PONE-D-24-24126CPI203, a BET inhibitor, down-regulates a consistent set of DNA synthesis genes across a wide array of glioblastoma lines.PLOS ONE

Dear Dr. Garrett,

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==============================

Detailed comments from reviewers are:

Reviewer#1:

The study demonstrates that CPI203, a BET inhibitor, effectively downregulates DNA synthesis genes across different glioblastoma lines. This finding offers a promising therapeutic approach for glioblastoma, potentially impacting the treatment of this aggressive disease. Additionally, the authors identified CDKN2A and CDKN2B as biomarkers for determining CPI203 sensitivity in glioblastoma lines through PCA clustering and differential expression analyses. Furthermore, using WCGNA, the authors discovered that the FBXO5 oncogenic module was downregulated by CPI203 treatment.

Q1. Validation of CDKN2A and CDKN2B as Biomarkers of CPI203 Sensitivity

The authors claim that high expression of CDKN2A and CDKN2B leads to higher CPI203 sensitivity. To substantiate this claim, it would be beneficial to perform genetic knockout or knockdown experiments using CRISPRko, CRISPRi, or RNAi targeting CDKN2A, CDKN2B, or both. These experiments should demonstrate that the loss of these genes results in reduced sensitivity to CPI203, thereby validating them as biomarkers.

Q2. Concerns about the General Toxicity of BET Inhibitor (CPI203)

The BET family of proteins includes four conserved mammalian members: BRD2, BRD3, BRD4, and BRDT. According to DepMap (24Q2), BRD4 is a common essential gene, raising general toxicity concerns about using CPI203, a BET inhibitor, in clinical applications. Can the authors address these concerns and discuss the potential toxicity of CPI203 in clinical settings?

Q3. Utilizing DepMap Data for Drug Sensitivity Profiles

On page 19 of the manuscript, the authors mention that a larger study with more cell lines could potentially identify gene signatures for individual drugs and create a more useful tumor classification based on drug response profiles. Public data from DepMap on the drug sensitivity profile of CPI203 across 472 cancer cell lines is available (source: https://depmap.org/portal/compound/CPI-203?tab=overview). The authors should consider utilizing this data to enhance their study and develop a more comprehensive tumor classification based on drug response profiles.

Q4. Data Availability and Code Reproducibility

The authors agreed to make all data fully available without restriction in the submission package. However, their GitHub repository currently provides links to the Illumina BaseSpace account, which requires login to retrieve the data. To ensure full public accessibility, the authors should upload their data to the Gene Expression Omnibus (GEO). Additionally, uploading their R/Python codes to the GitHub repository would make their major analysis workflows transparent and reproducible.

Reviewer#2

Summary: Glioblastoma is a complex disease that exhibits heterogeneity between patients and between tumors. To date, the standard of care treatment for glioblastoma is temozolomide. The varying response of temozolomide shows the need to develop new therapeutic targets and their associated compounds for glioblastoma treatment. Glioblastoma is propagated by the expression of pro-tumor growth factors (ie. EGFR) or deletion of tumor suppression genes (ie. PTEN, p53, Rb), the authors’ novelty utilizes chromatin modifying agents to identify new treatment options in glioblastoma. To identify viable chromatin modifying/epigenetic compounds as treatment options for glioblastoma, the authors screened 106 chromatin modifying/epigenetic compounds targeting 36 different genes first in independently derived gliomaspheres, lead compounds for each of the 12 compound class underwent a secondary screening using early passage of additional twelve gliomasphere lines. The authors calculated “delta AUC” to identify lead compound for each compound class. Of all compounds tested, CPI203, a BET class inhibitor reduced cell viability the most. RNA-seq of compound treated vs nontreated cells revealed that the same compound showed varying response in different cell line. However, CPI203, a BET class inhibitor shows the most consisted gene disruption in different cell lines. Further, the authors performed weighted correlation gene net analysis (WCGNA) ot identify sets of co-varying genes after compound treatment because genes often function through a network. WCGNA identified enriched genes “MELK” and “FBXO5” in sensitive cells, both of which as involved in mitotic and cell cycle, suggesting these two genes may serve as new therapeutic targets for glioblastoma treatment. Lastly, the author performed ATAC-seq in glioblastoma cell line after treatment with lead BET inhibitor(CPI203, JQ1, and OTX015). ATAC-seq showed a reduction of gene accessibility in cell lines after BET inhibitor treatment suggesting specificity of lead compounds.

Comments

1. In panel 1. The authors performed 106 compound screening in 5 cell lines. Each cell line was treated with 1uM or 10 uM for three days and 500 nM for twenty-eight days. Lead compound was identified by calculating “delta AUC” by the difference of day three and day twenty-eight by MTT assay.

a. In the twenty-eight day treatment, were the cells passaged as they become confluent? If cells were passaged, then the conditions of the twenty-eight day treatment would be different compared to that of three day treatment. If the goal was to identify lead compound by three days in each cell lines, why not use a vehicle control such as DMSO or solvent used to dilute each compound, then compare cell viability at day three to the vehicle control.

