bims-netuvo 2026-02-22 papers

Cell. 2026 Feb 19. pii: S0092-8674(26)00107-8. [Epub ahead of print]189(4): 993-994

Striking a nerve: Sensory neurons orchestrate ECM remodeling and immune exclusion in TNBC.

Debra Barki, Neta Eilat, Ruth Scherz-Shouval.

The tumor microenvironment drives cancer progression, yet neural contributions remain underexplored. Zhang et al. unravel a signaling circuit involving cancer cells, sensory neurons, and cancer-associated fibroblasts that promotes desmoplasia and excludes cytotoxic T cells, positioning the neuron-fibroblast axis as a therapeutic vulnerability and potential predictor of immunotherapy response.

DOI: https://doi.org/10.1016/j.cell.2026.01.020

Exp Ther Med. 2026 Apr;31(4): 96

Key role of the autonomic nervous system in breast cancer (Review).

Min Wu, Zhiwu Zhang, Lu Zhou, Shiqi Liu, Qing Chen, Cui Guo, Shasha Zhao, Xuedan Chen.

Evidence from tumor neuroscience and clinical observations have implicated the autonomic nervous system (ANS) in breast cancer pathobiology. Sympathetic activation (norepinephrine/β-adrenergic signaling) aligns with pro-angiogenic, pro-invasive programs and distant spread, whereas increased vagal activity is associated with an anti-inflammatory state and restraint of progression. The present review summarizes mechanistic, translational and clinical data supporting a bidirectional regulatory model and evaluates a variety of ANS-targeted strategies, including β-adrenergic modulation, non-invasive vagus nerve stimulation and related neuromodulatory approaches. Whilst biologic plausibility is strong, clinical evidence remains heterogeneous and limited by study design. To the best of our knowledge, no adequately powered randomized trials have demonstrated sufficient survival benefits. The present review outlines principles for standardized autonomic phenotyping (such as heart rate variability), candidate patient selection and trial endpoints to test whether ANS modulation can improve recurrence, metastasis, toxicity and quality-of-life outcomes. Through integrating convergent evidence and articulating testable hypotheses, the present review provides an ANS-informed framework to guide future breast cancer research and care.

Keywords: autonomic nervous system; breast cancer; sympathetic nerve; vagus nerve

DOI: https://doi.org/10.3892/etm.2026.13091

JCI Insight. 2026 Feb 19. pii: e192814. [Epub ahead of print]

Sympathetic nerve-fibroblast crosstalk drives nerve injury, fibroblast activation, and matrix remodeling in pancreatic cancer.

Ariana L Sattler, Parham Diba, Kevin Hawthorne, Carl Pelz, Joe Grieco, Tetiana Korzun, Bryan Chong, M J Kuykendall, Rosalie C Sears, Daniel L Marks, Mara H Sherman, Teresa A Zimmers, S Ece Eksi.

Pancreatic cancer is a highly innervated gastrointestinal disease in which sympathetic nerves play a critical role in modulating tumor growth and the tumor microenvironment (TME). While recent studies suggest that sympathetic nerves influence various TME components, including lymphoid and myeloid immune cells, their interactions with cancer-associated fibroblasts (CAFs) remain poorly understood. CAFs are a hallmark of pancreatic tumors and are known to upregulate axon guidance and neuroactive cues, suggesting a potential feedback loop with tumor-innervating nerves. Here, we investigated the bidirectional crosstalk between sympathetic nerves and CAFs in human and mouse pancreatic tumors. Using a chemo-genetic ablation model, we selectively eliminated pancreatic sympathetic nerves and found that denervation significantly reduced tumor size in female mice. To further dissect this interaction, we established co-culture systems with immortalized pancreatic fibroblasts and primary sympathetic neuron explants, identifying key transcriptional changes driven by CAF-sympathetic nerve signaling. Our findings demonstrated that sympathetic signaling enhanced CAF activation and extracellular matrix remodeling, while activated CAFs, in turn, induced transcriptional programs in sympathetic neurons associated with nerve injury response. These results establish CAFs as central mediators of the tumor-supportive role of sympathetic nerves, offering further insights into the neural regulation of pancreatic cancer progression.

Keywords: Cancer; Cell biology; Mouse models; Neuroscience; Oncology; Transcriptomics

DOI: https://doi.org/10.1172/jci.insight.192814

Front Oncol. 2026 ;16 1731999

Transcutaneous vagus nerve stimulation in breast cancer: a neuroimmune model to improve quality of life.

Melissa Do, William J Tyler.

Breast cancer care has shifted beyond remission toward optimizing long-term physiological, emotional, and functional recovery. Many survivors continue, however, to experience persistent symptom clusters, such as insomnia, fatigue, anxiety, pain, depression, and cognitive impairment. These poor quality of life outcomes reflect underlying dysregulation of autonomic, neuroendocrine, and immune systems. Autonomic imbalance characterized by vagal withdrawal and sympathetic hyperactivation is linked to increased inflammatory load, impaired stress regulation, disrupted sleep, and poorer survival outcomes. Given the role of the vagus nerve in coordinating brain-body signaling and immune modulation, transcutaneous vagus nerve stimulation (tVNS) has emerged as a promising intervention to restore autonomic balance and attenuate psychophysiological burdens. Evidence suggests that tVNS modulates locus coeruleus-norepinephrine activity, regulates arousal and sleep, reduces fatigue and anxiety, enhances cognitive function, and activates the cholinergic anti-inflammatory pathways. Supported by mechanistic and clinical evidence, we propose tVNS as a precision-guided bioelectronic strategy for improving survivorship outcomes in breast cancer.

