According to a study published in January of 2016, in the United States alone, more than 23,770 people are projected to be diagnosed with brain cancer and 16,050 are projected to die from it.1 Gliomas are highly malignant brain tumors. Afflicted individuals, disregarding the grade of the glioma,  have limited treatment options–diminishing the projected median survival time for all types of gliomas to 18 months, and the 5-year survival rate to less than 5%. Due to invasive growth patterns, gliomas are very difficult to fully resect or remove surgically, and have high recurrence and mortality rates.2,3 Prior studies indicate that up to 80% of gliomas have a mutation in the gene isocitrate dehydrogenase I (IDH1), with more than 83% of the mutations occurring at the 132nd amino acid residue, between arginine and histidine (R132H).4-6 Attempts in the past to detect this biomarker were labor intensive and time consuming.

        Researchers of Nagoya University have developed a highly sensitive antibody-based device called Immuno-Wall Micro Device .7 The tumor cell lines for the study were obtained from patients with variable grades of gliomas. This antibody, HMab-2, has high affinity for the IDH1-R132H location site. It can detect the mutation within 15 minutes versus 60 minutes or more required by other methods. This technology would markedly expedite brain cancer treatment and accurate surgical resection by enabling rapid detection while demarcating it from normal tissue or other brain tumors. Hence, the preoperative and intraoperative clinical applications of this device are likely to improve the mortality rates from gliomas and decrease recurrences due to more precise surgical resection.


  1. Siegel, R., Miller, K., & Jemal, A. (2016). Cancer statistics, 2016. CA: A Cancer Journal For Clinicians, 66(1), 7-30.
  2. Eyüpoglu, I., Hore, N., Savaskan, N., Grummich, P., Roessler, K., Buchfelder, M., & Ganslandt, O. (2012). Improving the Extent of Malignant Glioma Resection by Dual Intraoperative Visualization Approach. Plos ONE, 7(9), e44885.
  3. Gorovets, D., Kannan, K., Shen, R., Kastenhuber, E., Islamdoust, N., & Campos, C. et al. (2012). IDH Mutation and Neuroglial Developmental Features Define Clinically Distinct Subclasses of Lower Grade Diffuse Astrocytic Glioma. Clinical Cancer Research, 18(9), 2490-2501.
  4. Dolecek, T., Propp, J., Stroup, N., & Kruchko, C. (2012). CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2005-2009. Neuro-Oncology, 14(suppl 5), v1-v49.
  5. Hartmann, C., Meyer, J., Balss, J., Capper, D., Mueller, W., & Christians, A. et al. (2009). Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathologica, 118(4), 469-474.
  6. Suzuki, H., Aoki, K., Chiba, K., Sato, Y., Shiozawa, Y., & Shiraishi, Y. et al. (2015). Mutational landscape and clonal architecture in grade II and III gliomas. Nature Genetics, 47(5), 458-468.
  7. Yamamichi, Akane; Kasama, Toshihiro; Ohka, Fumiharu; Suzuki, Hiromichi; Kato, Akira; Motomura, Kazuya et al. (2016). An immuno-wall microdevice exhibits rapid and sensitive detection of IDH1-R132H mutation specific to grade II and III gliomas. Science and Technology of Advanced Materials. 17: 618-625.

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