Nature, Published online: 19 August 2025; doi:10.1038/d41586-025-02590-y
An infant with an inherited life-threatening metabolic condition has responded to a tailored therapy that uses the gene-editing tool CRISPR to correct a specific mutation.
Nature, Published online: 19 August 2025; doi:10.1038/d41586-025-02242-1
Like so much else, this small scientific programme is on the Trump administration’s hit list. This will hurt the United States, says Dan Seaton.
Nature Biotechnology, Published online: 19 August 2025; doi:10.1038/s41587-025-02770-1
A vast landscape of ‘undruggable’ cancer targets remains beyond the reach of conventional therapeutic agents. Recent advances in artificial intelligence (AI), however, are challenging this paradigm. Synthesizing insights from a Cancer Moonshot workshop, we argue that systemically addressing the undruggable target space with AI requires a new conceptual framework. We highlight the failure of current target taxonomies and the need for benchmarking datasets, and re-evaluate clinical validation for novel AI-driven modalities.
J Clin Microbiol. 2025 Aug 19:e0058525. doi: 10.1128/jcm.00585-25. Online ahead of print.
ABSTRACT
Human papillomavirus (HPV) is comprised of >200 genotypes and has an ~8 kb, circular, double-stranded DNA genome. Transmission of HPV occurs through skin-to-skin contact and infection of squamous epithelial cells of cutaneous and mucosal surfaces. HPV genotypes are categorized as low- or high-risk (hrHPV) based on oncogenic potential. There are approximately 14 types of hrHPV that can cause several types of cancer, including HPV-associated oropharyngeal squamous cell carcinoma (HPV(+)OPSCC). Detection of HPV(+)OPSCC is traditionally accomplished using p16 immunohistochemistry (IHC) and HPV-specific testing, either DNA or RNA in situ hybridization (ISH) staining or DNA-based PCR of suspected tumor biopsy tissue. More recently, platelet-poor plasma (PPP) samples from patients with HPV(+)OPSCC have proven useful for detection and quantitation of fragments of HPV circulating tumor DNA (ctDNA). ctDNA has been shown to be useful in determining treatment response and monitoring for disease recurrence. In this study, a novel droplet digital PCR assay (ddPCR) was developed and validated for the detection and quantitation of ctDNA from 5 hrHPV genotypes in PPP. Analytical sensitivity ranged from 7.71 to 19.45 fragments of HPV ctDNA per milliliter of PPP across five hrHPV genotypes. In patients with confirmed primary or recurrent HPV(+)OPSCC or HPV(-)OPSCC, testing of corresponding PPP samples (n = 32) by ddPCR demonstrated 90.63% (29/32) overall agreement with p16/HPV-ISH biopsy results. Compared with reference ddPCR assays performed at outside laboratories, our ddPCR assay yielded 90% (9/10) overall agreement. This assay may provide clinicians with a tool for monitoring HPV ctDNA prior to, during, and after treatment of an HPV-associated cancer.
IMPORTANCE: At least 14 genotypes of human papillomavirus (HPV) have been identified to have high oncogenic potential. While molecular diagnostic testing for HPV is widely available for liquid cytologic cervical samples, testing is limited for other sample types, including liquid biopsy samples, such as platelet-poor plasma (PPP). With the rising incidence of HPV-associated oropharyngeal squamous cell carcinoma (HPV(+)OPSCC), laboratory testing is an essential part of patient diagnosis, management, and surveillance. Here, we summarize the development and analytical performance validation of a multiplexed, droplet digital PCR (ddPCR) assay for the detection and quantitation of HPV circulating tumor DNA (ctDNA) in PPP. This assay may provide clinicians with a tool to address minimal residual disease for patients with an HPV-associated cancer.
PMID:40827899 | DOI:10.1128/jcm.00585-25
Expert Rev Anticancer Ther. 2025 Aug 18. doi: 10.1080/14737140.2025.2549538. Online ahead of print.
