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COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA
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| Zeitschriftentitel: | Neuro-Oncology |
|---|---|
| Personen und Körperschaften: | , , , , , |
| In: | Neuro-Oncology, 21, 2019, Supplement_6, S. vi62-vi63 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Oxford University Press (OUP)
|
| Schlagwörter: |
| author_facet |
Narayan, Ravi Molenaar, Piet Cornelissen, Fleur Wurdinger, Tom Koster, Jan Westerman, Bart Narayan, Ravi Molenaar, Piet Cornelissen, Fleur Wurdinger, Tom Koster, Jan Westerman, Bart |
|---|---|
| author |
Narayan, Ravi Molenaar, Piet Cornelissen, Fleur Wurdinger, Tom Koster, Jan Westerman, Bart |
| spellingShingle |
Narayan, Ravi Molenaar, Piet Cornelissen, Fleur Wurdinger, Tom Koster, Jan Westerman, Bart Neuro-Oncology COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA Cancer Research Neurology (clinical) Oncology |
| author_sort |
narayan, ravi |
| spelling |
Narayan, Ravi Molenaar, Piet Cornelissen, Fleur Wurdinger, Tom Koster, Jan Westerman, Bart 1522-8517 1523-5866 Oxford University Press (OUP) Cancer Research Neurology (clinical) Oncology http://dx.doi.org/10.1093/neuonc/noz175.252 <jats:title>Abstract</jats:title> <jats:p>Personalized cancer treatments using synergistic combinations of drugs is attractive but proves to be highly challenging. The combinatorial nature of such problems results in an enormous parameter space that cannot be resolved by empirical research, i.e. testing all combinations for all molecularly defined tumors. In addition, effective drug synergy is hard to predict. Here we present an approach to map data of drug-response encyclopedias and represent these as a drug atlas. This atlas consists of a framework of chemotherapeutic responses that represents a drug vulnerability landscape of cancer. Based on data from the literature we found that many synergistic drug combinations show distinct inter therapy responses and drug sensitivities. We confirmed this by performing a drug combination screen against glioblastoma where we used 270 combination experiments. From the identified dual therapies we were able to predict and validate a triple drug synergy which was validated in vivo. This new and generalizable strategy opens the door to unforeseen personalized multidrug combination approaches.</jats:p> COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA Neuro-Oncology |
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| title |
COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_unstemmed |
COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_full |
COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_fullStr |
COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_full_unstemmed |
COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_short |
COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_sort |
comp-09. a cancer drug atlas enables prediction of parallel drug vulnerabilities of glioblastoma |
| topic |
Cancer Research Neurology (clinical) Oncology |
| url |
http://dx.doi.org/10.1093/neuonc/noz175.252 |
| publishDate |
2019 |
| physical |
vi62-vi63 |
| description |
<jats:title>Abstract</jats:title>
<jats:p>Personalized cancer treatments using synergistic combinations of drugs is attractive but proves to be highly challenging. The combinatorial nature of such problems results in an enormous parameter space that cannot be resolved by empirical research, i.e. testing all combinations for all molecularly defined tumors. In addition, effective drug synergy is hard to predict. Here we present an approach to map data of drug-response encyclopedias and represent these as a drug atlas. This atlas consists of a framework of chemotherapeutic responses that represents a drug vulnerability landscape of cancer. Based on data from the literature we found that many synergistic drug combinations show distinct inter therapy responses and drug sensitivities. We confirmed this by performing a drug combination screen against glioblastoma where we used 270 combination experiments. From the identified dual therapies we were able to predict and validate a triple drug synergy which was validated in vivo. This new and generalizable strategy opens the door to unforeseen personalized multidrug combination approaches.</jats:p> |
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| author | Narayan, Ravi, Molenaar, Piet, Cornelissen, Fleur, Wurdinger, Tom, Koster, Jan, Westerman, Bart |
| author_facet | Narayan, Ravi, Molenaar, Piet, Cornelissen, Fleur, Wurdinger, Tom, Koster, Jan, Westerman, Bart, Narayan, Ravi, Molenaar, Piet, Cornelissen, Fleur, Wurdinger, Tom, Koster, Jan, Westerman, Bart |
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| description | <jats:title>Abstract</jats:title> <jats:p>Personalized cancer treatments using synergistic combinations of drugs is attractive but proves to be highly challenging. The combinatorial nature of such problems results in an enormous parameter space that cannot be resolved by empirical research, i.e. testing all combinations for all molecularly defined tumors. In addition, effective drug synergy is hard to predict. Here we present an approach to map data of drug-response encyclopedias and represent these as a drug atlas. This atlas consists of a framework of chemotherapeutic responses that represents a drug vulnerability landscape of cancer. Based on data from the literature we found that many synergistic drug combinations show distinct inter therapy responses and drug sensitivities. We confirmed this by performing a drug combination screen against glioblastoma where we used 270 combination experiments. From the identified dual therapies we were able to predict and validate a triple drug synergy which was validated in vivo. This new and generalizable strategy opens the door to unforeseen personalized multidrug combination approaches.</jats:p> |
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| imprint | Oxford University Press (OUP), 2019 |
| imprint_str_mv | Oxford University Press (OUP), 2019 |
| institution | DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161 |
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| spelling | Narayan, Ravi Molenaar, Piet Cornelissen, Fleur Wurdinger, Tom Koster, Jan Westerman, Bart 1522-8517 1523-5866 Oxford University Press (OUP) Cancer Research Neurology (clinical) Oncology http://dx.doi.org/10.1093/neuonc/noz175.252 <jats:title>Abstract</jats:title> <jats:p>Personalized cancer treatments using synergistic combinations of drugs is attractive but proves to be highly challenging. The combinatorial nature of such problems results in an enormous parameter space that cannot be resolved by empirical research, i.e. testing all combinations for all molecularly defined tumors. In addition, effective drug synergy is hard to predict. Here we present an approach to map data of drug-response encyclopedias and represent these as a drug atlas. This atlas consists of a framework of chemotherapeutic responses that represents a drug vulnerability landscape of cancer. Based on data from the literature we found that many synergistic drug combinations show distinct inter therapy responses and drug sensitivities. We confirmed this by performing a drug combination screen against glioblastoma where we used 270 combination experiments. From the identified dual therapies we were able to predict and validate a triple drug synergy which was validated in vivo. This new and generalizable strategy opens the door to unforeseen personalized multidrug combination approaches.</jats:p> COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA Neuro-Oncology |
| spellingShingle | Narayan, Ravi, Molenaar, Piet, Cornelissen, Fleur, Wurdinger, Tom, Koster, Jan, Westerman, Bart, Neuro-Oncology, COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA, Cancer Research, Neurology (clinical), Oncology |
| title | COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_full | COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_fullStr | COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_full_unstemmed | COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_short | COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| title_sort | comp-09. a cancer drug atlas enables prediction of parallel drug vulnerabilities of glioblastoma |
| title_unstemmed | COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA |
| topic | Cancer Research, Neurology (clinical), Oncology |
| url | http://dx.doi.org/10.1093/neuonc/noz175.252 |