Minor Comments

1. In figure 2F, the authors performed RNA-seq in compound treated vs control of each cell lines. PCA clustering analysis revealed two cluster of sensitive and resistant cells. Cluster 1, the sensitive cluster seems to have varying transcriptome across PCA1 whereas the cells in cluster 2 are more similar. Gene expression of cluster 2 may reveal additional gene sets in cluster 2 that can explain drug resistance.

a. Cluster 1 was observed to express higher well-known tumor suppressor genes (CHKN2A/CDKN2B), could CPI203 serve as conditional therapy?

b. Cluster 1 seems to have varied expression across PCA1. Could this suggest that CPI203 is binding to a specific target rather than a transcriptome similarity?

2. The authors made mentioned that the compounds used in the study were extensive but not exhaustive. Perhaps the authors should include rationale of why these compounds or specifically 106 was chosen.

==============================

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Academic Editor

PLOS ONE

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Additional Editor Comments:

This manuscript is well-written. The experiments were well-designed. Taken together with two reviewers' comments, we would like to request minor revision before publishing. Detailed comments from reviewers are:

Reviewer#1:

The study demonstrates that CPI203, a BET inhibitor, effectively downregulates DNA synthesis genes across different glioblastoma lines. This finding offers a promising therapeutic approach for glioblastoma, potentially impacting the treatment of this aggressive disease. Additionally, the authors identified CDKN2A and CDKN2B as biomarkers for determining CPI203 sensitivity in glioblastoma lines through PCA clustering and differential expression analyses. Furthermore, using WCGNA, the authors discovered that the FBXO5 oncogenic module was downregulated by CPI203 treatment.

Q1. Validation of CDKN2A and CDKN2B as Biomarkers of CPI203 Sensitivity

The authors claim that high expression of CDKN2A and CDKN2B leads to higher CPI203 sensitivity. To substantiate this claim, it would be beneficial to perform genetic knockout or knockdown experiments using CRISPRko, CRISPRi, or RNAi targeting CDKN2A, CDKN2B, or both. These experiments should demonstrate that the loss of these genes results in reduced sensitivity to CPI203, thereby validating them as biomarkers.

Q2. Concerns about the General Toxicity of BET Inhibitor (CPI203)

The BET family of proteins includes four conserved mammalian members: BRD2, BRD3, BRD4, and BRDT. According to DepMap (24Q2), BRD4 is a common essential gene, raising general toxicity concerns about using CPI203, a BET inhibitor, in clinical applications. Can the authors address these concerns and discuss the potential toxicity of CPI203 in clinical settings?

Q3. Utilizing DepMap Data for Drug Sensitivity Profiles

On page 19 of the manuscript, the authors mention that a larger study with more cell lines could potentially identify gene signatures for individual drugs and create a more useful tumor classification based on drug response profiles. Public data from DepMap on the drug sensitivity profile of CPI203 across 472 cancer cell lines is available (source: https://depmap.org/portal/compound/CPI-203?tab=overview). The authors should consider utilizing this data to enhance their study and develop a more comprehensive tumor classification based on drug response profiles.

Q4. Data Availability and Code Reproducibility

The authors agreed to make all data fully available without restriction in the submission package. However, their GitHub repository currently provides links to the Illumina BaseSpace account, which requires login to retrieve the data. To ensure full public accessibility, the authors should upload their data to the Gene Expression Omnibus (GEO). Additionally, uploading their R/Python codes to the GitHub repository would make their major analysis workflows transparent and reproducible.

Reviewer#2

Summary: Glioblastoma is a complex disease that exhibits heterogeneity between patients and between tumors. To date, the standard of care treatment for glioblastoma is temozolomide. The varying response of temozolomide shows the need to develop new therapeutic targets and their associated compounds for glioblastoma treatment. Glioblastoma is propagated by the expression of pro-tumor growth factors (ie. EGFR) or deletion of tumor suppression genes (ie. PTEN, p53, Rb), the authors’ novelty utilizes chromatin modifying agents to identify new treatment options in glioblastoma. To identify viable chromatin modifying/epigenetic compounds as treatment options for glioblastoma, the authors screened 106 chromatin modifying/epigenetic compounds targeting 36 different genes first in independently derived gliomaspheres, lead compounds for each of the 12 compound class underwent a secondary screening using early passage of additional twelve gliomasphere lines. The authors calculated “delta AUC” to identify lead compound for each compound class. Of all compounds tested, CPI203, a BET class inhibitor reduced cell viability the most. RNA-seq of compound treated vs nontreated cells revealed that the same compound showed varying response in different cell line. However, CPI203, a BET class inhibitor shows the most consisted gene disruption in different cell lines. Further, the authors performed weighted correlation gene net analysis (WCGNA) ot identify sets of co-varying genes after compound treatment because genes often function through a network. WCGNA identified enriched genes “MELK” and “FBXO5” in sensitive cells, both of which as involved in mitotic and cell cycle, suggesting these two genes may serve as new therapeutic targets for glioblastoma treatment. Lastly, the author performed ATAC-seq in glioblastoma cell line after treatment with lead BET inhibitor(CPI203, JQ1, and OTX015). ATAC-seq showed a reduction of gene accessibility in cell lines after BET inhibitor treatment suggesting specificity of lead compounds.

