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A systems approach to brain tumor treatment

Publication ,  Journal Article
Park, JH; de Lomana, ALG; Marzese, DM; Juarez, T; Feroze, A; Hothi, P; Cobbs, C; Patel, AP; Kesari, S; Huang, S; Baliga, NS
Published in: Cancers
July 1, 2021

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood–brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.

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Published In

Cancers

DOI

EISSN

2072-6694

Publication Date

July 1, 2021

Volume

13

Issue

13

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
 

Citation

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Park, J. H., de Lomana, A. L. G., Marzese, D. M., Juarez, T., Feroze, A., Hothi, P., … Baliga, N. S. (2021). A systems approach to brain tumor treatment. Cancers, 13(13). https://doi.org/10.3390/cancers13133152
Park, J. H., A. L. G. de Lomana, D. M. Marzese, T. Juarez, A. Feroze, P. Hothi, C. Cobbs, et al. “A systems approach to brain tumor treatment.” Cancers 13, no. 13 (July 1, 2021). https://doi.org/10.3390/cancers13133152.
Park JH, de Lomana ALG, Marzese DM, Juarez T, Feroze A, Hothi P, et al. A systems approach to brain tumor treatment. Cancers. 2021 Jul 1;13(13).
Park, J. H., et al. “A systems approach to brain tumor treatment.” Cancers, vol. 13, no. 13, July 2021. Scopus, doi:10.3390/cancers13133152.
Park JH, de Lomana ALG, Marzese DM, Juarez T, Feroze A, Hothi P, Cobbs C, Patel AP, Kesari S, Huang S, Baliga NS. A systems approach to brain tumor treatment. Cancers. 2021 Jul 1;13(13).

Published In

Cancers

DOI

EISSN

2072-6694

Publication Date

July 1, 2021

Volume

13

Issue

13

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis