Small-cell lung cancer (SCLC), representing 15–20% of all lung cancers, is an aggressive malignancy with a distinct natural history, poor prognosis, and limited treatment options. We have previously identified Schwann cells (SCs), the main glial cells of the peripheral nervous system, in tumor tissues and demonstrated that they may support tumor spreading and metastasis formation in the in vitro and in vivo models. However, the role of SCs in the progression of SCLC has not been investigated. To clarify this issue, the cell proliferation assay, the annexin V apoptosis assay, and the transwell migration and invasion assay were conducted to elucidate the roles in SCLC of tumor-associated SCs (TA-SCs) in the proliferation, apoptosis, migration, and invasion of SCLC cells in vitro, compared to control group. In addition, the animal models to assess SC action’s effects on SCLC in vivo were also developed. The result confirmed that TA-SCs have a well-established and significant role in facilitating SCLC cell cancer migration and invasion of SCLC in vitro, and we also observed that SC promotes tumor growth of SCLC in vivo and that TA-SCs exhibited an advantage and show a repair-like phenotype, which allowed defining them as tumor-associated repair SCs (TAR-SCs). Potential molecular mechanisms of pro-tumorigenic activity of TAR-SCs were investigated by the screening of differentially expressed genes and constructing networks of messenger-, micro-, and long- non-coding RNA (mRNA-miRNA-lncRNA) using DMS114 cells, a human SCLC, stimulated with media from DMS114-activated SCs, non-stimulated SCs, and appropriate controls. This study improves our understanding of how SCs, especially tumor-activated SCs, may promote SCLC progression. Our results highlight a new functional phenotype of SCs in cancer and bring new insights into the characterization of the nervous system-tumor crosstalk.

Objective: Immunotherapy extensively treats advanced non‐small‐cell lung cancer (NSCLC). Although immunotherapy is generally better tolerated than chemotherapy, it can cause multiple immune‐related adverse events (irAEs) involving multiple organs. Checkpoint inhibitor‐related pneumonitis (CIP) is a relatively uncommon irAE that, in severe cases, can be fatal. Potential risk factors for the occurrence of CIP are currently poorly understood. This study sought to develop a novel scoring system for predicting the risk of CIP based on a nomogram model.Methods: We retrospectively collected advanced NSCLC patients who received immunotherapy at our institution between January 1, 2018, and December 30, 2021. All patients who met the criteria were randomly divided into the training set and testing set (in a ratio of 7:3), and cases fulfilling the CIP diagnostic criteria were screened. The patients' baseline clinical characteristics, laboratory tests, imaging, and treatment information were extracted from the electronic medical records. The risk factors associated with the occurrence of CIP were identified based on the results of logistic regression analysis on the training set, and a nomogram prediction model was developed. The discrimination and prediction accuracy of the model was evaluated using the receiver operating characteristic (ROC) curve, the concordance index (C‐index), and the calibration curve. Decision curve analysis (DCA) was used to evaluate the clinical applicability of the model.Results: The training set comprised 526 (CIP: 42 cases), and the testing set comprised 226 (CIP: 18 cases) patients, respectively. In the training set, the final multivariate regression analysis revealed that age (p = 0.014; odds ratio [OR] = 1.056; 95% Confidence Interval [CI] =1.011–1.102), Eastern Cooperative Oncology Group performance status (p = 0.002; OR = 6.170; 95% CI = 1.943–19.590), history of prior radiotherapy (p < 0.001; OR = 4.005; 95% CI = 1.920–8.355), baseline white blood cell count (WBC) (p < 0.001; OR = 1.604; 95% CI = 1.250–2.059), and baseline absolute lymphocyte count (ALC) (p = 0.034; OR = 0.288; 95% CI = 0.091–0.909) were identified as independent risk factors for the occurrence of CIP. A prediction nomogram model was developed based on these five parameters. The area under the ROC curve and C‐index of the prediction model in the training set and testing set were 0.787 (95% CI: 0.716–0.857) and 0.874 (95% CI: 0.792–0.957), respectively. The calibration curves are in good agreement. The DCA curves indicate that the model has good clinical utility.Conclusion: We developed a nomogram model that proved to be a good assistant tool for predicting the risk of CIP in advanced NSCLC. This model has the potential power to help clinicians in making treatment decisions.

The lungs are a key organ in the respiratory system. They are regulated by a complex network of nerves that control their development, structure, function, and response to various pathological stimuli. Accumulating evidence suggests the involvement of a neural mechanism in different pathophysiological conditions in the lungs and the development and progression of common respiratory diseases. Lung diseases are the chief source of death globally. For instance, lung cancer is the second most commonly diagnosed malignancy, after prostate cancer in men and breast cancer in women, and is the most lethal cancer worldwide. However, although airway nerves are accepted as a mechanistically and therapeutically important feature that demands appropriate emphasizing in the context of many respiratory diseases, significantly less is known about the role of the neuroglial cells in lung physiology and pathophysiology, including lung cancer. New data have uncovered some cellular and molecular mechanisms of how Schwann cells, as fundamental components of the peripheral nervous system, may regulate lung cancer cells’ survival, spreading, and invasiveness in vitro and in vivo. Schwann cells control the formation and maintenance of the lung cancer microenvironment and support metastasis formation. It was also reported that the number of lung cancer-associated Schwann cells correlates with patients’ survival. Different factors secreted by Schwann cells, including microRNA, are known to sharpen the lung cancer environment by regulating the tumor-neuro-immune axis. Further clinical and experimental studies are required to elucidate the detailed role of Schwann cells in creating and maintaining pulmonary tumor-neuro-immune axis, which will advance our understanding of the pathogenesis of lung cancer and may inform therapeutic hypotheses aiming neoplasms and metastases in the lung.

Background:Lung cancer is a malignant disease that threatens human health. Hence, it is crucial to identify effective prognostic factors and treatment targets. Single-cell RNA sequencing can quantify the expression profiles of transcripts in individual cells.Methods:GSE117570profiles were downloaded from the Gene Expression Omnibus database. Key ligand-receptor genes in the tumor and the normal groups were screened to identify integrated differentially expressed genes (DEGs) from the GSE118370 and The Cancer Genome Atlas Lung Adenocarcinoma databases. DEGs associated with more ligand-receptor pairs were selected as candidate DEGs for Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and survival analysis. In addition, we conducted validation immunohistochemical experiments on postoperative specimens of 30 patients with lung cancer.Results:A total of 18 candidate DEGs were identified from the tumor and the normal groups. The analysis of the GO biological process revealed that these DEGs were mainly enriched in wound healing, in response to wounding, cell migration, cell motility, and regulation of cell motility, while the KEGG pathway analysis found that these DEGs were mainly enriched in proteoglycans in cancer, bladder cancer, malaria, tyrosine kinase inhibitor resistance in Epidermal Growth Factor Receptor (EGFR), and the ERBB signaling pathway. Survival analysis showed that a high, rather than a low, expression of platelet endothelial cell adhesion molecule-1 (PECAM-1) was associated with improved survival. Similarly, in postoperative patients with lung cancer, we found that the overall survival of the PECAM-1 high-expression group shows a better trend than the PECAM-1 low-expression group (p= 0.172).Conclusions:The candidate DEGs identified in this study may play some important roles in the occurrence and development of lung cancer, especially PECAM-1, which may present potential prognostic biomarkers for the outcome.