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AI Triage in Primary Care: Building Safer and More Equitable Real-World Evidence
Mental Health Professionals’ Perceptions of Benefits and Disadvantages of Telehealth: International Mixed Methods Study
Architecting Trust in Artificial Epistemic Agents
Establishing a commercial solution for extremely rare genetic diseases
Nature Biotechnology, Published online: 02 March 2026; doi:10.1038/s41587-026-03056-w
Establishing a commercial solution for extremely rare genetic diseasesThe Transformative Potential of Liquid Biopsies and Circulating Tumor DNA (ctDNA) in Modern Oncology
Diagnostics (Basel). 2026 Feb 9;16(4):523. doi: 10.3390/diagnostics16040523.
ABSTRACT
Background: Liquid biopsy, particularly through the analysis of circulating tumor DNA (ctDNA), represents a significant advancement in oncology. Unlike traditional tissue biopsies, ctDNA offers a minimally invasive, real-time approach to cancer management. It has demonstrated considerable potential in early cancer detection, monitoring of therapeutic responses, and assessing minimal residual disease (MRD) to predict recurrence. By enabling comprehensive molecular profiling through a simple blood test, ctDNA supports the core principles of precision oncology, facilitating more personalized and adaptive treatment strategies. Methods: In the following article we describe the recent developments focused on refining ctDNA detection assays to improve sensitivity and specificity. Advanced technologies, including next-generation sequencing (NGS) and digital PCR, are commonly employed. The integration of artificial intelligence (AI) and multi-omics approaches-such as combining genomic, epigenomic, and transcriptomic data-has further enhanced the analytical power of ctDNA assays. Results: Emerging evidence shows that ctDNA-based liquid biopsy enables dynamic, real-time tracking of tumor evolution and therapeutic resistance. Clinical studies have demonstrated its efficacy in detecting early-stage cancers, guiding treatment selection, and predicting relapse with higher accuracy than some conventional methods. Moreover, AI-enhanced algorithms have improved signal detection, allowing for more precise and earlier identification of actionable mutations and MRD. Conclusions: ctDNA analysis via liquid biopsy is poised to revolutionize cancer care by offering a non-invasive, precise, and adaptive tool for tumor characterization and monitoring. Although obstacles remain-particularly regarding assay sensitivity, standardization, and economic feasibility-ongoing technological innovations and multi-omics integration are rapidly advancing its clinical viability. With continued progress, ctDNA-based liquid biopsy is likely to become a cornerstone of routine oncology practice.
PMID:41750672 | PMC:PMC12938931 | DOI:10.3390/diagnostics16040523
3D, multi-omic imaging reveals molecular biomarkers of the pre-metastatic niche in lung cancer
bioRxiv [Preprint]. 2026 Feb 18:2026.02.18.706515. doi: 10.64898/2026.02.18.706515.
ABSTRACT
The recurrence rate following complete surgical resection of primary non-small cell lung cancer is as high as 55%, yet no approach currently exists to evaluate the risk of local recurrence. The premetastatic paradigm is the recognition that metastasis is preceded by reprogramming naïve tissues to prime a microenvironment for tumor cell survival and subsequent reactivation. Identification of biomarkers of the pre-metastatic niche would allow us to evaluate a patient's risk of local relapse in the normal lung parenchyma surrounding the resected tumor. We designed a workflow incorporating in vivo modelling, radiology, and deep learning-guided three-dimensional (3D) imaging, spatial proteomics, and transcriptomics to identify previously unreported signals associated with the early transformation of the lung parenchyma announcing regional metastasis. We curated biorepository spanning timepoints before and after resection of primary Lewis Lung Carcinoma (LLC) tumors. Using radiology and cellular resolution 3D histology, we calculated the number and distribution of metastases in mouse lungs and developed an algorithm to guide placement of spatial proteomics and transcriptomics to regions containing early micro-metastases and the pre-metastatic microenvironment. Molecular and tissue features associated with presence, size, and location of metastases guided the identification of both myeloid (F4/80) and senescent (p16/p21) cell signatures in the premetastatic and metastatic environments. Finally, multiparametric flow cytometry of metastatic lungs in a senescence reporter GEMM (tdTomato-p16 INKA mice) resolved senescent cells including alveolar macrophages as the cellular phenotypes associated with these early premetastatic signatures. Altogether, this work highlights a novel AI-assisted approach for detection of biomarkers of tissue remodeling during lung cancer invasion.
