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Zongcheng Yang

Researcher at Shandong University

Publications -  11
Citations -  253

Zongcheng Yang is an academic researcher from Shandong University. The author has contributed to research in topics: Immunotherapy & Cancer. The author has an hindex of 3, co-authored 11 publications receiving 31 citations.

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The Pyroptosis-Related Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Gastric Cancer

TL;DR: In this paper, consensus clustering by pyroptosis-related regulators was used to classify 618 patients with Gastric Cancer (GC) from four GEO cohorts, and a prognosis model (PS-score) was built by LASSO-Cox analysis.
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YKT6 , as a potential predictor of prognosis and immunotherapy response for oral squamous cell carcinoma, is related to cell invasion, metastasis, and CD8+ T cell infiltration.

TL;DR: In this paper, the authors explored promising prognostic and immune therapeutic candidate biomarkers for OSCC and to understand the expression pattern, prognostic value, immune effects, and biological functions of YKT6.
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Identification of AUNIP as a candidate diagnostic and prognostic biomarker for oral squamous cell carcinoma.

TL;DR: Bioinformatics analysis and in vitro experiments demonstrated that AUNIP could be associated with tumor microenvironment, human papillomavirus infection, and cell cycle in OSCC and suppression of A UNIP may be a potential approach to preventing and treating OSCC.
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AUNIP Expression Is Correlated With Immune Infiltration and Is a Candidate Diagnostic and Prognostic Biomarker for Hepatocellular Carcinoma and Lung Adenocarcinoma.

TL;DR: High AUNIP expression was associated with DNA replication, cell cycle, oocyte meiosis, homologous recombination, mismatch repair, the p53 signal transduction pathway, and progesterone-mediated oocyte maturation and is a candidate diagnostic and prognostic biomarker for HCC and LUAD.
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Multi-omics Analysis of Ferroptosis Regulation Patterns and Characterization of Tumor Microenvironment in Patients with Oral Squamous Cell Carcinoma

TL;DR: In this paper, a principal component analysis (PCA) algorithm was used to evaluate the ferroptosis regulation patterns of individual tumor and three distinct regulation subtypes, which linked to outcomes and clinical relevance of each patient, were established.