Cancer therapy has come a long way from its one-size-fits-all beginning to the awakening era of personalized medicine. This change has been largely driven by the discovery of biomarkers. Biomarkers can help refine patient selection for specific therapies. A blend of causal and correlative approaches is needed to elucidate the full potential of biomarkers in cancer research. This fusion of methodologies allows for a comprehensive exploration of biomarker efficacy, leading to more accurate predictions of drug response.
In a new paper, researchers Alberto Moscona-Nissan, Karl J. Habashy, Victor A. Arrieta, Adam M. Sonabend, and Crismita Dmello from the Universidad Panamericana School of Medicine, Northwestern University and Universidad Nacional Autónoma de México discuss causal and correlative approaches to identify potential biomarkers for predicting response to paclitaxel — a commonly used chemotherapeutic agent. On February 8, 2024, their research perspective was published in Oncotarget’s Volume 15, entitled, “Combining causal and correlative approaches to discover biomarkers of response to paclitaxel.”
“[…] studying the combination of non-overlapping biomarkers’ expression, in addition to clinical and sociodemographic data could generate predictive models for paclitaxel susceptibility.”
Full blog - https://www.oncotarget.org/2024/03/28/identifying-biomarkers-for-predicting-paclitaxel-response/
Paper DOI - https://doi.org/10.18632/oncotarget.28549
Correspondence to - Crismita Dmello - crismita.dmello@northwestern.edu, and Adam M. Sonabend - adam.sonabend@northwestern.edu
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Keywords - cancer, glioblastoma, predictive biomarker, CRISPR screen, paclitaxel
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