scholarly journals Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers

Genes ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. 268 ◽  
Author(s):  
Lina Lu ◽  
Zhonglin Jiang ◽  
Yulin Dai ◽  
Luonan Chen
Keyword(s):  
Cell Adhesion ◽  
Signaling Pathway ◽  
Dynamic Network ◽  
Tipping Point ◽  
Disease State ◽  
Janus Kinase ◽  
Low Grade ◽  
Type I ◽  
Dysplastic Nodules ◽  
Network Biomarkers

Hepatocellular carcinoma (HCC) is a complex disease with a multi-step carcinogenic process from preneoplastic lesions, including cirrhosis, low-grade dysplastic nodules (LGDNs), and high-grade dysplastic nodules (HGDNs) to HCC. There is only an elemental understanding of its molecular pathogenesis, for which a key problem is to identify when and how the critical transition happens during the HCC initiation period at a molecular level. In this work, for the first time, we revealed that LGDNs is the tipping point (i.e., pre-HCC state rather than HCC state) of hepatocarcinogenesis based on a series of gene expression profiles by a new mathematical model termed dynamic network biomarkers (DNB)—a group of dominant genes or molecules for the transition. Different from the conventional biomarkers based on the differential expressions of the observed genes (or molecules) for diagnosing a disease state, the DNB model exploits collective fluctuations and correlations of the observed genes, thereby predicting the imminent disease state or diagnosing the critical state. Our results show that DNB composed of 59 genes signals the tipping point of HCC (i.e., LGDNs). On the other hand, there are a large number of differentially expressed genes between cirrhosis and HGDNs, which highlighted the stark differences or drastic changes before and after the tipping point or LGDNs, implying the 59 DNB members serving as the early-warning signals of the upcoming drastic deterioration for HCC. We further identified the biological pathways responsible for this transition, such as the type I interferon signaling pathway, Janus kinase–signal transducers and activators of transcription (JAK–STAT) signaling pathway, transforming growth factor (TGF)-β signaling pathway, retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathway, cell adhesion molecules, and cell cycle. In particular, pathways related to immune system reactions and cell adhesion were downregulated, and pathways related to cell growth and death were upregulated. Furthermore, DNB was validated as an effective predictor of prognosis for HCV-induced HCC patients by survival analysis on independent data, suggesting a potential clinical application of DNB. This work provides biological insights into the dynamic regulations of the critical transitions during multistep hepatocarcinogenesis.

scholarly journals Erratum: Lina Lu et al.; Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers. Genes 2017, 8, 268

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 335 ◽  
Author(s):  
Lina Lu ◽  
Zhonglin Jiang ◽  
Yulin Dai ◽  
Luonan Chen
Keyword(s):  
Dynamic Network ◽  
Tipping Point ◽  
Low Grade ◽  
Dysplastic Nodules ◽  
Network Biomarkers

The authors wish to make the following correction to their paper [...]

Identifying critical states of hepatocellular carcinoma based on single-sample dynamic network biomarkers combined with simulated annealing algorithm

2021 ◽  
Vol 16 ◽  
Author(s):  
Hongqian Zhao ◽  
Jie Gao ◽  
Yichen Sun ◽  
Yujie Wang ◽  
Tianhao Guan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Simulated Annealing ◽  
Critical State ◽  
Simulated Annealing Algorithm ◽  
Dynamic Network ◽  
Disease State ◽  
Statistical Characteristics ◽  
Low Grade ◽  
Network Biomarkers ◽  
Annealing Algorithm

