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Yinglong Huang on Muck Rack

Yinglong Huang

As seen in: Frontiers in Immunology, Taylor & Francis Online, Dove Medical Press, Aging
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Articles

Commentary: Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through PSMA1- NF-κB-HIF-1α signaling axis

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By Yiling Qin, Zijun Wang, Wujie Chen, Qingyu Wan, Mingxia Ding, Yidao Liu, Jiyao Yang, Yinglong Huang, Haihao Li, Shunxin Lu
| Frontiers in Immunology
A Commentary on Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through PSMA1- NF-κB-HIF-1α signaling axis By Dai Q, Wang H, Li F, Huang R, Jiang C, Yuan L, Wang Y and Li X (2025) Front. Immunol. 16:1467357. doi: 10.3389/fimmu.2025.1467357 1 Introduction What role do neutrophils play in the tumor microenvironment? A recent study by Dai and colleagues offers a compelling answer ().
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Commentary: Characteristics of tertiary lymphoid structures in prostate cancer and the impact of neoadjuvant therapy on their formation and maturation

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By Qingyu Wan, Wujie Chen, Jiyao Yang, Yiling Qin, Haihao Li, Ji Li, Yinglong Huang, Yidao Liu, Mingxia Ding
| Frontiers in Immunology
A Commentary on Characteristics of tertiary lymphoid structures in prostate cancer and the impact of neoadjuvant therapy on their formation and maturation By Liu S, Yu Y, Zhou J, Yang L, Yan X, Liu X, Ma K, Liu L, Wang X, Zhao C and Dong Q (2025) Front. Immunol. 16:1663396.
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Construction of a gene-metabolite-microbiome regulatory network reveals novel therapeutic targets in bladder cancer through multi-omics analysis

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By Zhiyong Tan, Yinglong Huang, Haihao Li, Chen Gong
| Taylor & Francis Online
Abstract Background Bladder cancer (BLCA) is a prevalent malignancy with substantial consequences for patient health. This study aimed to elucidate the underlying mechanisms of BLCA through integrated multi-omics analysis. Methods Tumor and adjacent tissues from BLCA patients underwent transcriptomic, whole-exome sequencing, metabolomic, and intratumoral microbiome analyses. These data were integrated with public datasets to identify key genes, metabolites, and microorganisms.
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