Search bioRxiv⌕ Search

Biology subjects

Karhu, A.

Publications and source records attributed to Karhu, A..

2 recordsLinked to original sources

A phosphorylation switch in PAGE4 drives MED12-mutant fibroid pathogenesis

Recurrent somatic mutations in MED12, found in [~]70% of uterine leiomyomas (ULs), define the dominant molecular subtype of these highly prevalent tumors, yet the downstream effector mechanisms remain poorly understood. Using an integrated multi-omics workflow, encompassing discovery-phase DDA proteomics of matched leiomyoma-myometrium pairs, validation-phase DIA proteomics across genetically stratified cohorts (MED12 p.G44D, RAD51B-HMGA2, IRS4/FH subtypes), phosphoproteomics, immunohistochemistry, and AP-MS interactomics, we identify prostate-associated gene 4 (PAGE4) as a central effector of MED12-mutant UL pathogenesis. PAGE4 emerged as one of the most significantly upregulated proteins in MED12-mutant ULs and harbored the highest-occupancy hyperphosphorylation sites (T51, T85) in the tumor phosphoproteome, a pattern confirmed by immunohistochemistry and orthogonal phosphoproteomics. Kinase-substrate enrichment nominated HIPK2 as the primary upstream kinase, with supporting evidence from the broader CMGC family. Subsequent analysis revealed that phosphorylation acts as a molecular switch, fundamentally restructuring the PAGE4 interactome to favor the Mediator complex and RNA Pol II transcriptional machinery. This rewiring was functionally validated by ChIP-seq and luciferase reporter assays, which demonstrated corresponding shifts in transcription factor occupancy and downstream pathway activity. Collectively, these data establish phospho-PAGE4 as a critical mechanistic node downstream of MED12 mutation, expand PAGE4 biology from prostate cancer to female reproductive tumors, and nominate it as a mechanistic biomarker and candidate therapeutic vulnerability in the most prevalent molecular subtype of uterine leiomyomas.

systems biology↗

Multiomics and digital monitoring during lifestyle changes reveal independent dimensions of human biology and health

In order to explore opportunities for personalized and predictive health care, we collected serial clinical measurements, health surveys and multiomics profiles (genomics, proteomics, autoantibodies, metabolomics and gut microbiome) from 96 individuals. The participants underwent data-driven health coaching over a 16-month period with continuous digital monitoring of activity and sleep. Multiomics factor analysis resulted in an unsupervised, data-driven and integrated view of human health, revealing distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet and hormonal effects. The data revealed novel and previously uncovered associations between risk factors, molecular pathways, and quantitative lifestyle parameters. For example, ethinyl estradiol use had a distinct impact on metabolites, proteins and physiology. Multidimensional molecular and digital health signatures uncovered biological variability between people and quantitative effects of lifestyle changes, hence illustrating the value of the combined use of molecular and digital monitoring of human health.

systems biology↗