Background: Hepatocellular carcinoma(HCC) is one of the most common malignant tumors. Due to the insidious onset and poor prognosis, most patients have reached the advanced stage at the time of diagnosis. Objective: Studies have shown thatdynamic network biomarkers (DNB) can effectively identify the critical state of complex diseases such as HCC from normal state to disease state. Therefore, it is very important to detect DNB efficiently and reliably. Methods: This paper selects a dataset containing eight HCC disease states. First, anindividual-specific network is constructed for each sample and features are extracted. In the context of this network, a simulated annealing algorithm is used to search for potential dynamic network biomarker modules, and the evolution of HCC is determined. Results: In fact, in the period of low-grade dysplasia (LGD) and high-grade dysplasia (HGD), DNB will send an indicative warning signal, which means that liver dysplasia is a very important critical state in the development of HCC disease. Compared with landscape dynamic network biomarkers method (L-DNB), our method can not only describe the statistical characteristics of each disease state, but also yield better results including getting more DNBs enriched in HCC related pathways. Conclusion: The results of this study may be of great significance to the prevention and early diagnosis of HCC.

SMAD7 and SERPINE1 as novel dynamic network biomarkers detect and regulate the tipping point of TGF-beta induced EMT

2020 ◽  
Vol 65 (10) ◽  
pp. 842-853
Author(s):  
Zhonglin Jiang ◽  
Lina Lu ◽  
Yuwei Liu ◽  
Si Zhang ◽  
Shuxian Li ◽  
...  
Keyword(s):  
Dynamic Network ◽  
Tipping Point ◽  
Tgf Beta ◽  
Network Biomarkers

scholarly journals PS2 - 167 CIC Deficiency is Associated with Dysregulation of Genes Involved in Cell Adhesion and Developmental Processes

2016 ◽  
Vol 43 (S4) ◽  
pp. S13-S13
Author(s):  
V.G. LeBlanc ◽  
S. Chittaranjan ◽  
M. Firme ◽  
S.Y. Chan ◽  
J. Song ◽  
...  
Keyword(s):  
Cell Adhesion ◽  
Cell Lines ◽  
Somatic Mutations ◽  
Control Cell ◽  
The Cancer Genome Atlas ◽  
Mitogen Activated Protein Kinase ◽  
Low Grade ◽  
Type I ◽  
Developmental Processes

Somatic mutations in the Capicua (CIC) gene were first identified in Type I low-grade gliomas (LGGs), which are characterized by 1p/19q co-deletions and IDH mutations. They are found at frequencies of ~50-70% in this glioma subtype, and have since been identified in ~40% of stomach adenocarcinomas (STADs) of the microsatellite instability (MSI) subtype; however, the role of these somatic mutations in malignancy has yet to be established. In Drosophila, CIC functions as a transcriptional repressor whose activity is inhibited upon activation of the mitogen-activated protein kinase (MAPK) signalling pathway. Though mammalian CIC appears to retain these functions, only three of its target genes have been established in human cells: ETV1, ETV4, and ETV5 (ETV1/4/5). To further probe CIC’s transcriptional network, we developed CIC knockout cell lines and performed transcriptomic and proteiomic analyses in these and in control cell lines expressing wild type CIC, identifying a total of 582 differentially expressed genes. We also used RNA-seq data from The Cancer Genome Atlas (TCGA) for Type I LGGs and STADs to perform additional differential expression analyses between CIC-deficient and CIC-expressing samples. Though gene-level overlap was limited between the three contexts, we found that CIC appears to regulate the expression of genes involved in cell-cell adhesion, metabolism, and developmental processes in all three contexts. These results shed light on the pathological role of CIC mutations and may help explain why these have been associated with poorer outcome within Type I LGGs.

scholarly journals Genome-Wide Lymphocytic mRNA Sequencing to Identify Epithelial-Mesenchymal Transition Mechanism in Silicosis

2021 ◽  
Author(s):  
Hai bin Li ◽  
Lin Zhang ◽  
Yi Guan ◽  
Yingzheng Zhao ◽  
Ning Li ◽  
...  
Keyword(s):  
Cell Adhesion ◽  
Signaling Pathway ◽  
Peripheral Blood ◽  
Epithelial Mesenchymal Transition ◽  
Janus Kinase ◽  
Gene Set Enrichment Analysis ◽  
Healthy Controls ◽  
Blood Samples ◽  
Mesenchymal Transition ◽  
Transition Mechanism