ABSTRACT
INTRODUCTION: In the era of precision medicine, molecular biomarker testing is increasingly becoming standard of care for Non-Small Cell Lung Cancer (NSCLC) patients. Tissue and liquid biopsy-based Next-Generation Sequencing (NGS) is now highly recommended.
AREAS COVERED: Different NGS platforms emerged as a cost-effective strategy to perform a massive and parallel sequencing performing higher technical sensitivity than old generation technologies in detecting low abundant alterations in challenging diagnostic samples. NGS systems can detect single nucleotide variants (SNV), small insertions and deletions (indels), copy number alterations (CNAs) and structural variants (SVs) or gene fusions across selected druggable genes optimizing clinical administration of NSCLC patients. The diagnostic implementation of the most adequate NGS panel depending on several factors that could impact on the clinical utility of testing assay.
EXPERT OPINION: Promising advanced technologies are emerging as potentially integrative tools in personalized medicine. In this context, multi-omic evaluation including genomic, transcriptomic, fragmentomic and epigenomic signatures are under investigation to significantly modify clinical algorithm of NSCLC patients. On this basis, sequencing strategies may play a pivotal role in the implementation of a new predictive model for cancer diagnosis and prognosis.
PMID:40823981 | DOI:10.1080/14737140.2025.2549538
Curr Pharm Des. 2025 Aug 13. doi: 10.2174/0113816128413220250728182852. Online ahead of print.
ABSTRACT
The use of CRISPR-Cas9 to engineer cancer cell lines has made it possible to precisely examine how cancer cells react to different drugs and therapies. Some of the key improvements are in the use of Mediator Complex Subunit 12 (MED12)-knockout cells to study cell resistance to BRAF inhibitors, CRISPR models of Epithelial-Mesenchymal Transition for breast cancer, and pharmacogenomic analysis in various cancer cell lines. CRISPR is used in immunotherapy to help Chimeric Antigen Receptor T (CAR-T) cells function better by disrupting the immune checkpoints like Programmed Cell Death Protein 1 (PD-1) and Cytotoxic T-lymphocyte- associated protein 4 (CTLA-4) and to adapt T cells to react with various antigens. As a result of these innovations, it is now possible to track how cancers like non-small cell lung cancer (NSCLC) and ovarian cancer evolve, change their epigenetic features, and find strategies to reverse their resistance. Moving forward, mixing AI analytics, single-cell multi-omics, patient-derived organoids, and CRISPR mechanisms will help improve precision oncology and speed up effective treatment planning.
PMID:40814875 | DOI:10.2174/0113816128413220250728182852
Nature Biotechnology, Published online: 18 August 2025; doi:10.1038/s41587-025-02781-y
PepMLM, a protein language model fine-tuned on protein–peptide data, can generate potent, target-specific linear peptides capable of binding to and degrading proteins ranging from cancer receptors to drivers of neurodegeneration and viral proteins, all without requiring protein structural information.
Victor Dibia shares insights into multi-agent systems. He explains their definition, demonstrates implementation using the AutoGen framework, and identifies 10 common reasons these systems fail in production. He provides guidance on when a multi-agent approach is appropriate, emphasizing evaluation-driven design and tool-focused implementations.
By Victor Dibia
Transl Lung Cancer Res. 2025 Jul 31;14(7):2369-2373. doi: 10.21037/tlcr-2025-523. Epub 2025 Jul 17.
NO ABSTRACT
PMID:40799451 | PMC:PMC12337028 | DOI:10.21037/tlcr-2025-523
LangChain has released Open SWE, a fully open-source, asynchronous coding agent designed to operate in the cloud and handle complex software development tasks. The company says Open SWE represents a shift away from real-time “copilot” assistants toward more autonomous, long-running agents that integrate directly with a developer’s existing workflows.
By Robert Krzaczyński
Nature, Published online: 13 August 2025; doi:10.1038/s41586-025-09398-w
A study presents ALPACA, a computational method for inferring clone- and allele-specific copy numbers of individual clones from multi-sample bulk DNA-sequencing data, and demonstrates its use to study metastasis trajectories.
