bims-netuvo 2025-03-09 papers

J Transl Med. 2025 Feb 28. 23(1): 246

Neuronal guanine nucleotide exchange factor promotes the axonal growth and cancer cell proliferation via Ephrin-A3/EphA2 axis in lung adenocarcinoma.

Jie Mi, Wentian Zhang, Yijiu Ren, Lei Zhu, Bei Yang, Hao Wang, Liang Duan.

BACKGROUND: Neural infiltration has been found in various cancers and the infiltrating nerves influence tumor growth and dissemination. In non-small cell lung cancer, pan-neuronal marker PGP9.5 was detected by immunohistochemical staining and its high expression correlated with poor prognosis. However, the existence of nerve fibers and the mechanism driving neural infiltration remains unclear.
METHOD: We first used immunohistochemical staining to assess the density of nerve fibers in patients with lung adenocarcinoma of different tumor sizes. Following that, we performed differential expression analysis and univariate Cox prognostic analysis, using public datasets and cell experiments to identify the gene that triggers neural infiltration and is associated with cancer progression and unfavorable prognosis. Finally, molecular biology experiments and a subcutaneous tumor model were used to deeply analyze the mechanism that the gene regulates neural infiltration and tumor progression.
RESULTS: In lung adenocarcinoma patients, the density of PGP9.5 positive nerve fibers within tumors larger than 2 cm in diameter is significantly higher than that in tumors smaller than 2 cm. Bioinformatics analysis suggested NGEF, KIF4A, and PABPC1 could be the genes that trigger neural infiltration and are associated with cancer progression and unfavorable prognosis. Subsequent co-culture experiments with neurons showed that the increased expression of NGEF in lung cancer cells significantly enhanced axonal growth in neurons. Meanwhile, GSE30219 datasets indicated that patients exhibiting high levels of NGEF expression are associated with larger tumor sizes, higher lymph node involvement, and reduced overall survival rates. At the level of molecular mechanisms, the knockdown of Ephrin-A3 in ND7/23 neurons or the use of ALW-II-41-27 resulted in a significant decrease in neurite outgrowth when co-cultured with LA795 cells. In animal model, NGEF overexpression significantly promoted tumor growth and increased the density of nerve fibers, and these effects were inhibited by ALW-II-41-27.
CONCLUSIONS: NGEF facilitates the infiltration of nerve and the growth of cancer cells in lung adenocarcinoma through the Ephrin-A3/EphA2 pathway, suggesting that NGEF is a promising target for disrupting interactions between nerves and tumors. Biomaterials that focus on NGEF are anticipated to be a potential treatment option for lung cancer.

Keywords: Axonal growth; EphA2; Ephrin-A3; Lung adenocarcinoma; NGEF

DOI: https://doi.org/10.1186/s12967-025-06233-8

J Brown Hosp Med. 2024 ;3(1): 89988

Vagus Nerve Schwannoma.

Andrew J Aultman, Matthew Genelin, Jessica Gonzalez.

Schwannomas are peripheral nerve tumors that may impact cranial nerves. We present the case of a 21-year-old male with imaging findings consistent with vagal nerve schwannoma with an atypical symptomatic presentation. A review of the presentation, characteristic imaging findings, differential diagnosis, and treatment of vagal nerve schwannoma is provided.

Keywords: carotid sheath; schwannoma; vagal nerve schwannoma; vagus nerve

DOI: https://doi.org/10.56305/001c.89988

Brief Bioinform. 2025 Mar 04. pii: bbaf082. [Epub ahead of print]26(2):

Unveiling a novel cancer hallmark by evaluation of neural infiltration in cancer.

Qi Dong, Yingying Guo, Chen Lv, Lingxue Ren, Bo Chen, Yan Wang, Yang Liu, Mingyue Liu, Kaidong Liu, Nan Zhang, Linzhu Wang, Shaocong Sang, Xin Li, Yang Hui, Haihai Liang, Yunyan Gu.

Cancer cells acquire necessary functional capabilities for malignancy through the influence of the nervous system. We evaluate the extent of neural infiltration within the tumor microenvironment (TME) across multiple cancer types, highlighting its role as a cancer hallmark. We identify cancer-related neural genes using 40 bulk RNA-seq datasets across 10 cancer types, developing a predictive score for cancer-related neural infiltration (C-Neural score). Cancer samples with elevated C-Neural scores exhibit perineural invasion, recurrence, metastasis, higher stage or grade, or poor prognosis. Epithelial cells show the highest C-Neural scores among all cell types in 55 single-cell RNA sequencing datasets. The epithelial cells with high C-Neural scores (epi-highCNs) characterized by increased copy number variation, reduced cell differentiation, higher epithelial-mesenchymal transition scores, and elevated metabolic level. Epi-highCNs frequently communicate with Schwann cells by FN1 signaling pathway. The co-culture experiment indicates that Schwann cells may facilitate cancer progression through upregulation of VDAC1. Moreover, C-Neural scores positively correlate with the infiltration of antitumor immune cells, indicating potential response for immunotherapy. Melanoma patients with high C-Neural scores may benefit from trametinib. These analyses illuminate the extent of neural influence within TME, suggesting potential role as a cancer hallmark and offering implications for effective therapeutic strategies against cancer.

