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STAMP: Single-cell transcriptomics analysis and multimodal profiling through imaging
Spatial joint profiling of DNA methylome and transcriptome in tissues
Nature, Published online: 03 September 2025; doi:10.1038/s41586-025-09478-x
DNA-methylation and gene-expression profiling of tissue sections at near single-cell resolution can be used to create detailed spatial maps showing how methylation and transcription interact to shape cell identity and tissue development.Building the AI-enabled enterprise of the future
Artificial intelligence is fundamentally reshaping how the world operates. With its potential to automate repetitive tasks, analyze vast datasets, and augment human capabilities, the use of AI technologies is already driving changes across industries.

In health care and pharmaceuticals, machine learning and AI-powered tools are advancing disease diagnosis, reducing drug discovery timelines by as much as 50%, and heralding a new era of personalized medicine. In supply chain and logistics, AI models can help prevent or mitigate disruptions, allowing businesses to make informed decisions and enhance resilience amid geopolitical uncertainty. Across sectors, AI in research and development cycles may reduce time-to-market by 50% and lower costs in industries like automotive and aerospace by as much as 30%.
“This is one of those inflection points where I don’t think anybody really has a full view of the significance of the change this is going to have on not just companies but society as a whole,” says Patrick Milligan, chief information security officer at Ford, which is making AI an important part of its transformation efforts and expanding its use across company operations.
Given its game-changing potential—and the breakneck speed with which it is evolving—it is perhaps not surprising that companies are feeling the pressure to deploy AI as soon as possible: 98% say they feel an increased sense of urgency in the last year. And 85% believe they have less than 18 months to deploy an AI strategy or they will see negative business effects.
Companies that take a “wait and see” approach will fall behind, says Jeetu Patel, president and chief product officer at Cisco. “If you wait for too long, you risk becoming irrelevant,” he says. “I don’t worry about AI taking my job, but I definitely worry about another person that uses AI better than me or another company that uses AI better taking my job or making my company irrelevant.”

But despite the urgency, just 13% of companies globally say they are ready to leverage AI to its full potential. IT infrastructure is an increasing challenge as workloads grow ever larger. Two-thirds (68%) of organizations say their infrastructure is moderately ready at best to adopt and scale AI technologies.
Essential capabilities include adequate compute power to process complex AI models, optimized network performance across the organization and in data centers, and enhanced cybersecurity capabilities to detect and prevent sophisticated attacks. This must be combined with observability, which ensures the reliable and optimized performance of infrastructure, models, and the overall AI system by providing continuous monitoring and analysis of their behavior. Good quality, well-managed enterprise-wide data is also essential—after all, AI is only as good as the data it draws on. All of this must be supported by AI-focused company culture and talent development.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
Challenges in diagnosis of sarcoidosis
Curr Opin Immunol. 2025 Sep 1;97:102652. doi: 10.1016/j.coi.2025.102652. Online ahead of print.
ABSTRACT
PURPOSE OF REVIEW: Diagnosing sarcoidosis remains challenging. Histology findings and a variable clinical presentation can mimic other infectious, malignant, and autoimmune diseases. This review synthesizes current evidence on histopathology, sampling techniques, imaging modalities, and biomarkers and explores how emerging 'omics' and artificial intelligence tools may sharpen diagnostic accuracy.
RECENT FINDINGS: Within the typical granulomatous lesions, limited or 'burned-out' necrosis is an ancillary finding, which can be present in up to one-third of sarcoid biopsies, and demands a careful differential diagnostic work-up. Endobronchial ultrasound-guided transbronchial needle aspiration of lymph nodes has replaced mediastinoscopy as first-line sampling tool, while cryobiopsy is still under validation. Volumetric PET metrics such as total lung glycolysis and somatostatin-receptor tracers refine activity assessment; combined FDG PET/MRI improves detection of occult cardiac disease. Advanced bronchoalveolar lavage (BAL) immunophenotyping via flow cytometry and serum, BAL, and genetic biomarkers show to correlate with inflammatory burden but have low diagnostic value. Multi-omics signatures and Positron Emission Tomography with Computer Tomography radiomics, supported by deep-learning algorithms, show promising results for noninvasive diagnostic confirmation, phenotyping, and disease monitoring.
SUMMARY: No single test is conclusive for diagnosing sarcoidosis. An integrated, multidisciplinary strategy is needed. Large, multicenter, and multiethnic studies are essential to translate and validate data from emerging AI tools and -omics research into clinical routine.
