Res Sq [Preprint]. 2026 Mar 18:rs.3.rs-8913641. doi: 10.21203/rs.3.rs-8913641/v1.

ABSTRACT

Extracellular vesicles (EVs) represent a promising liquid biopsy platform in multiple myeloma (MM). We developed an MM EV Surface Protein Assay to quantify and dynamically monitor four MM EV subpopulations defined by targetable MM surface proteins (BCMA, CD38, GPRC5D, and CD319) across 336 serial blood samples from 45 relapsed/refractory MM (RRMM) patients treated with anti-BCMA chimeric antigen receptor (CAR) T-cell therapy. All four MM EV subpopulations significantly decreased in 43 patients with initial response, while BCMA⁺, GPRC5D⁺, and CD319⁺ MM EVs increased in 19 patients with progression, and antigen escape was detected by BCMA⁺ MM EVs. MM EV subpopulations differentiated minimal residual disease (MRD) status and complemented MRD for detecting early relapse before clinical progression. Notably, CD319⁺ MM EVs were early predictors of progression-free and overall survival in MRD-negative patients. This assay enables noninvasive monitoring of deep response, progression, and antigen escape, and stratifies survival in MRD-negative patients with RRMM.

PMID:41890853 | PMC:PMC13015583 | DOI:10.21203/rs.3.rs-8913641/v1

Environ Health (Wash). 2025 Nov 14;4(3):513-521. doi: 10.1021/envhealth.5c00401. eCollection 2026 Mar 20.

ABSTRACT

Prolonged exposure to fine particulate matter (PM_2.5) has been linked to chronic liver injury and cancer. However, an alternative risk assessment method to prospective longitudinal studies of exposome-metabolome interactions for liver inflammation-associated hepatocellular carcinoma (HCC) is lacking. This study investigates the risk of long-term real-world PM_2.5 exposure in hepatocarcinogenesis through machine learning techniques. Shotgun mass spectrometry (MS) imaging data were acquired from mouse models across a continuum of fibrosis, cirrhosis, and HCC for training a multiclass classification model to identify "No Risk", "Cancer Risk", and "Cancer". Direct infusion-MS data from PM_2.5-exposed mouse livers were analyzed to classify risk. By integrating data-driven and knowledge-based approaches, 14 disease progression biomarkers were identified for modeling. Our results suggest that chronic real-world PM_2.5 exposure can induce liver fibrosis, presenting cancer risk. Incorporating metabolomics, lipidomics, and transcriptomics, we propose PM_2.5 exposure induces mitochondrial dysfunction, activates AMPK signaling, and increases ceramide accumulation, potentially mediating insulin resistance that contributes to nonalcoholic fatty liver disease and HCC progression. This work represents a significant advancement in assessing hepatotoxicity of environmental toxicants by reducing reliance on traditional animal testing methods. It also underscores the potential of emerging technologies in transforming our understanding of PM_2.5 exposure, paving the way for targeted interventions.

PMID:41883379 | PMC:PMC13010293 | DOI:10.1021/envhealth.5c00401