Keywords: anxiety; autonomic regulation; breast cancer; fatigue; inflammation; insomnia; quality of life; vagus nerve stimulation

DOI: https://doi.org/10.3389/fonc.2026.1731999

Int J Med Inform. 2026 Feb 14. pii: S1386-5056(26)00088-2. [Epub ahead of print]212 106348

GAST-NET: A multi-modal and multi-task deep learning framework for preoperative prediction of perineural invasion and prognostic risk in gastric cancer.

Shidi Miao, Hexiang Dong, Jinyang Feng, Yuyang Jiang, Mengzhuo Sun, Zengyao Liu, Qiujun Wang, Xuemei Ding, Ruitao Wang.

BACKGROUND: Preoperative imaging prediction of perineural invasion in gastric cancer (GC-PNI) mainly relies on tumour characteristics and clinical variables, while the potential of non-tumour-derived multimodal features remains underexplored.
METHOD: We retrospectively enrolled 777 patients from three medical centers and divided them into a training cohort, an internal testing cohort (I-T), and two external testing cohorts (E-T1, E-T2). We developed an end-to-end multimodal and multitask deep learning framework, termed GAST-NET, that integrates tumour CT features, visceral adipose tissue characteristics, and clinical variables to jointly predict perineural invasion (PNI) and five-year prognostic survival risk (PR). The model incorporates an Adaptive Multi-scale Feature Fusion Module (AMFM) and a Cross-Scale Fusion Pooling (CSF Pooling) module to capture hierarchical semantic information and enhance discriminative cross-modal representation. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA). Furthermore, five radiologists were invited to participate in the image reading experiment to verify the clinical interpretability and diagnostic gain of the model.
RESULT: The proposed model achieved AUCs of 0.923 (95% CI: 0.865-0.969), 0.868 (95% CI: 0.791-0.934), and 0.871 (95% CI: 0.806-0.930) for PNI prediction across the internal and two external cohorts, respectively. For prognostic risk prediction, the AUC reached 0.873 (95% CI: 0.835-0.922). When used as a decision-support tool, GAST-NET significantly improved diagnostic accuracy and reduced misclassification compared with radiologists.
CONCLUSION: GAST-NET demonstrated strong generalizability and potential clinical utility in predicting perineural invasion (PNI) and prognosis in gastric cancer. Notably, visceral adipose tissue features provided complementary value for PNI prediction beyond conventional tumour characteristics.

Keywords: Deep learning; Gastric cancer; Multimodal fusion; Multitask learning; Perineural invasion; Prognostic risk

DOI: https://doi.org/10.1016/j.ijmedinf.2026.106348

Support Care Cancer. 2026 Feb 20. pii: 226. [Epub ahead of print]34(3):

Analysis of the current status and influencing factors of cognitive impairment in patients with different cancer types: a cross-sectional study.

Chen Hu, Yanfang Zheng, Xin Wang, Jie Li, Hao Gong, Ziqi Zhang, Shuyan Xing, Jiyu Wang, Yang Yang, Huiyi Lv.

OBJECTIVE: Investigation of the Prevalence of Cognitive Impairment and Its Influencing Factors in Patients with Different Cancer Types.
METHODS: A convenience sample of 1,269 cancer patients who were diagnosed and treated at our hospital from May 2024 to December 2024 was enrolled in the study. Assessments included the General Information Questionnaire, the Montreal Cognitive Assessment (MoCA), the Cancer Fatigue Scale (CFS), the Hospital Anxiety and Depression Scale (HADS), the Athens Insomnia Scale (AIS), and the Visual Analog Scale (VAS). Binary logistic regression analysis was used to identify factors influencing cognitive impairment among patients with different cancer types.
RESULTS: The average MoCA score for the 1,269 cancer patients was 22.71 ± 5.23, and 65.40% of the patients exhibited cognitive impairment. The binary logistic regression analysis indicated that clinical diagnosis, pain intensity, and the presence of depression were significant factors influencing Cognitive impairment (P < 0.05).
CONCLUSION: Cognitive impairment is highly prevalent in cancer patients, with significant variations observed across different cancer types. Pain and depression are key factors associated with this condition. The findings of this study suggest that in clinical care, routine cognitive screening should be conducted for patients with moderate to severe pain or depressive symptoms to facilitate the early identification of high-risk populations, thereby providing an evidence-based foundation for the delivery of targeted interventions and the improvement of patients' quality of life in the future.

Keywords: Cancer; Cognitive impairment; Depression; Influencing factors; Pain

DOI: https://doi.org/10.1007/s00520-026-10470-y