bims-netuvo 2025-12-21 papers

bims-netuvo

Biomed News

on Nerves in tumours of visceral organs

Issue of 2025–12–21
six papers selected by
Maksym V. Kopanitsa, Charles River Laboratories

Neuronal innervation of breast cancer promotes metastatic dissemination.
Aberrant hypothalamic neuronal activity blunts glucocorticoid diurnal rhythms in murine breast cancer.
Clinical significance of the relative location of perineural cancer invasion on prostate biopsy: Detection within 1-mm of the core tip as an independent prognosticator.
Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.
Novel magnetic resonance imaging (MRI)-based radiomics for predicting perineural invasion in rectal cancer: a two-centre study.
Prognostic Value of Cognitive Impairment in Patients with Pancreatic Cancer.

bioRxiv. 2025 Nov 29. pii: 2025.11.25.690523. [Epub ahead of print]

Neuronal innervation of breast cancer promotes metastatic dissemination.

Anthony J Schulte, Eran R Andrechek.

Metastasis is a leading cause of mortality in breast cancer patients, yet the signaling promoting metastatic dissemination is not completely understood. Prior literature implicates neuronal innervation in tumor progression, including recent studies in breast cancer progression with the 4T1 and PyMT cell line orthotopic injection models. Our experiments address the immune limitations of these studies with an alternative model to elucidate neuronal control of metastatic breast cancer by using a MMTV-PyMT transplant model and resiniferatoxin (RTX) for denervation. To this end, we generated a robust array of spontaneous MMTV-PyMT tumors with various histological subtypes. These tumors were transplanted into RTX challenged MMTV-Cre mice. In contrast to previous literature, denervation did not impact survival or tumor growth. Interestingly, we noticed a slight reduction in the percent of the solid poorly differentiated tumors with a corresponding increase in tumors that contained a mixed pathology in RTX challenged mice. Strikingly, and consistent with prior work, we noted a reduction in metastasis with denervation. Together, these data suggest neuronal innervation promotes metastasis without impacting tumor growth.

DOI: https://doi.org/10.1101/2025.11.25.690523
Neuron. 2025 Dec 15. pii: S0896-6273(25)00892-X. [Epub ahead of print]

Aberrant hypothalamic neuronal activity blunts glucocorticoid diurnal rhythms in murine breast cancer.

Adrian M Gomez, Yue Wu, Chao Zhang, Leah Boyd, Tse-Luen Wee, Joseph Gewolb, Corina Amor, Lucas Cheadle, Jeremy C Borniger.

  Breast cancer patients often exhibit disrupted diurnal rhythms in circulating glucocorticoids (GCs), such as cortisol. This disruption correlates with reduced quality of life and higher cancer mortality; however, the exact cause of this phenomenon remains unclear. Here, we demonstrate that breast tumor-bearing mice exhibit blunted GC rhythms and a loss of diurnal rhythms in the activity of paraventricular hypothalamic neurons expressing corticotropin-releasing hormone (PVNCRH). This change in neuronal activity is mediated by disinhibition from upstream GABAergic neurons. Using chemogenetics to stimulate PVNCRH neurons at different times of day, we show that stimulation just before the light-to-dark transition restores normal GC rhythms, reduces tumor progression, and increases intra-tumor effector T cells (CD8+). Our findings demonstrate that breast cancer distally regulates neurons in the hypothalamus that control the output of the hypothalamic-pituitary-adrenal (HPA) axis and provide evidence that therapeutic targeting of these neurons could mitigate tumor progression via enhancing anti-tumor immunity.

Keywords:  HPA axis; breast cancer; cancer neuroscience; diurnal; glucocorticoids; paraventricular nucleus

DOI:  https://doi.org/10.1016/j.neuron.2025.11.019
Hum Pathol. 2025 Dec 11. pii: S0046-8177(25)00302-8. [Epub ahead of print]168 106015

Clinical significance of the relative location of perineural cancer invasion on prostate biopsy: Detection within 1-mm of the core tip as an independent prognosticator.

Olalekan K Lanipekun, Ying Wang, Hiroshi Miyamoto.

