Hsin-Ling Hsu

922 total citations · 1 hit paper
15 papers, 679 citations indexed

About

Hsin-Ling Hsu is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Hsin-Ling Hsu has authored 15 papers receiving a total of 679 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Oncology and 5 papers in Immunology. Recurrent topics in Hsin-Ling Hsu's work include Immune cells in cancer (4 papers), Epigenetics and DNA Methylation (3 papers) and Microtubule and mitosis dynamics (3 papers). Hsin-Ling Hsu is often cited by papers focused on Immune cells in cancer (4 papers), Epigenetics and DNA Methylation (3 papers) and Microtubule and mitosis dynamics (3 papers). Hsin-Ling Hsu collaborates with scholars based in Taiwan and United States. Hsin-Ling Hsu's co-authors include Hong‐Yu Tseng, Aushia Tanzih Al Haq, Yen‐An Chen, Li‐Mei Chen, Pei-Chun Shen, Yueh‐Shan Weng, Yi‐Chung Tung, Ning-Hsing Yeh, Pai‐An Hwang and Linyi Chen and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Cell Science.

In The Last Decade

Hsin-Ling Hsu

15 papers receiving 673 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

MCT-1/miR-34a/IL-6/IL-6R signaling axis promotes EMT progression, cancer stemness and M2 macrophage polarization in triple-negative breast cancer

2019 333 citations Yueh‐Shan Weng, Hong‐Yu Tseng et al. Molecular Cancer profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hsin-Ling Hsu Taiwan	13	405	204	192	192	59	15	679
Hong‐Yu Tseng Taiwan	7	295 0.7×	181 0.9×	163 0.8×	177 0.9×	65 1.1×	7	510
Xinping Huang China	17	532 1.3×	154 0.8×	96 0.5×	218 1.1×	53 0.9×	28	796
Ta Xiao China	18	583 1.4×	175 0.9×	137 0.7×	285 1.5×	73 1.2×	28	838
Xiao‐Shun He China	13	392 1.0×	128 0.6×	143 0.7×	244 1.3×	160 2.7×	29	681
Stanley Borowicz United States	7	506 1.2×	207 1.0×	72 0.4×	182 0.9×	63 1.1×	14	768
Joshua Brown-Clay United States	6	298 0.7×	97 0.5×	106 0.6×	140 0.7×	44 0.7×	7	550
Shudi Luo China	12	456 1.1×	124 0.6×	141 0.7×	297 1.5×	56 0.9×	19	750
Mylène Tajan France	8	624 1.5×	161 0.8×	266 1.4×	221 1.2×	37 0.6×	12	816
Manoj Kumar Karuppusamy Rathinam United States	6	453 1.1×	157 0.8×	44 0.2×	144 0.8×	65 1.1×	7	657
John Byon United States	12	442 1.1×	152 0.7×	177 0.9×	87 0.5×	9 0.2×	17	600

Countries citing papers authored by Hsin-Ling Hsu

Since Specialization

Citations

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

Fields of papers citing papers by Hsin-Ling Hsu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin-Ling Hsu. 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 Hsin-Ling Hsu. The network helps show where Hsin-Ling Hsu may publish in the future.

Co-authorship network of co-authors of Hsin-Ling Hsu

This figure shows the co-authorship network connecting the top 25 collaborators of Hsin-Ling Hsu. A scholar is included among the top collaborators of Hsin-Ling Hsu 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 Hsin-Ling Hsu. Hsin-Ling Hsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Lin, Ya‐Hui, Kee‐Ming Man, Hsin-Ling Hsu, et al.. (2025). Real-time and regional analysis of the efficacy of anticancer drugs in a patient-derived intratumoral heterogeneous tumor microenvironment. Lab on a Chip. 25(7). 1728–1743. 1 indexed citations