Artificial intelligence models that can discover drugs and write code still fail at puzzles a lay person can master in minutes. This phenomenon sits at the heart of the challenge of artificial general intelligence (AGI). Can today’s AI revolution produce models that rival or surpass human intelligence across all domains? If so, what underlying enablers—whether hardware, software, or the orchestration of both—would be needed to power them?
Dario Amodei, co-founder of Anthropic, predicts some form of “powerful AI” could come as early as 2026, with properties that include Nobel Prize-level domain intelligence; the ability to switch between interfaces like text, audio, and the physical world; and the autonomy to reason toward goals, rather than responding to questions and prompts as they do now. Sam Altman, chief executive of OpenAI, believes AGI-like properties are already “coming into view,” unlocking a societal transformation on par with electricity and the internet. He credits progress to continuous gains in training, data, and compute, along with falling costs, and a socioeconomic value that is
“super-exponential.”
Optimism is not confined to founders. Aggregate forecasts give at least a 50% chance of AI systems achieving several AGI milestones by 2028. The chance of unaided machines outperforming humans in every possible task is estimated at 10% by 2027, and 50% by 2047, according to one expert survey. Time horizons shorten with each breakthrough, from 50 years at the time of GPT-3’s launch to five years by the end of 2024. “Large language and reasoning models are transforming nearly every industry,” says Ian Bratt, vice president of machine learning technology and fellow at Arm.
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.
This content 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.
Cell Cycle. 2025 Aug 13:1-22. doi: 10.1080/15384101.2025.2539645. Online ahead of print.
ABSTRACT
Epithelial carcinoma cells require penetration of the basement membrane (BM) to metastasize. The BM is a thin layer of extracellular matrix beneath epithelial and endothelial tissues. It acts as a structural barrier, preventing cancer cells from invading and undergoing endocytosis and exocytosis. Thus, understanding the relationship between the BM and tumor immunity can lead to new strategies for halting cancer progression and metastasis. Gene expression data of 33 cancers were obtained from the Cancer Genome Atlas database. The study analyzed the correlation between BM regulatory genes, copy number variations, immune-related genes, and tumor immune dysfunction rejection (TIDE). Immunohistochemical methods were used to analyze the expression of regulatory genes. And the BM score was calculated using single-sample gene set enrichment analysis. Single-cell transcriptional sequencing determined the activation status of the BM in the tumor microenvironment. The expression of BM-related genes (BMGs) exhibited significant heterogeneity across different cancer types. Most genes were up-regulated in tumor tissues. Major single nucleotide polymorphisms of BMGs included missense mutations, while major copy number variations were heterozygous deletion and heterozygous amplification. Additionally, the expressions of immune checkpoint molecules CD276, NRP1, and C10orf54 showed positive correlations with BMS. Numerous tumors displayed a significant positive correlation between BMS and TIDE scores. We demonstrate that BM regulatory genes undergo alterations specific to different cancer types, which are associated with the expression of immune checkpoints and immune dysfunction. This indicates that BM remodeling plays an active role in modulating immune resistance, rather than being a passive structural alteration.
PMID:40799172 | DOI:10.1080/15384101.2025.2539645
Biomark Res. 2025 Aug 11;13(1):101. doi: 10.1186/s40364-025-00812-z.
ABSTRACT
BACKGROUND: Early identification of high-risk individuals is crucial for optimizing cancer screening, particularly when considering expensive and invasive methods such as multi-omics technologies and endoscopic procedures. However, developing a robust, practical multi-cancer risk prediction model that integrates diverse, multi-scale data and with proper validation remains a significant challenge.