Keywords: cancer hallmark; immunotherapy; neural infiltration; single-cell RNA sequencing; tumor microenvironment

DOI: https://doi.org/10.1093/bib/bbaf082

Open Biol. 2025 Mar;15(3): 240337

Schwann cells in regeneration and cancer: an epithelial-mesenchymal transition perspective.

Francisco Gracia, Berta Sanchez-Laorden, Jose A Gomez-Sanchez.

In the peripheral nervous system, glial cells, known as Schwann cells (SCs), are responsible for supporting and maintaining nerves. One of the most important characteristics of SCs is their remarkable plasticity. In various injury contexts, SCs undergo a reprogramming process that generates specialized cells to promote tissue regeneration and repair. However, in pathological conditions, this same plasticity and regenerative potential can be hijacked. Different studies highlight the activation of the epithelial-mesenchymal transition (EMT) as a driver of SC phenotypic plasticity. Although SCs are not epithelial, their neural crest origin makes EMT activation crucial for their ability to adopt repair phenotypes, mirroring the plasticity observed during development. These adaptive processes are essential for regeneration. However, EMT activation in SCs-derived tumours enhances cancer progression and aggressiveness. Furthermore, in the tumour microenvironment (TME), SCs also acquire activated phenotypes that contribute to tumour migration and invasion by activating EMT in cancer cells. In this review, we will discuss how EMT impacts SC plasticity and function from development and tissue regeneration to pathological conditions, such as cancer.

Keywords: Schwann cells; cancer; epithelial–mesenchymal transition; plasticity; regeneration

DOI: https://doi.org/10.1098/rsob.240337

Abdom Radiol (NY). 2025 Mar 07.

The value of radiomics and deep learning based on PET/CT in predicting perineural nerve invasion in rectal cancer.

Mengzhang Jiao, Zongjing Ma, Zhaisong Gao, Yu Kong, Shumao Zhang, Guangjie Yang, Zhenguang Wang.

OBJECTIVE: The objective of this study is to investigate the value of radiomics features and deep learning features based on positron emission tomography/computed tomography (PET/CT) in predicting perineural invasion (PNI) in rectal cancer.
METHODS: We retrospectively collected 120 rectal cancer (56 PNI-positive patients 64 PNI-negative patients) patients with preoperative 18F-FDG PET/CT examination and randomly divided them into training and validation sets at a 7:3 ratio. We also collected 31 rectal cancer patients from two other hospitals as an independent external validation set. χ2 test and binary logistic regression were used to analyze PET metabolic parameters. PET/CT images were utilized to extract radiomics features and deep learning features. The Mann-Whitney U test and LASSO were employed to select valuable features. Metabolic parameter, radiomics, deep learning and combined models were constructed. ROC curves were generated to evaluate the performance of models.
RESULTS: The results indicate that metabolic tumor volume (MTV) is correlated with PNI (P = 0.001). In the training set and validation set, the AUC values of the metabolic parameter model were 0.673 (95%CI: 0.572-0.773), 0.748 (95%CI: 0.599-0.896). We selected 16 radiomics features and 17 deep learning features as valuable factors for predicting PNI. The AUC values of radiomics model and deep learning model were 0.768 (95%CI: 0.667-0.868) and 0.860 (95%CI: 0.780-0.940) in the training set. And the AUC values in the validation set were 0.803 (95%CI: 0.656-0.950) and 0.854 (95% CI 0.721-0.987). Finally, the combined model exhibited AUCs of 0.893 (95%CI: 0.825-0.961) in the training set and 0.883 (95%CI: 0.775-0.990) in the validation set. In the external validation set, the combined model achieved an AUC of 0.829 (95% CI: 0.674-0.984), outperforming each individual model. The decision curve analysis of these models indicated that using the combined model to guide treatment provided a substantial net benefit.
CONCLUSIONS: This combined model established by integrating PET metabolic parameters, radiomics features, and deep learning features can accurately predict the PNI in rectal cancer.

Keywords: Computed tomography; Perineural invasion; Positron emission tomography; Rectal cancer

DOI: https://doi.org/10.1007/s00261-025-04833-y