Peishan Hu

1.3k total citations · 1 hit paper
30 papers, 832 citations indexed

About

Peishan Hu is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Peishan Hu has authored 30 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 16 papers in Cancer Research and 7 papers in Oncology. Recurrent topics in Peishan Hu's work include RNA modifications and cancer (9 papers), Cancer, Hypoxia, and Metabolism (6 papers) and Cancer, Lipids, and Metabolism (4 papers). Peishan Hu is often cited by papers focused on RNA modifications and cancer (9 papers), Cancer, Hypoxia, and Metabolism (6 papers) and Cancer, Lipids, and Metabolism (4 papers). Peishan Hu collaborates with scholars based in China, United States and Hong Kong. Peishan Hu's co-authors include Zexian Liu, Huai‐Qiang Ju, Qi‐Nian Wu, Rui‐Hua Xu, Heng‐Ying Pu, Jin‐Fei Lin, Xiaozhong Peng, Tao Jiang, Miao‐Zhen Qiu and Boqin Qiang and has published in prestigious journals such as Journal of Clinical Investigation, Cancer Research and Oncogene.

In The Last Decade

Peishan Hu

28 papers receiving 827 citations

Hit Papers

Phosphorylated NFS1 weakens oxaliplatin-based chemosensit... 2022 2026 2023 2024 2022 50 100 150 200

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peishan Hu China 16 564 310 172 133 98 30 832
Qianqian Lei China 16 514 0.9× 333 1.1× 213 1.2× 82 0.6× 145 1.5× 39 831
Zhenhua Lin China 17 451 0.8× 189 0.6× 217 1.3× 108 0.8× 105 1.1× 55 814
Yanyan Shen China 21 824 1.5× 293 0.9× 219 1.3× 138 1.0× 120 1.2× 63 1.2k
Xi Yu China 15 410 0.7× 227 0.7× 162 0.9× 101 0.8× 71 0.7× 43 747
Huilin Zheng China 13 719 1.3× 592 1.9× 185 1.1× 80 0.6× 142 1.4× 43 1.1k
Chengyong Dong China 17 387 0.7× 251 0.8× 201 1.2× 100 0.8× 103 1.1× 29 721
Haijun Zhang China 15 544 1.0× 229 0.7× 211 1.2× 154 1.2× 70 0.7× 24 870
Xifa Zhou China 16 583 1.0× 354 1.1× 190 1.1× 104 0.8× 81 0.8× 34 817
Min Kyung Ju South Korea 12 691 1.2× 469 1.5× 365 2.1× 136 1.0× 100 1.0× 16 1.1k
Chiara Ciardiello Italy 11 616 1.1× 300 1.0× 137 0.8× 97 0.7× 88 0.9× 14 773

Countries citing papers authored by Peishan Hu

Since Specialization
Citations

This map shows the geographic impact of Peishan Hu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peishan Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peishan Hu more than expected).

Fields of papers citing papers by Peishan Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peishan Hu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peishan Hu. The network helps show where Peishan Hu may publish in the future.

