Oncotarget

Research Perspectives:

Combining causal and correlative approaches to discover biomarkers of response to paclitaxel

Alberto Moscona-Nissan, Karl J. Habashy, Victor A. Arrieta, Adam M. Sonabend _ and Crismita Dmello _

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Oncotarget. 2024; 15:117-122. https://doi.org/10.18632/oncotarget.28549

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Abstract

Alberto Moscona-Nissan1, Karl J. Habashy2,3, Victor A. Arrieta2,3,4, Adam M. Sonabend2,3 and Crismita Dmello2,3

1 Universidad Panamericana School of Medicine, Mexico City, Mexico

2 Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago IL 60611, USA

3 Northwestern Medicine, Malnati Brain Tumor Institute of the Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago IL 60611, USA

4 PECEM, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico

Correspondence to:

Crismita Dmello, email: [email protected]
Adam M. Sonabend, email: [email protected]

Keywords: glioblastoma; predictive biomarker; CRISPR screen; paclitaxel

Received: December 19, 2023     Accepted: December 26, 2023     Published: February 08, 2024

Copyright: © 2024 Moscona-Nissan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ABSTRACT

We recently discovered a putative paclitaxel response predictive biomarker for glioblastoma and breast cancer using the whole genome CRISPR knockout screen. The biomarker candidate was validated in two independent breast cancer patient cohorts that received taxane treatment. To further evaluate the potential application of this biomarker in the clinic for patients with glioblastoma, a prospective validation in cohorts of patients with glioblastoma is essential and will be performed as part of our ongoing phase II clinical trial (NCT04528680). The validation of novel biomarkers of susceptibility to therapy is critical to elucidate the efficacy signal of therapeutic agents. This is especially important in the context of glioblastoma, where therapeutic benefit is variable and unpredictable, leading to negative trials, yet the outcome of subset of patients has outperformed expectations.


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