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

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

Cancers (Basel). 2024 Dec 12;16(24):4145. doi: 10.3390/cancers16244145.

ABSTRACT

Lung cancer is a deadly disease with the highest rates of mortality. Over recent decades, a better understanding of the biological mechanisms implicated in its pathogenesis has led to the development of targeted therapies and immunotherapy, resulting in improvements in patient outcomes. To better understand lung cancer tumor biology and advance towards precision oncology, a comprehensive tumor profile is necessary. In recent years, novel in situ spatial multiomics approaches have emerged offering a more detailed view of the spatial location of tumor and tumor microenvironment cells, identifying their unique composition and functional status. In this sense, novel multiomics platforms have been developed to evaluate tumor heterogeneity, gene expression, metabolic reprogramming, signaling pathway activation, cell-cell interactions, and immune cell programs. In lung cancer research, several studies have used these spatial technologies to locate cells and associated them with histological features that are relevant to the pathogenesis of lung adenocarcinoma. These advancements may unveil further molecular and immune mechanisms in tumor biology that will lead to the discovery of biomarkers for treatment prediction and prognosis. In this review, we provide an overview of more widely used and emerging pathology-based approaches for spatial immune profiling in lung cancer and how they enhance our understanding of tumor biology and immune response.

PMID:39766047 | PMC:PMC11674389 | DOI:10.3390/cancers16244145

Nat Commun. 2025 Jan 8;16(1):430. doi: 10.1038/s41467-024-55428-y.

ABSTRACT

The analysis of circulating tumour DNA (ctDNA) through minimally invasive liquid biopsies is promising for early multi-cancer detection and monitoring minimal residual disease. Most existing methods focus on targeted deep sequencing, but few integrate multiple data modalities. Here, we develop a methodology for ctDNA detection using deep (80x) whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive approach than bisulphite sequencing, which permits the simultaneous analysis of genomic and methylomic data. We conduct a diagnostic accuracy study across multiple cancer types in symptomatic patients, achieving 94.9% sensitivity and 88.8% specificity. Matched tumour biopsies are used for validation, not for guiding the analysis, imitating an early detection scenario. Furthermore, in silico validation demonstrates strong discrimination (86% AUC) at ctDNA fractions as low as 0.7%. Additionally, we successfully track tumour burden and ctDNA shedding from precancerous lesions post-treatment without requiring matched tumour biopsies. This pipeline is ready for further clinical evaluation to extend cancer screening and improve patient triage and monitoring.

PMID:39779727 | PMC:PMC11711490 | DOI:10.1038/s41467-024-55428-y

Int J Mol Sci. 2024 Dec 20;25(24):13669. doi: 10.3390/ijms252413669.

ABSTRACT

Liquid biopsy (LB) involves the analysis of circulating tumour-derived DNA (ctDNA), providing a minimally invasive method for gathering both quantitative and qualitative information. Genomic analysis of ctDNA through next-generation sequencing (NGS) enables comprehensive genetic profiling of tumours, including non-driver alterations that offer prognostic insights. LB can be applied in both early-stage disease settings, for the diagnosis and monitoring of minimal residual disease (MRD), and advanced disease settings, for monitoring treatment response and understanding the mechanisms behind disease progression and tumour heterogeneity. Currently, LB has limited use in clinical practice, primarily due to its significant costs, limited diagnostic yield, and uncertain prognostic role. The application of artificial intelligence (AI) in the medical field is a promising approach to processing extensive information and applying it to individual cases to enhance therapeutic decision-making and refine risk assessment.

PMID:39769431 | PMC:PMC11727717 | DOI:10.3390/ijms252413669

Biomedicines. 2024 Dec 13;12(12):2840. doi: 10.3390/biomedicines12122840.