PMID:40902264 | DOI:10.1016/j.coi.2025.102652
Enabling Digital Compassion in Digital Health Environments: Modified eDelphi Study to Identify Interprofessional Competencies and Technology Attributes
Deep hierarchical subtyping of multi-organ systemic sclerosis trajectories - a EUSTAR study
npj Digital Medicine, Published online: 01 September 2025; doi:10.1038/s41746-025-01962-y
Deep hierarchical subtyping of multi-organ systemic sclerosis trajectories - a EUSTAR studyProtein lipoylation in cancer: metabolic reprogramming and therapeutic potential
Cell Death Discovery, Published online: 02 September 2025; doi:10.1038/s41420-025-02718-z
Protein lipoylation in cancer: metabolic reprogramming and therapeutic potentialLongitudinal liquid biopsy identifies an early predictive biomarker of immune checkpoint blockade response in head and neck squamous cell carcinoma
Nat Commun. 2025 Sep 1;16(1):8161. doi: 10.1038/s41467-025-63538-4.
ABSTRACT
Immune checkpoint blockade (ICB) has improved outcomes for patients with head and neck squamous cell carcinoma (HNSCC), but predictive biomarkers remain limited. Here, we use a time-resolved, multi-omic approach in a murine HNSCC model to characterize peripheral immune responses to ICB. Single-cell transcriptomics and T/B cell receptor analyses reveal early on-treatment expansion of effector memory T and B cell repertoires in responders, preceding tumor regression. These dynamic immune features inform a composite transcriptional signature that accurately predicts ICB response in independent human HNSCC cohorts. LiBIO outperforms existing biomarkers and generalizes to melanoma, non-small cell lung cancer, and breast cancer without retraining. These findings suggest that early treatment-induced changes in circulating immune repertoires reflect the host's capacity to mount an effective antitumor response. This work provides a framework for leveraging transient peripheral immune dynamics to develop non-invasive, high-fidelity biomarkers for response to immunotherapy across cancer types.
PMID:40890155 | PMC:PMC12402333 | DOI:10.1038/s41467-025-63538-4
Token Probabilities to Mitigate Large Language Models Overconfidence in Answering Medical Questions: Quantitative Study
Adherence to digital pregnancy care – lessons learned from the SMART start feasibility study
npj Digital Medicine, Published online: 30 August 2025; doi:10.1038/s41746-025-01966-8
Adherence to digital pregnancy care – lessons learned from the SMART start feasibility studyAn eyecare foundation model for clinical assistance: a randomized controlled trial
Nature Medicine, Published online: 28 August 2025; doi:10.1038/s41591-025-03900-7
Trained and validated on multimodal data from 14.5 million images from multicountry datasets, a foundation model is shown to increase diagnostic and referral accuracy of clinicians when used as an assistant in a trial involving 16 ophthalmologists and 668 patients.Multiomics Insights into the Mechanism and Enhanced Efficacy of Tumor Treating Fields (TTFields) Therapy in Glioblastoma
J Proteome Res. 2025 Sep 1. doi: 10.1021/acs.jproteome.5c00424. Online ahead of print.
ABSTRACT
Glioma is an aggressive brain tumor that requires challenging treatments. Tumor Treating Fields (TTFields), an FDA-approved therapy for glioblastoma (GBM), pleural mesothelioma, and platinum-refractory metastatic nonsmall cell lung cancer (in combination with PD-1/PD-L1 inhibitors or docetaxel), employs specific frequency electric fields to disrupt cell division and enhance treatment efficacy. However, their molecular mechanisms remain unclear. This study aimed to elucidate these mechanisms and optimize the therapeutic potential of TTFields through quantitative proteomics, phosphoproteomics, and glycoproteomics. Pathway analysis of the proteomics revealed that TTFields impact the cell cycle, DNA repair, autophagy, and DNA replication. Phosphoproteomic studies further demonstrated a marked decline in the activity of key kinases ABL1 and PDK1, while glycoproteomics highlighted disruptions in cell adhesion and ECM-receptor interactions. Notably, proteomic analysis identified an upregulation of PARP1 and BRD4 protein levels, suggesting a previously unrecognized resistance mechanism. Consistently, combining TTFields with inhibitors targeting these proteins significantly enhanced the treatment efficacy in U87 cells. Thus, this study uncovers comprehensive molecular mechanisms underlying TTFields' effects on GBM cells and supports the development of concomitant therapies to enhance treatment efficacy.
PMID:40889189 | DOI:10.1021/acs.jproteome.5c00424
How ageing changes our genes — huge epigenetic atlas gives clearest picture yet
Nature, Published online: 01 September 2025; doi:10.1038/d41586-025-02735-z
A map of DNA methylation changes in human organs could help researchers to discover more targets for anti-ageing therapies.Stereo-seq V2: Spatial mapping of total RNA on FFPE sections with high resolution
Cell. 2025 Aug 22:S0092-8674(25)00922-5. doi: 10.1016/j.cell.2025.08.008. Online ahead of print.
