3 results on '"Sun, Yaoqi"'
Search Results
2. Comprehensive Analysis Reveals Distinct Immunological and Prognostic Characteristics of CD276/B7-H3 in Pan-Cancer.
- Author
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Ding, Jinye, Sun, Yaoqi, Sulaiman, Zubaidan, Li, Caixia, Cheng, Zhongping, and Liu, Shupeng
- Subjects
GENE expression ,PROGNOSIS ,MULTIPLE tumors ,SURVIVAL rate ,SQUAMOUS cell carcinoma - Abstract
aiman,
1 Caixia Li,1, 2 Zhongping Cheng,1, 2 Shupeng Liu1, 2 1 Department of Obstetrics and Gynecology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, People's Republic of China;2 Institute of Gynecological Minimally Invasive Medicine, School of Medicine, Tongji University, Shanghai, People's Republic of ChinaCorrespondence: Zhongping Cheng; Shupeng Liu, Email [email protected] ; [email protected] Background: CD276 (also known as B7-H3), a newly discovered immunoregulatory protein that belongs to the B7 family, is a significant and attractive target for cancer immunotherapy. Existing evidence demonstrates its pivotal role in the tumorigenesis of some cancers. However, there still lacks a systematic and comprehensive pan-cancer analysis of the role of CD276 in tumor immunology and prognosis. Methods: We explored and validated the mRNA and protein expression levels of CD276 in multiple tumors through public databases and clinical tissues specimens. The Univariate Cox regression analysis and Kaplan–Meier analysis were applied to assess the prognostic value of CD276. The correlation between CD276 expression and clinical characteristics and immunological features in diverse tumors was also explored. GSEA was performed to illuminate the biological function and involved pathways of CD276. Moreover, the CellMiner database was used to interpret the relationship between CD276 and multiple chemotherapeutic agents. CCK-8 assay was performed to validate the biological function of CD276 in vitro. Results: In general, CD276 was differentially expressed between most tumor tissues and their corresponding normal tissues. Higher expression levels of CD276 were associated with poorer survival outcomes in most tumor cohorts from TCGA. There was a close correlation between CD276 expression and clinical features, the infiltration levels of specific immune cells, immune subtypes, TMB, MSI, MMR, recognized immunoregulatory genes and drug sensitivity across diverse human cancers. The scRNA-seq data analysis further revealed that CD276 was mainly expressed on the tumor infiltrating macrophages. Additionally, in vitro experiments showed that knockdown of CD276 inhibited the proliferation of ovarian cancer (OV) and cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) cell lines. Conclusion: CD276 is a potent biomarker for predicting the prognosis and immunological features in some tumors, and it may play a critical role in the tumor immune microenvironment (TIME) through macrophage-associated signaling. [ABSTRACT FROM AUTHOR]- Published
- 2023
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3. Identification of an Autophagy-Related Signature for Prognosis and Immunotherapy Response Prediction in Ovarian Cancer.
- Author
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Ding, Jinye, Wang, Chunyan, Sun, Yaoqi, Guo, Jing, Liu, Shupeng, and Cheng, Zhongping
- Subjects
OVARIAN cancer ,INDUCED ovulation ,IMMUNE checkpoint inhibitors ,DISEASE risk factors ,CELL communication ,PROGNOSIS ,PROPORTIONAL hazards models ,PROGRESSION-free survival - Abstract
Background: Ovarian cancer (OC) is one of the most malignant tumors in the female reproductive system, with a poor prognosis. Various responses to treatments including chemotherapy and immunotherapy are observed among patients due to their individual characteristics. Applicable prognostic markers could make it easier to refine risk stratification for OC patients. Autophagy is closely implicated in the occurrence and development of tumors, including OC. Whether autophagy -related genes can be used as prognostic markers for OC patients remains unclear. Methods: The gene transcriptome data of 374 OC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The correlation between the autophagy levels and outcomes of OC patients was identified through the single sample gene set enrichment analysis (ssGSEA). Recognized molecular markers of autophagy in different clinical specimens were detected by immunohistochemistry (IHC) assay. The gene set enrichment analysis (GSEA), ESTIMATE, and CIBERSORT analysis were applied to explore the correlation of autophagy with the tumor immune microenvironment (TIME). Single-cell RNA-sequencing (scRNA-seq) data from seven OC patients were included for characterizing cell-cell interaction patterns of autophagy-high or low tumor cells. Machine learning, Stepwise Cox regression and LASSO-Cox analysis were used to screen autophagy hub genes, which were used to establish an autophagy-related signature for prognosis evaluation. Four tumor immunotherapy cohorts were obtained from the GEO (Gene Expression Omnibus) database and the literature for autophagy risk score validation. Results: The autophagy levels were closely related to the prognosis of the OC patients. Additionally, the autophagy levels were correlated with TIME status including immune score, and immune-cell infiltration. The scRNA-seq analysis found that tumor cells with high or low autophagy levels had different interactions with immune cells, especially macrophages. Eight autophagy-hub genes (ZFYVE1, AMBRA1, LAMP2, TRAF6, PDPK1, ATG2B, DAPK1 and TP53INP2) were screened for an autophagy-related signature. According to this signature, higher risk score was correlated with poor prognosis and better immunotherapy response in the OC patients. Conclusions: The autophagy-related signature is applicable to predict the prognosis and immune checkpoint inhibitors (ICIs) therapy efficiency in OC patients. It is possible to identify OC patients who will respond to ICIs therapy and have a favorable prognosis, although more verification is needed. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
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