Weiskittel, T. | bioRxiv Science

bioRxiv2025

Aging-dependent dysregulation of EXOSC2 is maintained in cancer as a dependency

Reprogramming of aged donor tissue cells into induced pluripotent stem cells (A-iPSC) preserved the epigenetic memory of aged-donor tissue, defined as genomic instability and poor tissue differentiation in our previous study. The unbalanced expression of RNA exosome subunits affects the RNA degradation complex function and is associated with geriatric diseases including premature aging and cancer progression. We hypothesized that the age-dependent progressive subtle dysregulation of EXOSC2 (exosome component 2) causes the aging traits (abnormal cell cycle and poor tissue differentiation). We used embryonic stem cells as a tool to study EXOSC2 function as the aging trait epigenetic memory determined in A-iPSC because these aging traits could not be studied in senesced aged cells or immortalized cancer cells. We found that the regulatory subunit of PP2A phosphatase, PPP2R5E, is a key target of EXOSC2 and this regulation is preserved in stem cells and cancer.

cell biology↗

bioRxiv2025

Symmetry as a Fundamental Principle in Defining Gene Expression and Phenotypic Traits

Symmetry refers to properties that remain invariant upon mathematical transformations. The principles of symmetry have guided numerous important discoveries in physics and chemistry but not in biology and medicine. Here, we aim to explore the presence of symmetry relationships at the gene expression level as a mean to distinguish between healthy and disease states. We deployed Learning-Based Invariant Feature Engineering - LIFE, a hybrid machine learning approach implemented with two symmetric invariant feature functions (IFFs) to identify Invariant Feature Genes (IFGs), which are gene pairs whose IFF single-value outputs remain invariant across individual samples in a given biological phenotype. Our multiclass classification results across the transcriptomes of 25 normal organs, 25 cancer types, and blood samples obtained from 4 different types of neurodegenerative diseases revealed the presence of unique phenotype-specific IFGs. We constructed networks using these IFGs (IF-Nets) and intriguingly, we demonstrated that the hubs could serve as information encoders, capable of reconstructing sample-wise expression values in relation to their counterpart genes. More importantly, we found that hubs of cancer IF-Nets were enriched with both approved and clinical trial drugs, highlighting "symmetry breaking" as a novel approach for treating diseases.

systems biology↗