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Interaction of a traditional Chinese Medicine (PHY906) and CPT-11 on the inflammatory process in the tumor microenvironment.

Wang E, Bussom S, Chen J, Quinn C, Bedognetti D, Lam W, Guan F, Jiang Z, Mark Y, Zhao Y, Stroncek DF, White J, Marincola FM, Cheng YC - BMC Med Genomics (2011)

Bottom Line: Determining the mode of action of these mixtures was previously unsatisfactory; however, information rich RNA microarray technologies now allow for thorough mechanistic studies of the effects complex mixtures.PHY906 is a long used four herb TCM formula employed as an adjuvant to relieve the side effects associated with chemotherapy.Animal studies documented a decrease in global toxicity and an increase in therapeutic effectiveness of chemotherapy when combined with PHY906.

View Article: PubMed Central - HTML - PubMed

Affiliation: Infectious Disease and Immunogenetics Section (IDIS), Department of Transfusion Medicine, Clinical Center and trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda, Maryland 20892, USA.

ABSTRACT

Background: Traditional Chinese Medicine (TCM) has been used for thousands of years to treat or prevent diseases, including cancer. Good manufacturing practices (GMP) and sophisticated product analysis (PhytomicsQC) to ensure consistency are now available allowing the assessment of its utility. Polychemical Medicines, like TCM, include chemicals with distinct tissue-dependent pharmacodynamic properties that result in tissue-specific bioactivity. Determining the mode of action of these mixtures was previously unsatisfactory; however, information rich RNA microarray technologies now allow for thorough mechanistic studies of the effects complex mixtures. PHY906 is a long used four herb TCM formula employed as an adjuvant to relieve the side effects associated with chemotherapy. Animal studies documented a decrease in global toxicity and an increase in therapeutic effectiveness of chemotherapy when combined with PHY906.

Methods: Using a systems biology approach, we studied tumor tissue to identify reasons for the enhancement of the antitumor effect of CPT-11 (CPT-11) by PHY906 in a well-characterized pre-clinical model; the administration of PHY906 and CPT-11 to female BDF-1 mice bearing subcutaneous Colon 38 tumors.

Results: We observed that 1) individually PHY906 and CPT-11 induce distinct alterations in tumor, liver and spleen; 2) PHY906 alone predominantly induces repression of transcription and immune-suppression in tumors; 3) these effects are reverted in the presence of CPT-11, with prevalent induction of pro-apoptotic and pro-inflammatory pathways that may favor tumor rejection.

Conclusions: PHY906 together with CPT-11 triggers unique changes not activated by each one alone suggesting that the combination creates a unique tissue-specific response.

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Related in: MedlinePlus

Quantitative PCR validation of selected genes relevant to the study that were identified as differentially expressed according to transcriptional analysis among different treatment groups. For each transcript, the first graph shows RNA array results followed by qPCR validation results. The Y-axis of the Array data graphs shows relative expression ratio of specific gene in samples relative to the mean of the same gene across PBS control group (REA-Relative Expression in Array). For qPCR validation, the data shown are of the relative expression (RE) of a gene of interest per actin molecule in sample compared to the averaged ratio of the gene of interest to actin for the entire control group (Y-axis). Statistics were Student t-tests (two tailed) performed by GraphaPad software. Error bars represent SD. The four graph bars on the X-axis for each graph represent the different treatment groups.
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Figure 6: Quantitative PCR validation of selected genes relevant to the study that were identified as differentially expressed according to transcriptional analysis among different treatment groups. For each transcript, the first graph shows RNA array results followed by qPCR validation results. The Y-axis of the Array data graphs shows relative expression ratio of specific gene in samples relative to the mean of the same gene across PBS control group (REA-Relative Expression in Array). For qPCR validation, the data shown are of the relative expression (RE) of a gene of interest per actin molecule in sample compared to the averaged ratio of the gene of interest to actin for the entire control group (Y-axis). Statistics were Student t-tests (two tailed) performed by GraphaPad software. Error bars represent SD. The four graph bars on the X-axis for each graph represent the different treatment groups.

Mentions: Several transcripts were selected for validation by qPCR (Figure 6). Although we have previously shown that qPCR may not necessarily be an optimal validation method for array data because it lacks endogenous reference controls and it is based on reference genes [19], it still provides an approximate corroboration of the information obtained with one platform. As shown here, data from array or qPCR in 10 transcripts relevant to the study and representing distinct behaviors in distinct treatment groups were compared side by side demonstrating a high level of comparability; of note is the behavior of IRF-5 which was confirmed to be up-regulated particularly in the PHY-906 with CPT-11 combination and IRF-1 which was significantly down-regulated in expression by CTP-11 (array p2-value = 0.0002 and qPCR p2-value = 0.0035) treatment. This phenomenon was partially reversed in the presence of PHY-906.