PMID:41756853 | PMC:PMC12934922 | DOI:10.64898/2026.02.18.706515
Exploration of multi-omics liquid biopsy approaches for multi-cancer early detection: The PROMISE study
Innovation (Camb). 2025 Aug 6;7(1):101076. doi: 10.1016/j.xinn.2025.101076. eCollection 2026 Jan 5.
ABSTRACT
Although circulating cell-free DNA (cfDNA) methylation has emerged as the mainstream approach in multi-cancer detection blood tests (MCDBTs), the potential of integrating proteins and mutations, to enhance its performance remains unclear. The PROMISE study (NCT04972201) was conducted to investigate the feasibility of a multi-omics integration strategy in MCDBTs across nine types of cancers in head and neck (excluding nasopharynx), esophagus, lung, stomach, liver, biliary tract, pancreas, colorectum, and ovary. Blood samples were prospectively collected from 1,706 participants (840 non-cancer; 866 cancer) and then randomly divided into training and validation sets. The complementarity between various omics were investigated, and specific omics features were carefully selected for further multimodal model construction. The methylation-based classifier outperformed both the mutation-based and protein-based classifiers. As 95.0% of cancer cases detected by the mutation-based classifier were simultaneously identified by the methylation-based classifier, while 14.0% of the protein-positive samples were missed, protein markers may provide complementary value to the methylation-based classifier. Compared with the methylation-based classifier, the multimodal classifier combining methylation and protein features exhibited an improved sensitivity of 75.1% (95% confidence interval [CI], 69.3%-80.3%) at the same specificity of 98.8% with the accuracy of top predicted origin (TPO1) of 73.1% (95% CI, 66.2%-79.2%). Notably, the TPO1 accuracy reached 100% in liver and ovarian cancers with negative results of the methylation-based classifier. Collectively, these data suggest that the integration of protein markers in the multimodal classifier can offer additional benefits to the methylation-based classifier, particularly in identifying liver and ovarian cancers.
PMID:41737326 | PMC:PMC12925926 | DOI:10.1016/j.xinn.2025.101076
AI and Wearables for Early Detection of Cognitive Impairment and Dementia: Systematic Review
Evolving roles of liquid biopsy in precision medicine for colorectal cancer: from single-gene analysis to broad genomic profiling
Nat Rev Clin Oncol. 2026 Feb 20. doi: 10.1038/s41571-026-01126-1. Online ahead of print.
ABSTRACT
Colorectal cancer (CRC) is a heterogeneous malignancy, with various alterations in molecular signalling pathways driving disease progression and resistance to therapy. Liquid biopsy, as a source of circulating tumour DNA (ctDNA), has been utilized to characterize tumour molecular heterogeneity, facilitating the identification of actionable targets for precision medicine-guided therapies and the detection of emerging genomic drivers of drug resistance in patients with metastatic CRC. In addition, liquid biopsy-based analysis of ctDNA has been validated as a tool for detecting minimal residual disease (MRD) following locoregional treatment in patients with localized colon or rectal cancer, offering improved prognostic stratification and supporting the tailoring of adjuvant systemic therapy. Methodological evolution from PCR analysis of a few known mutations in one gene or a small panel of genes to the assessment of hundreds of genes and pathogenic variants by next-generation sequencing has enabled comprehensive genomic profiling (CGP), thereby improving knowledge of cancer molecular complexity at the individual patient level. In this respect, liquid biopsy-based CGP is an easily repeatable and minimally invasive approach that can provide a dynamic portrait of CRC molecular heterogeneity to guide personalized and adaptive treatment based on biomarkers of response and resistance. In this Review, we discuss current and potential roles of liquid biopsy-based ctDNA analysis in the clinical management of metastatic CRC. We also discuss the evidence supporting implementation of liquid biopsy-based assessment of MRD to refine the management of locoregional CRC and potentially improve cure rates while reducing overtreatment of many patients.
