Nature Nanotechnology, Published online: 29 September 2026; doi:10.1038/s41565-026-02298-8
A torsion-pendulum gravitational-force sensor with an optical microcavity readout leverages coupled photon–phonon effects to enhance sensitivity to the tiny gravitational pull from a millimetre-sized source mass.
Adv Sci (Weinh). 2026 Sep 27:e78005. doi: 10.1002/advs.78005. Online ahead of print.
ABSTRACT
Hepatocellular carcinoma (HCC) patients show heterogeneous responses to immune checkpoint inhibitors (ICIs). This study developed ECOS-Net, a transformer-based multitask network integrating CT-derived habitat and 2.5-dimensional (2.5D) deep learning features for simultaneously predicting early disease control (DC) and overall survival (OS). Of 1,234 patients with HCC enrolled from eight institutions and public databases, 832 ICI-treated patients were used for model development. ECOS-Net fused features using multi-head attention and generated early DC probabilities and OS risk scores. ECOS-DC achieved AUCs of 0.836, 0.822, and 0.817 in training, internal validation, and external test sets, outperforming clinical models (all p values < 0.05). ECOS-OS yielded C-indices of 0.730, 0.722, and 0.720, respectively. Integrated models also showed favorable external performance (early DC AUC: 0.825; OS C-index: 0.741). Patients with higher ECOS-DC probabilities had a higher likelihood of early DC, whereas those with higher ECOS-OS risk had shorter OS, with directionally consistent associations across most subgroups. Exploratory biological analyses suggested that the higher ECOS-DC probability and lower ECOS-OS risk groups were associated with immune-active tumor microenvironment features. Therefore, ECOS-Net shows potential as a non-invasive imaging-based risk stratification framework for simultaneously predicting early DC and OS in ICI-treated HCC patients.
PMID:42801546 | PMC:PMC13616327 | DOI:10.1002/advs.78005
Front Oncol. 2026 Apr 15;16:1791971. doi: 10.3389/fonc.2026.1791971. eCollection 2026.
ABSTRACT
OBJECTIVE: This study aimed to integrate multi-omics analyses with genetic causal inference to identify key genes associated with cisplatin resistance in gastric cancer and to evaluate the potential mechanism by which curcumin enhances cisplatin sensitivity through relevant pathways.
METHODS: Cisplatin resistance-related transcriptomic datasets(GSE14210 and GSE31811) and a gastric cancer single-cell transcriptomic dataset (GSE183904) were obtained from the Gene Expression Omnibus(GEO)database. Differential expression analysis was performed to identify resistance-associated differentially expressed genes(DEGs),followed by GO and KEGG enrichment analyses. Putative curcumin targets were collected and intersected with DEGs to obtain candidate genes. Mendelian randomization (MR) analysis was conducted using the TwoSampleMR framework to evaluate the genetic association between RXRA expression and gastric cancer risk, with robustness and sensitivity analyses based on multiple MR methods. RXRA expression was further evaluated, along with pathway activity assessment using GSEA and GSVA, and molecular docking was performed to explore the potential binding of curcumin to RXRA. In vitro experiments were performed using the cisplatin-resistant gastric cancer cell lineNCI-N87/DDP. Drug effects and chemosensitization under combination treatment were assessed by CCK-8 assays, synergy was evaluated using the combination index(CI),and changes in key proteins in thePI3K/AKT pathway were measured by Western blotting.
RESULTS: A total of 595 DEGs associated with cisplatin resistance were identified. Functional enrichment analyses indicated that these DEGs were mainly involved in extracellular matrix remodeling and adhesion, secretion and vesicular transport, and signaling pathways including PI3K-Akt.The intersection of curcumin targets with DEGs highlighted RXRA as a key candidate gene. MR results indicated that genetically predicted increased RXRA expression was significantly associated with elevated gastric cancer risk (OR = 4.216,95%CI:1.201-14.797,P=0.025). GSEA and GSVA suggested that high RXRA expression was associated with altered activity of pathways related to lysosome, proteasome, oxidative phosphorylation, and the pentose phosphate pathway. Single-cell analysis indicated that RXRA was mainly expressed in tissue stem cells and fibroblasts. Molecular docking predicted a feasible interaction between curcumin and RXRA. In vitro experiments demonstrated that curcumin inhibited the viability of resistant cells and showed a synergistic trend when combined with cisplatin. Western blotting revealed decreased p-PI3K and p-AKT levels following curcumin treatment, supporting an inhibitory effect on the PI3K/AKT pathway.
CONCLUSION: These findings highlight RXRA as a candidate gene associated with cisplatin resistance-related programs in gastric cancer. Curcumin may enhance cisplatin sensitivity by influencing RXRA-associated transcriptional networks and suppressing PI3K/AKT signaling. This study provides new candidate targets and experimental evidence for mechanistic investigation and combination treatment strategies to overcome cisplatin resistance in gastric cancer.
PMID:42063729 | PMC:PMC13124633 | DOI:10.3389/fonc.2026.1791971
Oncogenesis, Published online: 19 April 2026; doi:10.1038/s41389-026-00619-z
PRMT6-mediated EZH2 arginine methylation is critical for breast cancer development
Nature, Published online: 15 April 2026; doi:10.1038/s41586-026-10367-0
PerturbFate is a high-throughput, cost-effective, single-cell platform that systematically profiles CRISPR interference perturbations to reveal common regulatory nodes and convergent phenotypic states across diverse genetic alterations linked to vemurafenib resistance in melanoma cells.
Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01141-2
Li et al. present PRET, a few-shot system for pan-cancer detection not requiring model fine-tuning, validated it in multicenter datasets and found that it outperformed existing approaches across tasks and pathologists in lymph node metastasis detection.
Mol Cell Biochem. 2026 Mar 13. doi: 10.1007/s11010-026-05510-4. Online ahead of print.
ABSTRACT
Pulmonary fibrosis (PF), a progressive interstitial lung disease with elusive pathogenesis, remains a therapeutic challenge. Emerging evidence suggests cuproptosis-a copper-dependent cell death pathway-may play a regulatory role in disease progression. This study aims to elucidate cuproptosis's biological function and establish a prognostic model for PF. Through integrative analysis of single-cell RNA-seq data from bleomycin (BLM)-induced mouse models and bulk RNA-seq data from idiopathic pulmonary fibrosis (IPF) patients, we identified cuproptosis-related genes (CRGs) using LASSO regression and Cox regression. A novel 4-CRG signature (LIAS, LIPT1, ATP7A, PDHB) was constructed to stratify patients into distinct risk groups in the GSE70866 cohort, where high-risk individuals exhibited poorer survival and enhanced extracellular matrix/lipid metabolism activity via GO/KEGG analysis. Experimental validation in BLM-induced mouse models, TGF-β1-stimulated fibroblast-to-myofibroblast transition assays, and human IPF specimens demonstrated significant downregulation of CRGs through qRT-PCR and immunohistochemical analyses. Functional assays revealed impaired cell viability and elevated cuproptosis markers in fibrotic microenvironments. Our findings establish an inverse correlation between cuproptosis and PF progression, and propose a robust risk-score model for clinical prognosis prediction. This multi-omics approach provides new insights into copper-mediated regulatory mechanisms in fibrogenesis.
PMID:41824199 | DOI:10.1007/s11010-026-05510-4
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