Interaction of a traditional Chinese Medicine (PHY906) and CPT-11 on the inflammatory process in the tumor microenvironment.

Wang E, Bussom S, Chen J, Quinn C, Bedognetti D, Lam W, Guan F, Jiang Z, Mark Y, Zhao Y, Stroncek DF, White J, Marincola FM, Cheng YC - BMC Med Genomics (2011)

Quantitative PCR validation of selected genes relevant to the study that were identified as differentially expressed according to transcriptional analysis among different treatment groups. For each transcript, the first graph shows RNA array results followed by qPCR validation results. The Y-axis of the Array data graphs shows relative expression ratio of specific gene in samples relative to the mean of the same gene across PBS control group (REA-Relative Expression in Array). For qPCR validation, the data shown are of the relative expression (RE) of a gene of interest per actin molecule in sample compared to the averaged ratio of the gene of interest to actin for the entire control group (Y-axis). Statistics were Student t-tests (two tailed) performed by GraphaPad software. Error bars represent SD. The four graph bars on the X-axis for each graph represent the different treatment groups.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3117677&req=5

Figure 6: Quantitative PCR validation of selected genes relevant to the study that were identified as differentially expressed according to transcriptional analysis among different treatment groups. For each transcript, the first graph shows RNA array results followed by qPCR validation results. The Y-axis of the Array data graphs shows relative expression ratio of specific gene in samples relative to the mean of the same gene across PBS control group (REA-Relative Expression in Array). For qPCR validation, the data shown are of the relative expression (RE) of a gene of interest per actin molecule in sample compared to the averaged ratio of the gene of interest to actin for the entire control group (Y-axis). Statistics were Student t-tests (two tailed) performed by GraphaPad software. Error bars represent SD. The four graph bars on the X-axis for each graph represent the different treatment groups.
Mentions: Several transcripts were selected for validation by qPCR (Figure 6). Although we have previously shown that qPCR may not necessarily be an optimal validation method for array data because it lacks endogenous reference controls and it is based on reference genes [19], it still provides an approximate corroboration of the information obtained with one platform. As shown here, data from array or qPCR in 10 transcripts relevant to the study and representing distinct behaviors in distinct treatment groups were compared side by side demonstrating a high level of comparability; of note is the behavior of IRF-5 which was confirmed to be up-regulated particularly in the PHY-906 with CPT-11 combination and IRF-1 which was significantly down-regulated in expression by CTP-11 (array p2-value = 0.0002 and qPCR p2-value = 0.0035) treatment. This phenomenon was partially reversed in the presence of PHY-906.

Bottom Line: Determining the mode of action of these mixtures was previously unsatisfactory; however, information rich RNA microarray technologies now allow for thorough mechanistic studies of the effects complex mixtures.PHY906 is a long used four herb TCM formula employed as an adjuvant to relieve the side effects associated with chemotherapy.Animal studies documented a decrease in global toxicity and an increase in therapeutic effectiveness of chemotherapy when combined with PHY906.

View Article: PubMed Central - HTML - PubMed

Affiliation: Infectious Disease and Immunogenetics Section (IDIS), Department of Transfusion Medicine, Clinical Center and trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda, Maryland 20892, USA.

ABSTRACT

Background: Traditional Chinese Medicine (TCM) has been used for thousands of years to treat or prevent diseases, including cancer. Good manufacturing practices (GMP) and sophisticated product analysis (PhytomicsQC) to ensure consistency are now available allowing the assessment of its utility. Polychemical Medicines, like TCM, include chemicals with distinct tissue-dependent pharmacodynamic properties that result in tissue-specific bioactivity. Determining the mode of action of these mixtures was previously unsatisfactory; however, information rich RNA microarray technologies now allow for thorough mechanistic studies of the effects complex mixtures. PHY906 is a long used four herb TCM formula employed as an adjuvant to relieve the side effects associated with chemotherapy. Animal studies documented a decrease in global toxicity and an increase in therapeutic effectiveness of chemotherapy when combined with PHY906.

Methods: Using a systems biology approach, we studied tumor tissue to identify reasons for the enhancement of the antitumor effect of CPT-11 (CPT-11) by PHY906 in a well-characterized pre-clinical model; the administration of PHY906 and CPT-11 to female BDF-1 mice bearing subcutaneous Colon 38 tumors.

Results: We observed that 1) individually PHY906 and CPT-11 induce distinct alterations in tumor, liver and spleen; 2) PHY906 alone predominantly induces repression of transcription and immune-suppression in tumors; 3) these effects are reverted in the presence of CPT-11, with prevalent induction of pro-apoptotic and pro-inflammatory pathways that may favor tumor rejection.

Conclusions: PHY906 together with CPT-11 triggers unique changes not activated by each one alone suggesting that the combination creates a unique tissue-specific response.

Show MeSH
Related in: MedlinePlus