent can help improve the prediction of osteoporotic fracture (OF) risk and BMD in Chinese populations, we built assessment models for femoral neck (FN)-fracture prediction and BMD value prediction using 700 elderly Chinese Han subjects and 1,620 unrelated Chinese Han subjects, respectively. 17 fracture-associated genes and 82 FN-BMD associated genes identified in people of European descent were used to build a logistic regression model with clinical risk factors (CRFs) for FN-fracture prediction in Chinese. Meanwhile 107 BMD-associated genes from people of European descent were used to build a multiple linear regression model with CRFs for BMD prediction in Chinese. A Lasso algorithm was employed for informative SNP selection to construct the genetic risk score (GRS) with ten-fold cross-validation. The results showed that, adding fracture GRF and FN-BMD GRF to the model with CRFs, the area under the receiver operating characteristic curve (AUC) decrease from 0.653 to 0.587 and 0.588, respectively, for FN fracture prediction. 62.3% and 61.8% of the risk variation were explained by the Model with CRFs and fracture GRF and by the Model with CRFs and FN-BMD GRF, respectively, as compared to 65.5% in the Model with CRFs only. The net reclassification improvement (NRI) index in the reclassification analysis is 0.56% (P = 0.57) and 1.13% (P = 0.29), respectively. There is no significant difference either between the performance of the model with CRFs and that of the model with both CRFs and GRF for BMD prediction. We concluded that, in the current study, GRF of fracture identified in people of European descent does not contributes to improve the fracture prediction in Chinese; and GRF of BMD from people of European descent cannot help improve the accuracy of the fracture prediction in Chinese perhaps partially because GRF of BMD from people of European descent may not contribute to BMD prediction in Chinese. This study highlights the limited utility of the current genetics studies largely focused on people of European descent for disease or risk factor prediction in other ethnic groups, and calls for more and larger scale studies focused on other ethnic groups.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2019-04-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Comparative studies of copy number variation detection methods for next-generation sequencing technologies.

Junbo Duan / Ji-Gang Zhang / Hong-Wen Deng / Yu-Ping Wang

PLoS ONE, Vol 8, Iss 3, p e

2013 Volume 59128

Abstract: Copy number variation (CNV) has played an important role in studies of susceptibility or resistance to complex diseases. Traditional methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from ... ...

Abstract	Copy number variation (CNV) has played an important role in studies of susceptibility or resistance to complex diseases. Traditional methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from low resolution of genomic regions. Following the emergence of next generation sequencing (NGS) technologies, CNV detection methods based on the short read data have recently been developed. However, due to the relatively young age of the procedures, their performance is not fully understood. To help investigators choose suitable methods to detect CNVs, comparative studies are needed. We compared six publicly available CNV detection methods: CNV-seq, FREEC, readDepth, CNVnator, SegSeq and event-wise testing (EWT). They are evaluated both on simulated and real data with different experiment settings. The receiver operating characteristic (ROC) curve is employed to demonstrate the detection performance in terms of sensitivity and specificity, box plot is employed to compare their performances in terms of breakpoint and copy number estimation, Venn diagram is employed to show the consistency among these methods, and F-score is employed to show the overlapping quality of detected CNVs. The computational demands are also studied. The results of our work provide a comprehensive evaluation on the performances of the selected CNV detection methods, which will help biological investigators choose the best possible method.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2013-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: On combining reference data to improve imputation accuracy.

Jun Chen / Ji-Gang Zhang / Jian Li / Yu-Fang Pei / Hong-Wen Deng

PLoS ONE, Vol 8, Iss 1, p e

2013 Volume 55600

Abstract: Genotype imputation is an important tool in human genetics studies, which uses reference sets with known genotypes and prior knowledge on linkage disequilibrium and recombination rates to infer un-typed alleles for human genetic variations at a low cost. ...

Abstract	Genotype imputation is an important tool in human genetics studies, which uses reference sets with known genotypes and prior knowledge on linkage disequilibrium and recombination rates to infer un-typed alleles for human genetic variations at a low cost. The reference sets used by current imputation approaches are based on HapMap data, and/or based on recently available next-generation sequencing (NGS) data such as data generated by the 1000 Genomes Project. However, with different coverage and call rates for different NGS data sets, how to integrate NGS data sets of different accuracy as well as previously available reference data as references in imputation is not an easy task and has not been systematically investigated. In this study, we performed a comprehensive assessment of three strategies on using NGS data and previously available reference data in genotype imputation for both simulated data and empirical data, in order to obtain guidelines for optimal reference set construction. Briefly, we considered three strategies: strategy 1 uses one NGS data as a reference; strategy 2 imputes samples by using multiple individual data sets of different accuracy as independent references and then combines the imputed samples with samples based on the high accuracy reference selected when overlapping occurs; and strategy 3 combines multiple available data sets as a single reference after imputing each other. We used three software (MACH, IMPUTE2 and BEAGLE) for assessing the performances of these three strategies. Our results show that strategy 2 and strategy 3 have higher imputation accuracy than strategy 1. Particularly, strategy 2 is the best strategy across all the conditions that we have investigated, producing the best accuracy of imputation for rare variant. Our study is helpful in guiding application of imputation methods in next generation association analyses.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publishing date	2013-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Yuan-Cheng Chen / Chao Xu / Ji-Gang Zhang / Chun-Ping Zeng / Xia-Fang Wang / Rou Zhou / Xu Lin / Zeng-Xin Ao / Jun-Min Lu / Jie Shen / Hong-Wen Deng

PLoS ONE, Vol 13, Iss 8, p e

2018 Volume 0201173

Abstract: Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to ...

Abstract	Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power. To identify potential pleiotropic genes for these three disorders, we performed a systematic analysis by incorporating GWAS (genome-wide associated study) datasets of six correlated traits related to type 2 diabetes, obesity and dyslipidemia using Meta-CCA (meta-analysis using canonical correlation analysis). Meta-CCA is an emerging method to systematically identify potential pleiotropic genes using GWAS summary statistics of multiple correlated traits. 2,720 genes were identified as significant genes after multiple testing (Bonferroni corrected p value < 0.05). Further, to refine the identified genes, we tested their relationship to the six correlated traits using VEGAS-2 (versatile gene-based association study-2). Only the genes significantly associated (Bonferroni corrected p value < 0.05) with more than one trait were kept. Finally, 25 genes (including two confirmed pleiotropic genes and eleven novel pleiotropic genes) were identified as potential pleiotropic genes. They were enriched in 5 pathways including the statin pathway and the PPAR (peroxisome proliferator-activated receptor) Alpha pathway. In summary, our study identified potential pleiotropic genes and pathways of type 2 diabetes, obesity and dyslipidemia, which may shed light on the common biological etiology and pathogenesis of these three disorders and provide promising insights for new therapies.
Keywords	Medicine ; R ; Science ; Q
Subject code	616
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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