Comments

1. In panel 1. The authors performed 106 compound screening in 5 cell lines. Each cell line was treated with 1uM or 10 uM for three days and 500 nM for twenty-eight days. Lead compound was identified by calculating “delta AUC” by the difference of day three and day twenty-eight by MTT assay.

a. In the twenty-eight day treatment, were the cells passaged as they become confluent? If cells were passaged, then the conditions of the twenty-eight day treatment would be different compared to that of three day treatment. If the goal was to identify lead compound by three days in each cell lines, why not use a vehicle control such as DMSO or solvent used to dilute each compound, then compare cell viability at day three to the vehicle control.

Minor Comments

1. In figure 2F, the authors performed RNA-seq in compound treated vs control of each cell lines. PCA clustering analysis revealed two cluster of sensitive and resistant cells. Cluster 1, the sensitive cluster seems to have varying transcriptome across PCA1 whereas the cells in cluster 2 are more similar. Gene expression of cluster 2 may reveal additional gene sets in cluster 2 that can explain drug resistance.

a. Cluster 1 was observed to express higher well-known tumor suppressor genes (CHKN2A/CDKN2B), could CPI203 serve as conditional therapy?

b. Cluster 1 seems to have varied expression across PCA1. Could this suggest that CPI203 is binding to a specific target rather than a transcriptome similarity?

2. The authors made mentioned that the compounds used in the study were extensive but not exhaustive. Perhaps the authors should include rationale of why these compounds or specifically 106 was chosen.

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Reviewers' comments:

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Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: Review Comments to the Authors

The study demonstrates that CPI203, a BET inhibitor, effectively downregulates DNA synthesis genes across different glioblastoma lines. This finding offers a promising therapeutic approach for glioblastoma, potentially impacting the treatment of this aggressive disease. Additionally, the authors identified CDKN2A and CDKN2B as biomarkers for determining CPI203 sensitivity in glioblastoma lines through PCA clustering and differential expression analyses. Furthermore, using WCGNA, the authors discovered that the FBXO5 oncogenic module was downregulated by CPI203 treatment.

Q1. Validation of CDKN2A and CDKN2B as Biomarkers of CPI203 Sensitivity

The authors claim that high expression of CDKN2A and CDKN2B leads to higher CPI203 sensitivity. To substantiate this claim, it would be beneficial to perform genetic knockout or knockdown experiments using CRISPRko, CRISPRi, or RNAi targeting CDKN2A, CDKN2B, or both. These experiments should demonstrate that the loss of these genes results in reduced sensitivity to CPI203, thereby validating them as biomarkers.

Q2. Concerns about the General Toxicity of BET Inhibitor (CPI203)

The BET family of proteins includes four conserved mammalian members: BRD2, BRD3, BRD4, and BRDT. According to DepMap (24Q2), BRD4 is a common essential gene, raising general toxicity concerns about using CPI203, a BET inhibitor, in clinical applications. Can the authors address these concerns and discuss the potential toxicity of CPI203 in clinical settings?

Q3. Utilizing DepMap Data for Drug Sensitivity Profiles

On page 19 of the manuscript, the authors mention that a larger study with more cell lines could potentially identify gene signatures for individual drugs and create a more useful tumor classification based on drug response profiles. Public data from DepMap on the drug sensitivity profile of CPI203 across 472 cancer cell lines is available (source: https://depmap.org/portal/compound/CPI-203?tab=overview). The authors should consider utilizing this data to enhance their study and develop a more comprehensive tumor classification based on drug response profiles.

Q4. Data Availability and Code Reproducibility

The authors agreed to make all data fully available without restriction in the submission package. However, their GitHub repository currently provides links to the Illumina BaseSpace account, which requires login to retrieve the data. To ensure full public accessibility, the authors should upload their data to the Gene Expression Omnibus (GEO). Additionally, uploading their R/Python codes to the GitHub repository would make their major analysis workflows transparent and reproducible.

Reviewer #2: The authors have provided evidence in support of the potential of chromatin modifying agents. In the study, the authors have shown drug efficacy and pathway of action. The identification of a specific drug target and binding specificity can greatly improve the study.

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Reviewer #1: No

Reviewer #2: Yes:  Benjamin Z Kuang

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CPI203, a BET inhibitor, down-regulates a consistent set of DNA synthesis genes across a wide array of glioblastoma lines.

PONE-D-24-24126R1

Dear Dr. Garrett,

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Academic Editor

PLOS ONE