  Perineural invasion (PNI) detected on prostate biopsy is a recognized indicator of aggressive disease including extraprostatic extension. However, the clinical relevance of its relative location within the biopsy core remains poorly understood. We herein assessed corresponding radical prostatectomy findings and long-term oncologic outcomes in 180 prostate cancer patients exhibiting only a single focus of PNI on the entire systematic biopsy. PNI was located at <1-mm (n = 26; 14.4 %), ≥1 to <2-mm (n = 43; 23.9 %), ≥2 to <3-mm (n = 36; 20.0 %), ≥3 to <4-mm (n = 27; 15.0 %), ≥4 to <5-mm (n = 28; 15.6 %), or ≥5-mm (n = 20; 11.1 %) from the closest tip of the core. Univariate survival analysis in the dichotomized cohort based on the distance revealed significantly higher risks of biochemical recurrence (P < 0.001) and cancer-specific mortality (P = 0.042) in patients with PNI located <1-mm from the core tip than in those with PNI ≥1-mm. There were no significant differences in the clinicopathologic features examined, including total tumor length on biopsy or estimated tumor volume on prostatectomy, tumor grade on biopsy or prostatectomy, pT or pN category, and surgical margin status, between the <1-mm vs. ≥1-mm groups. In multivariable Cox regression analysis, PNI <1-mm from the tip (vs. ≥1-mm) showed significantly worse recurrence-free survival both before (hazard ratio 3.435, P < 0.001) and after (hazard ratio 3.228, P = 0.002) adjusting for prostatectomy factors. PNI detected within 1-mm of the biopsy core tip was thus found to independently predict a worse postoperative prognosis. This spatial detail of PNI on needle core biopsy may enhance the risk stratification of prostate cancer.

Keywords:  Perineural invasion; Prognosis; Prostate biopsy; Prostate cancer; Radical prostatectomy

DOI:  https://doi.org/10.1016/j.humpath.2025.106015
Eur J Radiol. 2025 Dec 15. pii: S0720-048X(25)00696-5. [Epub ahead of print]195 112610

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

Jianbo Li, Jie Xu, Tingting Shen, Jianjun Zhou, Peng Wang, Tianyu Lu, Dalong Li, Mengsu Zeng, Qiying Tang, Qiuyang Zhu, Haitao Sun.

   PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI for predicting preoperative perineural invasion (PNI) in pancreatic ductal adenocarcinoma (PDAC) and to evaluate its role in guiding postoperative prognostic and therapeutic decision-making.
MATERIALS AND METHODS: In this multicenter retrospective study, we enrolled 714 eligible patients, allocating 608 to a development/internal validation set and 106 from three external centers to an external validation set. The fusion clinical-radiomics-deep transfer learning (FCDR) was developed to predict PNI by integrating imaging signatures derived from deep learning and radiomics on SR-MRI with clinical risk factors and was optimized by selecting the best-performing among seven machine learning algorithms. The final model was subsequently validated for its incremental value in predicting postoperative prognosis and guiding adjuvant therapy.
RESULTS: The FCDR model achieved superior performance of PNI prediction with AUCs of 0.929, 0.886, and 0.832 across development, internal and external validation sets, significantly outperforming single clinical, DL, or radiomics models. The FCDR model-stratified high-risk group was associated with significantly worse postoperative OS and RFS (p < 0.05). Moreover, the high-risk PNI subgroup stratified by this model derived a significant OS and RFS benefit from adjuvant therapy. Model interpretability was affirmed by SHAP analysis.
CONCLUSION: The proposed interpretable fusion model serves as an effective tool for PNI evaluation, prognostic stratification, and tailoring of adjuvant therapy in PDAC, holding significant promise for personalized precision medicine.
CRITICAL RELEVANCE STATEMENT: The constructed fusion model offers a robust, non-invasive tool for identifying PNI in pancreatic ductal adenocarcinoma, showing significant potential to guide personalized treatment strategies and improve patient outcomes.

Keywords:  Deep Learning; Magnetic Resonance Imaging; Pancreatic Ductal Adenocarcinoma; Perineural Invasion

DOI:  https://doi.org/10.1016/j.ejrad.2025.112610
Clin Radiol. 2025 Nov 19. pii: S0009-9260(25)00387-3. [Epub ahead of print]92 107182

Novel magnetic resonance imaging (MRI)-based radiomics for predicting perineural invasion in rectal cancer: a two-centre study.