Haq, Aushia Tanzih Al, Christopher Jin, Jou‐Ho Shih, et al.. (2024). Immunotherapeutic IL-6R and targeting the MCT-1/IL-6/CXCL7/PD-L1 circuit prevent relapse and metastasis of triple-negative breast cancer. Theranostics. 14(5). 2167–2189. 16 indexed citations

Haq, Aushia Tanzih Al, Hong‐Yu Tseng, Li‐Mei Chen, Chien‐Chia Wang, & Hsin-Ling Hsu. (2022). Targeting prooxidant MnSOD effect inhibits triple-negative breast cancer (TNBC) progression and M2 macrophage functions under the oncogenic stress. Cell Death and Disease. 13(1). 49–49. 33 indexed citations

Chen, Limei, et al.. (2022). Oligo-Fucoidan supplementation enhances the effect of Olaparib on preventing metastasis and recurrence of triple-negative breast cancer in mice. Journal of Biomedical Science. 29(1). 70–70. 32 indexed citations

Chen, Li‐Mei, Hong‐Yu Tseng, Yen‐An Chen, et al.. (2020). Oligo-Fucoidan Prevents M2 Macrophage Differentiation and HCT116 Tumor Progression. Cancers. 12(2). 421–421. 28 indexed citations

Weng, Yueh‐Shan, Hong‐Yu Tseng, Yen‐An Chen, et al.. (2019). MCT-1/miR-34a/IL-6/IL-6R signaling axis promotes EMT progression, cancer stemness and M2 macrophage polarization in triple-negative breast cancer. Molecular Cancer. 18(1). 42–42. 333 indexed citations breakdown →

Chen, Limei, Po‐Yen Liu, Yen‐An Chen, et al.. (2017). Oligo-Fucoidan prevents IL-6 and CCL2 production and cooperates with p53 to suppress ATM signaling and tumor progression. Scientific Reports. 7(1). 11864–11864. 42 indexed citations

Chang, Yu‐Jung, et al.. (2012). Interplay between Cell Migration and Neurite Outgrowth Determines SH2B1β-Enhanced Neurite Regeneration of Differentiated PC12 Cells. PLoS ONE. 7(4). e34999–e34999. 21 indexed citations

Chen, Hsiao‐Huei, Yen‐An Chen, Gunn‐Guang Liou, et al.. (2012). Targeting MCT-1 oncogene inhibits Shc pathway and xenograft tumorigenicity. Oncotarget. 3(11). 1401–1415. 23 indexed citations

10.

Kasiappan, Ravi, et al.. (2010). The antagonism between MCT-1 and p53 affects the tumorigenic outcomes. Molecular Cancer. 9(1). 311–311. 13 indexed citations

11.

Hsu, Hsin-Ling, et al.. (2010). The adaptor protein SH2B1β reduces hydrogen peroxide-induced cell death in PC12 cells and hippocampal neurons. PubMed. 5. 17–17. 16 indexed citations

12.

Kasiappan, Ravi, Wei‐Ti Chen, Huiping Liu, et al.. (2009). Loss of p53 and MCT-1 Overexpression Synergistically Promote Chromosome Instability and Tumorigenicity. Molecular Cancer Research. 7(4). 536–548. 24 indexed citations

13.

Hsu, Hsin-Ling, Ravi Kasiappan, Jeffrey R. Sawyer, et al.. (2007). MCT-1 oncogene downregulates p53 and destabilizes genome structure in the response to DNA double-strand damage. DNA repair. 6(9). 1319–1332. 25 indexed citations

14.

Hsu, Hsin-Ling, et al.. (2007). Apoptotic cleavage of NuMA at the C-terminal end is related to nuclear disruption and death amplification. Journal of Biomedical Science. 14(5). 681–694. 12 indexed citations

15.

Hsu, Hsin-Ling & Ning-Hsing Yeh. (1996). Dynamic changes of NuMA during the cell cycle and possible appearance of a truncated form of NuMA during apoptosis. Journal of Cell Science. 109(2). 277–288. 60 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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