Balázs Győrffy

XPO1 controls VDR localization and activity in triple-negative breast cancer cells

This study shows XPO1 regulates VDR subcellular localization and vitamin D responsiveness in TNBC, with XPO1 inhibition enhancing vitamin D's antiproliferative effects.

LGR5-high colorectal cancer defines a Wnt-active stem-like state with multimodal therapeutic vulnerabilities

The paper identifies LGR5-high colorectal cancer as a Wnt-active stem-like state with therapeutic vulnerabilities across multiple modalities.

Site-dependent Treg cell transcriptional reprograming in a metastatic colorectal cancer model holds prognostic significance

The paper identifies location-specific transcriptional differences in tumor-infiltrating Treg cells across CRC metastases and links these to poor patient prognosis.

Neuroendocrine-like/EMT dedifferentiation mediates resistance to EGFR inhibitors via the NRG1/HER3 axis

The paper identifies NRG1/HER3 axis activation via NE-like/EMT dedifferentiation as a mechanism of EGFR inhibitor resistance in NSCLC and shows that combining EGFR inhibition with NRG1 neutralization can eradicate tumors.

Condensate-Driven Transcriptional Reprogramming Defines Core Vulnerabilities in Esophageal and Gastric Cancers

The paper identifies condensate-driven transcriptional programs in esophageal and gastric cancers, showing their role in tumor viability and suggesting therapeutic targets.

Self-assembly of hybrid 3D cultures by integrating living and synthetic cells

The paper develops hybrid 3D cancer cultures using synthetic and natural cells to mimic tumor immune microenvironments and identify immune evasion mechanisms.

Identifying Ferroptosis Inducers, HDAC, and RTK Inhibitor Sensitivity in Melanoma Subtypes through Unbiased Drug Target Prediction

This paper identifies potential drug targets and predicts treatment efficacy and resistance in melanoma subtypes using proteogenomic data and drug sensitivity analysis.

Development and validation of a gene expression score to account for tumour purity and improve prognostication in breast cancer

This paper develops and validates a 9-gene Breast Cancer Purity Score to improve prognostication by accounting for tumour purity in breast cancer datasets.

Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts

The paper identifies six proteins that predict response to immune checkpoint therapy across three melanoma cohorts and correlate with patient survival.

Up-regulated transcriptional regulators in mutant RAS gene signatures: a time-resolved multi-omics study in generic epithelial cell models

This study identifies HMGA2 as a master regulator of mutant RAS-driven gene expression by analyzing time-resolved transcriptome and proteome changes in epithelial cells.

Transient loss of Polycomb components induces an epigenetic cancer fate

The paper shows that transient loss of Polycomb components in Drosophila induces an irreversible cancer fate through epigenetic reprogramming without driver mutations.

CovidOutcome2: a tool for SARS-CoV2 mutation identification and for disease severity prediction

CovidOutcome2 predicts disease severity from SARS-CoV-2 mutation profiles using autoML and deep neural networks, achieving ROC-AUC scores of 0.899 and 0.83 with and without patient age.

MultipleTesting.com: a tool for life science researchers for multiple hypothesis testing correction

MultipleTesting.com provides an online tool for multiple hypothesis testing correction with examples and a guide to select appropriate statistical methods.

Pancancer survival analysis of cancer hallmark genes

This study analyzes the prognostic impact of cancer hallmark genes across 26 tumor types using RNA-seq and survival data from TCGA, identifying significant gene-expression associations with patient outcomes.

TNMplot.com: a web tool for the comparison of gene expression in normal, tumor and metastatic tissues

TNMplot.com compares gene expression across normal, tumor, and metastatic tissues using transcriptome data to identify differentially expressed genes and validate their significance in cancer.

COVIDOUTCOME - Estimating COVID Severity Based on Mutation Signatures in the SARS-CoV-2 Genome

The paper uses machine learning to link SARS-CoV-2 mutations to COVID-19 severity, identifying 26 mutations and achieving high classification accuracy.