Evaluation of BH3 mimetics as a combination therapy with irradiation in head and neck squamous cell carcinoma.

INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) is a common cancer with a five-year survival rate around 60%, indicating a need for new treatments. BH3 mimetics are small molecules that inhibit anti-apoptotic Bcl-2 family proteins, resulting in apoptosis induction. METHODS: We performed a high-throughput screen using a Myogel matrix to identify the synergy between irradiation and the novel BH3 mimetics A-1155463, A-1331852, and navitoclax in 12 HNSCC cell lines, normal (NOF) and cancer-associated fibroblasts (CAF), and dysplastic keratinocytes (ODA). Next, we examined synergy in an apoptosis assay, followed by a clonogenic assay and a Myogel spheroid on selected HNSCC cell lines. Finally, we applied zebrafish larvae xenograft to validate the effects of navitoclax and A-1331852. RESULTS: All three BH3 mimetics exhibited a strong synergy with irradiation in eight HNSCC cell lines and ODAs, but not in NOFs and CAFs. A-1155463 and A-1331852 induced apoptosis and reduced proliferation, and together with irradiation, significantly increased apoptosis and arrested proliferation. A-1331852 and navitoclax significantly decreased the clonogenicity compared with the control, and combination treatment led to a decreased clonogenicity compared with monotherapy or irradiation. However, unlike navitoclax or A-1155463, only A-1331852 significantly reduced cancer cell invasion. Furthermore, in spheroid and zebrafish, irradiation appeared ineffective and failed to significantly increase the drug effect. In the zebrafish, A-1331852 and navitoclax significantly reduced the tumor area and metastasis. CONCLUSIONS: Our findings encourage the further preclinical investigation of BH3 mimetics, particularly A-1331852, as a single agent or combined with irradiation as a treatment for HNSCC.

Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling.

Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs' protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective combinations with the least toxicity and the best synergistic effect on blast cells. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML treatment.

Breeze 2.0: an interactive web-tool for visual analysis and comparison of drug response data.

Functional precision medicine (fPM) offers an exciting, simplified approach to finding the right applications for existing molecules and enhancing therapeutic potential. Integrative and robust tools ensuring high accuracy and reliability of the results are critical. In response to this need, we previously developed Breeze, a drug screening data analysis pipeline, designed to facilitate quality control, dose-response curve fitting, and data visualization in a user-friendly manner. Here, we describe the latest version of Breeze (release 2.0), which implements an array of advanced data exploration capabilities, providing users with comprehensive post-analysis and interactive visualization options that are essential for minimizing false positive/negative outcomes and ensuring accurate interpretation of drug sensitivity and resistance data. The Breeze 2.0 web-tool also enables integrative analysis and cross-comparison of user-uploaded data with publicly available drug response datasets. The updated version incorporates new drug quantification metrics, supports analysis of both multi-dose and single-dose drug screening data and introduces a redesigned, intuitive user interface. With these enhancements, Breeze 2.0 is anticipated to substantially broaden its potential applications in diverse domains of fPM.