Xiaoling Shang

669 total citations
46 papers, 440 citations indexed

About

Xiaoling Shang is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Xiaoling Shang has authored 46 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 23 papers in Pulmonary and Respiratory Medicine and 10 papers in Molecular Biology. Recurrent topics in Xiaoling Shang's work include Lung Cancer Treatments and Mutations (17 papers), Lung Cancer Research Studies (13 papers) and Cancer Immunotherapy and Biomarkers (11 papers). Xiaoling Shang is often cited by papers focused on Lung Cancer Treatments and Mutations (17 papers), Lung Cancer Research Studies (13 papers) and Cancer Immunotherapy and Biomarkers (11 papers). Xiaoling Shang collaborates with scholars based in China, United States and Netherlands. Xiaoling Shang's co-authors include Haiyong Wang, Jiamao Lin, Xianrang Song, Li Xie, Xingguo Song, Yanguo Liu, Xiuwen Wang, Xiaohan Dong, Zhehai Wang and Zhenxiang Li and has published in prestigious journals such as Frontiers in Immunology, Frontiers in Plant Science and Advanced Science.

In The Last Decade

Xiaoling Shang

43 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaoling Shang China 13 181 171 149 117 63 46 440
Kaibo Guo China 13 175 1.0× 141 0.8× 121 0.8× 82 0.7× 26 0.4× 44 431
Ruilian Xu China 13 113 0.6× 218 1.3× 48 0.3× 111 0.9× 24 0.4× 40 388
Viola Regondi Italy 8 226 1.2× 262 1.5× 64 0.4× 157 1.3× 91 1.4× 17 466
Motonao Nakao Japan 11 63 0.3× 143 0.8× 47 0.3× 82 0.7× 10 0.2× 27 397
Judith YMN Engwegen Netherlands 9 93 0.5× 314 1.8× 54 0.4× 86 0.7× 23 0.4× 17 510
Takeshi Ota Japan 6 191 1.1× 136 0.8× 145 1.0× 74 0.6× 17 0.3× 9 390
Martin Letzkus Switzerland 11 64 0.4× 223 1.3× 19 0.1× 105 0.9× 187 3.0× 15 549
Patel Dd India 12 165 0.9× 165 1.0× 34 0.2× 107 0.9× 16 0.3× 28 416
Miral S. Grandhi United States 8 144 0.8× 198 1.2× 91 0.6× 173 1.5× 35 0.6× 39 544
Eszter Csánky Hungary 11 44 0.2× 268 1.6× 82 0.6× 106 0.9× 86 1.4× 29 459

Countries citing papers authored by Xiaoling Shang

Since Specialization
Citations

This map shows the geographic impact of Xiaoling Shang'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 Xiaoling Shang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoling Shang more than expected).

Fields of papers citing papers by Xiaoling Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaoling Shang. 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 Xiaoling Shang. The network helps show where Xiaoling Shang may publish in the future.