ABSTRACT
Performing total RNA profiling on formalin-fixed, paraffin-embedded (FFPE) samples, the predominant sample conservation method in clinical practice, remains challenging for current spatial transcriptomics techniques. Here, we introduce Stereo-seq V2, which employs random primers to capture and sequence RNAs in situ on FFPE sections and provides single-cell resolution. The random-priming-based strategy offers unbiased transcript capturing and uniform gene body coverage, which increase the sensitivity to marker genes, the efficiency of non-polyadenylation (poly(A)) RNA profiling, and immune repertoire coverage. We demonstrated the robust performance of Stereo-seq V2 on clinical FFPE samples using triple-negative breast cancer (TNBC) sections and identified tumor-specific alternative splicing events. In a Mycobacterium tuberculosis (Mtb)-infected mouse model, we monitored gene expression dynamics of host and pathogen transcriptomes simultaneously by utilizing Stereo-seq V2. We also assembled immune repertoires and identified Mtb-specific BCR clones, which could also be observed in human tuberculous lung samples. These results highlight Stereo-seq V2's potential in biomedical research and personalized medicine.
PMID:40882628 | DOI:10.1016/j.cell.2025.08.008
GeneBits: ultra-sensitive tumour-informed ctDNA monitoring of treatment response and relapse in cancer patients
J Transl Med. 2025 Aug 27;23(1):964. doi: 10.1186/s12967-025-06993-3.
ABSTRACT
BACKGROUND: Circulating tumour DNA (ctDNA) in liquid biopsies has emerged as a powerful biomarker in cancer patients. Its relative abundance in cell-free DNA serves as a proxy for the overall tumour burden. Here we present GeneBits, a method for cancer therapy monitoring and relapse detection. GeneBits employs tumour-informed enrichment panels targeting 20-100 somatic single-nucleotide variants (SNVs) in plasma-derived DNA, combined with ultra-deep sequencing and unique molecular barcoding. In conjunction with the newly developed computational method umiVar, GeneBits enables accurate detection of molecular residual disease and early relapse identification.
RESULTS: To assess the performance of GeneBits and umiVar, we conducted benchmarking experiments using three different commercial cell-free DNA reference standards. These standards were tested with targeted next-generation sequencing (NGS) workflows from both IDT and Twist, allowing us to evaluate the consistency and accuracy of our approach across different oligo-enrichment strategies. GeneBits achieved comparable depth of coverage across all target sites, demonstrating robust performance independent of the enrichment kit used. For duplex reads with ≥ 4x UMI-family size, umiVar achieved exceptionally low error rates, ranging from 7.4×10-7 to 7.5×10-5. Even when including mixed consensus reads (duplex & simplex), error rates remained low, between 6.1×10-6 and 9×10-5. Furthermore, umiVar enabled variant detection at a limit of detection as low as 0.0017%, with no false positive calls in mutation-free reference samples. In a reanalysed melanoma cohort, variant allele frequency kinetics closely mirrored imaging results, confirming the clinical relevance of our method.
CONCLUSION: GeneBits and umiVar enable highly accurate therapy and relapse monitoring in plasma as well as identification of molecular residual disease within four weeks of tumour surgery or biopsy. By leveraging small, tumour-informed sequencing panels, GeneBits provides a targeted, cost-effective, and scalable approach for ctDNA-based cancer monitoring. The benchmarking experiments using multiple commercial cell-free DNA reference standards confirmed the high sensitivity and specificity of GeneBits and umiVar, making them valuable tools for precision oncology. UmiVar is available at https://github.com/imgag/umiVar .
PMID:40866952 | PMC:PMC12382282 | DOI:10.1186/s12967-025-06993-3
A multilevel genomic approach to uncover causal connections between CPFE and lung cancer subtypes: A two-sample Mendelian randomization study
Medicine (Baltimore). 2025 Aug 22;104(34):e44050. doi: 10.1097/MD.0000000000044050.
