On 2015 Jul 10, Miguel Lopez-Lazaro commented:

The authors show a pharmacological strategy that might improve the therapy of a variety of cancer types. However, they tested the anticancer activity of their drug combinations using a preclinical validation approach that, in my opinion, does not reliably predict drug efficacy in cancer patients. Their approach was based on evaluating cytotoxic potency against cancer cells and tumor regression in mice. Although this experimental approach is used by many researchers (including myself in the recent past), it may be inadequate to detect the type of drugs that cancer patients need. I recently proposed an alternative way to assess preclinical anticancer activity: the new drug or drug combination should improve the selectivity (in vitro) and survival rate (in vivo) of the standard treatments used in cancer patients (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4381701/pdf/oncoscience-02-0091.pdf). This patient-oriented approach may help reveal whether or not a combination of kinase and BET inhibitors can improve the efficacy of the existing therapies. I wrote the following letter for Cancer Cell, but the Editors did not find it adequate for their journal. Perhaps someone finds it useful.

Combination of Kinase and BET Inhibitors to Overcome Resistance to Therapy: Preclinical Validation Required

Miguel López-Lázaro Department of Pharmacology, Faculty of Pharmacy, University of Seville, Spain

Kinase inhibitors are the standard of care for a variety of cancer types. Patients treated with kinase inhibitors often develop resistance to therapy, which has been associated with upregulation of tyrosine kinase receptors (RTKs) and subsequent activation of the PI3K pathway. In an article recently published in Cancer Cell, Stratikopoulos et al. showed that BRD4 is important for the feedback activation of several RTKs, and that combined PI3K and BET inhibition blocks PI3K reactivation in a variety of cancer cells. Then, the authors carried out experiments to validate this combination in preclinical in vitro and in vivo models. They observed in several cancer cell types that the cytotoxicity of the combination of a PI3K inhibitor and a BET inhibitor at a fixed concentration was higher than that observed when the inhibitors were tested alone at the same concentrations. They also found a better antitumor activity when mice with breast tumors were treated with kinase and BET inhibitors together than when they were treated with each inhibitor alone at the same doses. The authors discussed that these findings provide the rationale for combining kinase and BET inhibitors to improve therapy in several human cancers (Stratikopoulos et al., 2015).

Patients with unresectable or metastatic cancers are difficult to cure and require the development of better pharmacological therapies. The first step to developing better therapies is to find good drug candidates or pharmacological strategies for testing. Stratikopoulos et al. find that combined PI3K and BET inhibition sustains PI3K inhibition in a variety of cancer cells, thereby providing the rationale for testing the anticancer potential of this combination. The next step to developing better treatments is to evaluate the new drugs using robust preclinical models; these models should predict whether the anticancer potential of the new drugs is high enough to deserve clinical evaluation. The experimental approach used by Stratikopoulos et al. does not reveal, however, whether or not the combination of PI3K and BET inhibitors deserves clinical testing. The main reason is that their approach was based on evaluating cytotoxic potency in cancer cells and tumor shrinkage in animal models, and these parameters are poor predictors of clinical efficacy. Despite their widespread use, these parameters do not reliably detect the type of drugs that cancer patients need.

Cancer patients do not need drugs or drug combinations that target their cancer cells at low concentrations if they also target their normal cells at similar concentrations. Cancer patients will probably not benefit from drugs that reduce tumor volumes in mice if they do not extend their lives. Cancer patients need drugs that improve the efficacy of the existing treatments. Establishing the best parameters to measure efficacy in vitro and in vivo is essential, and evidence suggests that selectivity (in vitro) and survival rate (in vivo) are the most reliable parameters to predict drug efficacy in cancer patients (Lopez-Lazaro, 2015c). In vitro, the new treatment should improve the selectivity of the existing drugs when tested in cancer cells versus nonmalignant cells from a variety of healthy tissues (Lopez-Lazaro, 2015a; Lopez-Lazaro, 2015b; Lopez-Lazaro, 2015c). The efficacy of a drug combination should be assessed by testing in cancer cells versus nonmalignant cells if it improves the selectivity of the standard treatment, and not by testing in cancer cells if its cytotoxicity is enhanced in relation to the cytotoxicity induced by each drug alone. It is important to realize that a drug combination that induces a strong cytotoxic synergism in cancer cells will not be clinically effective if it induces a stronger synergism in nonmalignant cells, or that a drug combination that induces synergism in cancer cells and antagonism in nonmalignant cells will not be clinically useful if its selectivity towards cancer cells is lower than that of the standard treatment (Lopez-Lazaro, 2015c). In vivo, the new drug or drug combination should improve the survival rate of the existing therapy when tested under equivalent experimental conditions (e.g., equitoxic doses) in animal models representative of the patients who would eventually receive the new treatment (Lopez-Lazaro, 2015c). Unfortunately, many drugs and drug combinations are tested in cancer patients after showing cytotoxic potency against cancer cells and tumor regression in mice. This preclinical validation approach may contribute to explain why our ability to translate preclinical cancer research to clinical success is remarkably low (Hutchinson and Kirk, 2011). A preclinical validation model based on assessing whether the drug candidates improve the selectivity and survival rate of the standard therapies would facilitate the development of better treatments, and would also prevent many cancer patients from receiving ineffective drugs (Lopez-Lazaro, 2015c).