PMID:41720942 | DOI:10.1038/s41571-026-01126-1
Artificial intelligence–enhanced microsurgical training: a systematic review
npj Digital Medicine, Published online: 20 February 2026; doi:10.1038/s41746-026-02452-5
Artificial intelligence–enhanced microsurgical training: a systematic reviewHunt Globally: Deep Research AI Agents for Drug Asset Scouting in Investing, Business Development, and Search & Evaluation
Randomized-controlled trial of skills-based vr vs. distraction vr vs. sham VR for chronic low back pain
npj Digital Medicine, Published online: 16 February 2026; doi:10.1038/s41746-026-02437-4
Randomized-controlled trial of skills-based vr vs. distraction vr vs. sham VR for chronic low back painAdvancing healthcare AI governance through a comprehensive maturity model based on systematic review
npj Digital Medicine, Published online: 11 February 2026; doi:10.1038/s41746-026-02418-7
Advancing healthcare AI governance through a comprehensive maturity model based on systematic reviewThe challenge of generating and evolving real-life like synthetic test data without accessing real-world raw data -- a Systematic Review
Exploring AI-Augmented Sensemaking of Patient-Generated Health Data: A Mixed-Method Study with Healthcare Professionals in Cardiac Risk Reduction
Reliability of LLMs as medical assistants for the general public: a randomized preregistered study
Nature Medicine, Published online: 09 February 2026; doi:10.1038/s41591-025-04074-y
In a randomized controlled study involving 1,298 participants from a general sample, performance of humans when assisted by a large language model (LLM) was sensibly inferior to that of the LLM alone when assessing ten medical scenarios leading to disease identification and recommendations for treatment.Sensitive detection of cancer antigens enabled by user-defined peptide libraries
Nature Biotechnology, Published online: 09 February 2026; doi:10.1038/s41587-026-03003-9
Insights into regulatory T cell biology are accelerating therapeutic innovation in cancer immunotherapy, autoimmune diseases and transplant rejection.Integrating liquid biopsies in non-small cell lung cancer diagnosis and management: opportunities and challenges
Expert Rev Anticancer Ther. 2026 Feb 15:1-12. doi: 10.1080/14737140.2026.2630026. Online ahead of print.
ABSTRACT
INTRODUCTION: Liquid biopsy has emerged as an important approach to capture tumor-derived material from blood and other body fluids, offering a minimally invasive window into cancer biology. In non - small cell lung cancer (NSCLC), it enables comprehensive molecular profiling that informs patient management, from guiding therapy choices to monitoring disease status and assessing minimal residual disease (MRD).
AREAS COVERED: Its main advantages over tissue biopsy lie in being noninvasive, capable of reflecting tumor heterogeneity and real-time biological changes. These strengths allow liquid biopsy to be applied at different clinical timepoints, including diagnosis, treatment decision-making, evaluation during therapy, detection of resistance, and surveillance for recurrence. Although circulating tumor DNA (ctDNA) remains the most established analyte, the scope is broadening to include circulating RNAs, circulating tumor cells, exosomes, DNA methylation signatures, and tumor-educated platelets, each providing complementary insights. A literature search of PubMed, EMBASE, and Web of Science was conducted without restrictions, supplemented by screening reference lists and major oncology conference abstracts.
EXPERT OPINION: While significant progress has been made integrating liquid biopsies in NSCLC, challenges persist, encompassing issues of standardization, cost, and clinical integration.
PMID:41656166 | DOI:10.1080/14737140.2026.2630026