METHODS: We initialized the FuSion study by recruiting 42,666 participants from Taizhou, China, with a discovery cohort (n = 16,340) and an independent validation cohort (n = 26,308) after exclusion criteria. We integrated multi-scale data from 54 blood-derived biomarkers and 26 epidemiological exposures to develop a risk prediction model for five common cancers, including lung, esophageal, liver, gastric, and colorectal cancer. Employing five supervised machine learning approaches, we used a LASSO-based feature selection strategy to identify the most informative predictors. The model was trained and internally validated in the discovery cohort, externally applied in the validation cohort, and further evaluated through a prospective clinical follow-up to assess cancer events via clinical examinations.
RESULTS: The final model comprising four key biomarkers along with age, sex, and smoking intensity, achieving an AUROC of 0.767 (95% CI: 0.723-0.814) for five-year risk prediction. High-risk individuals (17.19% of the cohort) accounted for 50.42% of incident cancer cases, with a 15.19-fold increased risk compared to the low-risk group. During follow-up of 2,863 high-risk subjects, 9.64% were newly diagnosed with cancer or precancerous lesions. Notably, cancer detection in the high-risk group was 5.02 times higher than in the low-risk group and 1.74 times higher than in the intermediate-risk group. In particular, the incidence of esophageal cancers in the high-risk group was 16.84 times that of the low-risk group.
CONCLUSIONS: This is the first population-based prospective study in a large Chinese cohort that leverage multi-scale data including biomarkers for multi-cancer risk prediction. Our effective risk stratification model not only enhances early cancer detection but also lays the foundation for the targeted application of advanced screening methods, including but not limited to multi-omics technologies and endoscopy. These findings support precision prevention strategies and the optimal allocation of healthcare resources.
PMID:40790537 | PMC:PMC12341305 | DOI:10.1186/s40364-025-00812-z
Cell Death Discovery, Published online: 11 August 2025; doi:10.1038/s41420-025-02674-8
Cannabichromene: integrative modulation of apoptosis, ferroptosis, and endocannabinoid signaling in pancreatic cancer therapy
Explor Target Antitumor Ther. 2025 Aug 8;6:1002333. doi: 10.37349/etat.2025.1002333. eCollection 2025.
ABSTRACT
Liquid biopsy (LB) is a complex of procedures aimed at the detection of tumor-derived fragments (nucleic acids, proteins, cells, etc.) persisting in the blood or other body fluids. It can be utilized for early cancer diagnosis, analysis of biomarkers of tumor drug sensitivity and prognosis, monitoring of minimal residual disease (MRD), etc. Circulating tumor DNA (ctDNA) is an accessible and reliable LB analyte as it may contain tumor-specific mutations and is amenable to efficient detection by next-generation sequencing (NGS) or droplet digital PCR (ddPCR). High level of ctDNA is typically associated with increased tumor burden and poor prognosis, whereas treatment-related ctDNA clearance increases the probability of a favorable disease outcome. Major efforts have been invested in enhancing the analytical performance of ctDNA detection. Stimulation of apoptosis of tumor cells by irradiation of cancer lumps has been shown to result in a transient but modest increase in ctDNA concentration. There are several sophisticated modifications of ultra-deep NGS protocols, which discriminate between "true" low-copy mutation-specific signals and sequencing artifacts. Slowing physiological ctDNA decay by interfering with liver macrophages and circulating nucleases has shown promise in animal experiments. Reproducibility of ctDNA-based LB assays remains insufficient for samples with ultra-low content of ctDNA; hence, interlaboratory harmonization of ctDNA testing procedures is of paramount importance.
PMID:40787067 | PMC:PMC12332530 | DOI:10.37349/etat.2025.1002333
Nature Biotechnology, Published online: 12 August 2025; doi:10.1038/s41587-025-02795-6
Children with rare genetic diseases get CRISPR Cures center
Recent research by Anthropic engineers explores identifiable patterns of activity that seems to give rise to an emerging personality. These traits, known as persona vectors, help explain how a model's personality shifts over its lifecycle and lay the groundwork for better controlling those changes.
By Sergio De Simone
Vercel has released AI Elements, an open-source library of React UI primitives built atop shadcn/ui and designed to integrate with the Vercel AI SDK.
By Daniel Dominguez
Login