Gene expression in endoprosthesis loosening: Chitinase activity for early diagnosis?

2008 ◽  
Vol 26 (3) ◽  
pp. 394-403 ◽  
Author(s):  
L. Morawietz ◽  
A. Weimann ◽  
J. H. Schroeder ◽  
R. J. Kuban ◽  
U. Ungethuem ◽  
...  
Keyword(s):  
Gene Expression ◽  
Early Diagnosis ◽  
Chitinase Activity ◽  
Endoprosthesis Loosening

scholarly journals Novel Indications of Epigenetic Therapy in Ovarian Cancer

2021 ◽  
Author(s):  
Courtney Griffiths ◽  
Michelle Bilbao ◽  
Lauren Krill ◽  
Olga Ostrovsky
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Early Diagnosis ◽  
Gynecologic Cancer ◽  
Epigenetic Modifications ◽  
Epigenetic Therapy ◽  
Intratumor Heterogeneity ◽  
Survival Outcomes ◽  
Advanced Stage ◽  
Stage Disease

Early diagnosis and intervention are some of the longstanding challenges associated with ovarian cancer, which is the leading cause of gynecologic cancer mortality. While the majority of patients who present with advanced stage disease at time of diagnosis will initially respond to traditional combination platinum and taxane-based chemotherapy in conjunction with cytoreductive surgery, approximately 70% will ultimately recur due to chemoresistance within the first two years. Intratumor heterogeneity is proposed to be a leading factor in the development of chemoresistance and resultant poorer outcomes for those with recurrent or advanced stage disease. Both inherent and acquired mechanisms of chemoresistance are postulated to be a result of alterations in gene expression, also known as epigenetic modifications. Therefore, epigenetic therapy is a pivotal avenue which allows for reversal of chemoresistance in cancer through the targeting of aberrant mutations. In this chapter, we discuss how these epigenetic modifications prove to be promising targets in cancer therapy leading to heightened drug sensitivity and improved patient survival outcomes.

Diagnosis value of EGFR gene expression for early diagnosis in oral leukoplakias

2008 ◽  
Vol 6 (9) ◽  
pp. 156-157
Author(s):  
G. Aparicio Gallego ◽  
S.m. Díaz Prado ◽  
V. Medina Villaamil ◽  
L.m. Antón Aparicio ◽  
J.l. López Cedrún ◽  
...  
Keyword(s):  
Gene Expression ◽  
Early Diagnosis ◽  
Egfr Gene

scholarly journals Application of Microarrays to the Analysis of Gene Expression in Cancer

2002 ◽  
Vol 48 (8) ◽  
pp. 1170-1177 ◽  
Author(s):  
Pascale F Macgregor ◽  
Jeremy A Squire
Keyword(s):  
Gene Expression ◽  
Early Diagnosis ◽  
Molecular Signatures ◽  
Therapeutic Approaches ◽  
Individual Gene ◽  
Prognostic Assessment ◽  
Disease Mechanisms ◽  
New Gene ◽  
Cellular Microenvironments ◽  
State Of Activity

Abstract Molecular diagnostics is a rapidly advancing field in which insights into disease mechanisms are being elucidated by use of new gene-based biomarkers. Until recently, diagnostic and prognostic assessment of diseased tissues and tumors relied heavily on indirect indicators that permitted only general classifications into broad histologic or morphologic subtypes and did not take into account the alterations in individual gene expression. Global expression analysis using microarrays now allows for simultaneous interrogation of the expression of thousands of genes in a high-throughput fashion and offers unprecedented opportunities to obtain molecular signatures of the state of activity of diseased cells and patient samples. Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments and ultimately may lead to improved early diagnosis and innovative therapeutic approaches for cancer.

Early diagnosis of breast cancer by gene expression profiles

2016 ◽  
Vol 20 (2) ◽  
pp. 567-578 ◽  
Author(s):  
Hanaa Salem ◽  
Gamal Attiya ◽  
Nawal El-Fishawy
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Early Diagnosis ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6694 ◽  
Author(s):  
Yu Liu ◽  
Deyao Xie ◽  
Zhifeng He ◽  
Liangcheng Zheng
Keyword(s):  
Gene Expression ◽  
Functional Analysis ◽  
Transcription Factor ◽  
Early Diagnosis ◽  
Lung Adenocarcinoma ◽  
Integrated Analysis ◽  
Aberrant Expression ◽  
Ontology Term ◽  
Tumor Stages ◽  
Potential Biomarkers