Abstract Background Lymphocytes are immune cells that play dual roles in the pathogenesis of silicosis. Epithelial-mesenchymal transition (EMT), a vital phenomenon in the pathogenesis of silicosis, is regulated by cytokines, chemokines, and other molecules secreted by lymphocytes; however, the underlying regulatory mechanism is unclear. Here, we investigated the role of lymphocytes in EMT in silicosis. Methods Three patients with silicosis and three healthy controls that underwent pre-job physical examination were recruited; fasting venous blood samples were collected and lymphocytes were separated by Ficoll. High-throughput sequencing technology and bioinformatic analysis were used to identify specific genes and signaling pathways. The results were verified through the detection of related indices of peripheral blood samples. Results The baseline characteristics of subjects from silicosis group were matched with those of healthy controls. In comparison with healthy controls, patients with silicosis showed 1915 dysregulated genes that were thought to participate in various biological processes, including angiogenesis, tissue repair, cell proliferation, invasion, migration, and EMT. Protein-protein interaction analysis grouped these genes into three hub targets, including phosphoinositide 3-kinase (PI3K), integrin beta 1 (ITGB1), and integrin-linked protein kinase (ILK). Gene set enrichment analysis (GSEA) confirmed that PI3K, ITGB1, and ILK were tightly associated with EMT through the Wnt signaling pathway, Janus kinase/signal transducer and activator of transcription (JAK-STAT) signaling pathway, and cell adhesion molecular pathway. ITGB1 is a member of the adhesion molecule family. The identified genes were verified through the detection of soluble adhesion molecules in peripheral blood samples of patients with silicosis and healthy subjects. Conclusion Dysregulation of PI3K, ITGB1, and ILK in lymphocytes may contribute to EMT via JAK-STAT, Wnt, and cell adhesion molecular pathways in patients with silicosis.

Understanding migraine using dynamic network biomarkers

Cephalalgia ◽  
2014 ◽  
Vol 35 (7) ◽  
pp. 627-630 ◽  
Author(s):  
Markus A Dahlem ◽  
Jürgen Kurths ◽  
Michel D Ferrari ◽  
Kazuyuki Aihara ◽  
Marten Scheffer ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Dynamic Network ◽  
Tipping Point ◽  
Trigger Factors ◽  
Clinical Neuroscience ◽  
Complex Interactions ◽  
Network Biomarker ◽  
Network Biomarkers ◽  
Premonitory Symptoms

Background Mathematical modeling approaches are becoming ever more established in clinical neuroscience. They provide insight that is key to understanding complex interactions of network phenomena, in general, and interactions within the migraine-generator network, in particular. Purpose In this study, two recent modeling studies on migraine are set in the context of premonitory symptoms that are easy to confuse for trigger factors. This causality confusion is explained, if migraine attacks are initiated by a transition caused by a tipping point. Conclusion We need to characterize the involved neuronal and autonomic subnetworks and their connections during all parts of the migraine cycle if we are ever to understand migraine. We predict that mathematical models have the potential to dismantle large and correlated fluctuations in such subnetworks as a dynamic network biomarker of migraine.

Therapeutic potential of JAK/STAT pathway modulation in mood disorders

2018 ◽  
Vol 30 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Aisha S. Shariq ◽  
Elisa Brietzke ◽  
Joshua D. Rosenblat ◽  
Zihang Pan ◽  
Carola Rong ◽  
...  
Keyword(s):  
Mood Disorders ◽  
Signaling Pathway ◽  
Depressive Disorders ◽  
Therapeutic Potential ◽  
Indirect Evidence ◽  
Janus Kinase ◽  
Low Grade ◽  
Signal Transducers ◽  
Inflammatory Conditions ◽  
Stat Signaling

