Iannis Aifantis

This study identifies cGAS-STING pathway activation as a key mechanism of inflammation in VEXAS, showing that UBA1 mutations disrupt ERAD and mitochondrial homeostasis, leading to STING-driven inflammation.

This study shows that chromatin architecture and physical constriction together drive phenotype switching and metastasis in melanoma by altering CTCF positioning and heterochromatin structure.

This study identifies circPCMTD1 as a circular RNA that promotes leukemic cell proliferation by enhancing DNA damage response tolerance through a novel peptide product.

This paper introduces a transcriptome-driven machine learning classifier to predict molecular subtypes in T-cell Acute Lymphoblastic Leukemia and reveals subtype-specific relapse patterns.

This study identifies UVRAG as a negative regulator of NOTCH1 by promoting K27-linked ubiquitination and lysosomal degradation, revealing a checkpoint to prevent excessive NOTCH signaling.

This study characterizes myeloid sarcoma through multi-omic profiling, identifies RAS pathway activation as a hallmark, and shows RAS inhibition reduces tumor burden in mouse models.

The paper identifies GAPDH as a non-canonical RNA-binding protein in AML that stabilizes transcripts and promotes translation, revealing its role in tumor proliferation.

This study shows that transient skin inflammation activates hematopoietic stem/progenitor cells via type I interferon, altering systemic immunity and affecting atherosclerosis and influenza outcomes.

The paper identifies lncRNAs involved in melanoma growth and metastasis using CRISPR-inhibition screens and validates their functional roles.

This study introduces C.Origami, a deep learning model that predicts cell type-specific 3D chromatin organization, enabling in silico genetic screening to identify genomic regions affecting chromatin structure.

This study demonstrates that a circular human artificial chromosome can be transmitted through three generations of mice without health or reproductive issues.

The paper improves Hi-C contact matrix reproducibility using fused two-dimensional lasso, identifies TAD boundaries with varying insulation strength, and shows super-enhancers are preferentially insulated by strong boundaries, which are frequently co-duplicated in cancer.

lncRNA-screen is a pipeline for computationally screening lncRNAs in large genomics datasets, generating interactive reports for further experimental validation.

HiC-bench provides a comprehensive and reproducible platform for Hi-C data analysis, enabling parameter exploration and benchmarking of different tools and methods.