ABSTRACT

Pancreatic cancer is one of the most aggressive cancers with a very poor 5-year survival rate and reduced therapeutic options when diagnosed in an advanced stage. The dismal prognosis of pancreatic cancer has guided significant efforts to discover novel biomarkers in order to anticipate diagnosis, increasing the population of patients who can benefit from curative surgical treatment. CA 19-9 is the reference biomarker that supports the diagnosis and guides the response to treatments. However, it has significant limitations, a low specificity, and is inefficient as a screening tool. Several potential biomarkers have been discovered in the serum, urine, feces, and pancreatic juice of patients. However, most of this evidence needs further validation in larger cohorts. The advent of advanced omics sciences and liquid biopsy techniques has further enhanced this field of research. The aim of this review is to analyze the historical evolution of the research on novel biomarkers for the early diagnosis of pancreatic cancer, focusing on the current evidence for the most promising biomarkers from different body fluids and the novel trends in research, such as omics sciences and liquid biopsy, in order to favor the application of modern personalized medicine.

PMID:39767746 | PMC:PMC11673965 | DOI:10.3390/biomedicines12122840

Sci Rep. 2025 Jan 2;15(1):129. doi: 10.1038/s41598-024-83742-4.

ABSTRACT

Integration of multi-omic data for the purposes of biomarker discovery can provide novel and robust panels across multiple biological compartments. Appropriate analytical methods are key to ensuring accurate and meaningful outputs in the multi-omic setting. Here, we extensively profile the proteome and transcriptome of patient pancreatic cyst fluid (PCF) (n = 32) and serum (n = 68), before integrating matched omic and biofluid data, to identify biomarkers of pancreatic cancer risk. Differential expression analysis, feature reduction, multi-omic data integration, unsupervised hierarchical clustering, principal component analysis, spearman correlations and leave-one-out cross-validation were performed using RStudio and CombiROC software. An 11-feature multi-omic panel in PCF [PIGR, S100A8, REG1A, LGALS3, TCN1, LCN2, PRSS8, MUC6, SNORA66, miR-216a-5p, miR-216b-5p] generated an AUC = 0.806. A 13-feature multi-omic panel in serum [SHROOM3, IGHV3-72, IGJ, IGHA1, PPBP, APOD, SFN, IGHG1, miR-197-5p, miR-6741-5p, miR-3180, miR-3180-3p, miR-6782-5p] produced an AUC = 0.824. Integration of the strongest performing biomarkers generated a 10-feature cross-biofluid multi-omic panel [S100A8, LGALS3, SNORA66, miR-216b-5p, IGHV3-72, IGJ, IGHA1, PPBP, miR-3180, miR-3180-3p] with an AUC = 0.970. Multi-omic profiling provides an abundance of potential biomarkers. Integration of data from different omic compartments, and across biofluids, produced a biomarker panel that performs with high accuracy, showing promise for the risk stratification of patients with pancreatic cystic lesions.

PMID:39747972 | PMC:PMC11696309 | DOI:10.1038/s41598-024-83742-4

Semin Cancer Biol. 2024 Dec 27;109:25-43. doi: 10.1016/j.semcancer.2024.12.005. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal and common form of pancreatic cancer, it has no specific symptoms, and most of the patients are diagnosed when the disease is already at an advanced stage. Chemotherapy typically has only a modest effect, making surgery the most effective treatment option. However, only a small percentage of patients are amenable to surgery. One viable strategy to reduce PDAC death burden associated with the disease is to focus on precursor lesions and identify markers able to predict who will evolve into PDAC. While most PDACs are believed to be preceded by pancreatic intraepithelial neoplasms (PanINs), 5-10 % arise from Intraductal papillary mucinous neoplasms (IPMNs), which are mass-forming cystic lesions that are very common in the general population. IPMNs offer an invaluable model of pancreatic carcinogenesis for researchers to analyse, as well as a target population for PDAC early detection by clinicians. The evolution of IPMN into cancer is a complex and multistep process, therefore the identification of individual markers will not be the solution. In recent years, multiple omics technologies have been instrumental to identify possible biomarkers of IPMN progression and carcinogenesis. The only foreseeable strategy will be to integrate multi-omics data, alongside clinical and morphological features, into a progression score or signature using either standard epidemiologic tools or artificial intelligence. The aim of this manuscript is to review the current knowledge on genetic biomarkers and to briefly mention also additional omics, such as metabolomics, the exposome, the miRNome and epigenomics of IPMNs.

PMID:39733817 | DOI:10.1016/j.semcancer.2024.12.005