Background Competing endogenous RNAs (ceRNAs) are a newly identified type of regulatory RNA. Accumulating evidence suggests that ceRNAs play an important role in the pathogenesis of diseases such as cancer. Thus, ceRNA dysregulation may represent an important molecular mechanism underlying cancer progression and poor prognosis. In this study, we aimed to identify ceRNAs that may serve as potential biomarkers for early diagnosis of lung adenocarcinoma (LUAD). Methods We performed differential gene expression analysis on TCGA-LUAD datasets to identify differentially expressed (DE) mRNAs, lncRNAs, and miRNAs at different tumor stages. Based on the ceRNA hypothesis and considering the synergistic or feedback regulation of ceRNAs, a lncRNA–miRNA–mRNA network was constructed. Functional analysis was performed using gene ontology term and KEGG pathway enrichment analysis and KOBAS 2.0 software. Transcription factor (TF) analysis was carried out to identify direct targets of the TFs associated with LUAD prognosis. Identified DE genes were validated using gene expression omnibus (GEO) datasets. Results Based on analysis of TCGA-LUAD datasets, we obtained 2,610 DE mRNAs, 915 lncRNAs, and 125 miRNAs that were common to different tumor stages (|log2(Fold change)| ≥ 1, false discovery rate < 0.01), respectively. Functional analysis showed that the aberrantly expressed mRNAs were closely related to tumor development. Survival analyses of the constructed ceRNA network modules demonstrated that five of them exhibit prognostic significance. The five ceRNA interaction modules contained one lncRNA (FENDRR), three mRNAs (EPAS1, FOXF1, and EDNRB), and four miRNAs (hsa-miR-148a, hsa-miR-195, hsa-miR-196b, and hsa-miR-301b). The aberrant expression of one lncRNA and three mRNAs was verified in the LUAD GEO dataset. Transcription factor analysis demonstrated that EPAS1 directly targeted 13 DE mRNAs. Conclusion Our observations indicate that lncRNA-related ceRNAs and TFs play an important role in LUAD. The present study provides novel insights into the molecular mechanisms underlying LUAD pathogenesis. Furthermore, our study facilitates the identification of potential biomarkers for the early diagnosis and prognosis of LUAD and therapeutic targets for its treatment.

scholarly journals Targeted Gene Candidates for Treatment and Early Diagnosis of Age-Related Macular Degeneration

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Emine Cinici ◽  
Ozge Caglar ◽  
Mehmet Enes Arslan ◽  
Nilay Dilekmen ◽  
Bahadır Utlu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Early Diagnosis ◽  
Macular Degeneration ◽  
Expression Analysis ◽  
Peripheral Blood ◽  
Gene Expression Analysis ◽  
Mononuclear Cells ◽  
Age Related Macular Degeneration ◽  
Pcr Analysis ◽  
Age Related

Age-related macular degeneration (AMD) is an eye disease that impairs the sharp and central vision need for daily activities. Recent advances in molecular biology research not only lead to a better understanding of the genetics and pathophysiology of AMD but also to the development of applications based on targeted gene expressions to treat the disease. Clarification of molecular pathways that causing to development and progression in dry and wet types of AMD needs comprehensive and comparative investigations in particular precious biopsies involving peripheral blood samples from the patients. Therefore, in this investigation, dry and wet types of AMD patients and healthy individuals were aimed at investigating in regard to targeted gene candidates by using gene expression analysis for the first time. 13 most potent candidate genes involved in neurodegeneration were selected via in silico approach and investigated through gene expression analysis to suggest new targets for disease therapy. For the analyses, 30 individuals (10 dry and 10 wet types AMD patients and 10 healthy people) were involved in the study. SYBR-Green based Real-Time PCR analysis was performed on isolated peripheral blood mononuclear cells (PBMCs) to analyze differentially expressed genes related to these cases. According to the investigations, only the CRP gene was found to be upregulated for both dry and wet disease types. When the downregulated genes were analyzed, it was found that 11 genes were commonly decreased for both dry and wet types in the aspect of expression pattern. From these genes, CFH, CX3CR1, FLT1, and TIMP3 were found to have the most downregulated gene expression properties for both diseases. From these results, it might be concluded that these common upregulated and downregulated genes could be used as targets for early diagnosis and treatment for AMD.

scholarly journals OVEREXPRESSION OF STAT4 - A POSSIBLE DIAGNOSTIC MARKER OF EARLY STAGES OF MYCOSIS FUNGOIDES

2018 ◽  
Vol 21 (2) ◽  
pp. 94-100
Author(s):  
O. Yu Olisova ◽  
Ekaterina V. Grekova ◽  
L. G Gorenkova ◽  
E. A Alekseeva ◽  
D. V Zaletayev
Keyword(s):  
Gene Expression ◽  
Early Diagnosis ◽  
Healthy Volunteers ◽  
Mrna Expression ◽  
Mycosis Fungoides ◽  
Sharp Decrease ◽  
Control Group ◽  
Common Disease ◽  
Diagnostic Features ◽  
Dermatology Department

