KHKai-Wen Hsu

Kai-Wen Hsu

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Kai-Wen Hsu has a total of 15 co-authors. Here are the top co-authors by number of shared publications:

  • Chia-Hwa Lee

    School of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan

    1 shared publication
  • Chun-Yu Lin

    Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

    1 shared publication
  • Fang-Hsin Chen

    Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 33302, Taiwan, ROC

    1 shared publication
  • Heng-Hsiung Wu

    The Ph.D. Program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung, 40403, Taiwan, ROC

    1 shared publication
  • Li-Chi Huang

    Department of Endocrinology and metabolism, Cathay General Hospital, Taipei 10630, Taiwan

    1 shared publication
  • Li-Jie Lin

    The Ph.D. Program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung, 40403, Taiwan, ROC

    1 shared publication

Latest Publications

  • Open Access

    Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach

    by Yumei Qi, Yo-Liang Lai, Pei-Chun Shen, Fang-Hsin Chen, Li-Jie Lin, Heng-Hsiung Wu, Pei-Hua Peng, Kai-Wen Hsu, Wei-Chung Cheng

    Cervical cancer is the fourth most common cancer in women worldwide. Increasing evidence has shown that miRNAs are related to the progression of cervical cancer. However, the mechanisms that affect the prognosis of cancer are still largely unknown. In the present study, we sought to identify miRNAs associated with poor prognosis of patient with cervical cancer, as well as the possible mechanisms regulated by them. The miRNA expression profiles and relevant clinical information of patients with cervical cancer were obtained from The Cancer Genome Atlas (TCGA). The selection of prognostic miRNAs was carried out through an integrated bioinformatics approach. The most effective miRNAs with synergistic and additive effects were selected for validation through in vitro experiments. Three miRNAs (miR-216b-5p, miR-585-5p, and miR-7641) were identified as exhibiting good performance in predicting poor prognosis through additive effects analysis. The functional enrichment analysis suggested that not only pathways traditionally involved in cancer but also immune system pathways might be important in regulating the outcome of the disease. Our findings demonstrated that a synergistic combination of three miRNAs may be associated, through their regulation of specific pathways, with very poor survival rates for patients with cervical cancer.


  • Open Access

    A rapid and quantitative method to detect human circulating tumor cells in a preclinical animal model

    by Shih-Hsin Tu, Yi-Chen Hsieh, Li-Chi Huang, Chun-Yu Lin, Kai-Wen Hsu, Wen-Shyang Hsieh, Wei-Ming Chi, Chia-Hwa Lee

    As cancer metastasis is the deadliest aspect of cancer, causing 90% of human deaths, evaluating the molecular mechanisms underlying this process is the major interest to those in the drug development field. Both therapeutic target identification and proof-of-concept experimentation in anti-cancer drug development require appropriate animal models, such as xenograft tumor transplantation in transgenic and knockout mice. In the progression of cancer metastasis, circulating tumor cells (CTCs) are the most critical factor in determining the prognosis of cancer patients. Several studies have demonstrated that measuring CTC-specific markers in a clinical setting (e.g., flow cytometry) can provide a current status of cancer development in patients. However, this useful technique has rarely been applied in the real-time monitoring of CTCs in preclinical animal models. In this study, we designed a rapid and reliable detection method by combining a bioluminescent in vivo imaging system (IVIS) and quantitative polymerase chain reaction (QPCR)-based analysis to measure CTCs in animal blood. Using the IVIS Spectrum CT System with 3D–imaging on orthotropic-developed breast-tumor-bearing mice. In this manuscript, we established a quick and reliable method for measuring CTCs in a preclinical animal mode. The key to this technique is the use of specific human and mouse GUS primers on DNA/RNA of mouse peripheral blood under an absolute qPCR system. First, the high sensitivity of cancer cell detection on IVIS was presented by measuring the luciferase carried MDA-MB-231 cells from 5 to 5x1011 cell numbers with great correlation (R2 = 0.999). Next, the MDA-MB-231 cell numbers injected by tail vein and their IVIS radiance signals were strongly corrected with qPCR-calculated copy numbers (R2 > 0.99). Furthermore, by applying an orthotropic implantation animal model, we successfully distinguished xenograft tumor-bearing mice and control mice with a significant difference (p < 0.001), whereas IVIS Spectrum-CT 3D–visualization showed that blood of mice with lung metastasis contained more than twice the CTC numbers than ordinary tumor-bearing mice. We demonstrated a positive correlation between lung metastasis status and CTC numbers in peripheral mouse blood. Collectively, the techniques developed for this study resulted in the integration of CTC assessments into preclinical models both in vivo and ex vivo, which will facilitate translational targeted therapy in clinical practice.