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Spatial evolution of a cachexia-promoting microenvironment in pancreatic cancer

Cell. 2026 Sep 29:S0092-8674(26)01081-0. doi: 10.1016/j.cell.2026.09.012. Online ahead of print.

ABSTRACT

Cachexia is a major cause of morbidity in pancreatic cancer, but the cellular circuitry linking tumor progression to systemic wasting remains incompletely understood. Integrating single-cell RNA sequencing, Xenium spatial transcriptomics, multiplex immunohistochemistry, bulk transcriptomics, and functional studies across human non-cachexia, pre-cachexia, and cachexia samples, together with mouse models, we define a cachexia-associated microenvironmental niche composed of SEMA4A+ tumor cells, AQP9+ macrophages, and LOXL2+ cancer-associated fibroblasts. Mechanistically, SEMA4A-associated signaling promotes bone morphogenetic protein-2 (BMP2)-dependent acquisition of an AQP9-associated macrophage phenotype, and macrophage-derived CXCL8 activates LOXL2+ fibroblasts. LOXL2+ fibroblasts reciprocally enhance tumor cell FOSL1/SEMA4A signaling through exosomal N-glycosylated LOXL2. Spatial analyses demonstrate progressive enrichment of this niche with cachexia severity and association with postoperative development of cachexia in previously non-cachectic patients. These findings provide a framework linking local tumor ecosystem dynamics to cachexia progression.

PMID:42810340 | DOI:10.1016/j.cell.2026.09.012

Single-crystal rhombohedral boron nitride wafers for integrated sliding ferroelectric memory

Nature Nanotechnology, Published online: 29 September 2026; doi:10.1038/s41565-026-02280-4

Four-inch rhombohedral-stacked boron nitride wafers are reproducibly synthesized through a step-templated interfacial epitaxy strategy, exhibiting high-density, fast-speed and non-volatile memory performances.

Transformer-Based Multitask Framework Integrating Habitat and Deep Learning for Predicting Early Disease Control and Survival in Immunotherapy-Treated Hepatocellular Carcinoma

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

GPAT3 protects against lipid stress-induced ferroptosis in hepatocellular carcinoma: From multi-omics analysis to functional validation

Biochim Biophys Acta Mol Basis Dis. 2027 Jan;1873(1):168471. doi: 10.1016/j.bbadis.2026.168471. Epub 2026 Sep 24.

ABSTRACT

BACKGROUND: The global burden of metabolic-associated hepatocellular carcinoma (HCC) is increasing, with obesity emerging as a key causal factor. However, the molecular mechanisms linking lipid metabolic dysregulation to HCC progression and therapeutic vulnerability remain unclear.

METHODS: We analyzed Global Burden of Disease 2021 data to assess liver cancer burden attributable to metabolic risks from 1990 to 2021. Mendelian randomization was used to evaluate causal associations between metabolic traits and liver cancer risk. TCGA, GTEx, and GEO datasets were integrated to identify lipid stress-responsive regulators. Clinical relevance was assessed using public datasets and tissue microarray immunohistochemistry. Functional validation was performed in HCC cells and a high-fat diet-fed syngeneic mouse tumor model.

RESULTS: Liver cancer deaths and DALYs attributable to metabolic risks increased markedly from 1990 to 2021. Mendelian randomization showed that obesity-related traits, including BMI, waist circumference, and body fat percentage, were causally associated with liver cancer risk, whereas glycemic traits were not. Bioinformatics screening identified GPAT3 as a lipid metabolism regulator upregulated in HCC, induced by palmitic acid, associated with poor prognosis, and enriched in patients with higher BMI. Tissue microarray analysis confirmed increased GPAT3 protein expression in HCC and its association with higher BMI and GPX4 expression. GPAT3 depletion sensitized HCC cells to palmitic acid-induced ferroptosis, whereas Fer-1 rescue and GPAT3 overexpression supported its protective role. In vivo, FSG67 enhanced sorafenib-associated antitumor effects and increased tumor lipid peroxidation.

CONCLUSIONS: GPAT3 protects HCC cells from lipid stress-induced ferroptosis and represents a potential metabolic vulnerability in obesity-associated HCC.

PMID:42785105 | DOI:10.1016/j.bbadis.2026.168471

GPAT3 protects against lipid stress-induced ferroptosis in hepatocellular carcinoma: From multi-omics analysis to functional validation

Biochim Biophys Acta Mol Basis Dis. 2027 Jan;1873(1):168471. doi: 10.1016/j.bbadis.2026.168471. Epub 2026 Sep 24.

ABSTRACT

BACKGROUND: The global burden of metabolic-associated hepatocellular carcinoma (HCC) is increasing, with obesity emerging as a key causal factor. However, the molecular mechanisms linking lipid metabolic dysregulation to HCC progression and therapeutic vulnerability remain unclear.

METHODS: We analyzed Global Burden of Disease 2021 data to assess liver cancer burden attributable to metabolic risks from 1990 to 2021. Mendelian randomization was used to evaluate causal associations between metabolic traits and liver cancer risk. TCGA, GTEx, and GEO datasets were integrated to identify lipid stress-responsive regulators. Clinical relevance was assessed using public datasets and tissue microarray immunohistochemistry. Functional validation was performed in HCC cells and a high-fat diet-fed syngeneic mouse tumor model.

RESULTS: Liver cancer deaths and DALYs attributable to metabolic risks increased markedly from 1990 to 2021. Mendelian randomization showed that obesity-related traits, including BMI, waist circumference, and body fat percentage, were causally associated with liver cancer risk, whereas glycemic traits were not. Bioinformatics screening identified GPAT3 as a lipid metabolism regulator upregulated in HCC, induced by palmitic acid, associated with poor prognosis, and enriched in patients with higher BMI. Tissue microarray analysis confirmed increased GPAT3 protein expression in HCC and its association with higher BMI and GPX4 expression. GPAT3 depletion sensitized HCC cells to palmitic acid-induced ferroptosis, whereas Fer-1 rescue and GPAT3 overexpression supported its protective role. In vivo, FSG67 enhanced sorafenib-associated antitumor effects and increased tumor lipid peroxidation.

CONCLUSIONS: GPAT3 protects HCC cells from lipid stress-induced ferroptosis and represents a potential metabolic vulnerability in obesity-associated HCC.

PMID:42785105 | DOI:10.1016/j.bbadis.2026.168471

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