ABSTRACT
Combined pulmonary fibrosis and emphysema (CPFE) and lung cancer cast intertwined shadows, yet the molecular nexus binding them remains largely obscured. By integrating high-resolution transcriptomic landscapes, extensive genome-wide association resources, and a stratified Mendelian randomization (MR) framework, we distilled 809 differentially expressed genes and, in successive steps, confirmed their causal ties to squamous cell carcinoma, adenocarcinoma, and small cell lung cancer. The credibility of these associations was bolstered through 3 sequential validation tiers - eQTL-anchored MR, eQTL-anchored SMR, and pQTL-anchored MR analyses - each reinforcing the robustness of the signals. Within this constellation, CPPED1 emerged as a watchful sentinel that mitigates risk in squamous carcinoma, whereas CD300LF proved a formidable oncogenic catalyst in the small cell lineage. Collectively, these insights illuminate the heritable circuitry linking CPFE and lung cancer, chart avenues for proactive surveillance and precision therapeutics in vulnerable patients, and enrich the conceptual framework of the fibrosis-to-carcinoma transition, inviting deeper multi-omic synthesis and incisive mechanistic exploration.
PMID:40859573 | PMC:PMC12385043 | DOI:10.1097/MD.0000000000044050
RPN1 Is Associated With Immunosuppression in Pan-Cancer and Affects the Malignant Phenotype of Tumor
FASEB J. 2025 Aug 31;39(16):e70978. doi: 10.1096/fj.202500722RR.
ABSTRACT
Ribophorin 1 (RPN1), a key component of the oligosaccharyltransferase complex, is implicated in tumor progression through glycosylation-mediated pathways, yet its pan-cancer roles remain unexplored. This study presents a comprehensive multi-omics analysis of RPN1 across 33 cancers such as sarcoma (SARC), integrating genomic, transcriptomic, and proteomic data from TCGA, GTEx, and CPTAC. RPN1 was significantly overexpressed in 14 malignancies and correlated with advanced tumor stages and poor prognosis in glioblastoma (GBM), lower-grade glioma, SARC and hepatocellular carcinoma, validated in an independent glioma cohort (n = 151). Genomically, RPN1 amplification linked to homologous recombination deficiency and elevated tumor mutational burden, suggesting a role in genomic instability. Critically, multiplex immunofluorescence demonstrates RPN1 overexpression colocalizes with CD206+ M2 macrophages in tumor microenvironments, while in vitro coculture experiments confirm RPN1-dependent microglial recruitment and M2 polarization. RPN1 expression negatively correlates with CD8+ T cell infiltration and predicts resistance to chemotherapy (GBM, ovarian cancer) and immunotherapy (GBM, esophageal carcinoma), though it associates with PD-1 inhibitor sensitivity in bladder cancer. Functional validation shows RPN1 knockdown suppresses proliferation, migration, and invasion in GBM cells. Pathway enrichment connects RPN1 to endoplasmic reticulum stress, glycosylation, DNA repair, and immune checkpoint regulation. These findings position RPN1 as a multimodal oncogenic driver promoting genomic instability, immunosuppressive microenvironment remodeling, and context-dependent therapeutic vulnerabilities across cancers.
PMID:40857034 | DOI:10.1096/fj.202500722RR
The emerging role of microbiota in lung cancer: a new perspective on lung cancer development and treatment
Cell Oncol (Dordr). 2025 Aug 26. doi: 10.1007/s13402-025-01103-3. Online ahead of print.
ABSTRACT
Lung cancer remains the leading cause of cancer-related mortality worldwide, with limited treatment efficacy and frequent resistance to conventional therapies. Recent advances have uncovered the critical influence of the human microbiota-complex communities of bacteria, viruses, fungi, and other microorganisms-on lung cancer pathogenesis and therapeutic responses. This review synthesizes current knowledge on the compositional and functional roles of microbiota across multiple body sites, including the gut, lung, tumor microenvironment, circulation, and oral cavity, highlighting their contributions to tumor initiation, progression, metastasis, and immune regulation. We emphasize the bidirectional communication between microbial metabolites and host immune pathways, particularly the gut-lung axis, which modulates systemic and local antitumor immunity. Importantly, microbiota composition has been linked to differential responses and toxicities in chemotherapy, radiotherapy, targeted therapy, and immune checkpoint blockade. Microbiota-targeted interventions, such as probiotics, fecal microbiota transplantation, and selective antibiotics, show promising potential to enhance treatment efficacy and mitigate adverse effects. However, challenges remain in clinical translation due to interindividual microbiome variability, mechanistic complexities, and limited longitudinal data. Future research integrating multi-omics, microbial functional profiling, and controlled clinical trials is essential to harness the microbiome as a precision medicine tool in lung cancer management. This review provides a comprehensive overview of the emerging role of microbiota in lung cancer development and therapy, offering new perspectives for innovative therapeutic strategies.
PMID:40856929 | DOI:10.1007/s13402-025-01103-3
Pig lung transplanted into a person in world first
Nature, Published online: 26 August 2025; doi:10.1038/d41586-025-02708-2
Lungs are complex organs to transplant, but the surgery is a step towards clinical trials.