Background. Mycosis fungoides (MF) is the most common disease among the cutaneous T-cell lymphomas (85-90%). The accuracy of the diagnosis of MF, which is confirmed only by clinical, histological and immunohistochemical signs, is 50-75%. The aim of the study was to investigate genetic markers (FOXP3, STAT4, IL-12B) for early diagnosis of mycosis fungoides. Material and methods. A study involving 42 patients with MF and plaque parapsoriasis (PP) treated at the Dermatology Department of I.M. Sechenov First Moscow State Medical University and National Medical Hematology Research Сenter, was performed. The analysis of gene expression FOXP3, STAT4, IL-12B was carried out by TaqMan Real time-PCR. The objects of the study were lesional skin samples of patients. A group with MF consisted of 29 patients, a group with PP consisted of 13 patients, a control group included 10 healthy volunteers. Results. The study revealed that the level of STAT4 gene expression showed a significant (9 times) increase in the mRNA expression of STAT4 transcripts in patients with MF (166) compared with patients with PP (17.9; p < 0.05) and 553 times - with healthy volunteers (0.3; p < 0.05). There was also a statistically significant predominance of the level of mRNA expression of STAT4 transcripts in patients with spotted and plaque stages of MF (180; 318) compared with patients with PP (17.9; p < 0.05) and healthy volunteers (0.3; p < 0.05), as well as a sharp decrease in patients with erythrodermic form of MF (7.19). For early diagnosis of MF the level of expression of mRNA transcripts STAT4 is of great importance. Inclusion of STAT4 in the list of diagnostic features increases the accuracy of differential diagnosis of MF and PP from 59.1 to 81.8%.

Identification of the diagnostic signature of sepsis based on bioinformatic analysis of gene expression and machine learning

2020 ◽  
Vol 23 ◽  
Author(s):  
Qian Zhao ◽  
Ning Xu ◽  
Hui Guo ◽  
Jianguo Li
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Random Forest ◽  
Early Diagnosis ◽  
Bioinformatic Analysis ◽  
Random Forest Model ◽  
Diagnostic Methods ◽  
Ppi Network ◽  
Hub Genes ◽  
Forest Model

Background: Sepsis is a life-threatening disease caused by the dysregulated host response to the infection, and being the major cause of death to patients in intensive care unit (ICU). Objective: Early diagnosis of sepsis could significantly reduce in-hospital mortality. Though generated from infection, the development of sepsis follows its own psychological process and disciplines, alters with gender, health status and other factors. Hence, the analysis of mass data by bioinformatic tools and machine learning is a promising method for exploring early diagnosis manners. Method: We collected miRNA and mRNA expression data of sepsis blood samples from Gene Expression Omnibus (GEO) and ArrayExpress databases, screened out differentially expressed genes (DEGs) by R software, predicted miRNA targets on TargetScanHuman and miRTarBase websites, conducted Gene Ontology (GO) term and KEGG pathway enrichment based on overlapping DEGs. The STRING database and Cytoscape were used to build protein-protein interaction (PPI) network and predict hub genes. Then we constructed a Random Forest model by using the hub genes to assess sample type. Results: Bioinformatic analysis of GEO dataset revealed 46 overlapping DEGs in sepsis. The PPI network analysis identified five hub genes, SOCS3, KBTBD6, FBXL5, FEM1C and WSB1. Random Forest model based on these five hub genes was used to assess GSE95233 and GSE95233 datasets, and the area under curve (AUC) of ROC are 0.900 and 0.7988, respectively, which confirmed the efficacy of this model. Conclusion: The integrated analysis of gene expression in sepsis and the effective Random Forest model built in this study may provide promising diagnostic methods for sepsis.

Co-expression network analysis of placental transcriptome as the basis for searching signal ways and preeclampsia biomarkers

2020 ◽  
pp. 71-72
Author(s):  
А.А. Бабовская ◽  
Е.А. Трифонова ◽  
А.А. Зарубин ◽  
А.В. Марков ◽  
В.А. Степанов
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Early Diagnosis ◽  
Differentially Expressed Genes ◽  
Pathological Process ◽  
Biological Pathways ◽  
Perinatal Morbidity ◽  
Hub Gene ◽  
Significant Gene ◽  
Placental Diseases

Проблема профилактики и ранней диагностики преэклампсии (ПЭ) продолжает оставаться одной из ведущих в акушерстве, поскольку данное осложнение беременности несет большой риск материнской и младенческой смертности. Считается, что основная причина ПЭ - это нарушение этапов формирования плаценты, а регуляции экспрессии генов является значимым механизмом развития плацентарной патологии. Классический подход в транскриптомных исследованиях экспрессии основан на поиске дифференциально-экспрессирующихся генов при заболевании, однако такой подход рассматривает гены изолированно, не учитывая их возможные взаимодействия. Более перспективным подходом является анализ коэкспрессии, который описывает гены, вовлеченные в единые биологические пути патологического процесса, а также позволяет выделять в каждом из кластеров наиболее функционально значимый ген в сети - центральный (hub gene). The problem of prevention and early diagnosis of preeclampsia continues to be one of the leading in obstetrics. It`s a major problem that contributes substantially to maternal and perinatal morbidity and mortality worldwide . Gene expression contributes significantly to the pathogenesis of placental diseases. Traditional methods of studying gene expression are based on the search of differentially expressed genes in a disease, but this approach considers genes in isolation. Coexpression analysis describes the genes involved in the unified biological pathways of the pathological process and also allows you to select in each of the clusters the most functionally significant gene in the network - the hub gene.

Sign in / Sign up

Export Citation Format

Share Document