Biology subjects

Nojima, Y.

Publications and source records attributed to Nojima, Y..

2 recordsLinked to original sources

bioRxiv2024

Identification of the differences in molecular networks between idiopathic pulmonaryfibrosis and lung squamous cell carcinoma using machine learning

Idiopathic pulmonary fibrosis (IPF), a form of idiopathic interstitial pneumonia, is an independent risk factor for lung cancer. The prognosis of IPF patients with lung cancer is poorer than that of IPF patients without lung cancer, and preventive measures for lung cancer remain elusive in patients with IPF. To mitigate lung cancer onset in patients with IPF, understanding the distinct mechanisms that induce both diseases is crucial. We developed highly accurate machine learning (ML) models to classify patients with IPF and lung cancer using public RNA sequencing data. To construct the ML models, the random restart technique was applied to five algorithms, namely, k-nearest neighbors, support vector machines (SVM) with radial basis function kernel, SVM with linear kernel, eXtreme gradient boosting, and random forest. To identify differentially expressed genes between IPF and lung cancer, feature importance was calculated in the classification models. Furthermore, we detected somatic mutations impacting gene expression using lung cancer data. The ML models identified VCX2, TMPRSS11B, PRUNE2, PRG4, PZP, SCARA5, DES, HPSE2, HOXD11, S100A7A, and PLA2G2A11 as differentially expressed genes. Somatic mutations were detected in four transcription factors, BHLHE40, MYC, STAT1, and E2F4, that regulate the expression of the abovementioned 11 genes. Furthermore, a molecular network was discovered, comprising the four transcription factors and 11 downstream genes. The newly identified molecular network enhances our understanding of the distinct mechanisms underlying IPF and lung cancer onset, providing new insights into the prevention of lung cancer complications in patients with IPF.

cancer biology↗

bioRxiv2020

PD-L1 expression in equine malignant melanoma and functional effects of PD-L1 blockade

Programmed death-1 (PD-1) is an immunoinhibitory receptor expressed on exhausted T cells during chronic illness. Interaction of PD-1 with its ligand PD-ligand 1 (PD-L1) delivers inhibitory signals and impairs proliferation, cytokine production, and cytotoxicity of T cells. We reported that the PD-1/PD-L1 pathway is closely associated with T-cell exhaustion and disease progression in bovine chronic infections and canine tumors. Moreover, we found that blocking antibodies targeting PD-1 and PD-L1 restore T-cell functions and may be used in immunotherapy in cattle and dogs. However, the immunological role of the PD-1/PD-L1 pathway remains unclear for chronic equine diseases, including tumors. In this study, we identified nucleotide sequences of equine PD-1 (EqPD-1) and PD-L1 (EqPD-L1) and investigated the role of anti-bovine PD-L1 monoclonal antibodies (mAbs) against EqPD-L1 using in vitro assays. We also evaluated the expression of PD-L1 in tumor tissues of equine malignant melanoma (EMM). The amino acid sequences of EqPD-1 and EqPD-L1 share a high identity and similarity with homologs from other mammalian species. Two clones of the anti-bovine PD-L1 mAbs recognized EqPD-L1 in flow cytometry, and one of these cross-reactive mAbs blocked the binding of equine PD-1/PD-L1. Importantly, PD-L1 expression was confirmed in EMM tumor tissues by immunohistochemistry. A cultivation assay revealed that PD-L1 blockade enhanced the production of Th1 cytokines in equine immune cells. These results suggest that our anti-PD-L1 mAbs may be useful for investigating the expression and role of the equine PD-1/PD-L1 pathway. Further research is required to discover the immunological role of PD-1/PD-L1 in chronic equine diseases and elucidate a future application in immunotherapy for horse.

immunology↗