Abstract Convergent evidence demonstrates that immune dysfunction (e.g. chronic low-grade inflammatory activation) plays an important role in the development and progression of mood disorders. The Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway is a pleiotropic cellular cascade that transduces numerous signals, including signals from the release of cytokines and growth factors. The JAK/STAT signaling pathway is involved in mediating several functions of the central nervous system, including neurogenesis, synaptic plasticity, gliogenesis, and microglial activation, all of which have been implicated in the pathophysiology of mood disorders. In addition, the antidepressant actions of current treatments have been shown to be mediated by JAK/STAT-dependent mechanisms. To date, two JAK inhibitors (JAKinibs) have been approved by the U.S. Food and Drug Administration and are primarily indicated for the treatment of inflammatory conditions such as rheumatoid arthritis. Indirect evidence from studies in populations with inflammatory conditions indicates that JAKinibs significantly improve measures of mood and quality of life. There is also direct evidence from studies in populations with depressive disorders, suggesting that JAK/STAT pathways may be involved in the pathophysiology of depression and that the inhibition of specific JAK/STAT pathways (i.e. via JAKinibs) may be a promising novel treatment for depressive disorders.

scholarly journals Clincial and Genetic Landscapes Differ Between IGH-CRLF2 and P2RY8-CRLF2 Acute Lymphoblastic Leukaemia

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1426-1426 ◽  
Author(s):  
Lisa Jane Russell ◽  
Lisa Jones ◽  
Amir Enshaei ◽  
Jamie Rutherford ◽  
Stefano Tonin ◽  
...  
Keyword(s):  
Cell Adhesion ◽  
Acute Lymphoblastic Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
Interstitial Deletion ◽  
Janus Kinase ◽  
Cytokine Receptor ◽  
Type I ◽  
Treatment Trial ◽  
Recurrent Mutations ◽  
Significant Difference

Abstract Deregulated expression of the type I cytokine receptor, cytokine receptor-like factor 2 (CRLF2 -d), is observed in 5% of B-cell precursor acute lymphoblastic leukaemia (BCP-ALL). It occurs via three known aberrations; a cryptic reciprocal translocation with the immunoglobulin heavy chain locus (IGH); an interstitial deletion within PAR1, resulting in the P2RY8-CRLF2 fusion; rare but recurrent CRLF2 mutation (F323C). All three result in overexpression of CRLF2, however alone it is insufficient to cause overt leukaemia. Mutations of the Janus kinase (JAK) family genes and the IL7 receptor, are recurrent (50% of CRLF2-d) and together with CRLF2 -d result in transformation of mouse BaF3 cells. We noted that outcome data from different study groups were inconsistent, with patients being classified as either high or intermediate risk. Thus, in this largest study to date, our aim was to acertain whether differences in clinical and/or genetic features between patients with CRLF2-d and involvement of either IGH or P2RY8 may define them as different disease entities and partly explain the outcome heterogeneity. Among 160 CRLF2-d patients, chromosomal analysis confirmed a high incidence of additional somatic copies of chromosomes X (39/88, 44%) and 21 (23/88, 26%) and identified that aneuploidy of chromosomes 9 (5/88, 6%) and 17 (7/88, 8%) were recurrent in both groups. From comparison of patients with IGH-CRLF2 and P2RY8-CRLF2, we noted a higher frequency of IKZF1 (79% v 37% p<0.001) and BTG1 (50% v 8%, p<0.001) deletions and greater complexity (>3 additional copy number alterations (CNA)) by MLPA (SALSA MLPA P335 kit, MRC Holland, The Netherlands) (p=0.037) among IGH-CRLF2 patients. We verified that (48/160) 30% of CRLF2 -d patients were Down syndrome (DS). In addition to CNA within the immunoglobulin loci and the genes investigated by MLPA, SNP6.0 arrays (Affymetrix, Santa Clara, USA) (n=25) and subsequent FISH screening identified recurrent CNA in the histone cluster at 6p22.2 (7/25, 28%), VPREB1 (6/25, 24%), ADD3 (14/58, 24%), BTLA (4/25, 16%), SLX4IP (12/43, 28%), SERP2 and TSC22D1 (6/53, 11%), PBX3 (16/54, 30%). A novel finding was an interstitial deletion at Xp11.4 fusing USP9X to DDX3X (9/50, 18%). A total of 137 somatic structural variants (SV) were detected by whole genome sequencing of 11 patients [tandem duplication- (n=6), deletion- (n=104), inversion- (n=14) and translocation-type (n=13)] creating an average of 12.7 validated SV per patient. Mutations were identified at an incidence of 12.8 per patient, including mutations in JAK1 and JAK2 (40%) and IL7R, CACNA1D and USH2A (n=2). Mutations in kinase genes were common and unique to all patients, a number have not been previously reported (e.g. ERBB4, TTBK1 and STK38L). Of interest, 7 patients had ≥1 point mutation in gene(s) involved in cell adhesion (e.g. NPNT, ADAM29, ITGB7, COL3A1 and USH2A). There was a significant difference in the median age and white blood cell count (WBC) between P2RY8-CRLF2 and IGH-CRLF2 (4yrs v 14yrs, p<0.001 and WBC >50x106 /L - 25% v 44%, p=0.021). Overall IGH-CRLF2 patients had a worse outcome compared to P2RY8-CRLF2 (p=0.191) with outcome heterogeneity in relation to gender (IGH females, HR 3.75, p=0.003), number of CNA (IGH <3 genes deleted, HR 3.79, p=0.047) and treatment trial (IGH have worse outcome on ALL97, HR 3.15, p=0.014) being observed. There was no heterogeneity for age (p=0.458), WBC (p=0.331), cytogenetic risk (p=1.0), MRD (p=1.0) or DS-ALL (p=0.877). In summary we have confirmed differences in age and WBC, involvement of kinase gene mutations and chromosomal gains in CRLF2-d ALL. Other findings included recurrent deletions involving TSC22D1 and PBX3, transcription factors involved in other human cancers; SLX4IP, an uncharacterized gene, frequently deleted in childhood ALL; the novel involvement of USP9X, a deubiquitinase involved in cancer development. We also identified recurrent mutations in cell adhesion genes. We showed that IGH-CRLF2 patients had a worse outcome, with heterogeneity seen between gender, number of gene deletions and treatment trial. We have shown that there are genetic and clinical differences dependent on whether CRLF2 is deregulated by IGH or P2RY8, suggesting that they should be regarded as different clincial entities in future studies. Disclosures Campbell: 14M genomics: Other: Co-founder and consultant.