In conclusion, Stratikopoulos et al. have discovered a pharmacological strategy that might improve the therapy of a variety of cancer types. However, they assessed the anticancer potential of their strategy using a preclinical validation approach that does not reliably predict drug efficacy in cancer patients. Testing if BET inhibitors improve the selectivity and survival rate of the kinase inhibitors used in oncology would help reveal whether or not kinase and BET inhibitors together can overcome resistance to therapy.

REFERENCES

Hutchinson, L. and Kirk, R. (2011). High drug attrition rates--where are we going wrong? Nat. Rev. Clin. Oncol. 8, 189-190.

Lopez-Lazaro, M. (2015a). A Simple and Reliable Approach for Assessing Anticancer Activity In Vitro. Curr. Med. Chem. 22, 1324-1334.

Lopez-Lazaro, M. (2015b). How many times should we screen a chemical library to discover an anticancer drug? Drug Discov. Today. 20, 167-169.

Lopez-Lazaro, M. (2015c). Two preclinical tests to evaluate anticancer activity and to help validate drug candidates for clinical trials. Oncoscience 2, 91-98.

Stratikopoulos, E.E., Dendy, M., Szabolcs, M., Khaykin, A.J., Lefebvre, C., Zhou, M.M., and Parsons, R. (2015). Kinase and BET Inhibitors Together Clamp Inhibition of PI3K Signaling and Overcome Resistance to Therapy. Cancer Cell. 27, 837-851.

On 2015 Jul 10, Miguel Lopez-Lazaro commented:

The authors show a pharmacological strategy that might improve the therapy of a variety of cancer types. However, they tested the anticancer activity of their drug combinations using a preclinical validation approach that, in my opinion, does not reliably predict drug efficacy in cancer patients. Their approach was based on evaluating cytotoxic potency against cancer cells and tumor regression in mice. Although this experimental approach is used by many researchers (including myself in the recent past), it may be inadequate to detect the type of drugs that cancer patients need. I recently proposed an alternative way to assess preclinical anticancer activity: the new drug or drug combination should improve the selectivity (in vitro) and survival rate (in vivo) of the standard treatments used in cancer patients (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4381701/pdf/oncoscience-02-0091.pdf). This patient-oriented approach may help reveal whether or not a combination of kinase and BET inhibitors can improve the efficacy of the existing therapies. I wrote the following letter for Cancer Cell, but the Editors did not find it adequate for their journal. Perhaps someone finds it useful.

Combination of Kinase and BET Inhibitors to Overcome Resistance to Therapy: Preclinical Validation Required

Miguel López-Lázaro Department of Pharmacology, Faculty of Pharmacy, University of Seville, Spain

Kinase inhibitors are the standard of care for a variety of cancer types. Patients treated with kinase inhibitors often develop resistance to therapy, which has been associated with upregulation of tyrosine kinase receptors (RTKs) and subsequent activation of the PI3K pathway. In an article recently published in Cancer Cell, Stratikopoulos et al. showed that BRD4 is important for the feedback activation of several RTKs, and that combined PI3K and BET inhibition blocks PI3K reactivation in a variety of cancer cells. Then, the authors carried out experiments to validate this combination in preclinical in vitro and in vivo models. They observed in several cancer cell types that the cytotoxicity of the combination of a PI3K inhibitor and a BET inhibitor at a fixed concentration was higher than that observed when the inhibitors were tested alone at the same concentrations. They also found a better antitumor activity when mice with breast tumors were treated with kinase and BET inhibitors together than when they were treated with each inhibitor alone at the same doses. The authors discussed that these findings provide the rationale for combining kinase and BET inhibitors to improve therapy in several human cancers (Stratikopoulos et al., 2015).

