Biology subjects

Adomat, H.

Publications and source records attributed to Adomat, H..

4 recordsLinked to original sources

bioRxiv2026

Proteomic Characterization of Prostate Cancer Bone Metastasis Subtypes Defines Progressive Remodeling States of the Bone-Tumor Microenvironment

Prostate cancer (PC) bone metastases (PCBM) are a debilitating disease morbidity that primarily affects the axial skeleton. PCBM are predominantly osteosclerotic with mixed osteosclerotic/osteolytic features, including irregular bone deposition, loss of collagen alignment and increased porosity that mimic features of woven bone formed during development and repair. We hypothesize that progression of PCBM is driven by interactions between tumor cells and the bone microenvironment and is associated with changes in the stromal compartment. We performed tandem mass tag mass spectrometry proteomics on lumbar vertebral specimens from 32 cadaveric PCBM specimens and 3 age-matched controls. Unsupervised clustering segregated specimens into three clusters associated with benign, mixed, and osteosclerotic lesion states, characterized by distinct immune-, tumor-, and osteogenic-associated protein signatures. Histological analysis showed tumor infiltration was accompanied by marrow fibrosis and increased collagen III deposition. We identified a marker signature associated with osteosclerotic remodeling and mapped this signature to independent metastatic PC transcriptomic datasets. The proteomics-derived markers reproduced similar molecular groupings at RNA level, and robustly segregated bone PCBMs from soft tissue metastases PC in RNA data. Together, these findings define molecularly distinct states of tumor-driven changes in PCBM that extend beyond histological classification and may inform biomarker development and therapeutic stratification.

cancer biology↗

bioRxiv2025

The SARS-CoV-2 nonstructural protein 15 collapses the host cytoskeleton by interacting with the host keratin type II cytoskeletal 1

COVID-19, the deadliest recorded pandemic of the 21st century, was caused by a novel coronavirus, SARS-CoV-2. To explore why this coronavirus was significantly more pathogenic than its predecessors, more information is needed about the functions of the viral proteins that contributed to this uptick in virulence. This study explored how one of these viral proteins, the nonstructural protein 15 (NSP15), interacts with the host. Our findings revealed a novel protein-protein interaction between NSP15 and the host keratin type II cytoskeletal 1 in Vero E6 cells, as determined by mass spectrometry, and subsequently validated by immunoprecipitation. We observed that when NSP15 was delivered into Vero E6 cells, the fibrous network of keratin intermediate filaments was disrupted, and the nuclear structure was lost. This disruption of the keratin cytoskeleton was then shown to cause a statistically significant reduction in cell viability of Vero E6 cells. These results indicate that the presence of NSP15 in host cells leads to a collapse of the keratin cytoskeleton. This cytoskeletal collapse could be a mechanism the virus employs to escape the infected host cell via cell lysis, once significant amounts of viral protein and progeny have accumulated.

microbiology↗

bioRxiv2022

A bi-functional PARP-HDAC inhibitor with activity in Ewing sarcoma

HDAC inhibition has been shown to induce pharmacological BRCAness in cancer cells with proficient DNA repair activity. This provides a rationale for exploring combination treatments with HDAC and PARP inhibition in cancer types that are insensitive to single-agent PARP inhibitors. Here, we report the concept and characterization of a novel bifunctional PARP inhibitor (kt-3283) with dual activity towards PARP1/2 and HDAC enzymes in Ewing sarcoma cells. Compared to the FDA-approved PARP (olaparib) and HDAC (vorinostat) inhibitors, kt-3283 displayed enhanced cytotoxicity in Ewing sarcoma models. The kt-3283-induced cytotoxicity was associated with a strong S and G2/M cell cycle arrest in the nanomolar concentration range and elevated DNA damage as assessed by {gamma}H2AX tracking and comet assays. In three-dimensional spheroid models of Ewing sarcoma, kt-3283 showed efficacy in lower concentrations than olaparib and vorinostat and kt-3283 inhibited colonization of Ewing sarcoma cells in an ex vivo lung metastasis model. In summary, our data demonstrates the preclinical justification for studying the benefit of dual PARP and HDAC inhibition in the treatment of Ewing sarcoma in a clinical trial and provides proof-of-concept for a bi-functional single-molecule therapeutic strategy.

cancer biology↗

bioRxiv2018

High-flow Nano-chromatography Columns Facilitate Rapid and High-quality Proteome Analysis on Standard Nano-LC Hardware

Optimizing the acquisition of proteomics data collected from a mass spectrometer (MS) requires careful selection of processed material quantities, liquid-chromatography (LC) setup, and data acquisition parameters. The small internal diameter (ID) columns standardly used in nano-chromatography coupled MS result in long per injection overhead times that require sacrifices in design of offline-fractionation and data acquisition schemes. As cohort sizes and the numbers of samples to be analyzed continue to increase, there is a need to investigate methods for improving the efficiency and time of an acquisition (LC + MS). In this work, the ability to improve throughput in single runs or as part of an in-depth proteome analysis of a fractionated sample using standard LC hardware is investigated. Capitalizing on the increased loading capacity of nanochromatography columns with larger IDs, substantially improved throughput with no reduction in detection sensitivity is achieved in single-injection proteome analyses. An optimized 150 m ID column setup is paired with an offline fractionation-concatenation scheme to demonstrate the ability to perform in-depth proteome analysis on-par with current state-of-the-art studies, while minimizing sample loading overhead. Together, these data demonstrate an easy and effective means to improve sample analysis throughput with no reduction in data quality using an approach that is applicable to any standard nano-LC hardware.

biochemistry↗