Co-authorship network of co-authors of Xiaoling Shang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoling Shang. A scholar is included among the top collaborators of Xiaoling Shang 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 Xiaoling Shang. Xiaoling Shang 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.
Shang, Xiaoling, Bo Cheng, Chenyue Zhang, et al.. (2025). The LDH‐H3K18La‐Nur77 Axis Potentiates Immune Escape in Small Cell Lung Cancer. Advanced Science. 12(34). e13608–e13608. 1 indexed citations
2.
Shang, Xiaoling, Yiqiu Zhang, Miao Liu, et al.. (2025). Tear IgE point-of-care testing for differentiating type I and type IV allergic conjunctivitis. Frontiers in Medicine. 12. 1577656–1577656. 1 indexed citations
3.
4.
Shang, Xiaoling, Chenyue Zhang, Yuanyuan Lv, et al.. (2024). Patients with Extensive-Stage Small Cell Lung Cancer Harboring Less Than 4 Metastatic Sites May Benefit from Immune Checkpoint Inhibitor Rechallenge by Reshaping Tumor Microenvironment. ImmunoTargets and Therapy. Volume 13. 571–583. 1 indexed citations
5.
Zhang, Yue, Xiaoling Shang, Miao Yu, et al.. (2023). A three-snoRNA signature: SNORD15A, SNORD35B and SNORD60 as novel biomarker for renal cell carcinoma. Cancer Cell International. 23(1). 136–136. 11 indexed citations
6.
Shang, Xiaoling, Wengang Zhang, Wenfei Han, et al.. (2023). Efficacy of immune checkpoint inhibitors in non-small cell lung cancer with NTRK family mutations. BMC Pulmonary Medicine. 23(1). 482–482. 1 indexed citations
7.
Chang, Ming‐Hui, Shanshan Ding, Xiaohan Dong, et al.. (2022). Liensinine Inhibits Cell Growth and Blocks Autophagic Flux in Nonsmall-Cell Lung Cancer. Journal of Oncology. 2022. 1–17. 11 indexed citations
8.
Yang, Chuncheng, et al.. (2022). The causal relationship between white blood cell counts and hepatocellular carcinoma: a Mendelian randomization study. European journal of medical research. 27(1). 278–278. 12 indexed citations
9.
Zhang, Wengang, Xiaoling Shang, Fei Yang, et al.. (2022). CDC25C as a Predictive Biomarker for Immune Checkpoint Inhibitors in Patients With Lung Adenocarcinoma. Frontiers in Oncology. 12. 867788–867788. 10 indexed citations
10.
Shang, Xiaoling, Wengang Zhang, Xun Zhang, et al.. (2022). PTPRD/PTPRT mutation as a predictive biomarker of immune checkpoint inhibitors across multiple cancer types. Frontiers in Immunology. 13. 991091–991091. 8 indexed citations
11.
Zhang, Wengang, Xiaoling Shang, Ni Liu, et al.. (2022). ANK2 as a novel predictive biomarker for immune checkpoint inhibitors and its correlation with antitumor immunity in lung adenocarcinoma. BMC Pulmonary Medicine. 22(1). 483–483. 8 indexed citations
12.
Dong, Xiaohan, Xingguo Song, Shanshan Ding, et al.. (2021). Tumor‐educated platelet SNORD55 as a potential biomarker for the early diagnosis of non‐small cell lung cancer. Thoracic Cancer. 12(5). 659–666. 33 indexed citations
13.
Shang, Xiaoling, et al.. (2021). Survival analysis for non-squamous NSCLC patients harbored STK11 or KEAP1 mutation receiving atezolizumab. Lung Cancer. 154. 105–112. 19 indexed citations
14.
Yu, Miao, Xingguo Song, Yajing Zhao, et al.. (2021). Circulating Serum Exosomal Long Non-Coding RNAs FOXD2-AS1, NRIR, and XLOC_009459 as Diagnostic Biomarkers for Colorectal Cancer. Frontiers in Oncology. 11. 618967–618967. 30 indexed citations
15.
Hu, Fang‐Wen, et al.. (2020). Joint Detection of Serum IgM/IgG Antibody Is an Important Key to Clinical Diagnosis of SARS-CoV-2 Infection. Canadian Journal of Infectious Diseases and Medical Microbiology. 2020. 1–5. 9 indexed citations
16.
Shang, Xiaoling, Jia Li, Hui Wang, et al.. (2020). CMTM6 is positively correlated with PD-L1 expression and immune cells infiltration in lung squamous carcinoma. International Immunopharmacology. 88. 106864–106864. 16 indexed citations
17.
18.
Shang, Xiaoling, et al.. (2018). PLNR≤20% may be a benefit from PORT for patients with IIIA-N2 NSCLC: a large population-based study. Cancer Management and Research. Volume 10. 3561–3567. 6 indexed citations
19.
Liu, Yong, Haofeng Ji, Yumin Zhang, et al.. (2015). Negative CD4 + TIM-3 Signaling Confers Resistance Against Cold Preservation Damage in Mouse Liver Transplantation. American Journal of Transplantation. 15(4). 954–964. 20 indexed citations
20.
Xue, Gang, Junchao Liu, Jing Zhang, et al.. (2013). [Detection of galectin-3 in both serum and tissue for early diagnosis of thyroid carcinoma].. PubMed. 33(7). 1027–30. 6 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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