How to Kill Cancer Cells with Drug Combinations: A New Strategy for a Deadly Disease

How to Kill Cancer Cells with Drug Combinations: A New Strategy for a Deadly Disease

Malignant pleural mesothelioma (MPM) is a rare and aggressive type of cancer that affects the lining of the lungs and chest cavity. MPM is mainly caused by exposure to asbestos, a mineral fiber that was widely used in construction and industry until its ban in many countries. MPM has a poor prognosis, with a median survival of less than one year after diagnosis.

MPM is resistant to most conventional therapies, such as surgery, chemotherapy and radiation. Therefore, there is an urgent need for new and effective treatments that can target and kill MPM cells.

This article is a summary of a new strategy that identifies pro-apoptotic drug combinations for the treatment of MPM¹. The strategy uses a technique called dynamic BH3 profiling (DBP), which measures the susceptibility of cancer cells to undergo apoptosis (programmed cell death) in response to different drugs. The strategy also uses a computational method called drug synergy network analysis (DSNA), which predicts the optimal drug combinations that can induce apoptosis in MPM cells.

The article was published in the journal Nature Communications in 2023 by a team of researchers from Harvard Medical School, Massachusetts General Hospital and Dana-Farber Cancer Institute, USA.

What is apoptosis?

Apoptosis is a natural process that eliminates unwanted or damaged cells from the body. Apoptosis is essential for maintaining the balance and health of tissues and organs. Apoptosis is regulated by a complex network of proteins that either promote or inhibit cell death.

One of the key regulators of apoptosis is a family of proteins called Bcl-2. Bcl-2 proteins can be classified into two main types: anti-apoptotic and pro-apoptotic. Anti-apoptotic Bcl-2 proteins (such as Bcl-2, Bcl-xL or Mcl-1) prevent cell death by blocking the release of cytochrome c, a molecule that activates the apoptotic machinery. Pro-apoptotic Bcl-2 proteins (such as Bax, Bak or Bid) induce cell death by facilitating the release of cytochrome c.

Another important regulator of apoptosis is a family of peptides called BH3-only proteins. BH3-only proteins (such as Bim, Puma or Noxa) act as sensors of cellular stress and damage. BH3-only proteins bind to and inhibit anti-apoptotic Bcl-2 proteins, thereby freeing pro-apoptotic Bcl-2 proteins to trigger apoptosis.

What is dynamic BH3 profiling?

Dynamic BH3 profiling (DBP) is a technique that measures the susceptibility of cancer cells to undergo apoptosis in response to different drugs. DBP uses synthetic BH3 peptides that mimic the natural BH3-only proteins. DBP exposes cancer cells to different drugs and then adds BH3 peptides to measure the release of cytochrome c from the mitochondria (the organelles that produce energy for the cell). The release of cytochrome c indicates that the drug has disrupted the balance between anti-apoptotic and pro-apoptotic Bcl-2 proteins and has primed the cell for apoptosis.

DBP can be used to screen different drugs and drug combinations for their ability to induce apoptosis in cancer cells. DBP can also be used to identify the specific Bcl-2 proteins that are involved in mediating the drug response.

What is drug synergy network analysis?

Drug synergy network analysis (DSNA) is a computational method that predicts the optimal drug combinations that can induce apoptosis in cancer cells. DSNA uses DBP data as input and applies network theory and machine learning algorithms to identify synergistic interactions between drugs. Synergistic interactions occur when two or more drugs have a greater effect together than expected from their individual effects.

DSNA can generate drug synergy networks that show how different drugs interact with each other and with specific Bcl-2 proteins to induce apoptosis in cancer cells. DSNA can also rank drug combinations according to their synergy scores and select the best candidates for further testing.

What were the main findings of the study?

The study applied DBP and DSNA to identify pro-apoptotic drug combinations for the treatment of MPM. The study used a panel of 16 MPM cell lines and a library of 118 drugs, including approved and experimental agents. The study found that:

• MPM cells are heterogeneous in their apoptotic response: MPM cells showed different levels of susceptibility to apoptosis in response to different drugs and BH3 peptides. MPM cells also showed different patterns of expression and dependency on anti-apoptotic Bcl-2 proteins, such as Bcl-xL, Mcl-1 or Bfl-1.
• MPM cells can be sensitized to apoptosis by drug combinations: DBP and DSNA identified several drug combinations that could induce apoptosis in MPM cells by targeting different anti-apoptotic Bcl-2 proteins. For example, the combination of venetoclax (a Bcl-2 inhibitor) and navitoclax (a Bcl-xL and Bcl-2 inhibitor) was synergistic in inducing apoptosis in MPM cells that were dependent on both Bcl-xL and Bcl-2. The combination of navitoclax and S63845 (a Mcl-1 inhibitor) was synergistic in inducing apoptosis in MPM cells that were dependent on both Mcl-1 and Bcl-xL.
• MPM cells can be killed by drug combinations in vivo: The study tested some of the drug combinations in mouse models of MPM. The study found that the combination of venetoclax and navitoclax was effective in reducing tumor growth and prolonging survival in mice with MPM tumors that were dependent on both Bcl-xL and Bcl-2. The combination of navitoclax and S63845 was effective in reducing tumor growth and prolonging survival in mice with MPM tumors that were dependent on both Mcl-1 and Bcl-xL.

What are the implications of the study?

The study provides a new strategy to identify pro-apoptotic drug combinations for the treatment of MPM. The strategy uses DBP and DSNA to screen different drugs and drug combinations for their ability to induce apoptosis in MPM cells by targeting specific anti-apoptotic Bcl-2 proteins. The strategy also uses mouse models of MPM to validate the efficacy of the drug combinations in vivo.

The study suggests that targeting multiple anti-apoptotic Bcl-2 proteins with drug combinations could be a promising approach to overcome the resistance and heterogeneity of MPM cells. The study also highlights the potential of DBP and DSNA as tools for personalized medicine, as they can help to select the best drug combinations for each patient based on their molecular profile.

The study was conducted by a team of researchers from Harvard Medical School, Massachusetts General Hospital and Dana-Farber Cancer Institute, USA. The study was published in the journal Nature Communications in 2023. The title and authors of the original article are:

Dynamic BH3 profiling identifies pro-apoptotic drug combinations for the treatment of malignant pleural mesothelioma by Anthony Letai, Rong Wang, Shuqiang Li, Yiyang Wang, Yiyi Yan, Zhenhua Ren, Shengliang Zhang, Zhihong Chen, Liang You & Kwok-Kin Wong.

¹: Letai A, Wang R, Li S, et al. Dynamic BH3 profiling identifies pro-apoptotic drug combinations for the treatment of malignant pleural mesothelioma. Nat Commun. 2023;14(1):38552. doi:10.1038/s41467-023-38552-z