Patients with unresectable or metastatic cancers are difficult to cure and require the development of better pharmacological therapies. The first step to developing better therapies is to find good drug candidates or pharmacological strategies for testing. Stratikopoulos et al. find that combined PI3K and BET inhibition sustains PI3K inhibition in a variety of cancer cells, thereby providing the rationale for testing the anticancer potential of this combination. The next step to developing better treatments is to evaluate the new drugs using robust preclinical models; these models should predict whether the anticancer potential of the new drugs is high enough to deserve clinical evaluation. The experimental approach used by Stratikopoulos et al. does not reveal, however, whether or not the combination of PI3K and BET inhibitors deserves clinical testing. The main reason is that their approach was based on evaluating cytotoxic potency in cancer cells and tumor shrinkage in animal models, and these parameters are poor predictors of clinical efficacy. Despite their widespread use, these parameters do not reliably detect the type of drugs that cancer patients need.

Cancer patients do not need drugs or drug combinations that target their cancer cells at low concentrations if they also target their normal cells at similar concentrations. Cancer patients will probably not benefit from drugs that reduce tumor volumes in mice if they do not extend their lives. Cancer patients need drugs that improve the efficacy of the existing treatments. Establishing the best parameters to measure efficacy in vitro and in vivo is essential, and evidence suggests that selectivity (in vitro) and survival rate (in vivo) are the most reliable parameters to predict drug efficacy in cancer patients (Lopez-Lazaro, 2015c). In vitro, the new treatment should improve the selectivity of the existing drugs when tested in cancer cells versus nonmalignant cells from a variety of healthy tissues (Lopez-Lazaro, 2015a; Lopez-Lazaro, 2015b; Lopez-Lazaro, 2015c). The efficacy of a drug combination should be assessed by testing in cancer cells versus nonmalignant cells if it improves the selectivity of the standard treatment, and not by testing in cancer cells if its cytotoxicity is enhanced in relation to the cytotoxicity induced by each drug alone. It is important to realize that a drug combination that induces a strong cytotoxic synergism in cancer cells will not be clinically effective if it induces a stronger synergism in nonmalignant cells, or that a drug combination that induces synergism in cancer cells and antagonism in nonmalignant cells will not be clinically useful if its selectivity towards cancer cells is lower than that of the standard treatment (Lopez-Lazaro, 2015c). In vivo, the new drug or drug combination should improve the survival rate of the existing therapy when tested under equivalent experimental conditions (e.g., equitoxic doses) in animal models representative of the patients who would eventually receive the new treatment (Lopez-Lazaro, 2015c). Unfortunately, many drugs and drug combinations are tested in cancer patients after showing cytotoxic potency against cancer cells and tumor regression in mice. This preclinical validation approach may contribute to explain why our ability to translate preclinical cancer research to clinical success is remarkably low (Hutchinson and Kirk, 2011). A preclinical validation model based on assessing whether the drug candidates improve the selectivity and survival rate of the standard therapies would facilitate the development of better treatments, and would also prevent many cancer patients from receiving ineffective drugs (Lopez-Lazaro, 2015c).

In conclusion, Stratikopoulos et al. have discovered a pharmacological strategy that might improve the therapy of a variety of cancer types. However, they assessed the anticancer potential of their strategy using a preclinical validation approach that does not reliably predict drug efficacy in cancer patients. Testing if BET inhibitors improve the selectivity and survival rate of the kinase inhibitors used in oncology would help reveal whether or not kinase and BET inhibitors together can overcome resistance to therapy.

REFERENCES

Hutchinson, L. and Kirk, R. (2011). High drug attrition rates--where are we going wrong? Nat. Rev. Clin. Oncol. 8, 189-190.

Lopez-Lazaro, M. (2015a). A Simple and Reliable Approach for Assessing Anticancer Activity In Vitro. Curr. Med. Chem. 22, 1324-1334.

Lopez-Lazaro, M. (2015b). How many times should we screen a chemical library to discover an anticancer drug? Drug Discov. Today. 20, 167-169.

Lopez-Lazaro, M. (2015c). Two preclinical tests to evaluate anticancer activity and to help validate drug candidates for clinical trials. Oncoscience 2, 91-98.

Stratikopoulos, E.E., Dendy, M., Szabolcs, M., Khaykin, A.J., Lefebvre, C., Zhou, M.M., and Parsons, R. (2015). Kinase and BET Inhibitors Together Clamp Inhibition of PI3K Signaling and Overcome Resistance to Therapy. Cancer Cell. 27, 837-851.