scholarly journals Single-sample landscape entropy reveals the imminent phase transition during disease progression

2019 ◽  
Vol 36 (5) ◽  
pp. 1522-1532 ◽  
Author(s):  
Rui Liu ◽  
Pei Chen ◽  
Luonan Chen
Keyword(s):  
Disease Progression ◽  
Cancer Metastasis ◽  
Dynamic Change ◽  
Influenza Virus Infection ◽  
Dynamic Network ◽  
Tipping Point ◽  
Disease State ◽  
Single Sample ◽  
Supplementary Information ◽  
Sample Data

Abstract Motivation The time evolution or dynamic change of many biological systems during disease progression is not always smooth but occasionally abrupt, that is, there is a tipping point during such a process at which the system state shifts from the normal state to a disease state. It is challenging to predict such disease state with the measured omics data, in particular when only a single sample is available. Results In this study, we developed a novel approach, i.e. single-sample landscape entropy (SLE) method, to identify the tipping point during disease progression with only one sample data. Specifically, by evaluating the disorder of a network projected from a single-sample data, SLE effectively characterizes the criticality of this single sample network in terms of network entropy, thereby capturing not only the signals of the impending transition but also its leading network, i.e. dynamic network biomarkers. Using this method, we can characterize sample-specific state during disease progression and thus achieve the disease prediction of each individual by only one sample. Our method was validated by successfully identifying the tipping points just before the serious disease symptoms from four real datasets of individuals or subjects, including influenza virus infection, lung cancer metastasis, prostate cancer and acute lung injury. Availability and implementation https://github.com/rabbitpei/SLE. Supplementary information Supplementary data are available at Bioinformatics online.

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