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Biomedical subjects

Yue Pan

Publications and source records attributed to Yue Pan.

3 recordsLinked to original sources

CTSG Suppresses Breast Cancer Progression by Inhibiting the EGFR/ERK Signaling Pathway and Enhancing CD8⁺ T Cell Activation.

BACKGROUND: Breast cancer (BC), the most common female malignancy, has metastasis as its main cause of mortality. Cathepsin G (CTSG) is involved in tumorigenesis and immunity. This study explores the role of CTSG in BC progression and CD8 + T cell regulation. METHODS: Differentially expressed genes and proteins (DEGs/DEPs) were analyzed using Limma, and core genes were screened using Random Forest (RF) and Least absolute shrinkage and selection operator (LASSO). CTSG expression was analyzed using GSE36295, the Cancer Genome Atlas (TCGA), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and western blot. Cell viability, proliferation, cell cycle, migration, and invasion were detected using Cell Counting Kit-8 (CCK8), 5&#x2011;Ethynyl&#x2011;2'&#x2011;deoxyuridine (EdU), flow cytometry, and Transwell assays, respectively. Sphere diameter was analyzed via sphere formation assay. Downstream mechanisms were examined using western blot, CCK8, flow cytometry, and Transwell assays. CD8 + T cell activity was examined using EdU, western blot, and flow cytometry. RESULTS: A total of 177 genes overlapped between GSE36295 DEGs and PDC000173 DEPs. CTSG was the hub gene identified by RF and LASSO. CTSG expression was significantly reduced in BC (P < 0.01). CTSG overexpression suppressed cell viability, proliferation, migration, invasion, sphere formation, and CD44 and CD133 expression (P < 0.01). CTSG up-regulation inhibited epidermal growth factor receptor (EGFR)/extracellular signal-regulated kinase (ERK) signaling axis and reduced cancer cell malignancy (P < 0.01). CTSG overexpression activated CD8 + T cells via EGFR/ERK inhibition, enhancing their cytotoxic effect on cancer cells (P < 0.01). CONCLUSION: CTSG inhibits BC malignancy and enhances CD8 + T cell function via EGFR/ERK inhibition.

Humans

Genome-wide characterization of ZmCRY genes: unveiling stress response mechanisms and the role of ZmCRYPHR2 in salinity tolerance.

BACKGROUND: Blue light serves as a crucial environmental signal regulating plant growth and development. The cryptochrome (CRY) family represents a key class of blue light receptors involved in these processes, as well as plant growth, development, and defense. However, the functions of CRYs in maize remain largely unexplored. RESULTS: In this study, nine ZmCRY genes were identified and found to be unevenly distributed across five chromosomes. Gene structure and conserved motif analyses revealed that ZmCRYs within the same phylogenetic groups are highly conserved. Synteny analysis indicated a close evolutionary relationship between ZmCRYs and their homologs in Oryza sativa. Promoter analysis identified diverse cis-regulatory elements linked to light response, stress tolerance, and hormone signaling. RT-qPCR analysis showed that ZmCRYs respond to various abiotic and biotic stresses, including high salinity, drought, nitrogen deficiency, Fusarium verticillioides, and Puccinia polysora. Functional studies demonstrated that ZmCRYPHR2, localized in chloroplasts and the cytoplasmic membrane, plays a role in scavenging reactive oxygen and regulating maize salt tolerance. Haplotype 2 of ZmCRYPHR2 was identified as the preferred haplotype in a panel of 269 inbred lines. CONCLUSIONS: These findings provide a comprehensive genomic and functional characterization of the ZmCRY gene family, with ZmCRYPHR2 identified as a pivotal regulator of salt tolerance, offering valuable genetic insights for the development of stress-resilient maize breeding.

Zea mays

MOADE: a multimodal autoencoder for dissociating bulk multi-omics data.

In single cell biology, the complexity of tissues may hinder lineage cell mapping or tumor microenvironment decomposition, requiring digital dissociation of bulk tissues. Many deconvolution methods focus on transcriptomic assay, not easily applicable to other omics due to ambiguous cell markers and reference-to-target difference. Here, we present MOADE, a multimodal autoencoder pipeline linking multi-dimensional features to jointly predict personalized multi-omic profiles and cellular compositions, using pseudo-bulk data constructed by internal non-transcriptomic reference and external scRNA-seq data. MOADE is evaluated through rigorous simulation experiments and real multi-omic data from multiple tissue types, outperforming nine deconvolution pipelines with superior generalizability and fidelity.

Humans