A5021895080- RNA Research and Splicing
- RNA modifications and cancer
- Cancer-related molecular mechanisms research
- Ovarian cancer diagnosis and treatment
- HER2/EGFR in Cancer Research
- Circular RNAs in diseases
- MicroRNA in disease regulation
- Bioinformatics and Genomic Networks
- Radiomics and Machine Learning in Medical Imaging
- Gene expression and cancer classification
- Breast Cancer Treatment Studies
- Cancer, Lipids, and Metabolism
- Cancer Mechanisms and Therapy
- Advanced biosensing and bioanalysis techniques
- Machine Learning in Materials Science
- Metabolomics and Mass Spectrometry Studies
- Advanced Proteomics Techniques and Applications
- Data Analysis with R
- Genital Health and Disease
- Epigenetics and DNA Methylation
- Glycosylation and Glycoproteins Research
- Ferroptosis and cancer prognosis
- Histone Deacetylase Inhibitors Research
- 14-3-3 protein interactions
- Nuclear Structure and Function
Semmelweis University
2009-2024
HUN-REN Research Centre for Natural Sciences
2014-2021
Institute of Molecular Life Sciences
2018-2021
Montavid Thermodynamic Research Group
2016
Pázmány Péter Catholic University
2009-2014
Eötvös Loránd University
2009-2014
Hungarian Academy of Sciences
2009-2013
In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but overall survival is still very short. To further understand molecular basis of disease we have identify biomarkers related survival. Here present development an online tool suitable real-time meta-analysis published microarray datasets We searched caBIG, GEO and TCGA repositories samples with gene expression data information. Univariate multivariate Cox regression analysis, Kaplan-Meier...
Background Survival analysis is a cornerstone of medical research, enabling the assessment clinical outcomes for disease progression and treatment efficiency. Despite its central importance, no commonly used spreadsheet software can handle survival there web server available computation. Objective Here, we introduce web-based tool capable performing univariate multivariate Cox proportional hazards using data generated by genomic, transcriptomic, proteomic, or metabolomic studies. Methods We...
The validation of prognostic biomarkers in large independent patient cohorts is a major bottleneck ovarian cancer research. We implemented an online tool to assess the value expression levels all microarray-quantified genes patients. First, database was set up using gene data and survival information 1287 patients downloaded from Gene Expression Omnibus Cancer Genome Atlas (Affymetrix HG-U133A, HG-U133A 2.0, HG-U133 Plus 2.0 microarrays). After quality control normalization, only probes...
Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma. However, without confirmation an independent validation study, their clinical utility is limited. Our goal was to establish a robust database enabling the swift of previous and future cancer survival biomarker candidates.The entire incorporates 1,065 carcinoma samples, data. Out 29 established markers, higher BECN1 (HR = 0.68, p 1.5E-05), CASP3 0.5, 6E-14), COX2 0.72, 0.0013), CTGF...
Significance Resistance to treatment with endocrine therapy occurs in ∼50% of all breast cancer patients. The pathway(s) leading drug resistance is ill-defined. We show that accessibility the genome altered drug-resistant compared responsive cells. This coincides overactivation NOTCH pathway transcription factor PBX1, a known target gene, required for growth therapy-resistant Accordingly, gene expression signature based on NOTCH-PBX1 activity can discriminate priori patients are or not therapy.
Abstract Breast cancer clinical treatment selection is based on the immunohistochemical determination of four protein biomarkers: ESR1, PGR, HER2, and MKI67. Our aim was to correlate results proteome-level technologies in measuring expression these markers. We also aimed integrate available breast datasets identify validate new prognostic biomarker candidates. searched studies involving patient cohorts with published survival proteomic information. Immunohistochemistry were compared using...
