Chemo-predictive assay for targeting cancer stem-like cells in patients affected by brain tumors

Sarah E Mathis1, Anthony Alberico2, Rounak Nande1

  • 1Department of Biochemistry and Microbiology, Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia, United States of America; Translational Genomic Research Institute, Marshall University, Huntington, West Virginia, United States of America.

Plos One
|August 22, 2014
PubMed

Insights

A new ChemoID assay predicts chemotherapy effectiveness for cancer stem-like cells (CSLCs) and tumor cells. This personalized approach improved outcomes for one patient, highlighting its potential for individualized cancer treatment.

Area of Science:

  • Oncology
  • Cancer Research
  • Personalized Medicine

Background:

  • Ineffective chemotherapy causes toxicity and resistance, particularly from cancer stem-like cells (CSLCs), leading to relapse.
  • Identifying effective chemotherapy is crucial for successful individualized anticancer treatments.
  • Current treatment strategies often fail to account for differential cell sensitivities within a tumor.

Purpose of the Study:

  • To develop and evaluate an ex vivo chemotherapy sensitivity assay (ChemoID) for both CSLCs and bulk tumor cells.
  • To assess the potential of ChemoID for guiding personalized chemotherapy selection in ependymoma patients.
  • To investigate novel therapeutic combinations, including benzyl isothiocyanate (BITC), to overcome chemotherapy resistance.

Main Methods:

  • Developed the ChemoID assay to measure ex vivo sensitivity of CSLCs and bulk tumor cells to various chemotherapy agents.
  • Screened two anaplastic ependymoma patients (WHO grade-III) using the ChemoID assay.
  • Correlated ChemoID assay results with clinical outcomes and patient-derived xenograft (PDX) animal models.

Main Results:

  • Patient 1 showed sensitivity to irinotecan and bevacizumab, achieving an 18-month progression-free survival.
  • ChemoID identified benzyl isothiocyanate (BITC) as enhancing chemosensitivity, leading to >50% tumor regression in Patient 1.
  • Patient 2 exhibited resistance to all tested agents, with rapid tumor progression, underscoring treatment variability.

Conclusions:

  • The ChemoID assay effectively predicts patient response to chemotherapy by assessing both CSLCs and bulk tumor cells.
  • Personalized treatment guided by ChemoID, including novel combinations like BITC, can significantly improve clinical outcomes.
  • ChemoID testing holds promise for developing more effective and individualized anticancer therapies, reducing toxicity and improving survival.