Am J Hum Genet. 2025 Jan 6:S0002-9297(24)00456-7. doi: 10.1016/j.ajhg.2024.12.014. Online ahead of print.

ABSTRACT

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole-genome sequencing (WGS) of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. We show that haplotype-based calling methods can be used with WGS data to successfully identify mLOY events. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European (EUR) ancestry group compared to other ancestries. We identify multiple loci associated with mLOY susceptibility and show that subsets of human hematopoietic stem cells are enriched for the activity of mLOY susceptibility variants. Finally, we found that certain alleles on chromosome Y are more likely to be lost than others in detectable mLOY clones.

PMID:39809269 | DOI:10.1016/j.ajhg.2024.12.014

Cancer Lett. 2025 Jan 12;612:217462. doi: 10.1016/j.canlet.2025.217462. Online ahead of print.

ABSTRACT

A user-friendly integrated database, RMethyMD (http://www.tmliang.cn/rnamethy), was developed to provide a comprehensive analysis of methylation regulators aimed at facilitating the exploration of molecular features in tumorigenesis and clinical implications in cancer diagnosis and treatment via a multiomics approach. Subsequently, molecular landscapes and a robust constructed m6A-based prognostic model using coxBoost + RSF algorithms in lung cancer highlighted m6A as a suitable marker to guide therapeutic strategy. RMethyMD provides a comprehensive resource and multiomics analysis to explore m6A-based prognostic and clinical values, thereby contributing to aiding personalized cancer therapy.

PMID:39809358 | DOI:10.1016/j.canlet.2025.217462

Radiother Oncol. 2025 Jan 10;204:110715. doi: 10.1016/j.radonc.2025.110715. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Quantifying tumor heterogeneity from various dimensions is crucial for precise treatment. This study aimed to develop and validate multi-omics models based on the computed tomography images, pathological images, dose and clinical information to predict treatment response and overall survival of non-small cell lung cancer (NSCLC) patients undergoing chemotherapy and radiotherapy.

MATERIALS AND METHODS: This retrospective study included 220 NSCLC patients from three centers. Following feature extraction and selection, single-omics and multi-omics models were built for treatment response and overall survival prediction. The performance of treatment response models was evaluated using the area under the curve (AUC) and box plots. For overall survival analysis, the model's evaluation included AUC, concordance index (C-index), Kaplan-Meier curves, and calibration curves. Shapley values were used to assess the contribution of different features to multi-omics models.

RESULTS: Multi-omics models consistently exhibited superior discriminative ability compared to single-omics models in predicting both treatment response and overall survival. For treatment response, the three all-modality models achieved AUC values of 0.87, 0.91, and 0.82 in the external validation set, respectively. In overall survival analysis, the three all-modality models demonstrated AUC values and C-index of 0.73/0.72, 0.80/0.77, 0.79/0.78 in the external validation set, respectively.

CONCLUSION: Multi-omics prediction models demonstrated superior predictive ability with robustness and interpretability. By predicting treatment response and overall survival in NSCLC patients, these models have the potential to assist clinician optimizing treatment plans, supporting individualized treatment strategies, improving the tumor control probability and prolonging the patients' survival.

PMID:39800269 | DOI:10.1016/j.radonc.2025.110715

Global Spine J. 2025 Jan;15(1_suppl):16S-28S. doi: 10.1177/21925682231222012.

ABSTRACT

STUDY DESIGN: Narrative review.

OBJECTIVES: This article aims to provide a narrative review of the current state of research for liquid biopsy in spinal tumors and to discuss the potential application of liquid biopsy in the clinical management of patients with spinal tumors.

METHODS: A comprehensive review of the literature was performed using PubMed, Google Scholar, Medline, Embase and Cochrane databases, and the review was limited to articles of English language. All the relevant articles which were identified to be related to liquid biomarker study in spinal tumors, were studied in full text.

RESULTS: Liquid biopsy has revolutionized the field of precision medicine by guiding personalized clinical management of cancer patients based on the liquid biomarker status. In recent years, more research has been done to investigate its potential utilization in patients with tumors from the spine. Herein, we review the liquid biomarkers that have been proposed in different spine malignancies including chordoma, chondrosarcoma, Ewing sarcoma, osteosarcoma, astrocytoma and ependymoma. We also discuss the wide window of opportunity to utilize these liquid biomarkers in diagnosis, treatment response, monitoring, and detection of minimal residual disease in patients with spinal tumors.

CONCLUSIONS: Liquid biomarkers, especially blood-derived circulating tumor DNA, has a promising clinical utility as they are disease-specific, minimally invasive, and the procedure is repeatable. Prospective studies with larger populations are needed to fully establish its use in the setting of spinal tumors.

PMID:39801114 | PMC:PMC11726521 | DOI:10.1177/21925682231222012