J Wang, T Yang, W Gong, Z Cao, W Fu, D Yang, Y Guo.

AIM: This study investigates the use of multiparametric magnetic resonance imaging (mp-MRI)-based radiomics for assessing perineural invasion (PNI) in rectal cancer.
MATERIALS AND METHODS: A retrospective analysis was performed on clinical and MRI data from 423 rectal cancer patients with confirmed surgical pathology, gathered from two centres. Of these, 343 patients from centre 1 were divided into a training set and an internal validation (in-vad) set in an 8:2 ratio, while 80 patients from centre 2 were used for independent external validation (ex-vad). Univariate and multivariate analyses were conducted on clinical features to build a clinical model. A combined model integrating both clinical and radiomic features was developed.
RESULTS: Among all patients, 131 cases (31.0 %) were PNI-positive. A multivariate analysis revealed MRI-reported T (mrT) stage (odds ratio [OR] = 1.66, P=.010) and MRI-reported N (mrN) stage (OR = 1.91, P=.002) as independent predictors of PNI, forming the clinical model. After selecting radiomic features, 30 features were used to construct the radiomics model. The area under the curve (AUC) values for the clinical model in the training, in-vad, and ex-vad sets were 0.719, 0.631, and 0.760, respectively. The AUC values for the radiomics model in the training, in-vad, and ex-vad sets were 0.841, 0.815, and 0.916, respectively, while the AUC values for the combined model in the training, in-vad, and ex-vad sets showed AUC values of 0.899, 0.826, and 0.914, respectively.
CONCLUSION: The mp-MRI-based radiomics model demonstrates high accuracy in predicting PNI status in rectal cancer, offering a noninvasive and reliable tool for preoperative assessment.

DOI: https://doi.org/10.1016/j.crad.2025.107182
Biopsychosoc Sci Med. 2025 Dec 16.

Prognostic Value of Cognitive Impairment in Patients with Pancreatic Cancer.

Yang-Chen Shen, Amornthep Jankaew, Cheng-Feng Lin, Chia-Jui Yen, Yan-Shen Shan, Po See Chen.

   OBJECTIVE: Cognitive impairment is increasingly recognized as having a significant influence on cancer prognosis; however, its relevance in pancreatic cancer remains underexplored. This study aims to evaluate the prevalence of cognitive impairment in patients with pancreatic cancer and examine its association with overall survival (OS).
METHODS: In this prospective study, 516 patients with newly diagnosed pancreatic cancer were enrolled. Baseline cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), with cognitive impairment defined as a MoCA score < 24. Kaplan-Meier survival analysis and Cox proportional hazards models were used to examine the prognostic significance of cognitive impairment, adjusting for demographic and clinical covariates.
RESULTS: The study cohort had a mean age of 64.30 years (standard deviation: 10.85), and 54.0% of the patients were diagnosed with stage IV pancreatic cancer. The median OS for the entire cohort was 17.18 months (95% confidence interval [CI]: 14.48 -19.88). Cognitive impairment was observed in 53.5% of patients. Median OS was significantly shorter in patients with cognitive impairment than in those without (14.71 vs. 26.80 mo, log-rank P <0.001). Cognitive impairment (hazard ratio [HR]=1.765, 95% CI: 1.206-2.583, P=0.003) and tumor stage (HR=2.582, 95% CI: 1.853-3.598, P <0.001) were independent prognostic factors for OS.
CONCLUSIONS: Cognitive impairment is highly prevalent and independently associated with poorer OS in pancreatic cancer. These findings support routine cognitive assessments in pancreatic cancer management and highlight the need for further investigation into underlying mechanisms.

Keywords:  CI = confidence interval; CNS = central nervous system; CRCI = cancer-related cognitive impairment; GI = gastrointestinal; HR = hazard ratio; MCI = mild cognitive impairment; MoCA = Montreal Cognitive Assessment; OS = overall survival; PHQ-9 = Patient Health Questionnaire-9; SD = standard deviation; cognitive impairment; pancreatic cancer; prognostic factor

DOI:  https://doi.org/10.1097/PSY.0000000000001465