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Novel Spatial Approaches to Dissect the Lung Cancer Immune Microenvironment

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

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

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

The Role of ctDNA in the Management of Non-Small-Cell Lung Cancer in the AI and NGS Era

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

The Past, Present, and Future of Biomarkers for the Early Diagnosis of Pancreatic Cancer

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

Complex rearrangements fuel ER<sup>+</sup> and HER2<sup>+</sup> breast tumours

Nature, Published online: 08 January 2025; doi:10.1038/s41586-024-08377-x

A study identifies three dominant genomic archetypes of breast cancer induced by discrete mutational processes, describing a continuum of genomic profiles and detailing the mechanisms underlying the progression of breast cancer.
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