Defects in AU-rich elements (ARE)-mediated posttranscriptional control can lead to several abnormal processes that underlie carcinogenesis. Here, we performed a systematic analysis of ARE-mRNA expression across multiple cancer types. First, the ARE database (ARED) was intersected with The Cancer Genome Atlas databases and others. A large set ARE-mRNAs over-represented and, unlike non-ARE-mRNAs, correlated reversed balance RNA-binding proteins tristetraprolin (TTP, ZFP36) HuR (ELAVL1). Serial...
Abstract The pre-clinical validation of prognostic gene candidates in large independent patient cohorts is a pre-requisite for the development robust biomarkers. We earlier implemented an online tool to assess or predictive value expression levels all microarray quantified genes breast cancer patients. In present study, we further expanded our database, added additional analytical options and ovarian database was set up using data survival information patients downloaded from GEO TCGA...
Primary systemic treatment for ovarian cancer is surgery, followed by platinum based chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six months. We aimed to identify clinically useful biomarkers resistance. A database transcriptomic datasets including and response information was set up mining the GEO TCGA repositories. Receiver operator characteristics (ROC) analysis performed R each gene these were then ranked using their achieved area under...
ABSTRACT Breast cancer clinical treatment selection is based on the immunohistochemical determination of four proteins: ESR1, PGR, HER2, and MKI67. Our aim was to correlate results proteome-level technologies in measuring expression these markers. We also aimed integrate available breast datasets identify validate new prognostic biomarker candidates. identified protein studies involving patient cohorts with published survival proteomic information. Immunohistochemistry were compared using...
<sec> <title>BACKGROUND</title> Survival analysis is a cornerstone of medical research, enabling the assessment clinical outcomes for disease progression and treatment efficiency. Despite its central importance, no commonly used spreadsheet software can handle survival there web server available computation. </sec> <title>OBJECTIVE</title> Here, we introduce web-based tool capable performing univariate multivariate Cox proportional hazards using data generated by genomic, transcriptomic,...
<h3>Background</h3> Immune checkpoint inhibitors, such as anti-PD-1, have transformed cancer therapy in the last decade. Yet, questions persist regarding their efficacy and pose ongoing challenges. Identifying more robust biomarkers is crucial immuno-oncology, iterative process between silico discovery experimental studies emphasizes of most suitable therapies for patients. Our aim was to pinpoint druggable, predictive resistance immune inhibitors by leveraging publicly available...
Abstract Background. MicroRNAs (miRNAs) are small non-coding RNAs capable of simultaneously regulating multiple gene networks, and affecting breast cancer patients’ outcome. Here we present the development an online tool for real-time meta-analysis published miRNA datasets to identify novel prognostic biomarkers in cancer. Methods. First, a comprehensive database was set up by searching GEO, TCGA, PubMed repositories with expression clinical data. Due platform differences, each dataset...
5557 Background: Primary systemic treatments for ovarian cancer are paclitaxel and carboplatin chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six months. We aimed to identify clinically useful biomarkers platinum resistance. Methods: A database transcriptomic datasets including treatment response data was set up by mining the GEO TCGA repositories. Receiver operator characteristics (ROC) analysis performed R each gene these were then ranked using...
<div>Abstract<p>Defects in AU-rich elements (ARE)-mediated posttranscriptional control can lead to several abnormal processes that underlie carcinogenesis. Here, we performed a systematic analysis of ARE-mRNA expression across multiple cancer types. First, the ARE database (ARED) was intersected with The Cancer Genome Atlas databases and others. A large set ARE-mRNAs over-represented and, unlike non-ARE-mRNAs, correlated reversed balance RNA-binding proteins tristetraprolin (TTP,...
<p>Supplementary Figures comprising Fig.S1: HuR kb polyadenylation variants in Glioblastoma and lung adenocarcinoma; Fig. S2: Correlations of TTP with cancer ARE-mRNAs; S3: Normal versus mRNA intensity levels the mitotic ARE-gene cluster members. S4: Negative correlation between 11 members ARE-mitotic genes TTP/HuR ratio; S5 Kaplan Meier survival analysis for expression level ARE-mRNA cluster</p>