Assessing Spatial Distribution of Multicellular Self-Assembly Enables the Prediction of Phenotypic Heterogeneity in Glioblastoma

Junghwa Cha, Woogwang Sim, Insung Yong, Junseong Park, Jin Kyoung Shim, Jong Hee Chang, Seok Gu Kang, Pilnam Kim

Research output: Contribution to journalArticlepeer-review


Phenotypic heterogeneity of glioblastomas is a leading determinant of therapeutic resistance and treatment failure. However, functional assessment of the heterogeneity of glioblastomas is lacking. We developed a self-assembly-based assessment system that predicts inter/intracellular heterogeneity and phenotype associations, such as cell proliferation, invasiveness, drug responses, and gene expression profiles. Under physical constraints for cellular interactions, mixed populations of glioblastoma cells are sorted to form a segregated architecture, depending on their preference for binding to cells of the same phenotype. Cells distributed at the periphery exhibit a reduced temozolomide (TMZ) response and are associated with poor patient survival, whereas cells in the core of the aggregates exhibit a significant response to TMZ. Our results suggest that the multicellular self-assembly pattern is indicative of the intertumoral and intra-patient heterogeneity of glioblastomas, and is predictive of the therapeutic response.

Original languageEnglish
Article number5910
Issue number23
Publication statusPublished - 2022 Dec

Bibliographical note

Funding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-NRF2019R1A2C2084142) and by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324).

Publisher Copyright:
© 2022 by the authors.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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