Co-authorship network of co-authors of Peishan Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Peishan Hu. A scholar is included among the top collaborators of Peishan Hu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peishan Hu. Peishan Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cai, Zerong, Yongqiang Zheng, Yan Hu, et al.. (2025). Construction of exosome non-coding RNA feature for non-invasive, early detection of gastric cancer patients by machine learning: a multi-cohort study. Gut. 74(6). 884–893. 12 indexed citations
2.
Li, Ting, et al.. (2025). Fatty acid in the tumor microenvironment: Perspectives for immunotherapy. Critical Reviews in Oncology/Hematology. 215. 104878–104878.
3.
Hu, Peishan, et al.. (2024). Point-of-Use SERS Approach for Efficient Determination and Removal of Phthalic Acid Esters Based on a Metal–Organic Framework-Coated Melamine Sponge. ACS Applied Materials & Interfaces. 16(9). 11528–11536. 15 indexed citations
4.
Zhang, Wei, et al.. (2024). Portable SERS-Based POCT Kit for Ultrafast and Sensitive Determining Paraquat in Human Gastric Juice and Urine. ACS Omega. 9(16). 18576–18583. 3 indexed citations
5.
Hu, Chuling, Zhaoliang Yu, Xinxin Huang, et al.. (2024). KRAS inhibitors may prevent colorectal cancer metachronous metastasis by suppressing TGF‑β mediated epithelial‑mesenchymal transition. Molecular Medicine Reports. 31(1). 2 indexed citations
6.
Hu, Yan, Peishan Hu, & Xiaozhong Peng. (2024). Paracrine function amplifies pro-tumor electrochemical signal within neuron-glioma synapses. Science China Life Sciences. 67(6). 1318–1320. 2 indexed citations
7.
Li, Wanru, Nianlu Li, Shunyu Li, et al.. (2023). Rapid identification and quantification of diquat in biological fluids within 30 s using a portable Raman spectrometer. Biosensors and Bioelectronics. 225. 115083–115083. 24 indexed citations
8.
Hu, Peishan, et al.. (2023). TIM-3 blockade: immune and targeted therapy in DIPG. Trends in Molecular Medicine. 30(2). 110–112. 1 indexed citations
9.
Liu, Furong, Xiaoli Wei, Zhanhong Chen, et al.. (2023). PFKFB2 is a favorable prognostic biomarker for colorectal cancer by suppressing metastasis and tumor glycolysis. Journal of Cancer Research and Clinical Oncology. 149(12). 10737–10752. 7 indexed citations
10.
You, Weiqiang, Yufeng Chen, Zerong Cai, et al.. (2022). SQLE, A Key Enzyme in Cholesterol Metabolism, Correlates With Tumor Immune Infiltration and Immunotherapy Outcome of Pancreatic Adenocarcinoma. Frontiers in Immunology. 13. 864244–864244. 36 indexed citations
11.
Wu, Qi‐Nian, Xiao-Jing Luo, Jia Liu, et al.. (2021). MYC-Activated LncRNA MNX1-AS1 Promotes the Progression of Colorectal Cancer by Stabilizing YB1. Cancer Research. 81(10). 2636–2650. 59 indexed citations
12.
Hu, Peishan, Ting Li, Jin‐Fei Lin, et al.. (2020). VDR–SOX2 signaling promotes colorectal cancer stemness and malignancy in an acidic microenvironment. Signal Transduction and Targeted Therapy. 5(1). 183–183. 46 indexed citations
14.
Li, Dengke, Yan Hu, Shanshan Li, et al.. (2019). Glioma-associated human endothelial cell-derived extracellular vesicles specifically promote the tumourigenicity of glioma stem cells via CD9. Oncogene. 38(43). 6898–6912. 33 indexed citations
15.
Hu, Peishan, Shanshan Li, Fan Wu, et al.. (2019). Acidosis enhances the self-renewal and mitochondrial respiration of stem cell-like glioma cells through CYP24A1-mediated reduction of vitamin D. Cell Death and Disease. 10(1). 25–25. 50 indexed citations
17.
Li, Ting, Peishan Hu, Zhixiang Zuo, et al.. (2019). Additional file 10: of METTL3 facilitates tumor progression via an m6A-IGF2BP2-dependent mechanism in colorectal carcinoma. Figshare. 1 indexed citations
18.
Hu, Yan, Dengke Li, Fan Wu, et al.. (2019). The antibiotic clofoctol suppresses glioma stem cell proliferation by activating KLF13. Journal of Clinical Investigation. 129(8). 3072–3085. 39 indexed citations
19.
Li, Ting, Peishan Hu, Zhixiang Zuo, & Huai‐Qiang Ju. (2018). IDDF2018-ABS-0233 N6-adenosine methyltransferase METTL3 promotes tumour metastasis via SOX2 MRNA M6A modification in colorectal carcinoma. A17.1–A17. 1 indexed citations
20.
Han, Wei, Peishan Hu, Fan Wu, et al.. (2018). FHL3 links cell growth and self-renewal by modulating SOX4 in glioma. Cell Death and Differentiation. 26(5). 796–811. 27 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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