Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

Development of a Framework and the Content for a Psychoeducational Internet-Delivered Intervention for Women after Treatment for Gynecological Cancer

The number of women treated for gynecological cancer is increasing. At the same time, the duration of in-patient hospitalization has decreased, and follow-up with its primary focus on early recognition of recurrence does not meet all patients' needs. One method of follow-up may be digital intervention. This study describes the development of a psychoeducational Internet-delivered intervention targeting women's psychosocial needs during the follow-up period after treatment for gynecological cancer. The project consisted of three phases following the UK Medical Research Council Framework guidelines for the development of complex interventions. Phase one identified the evidence in the field, phase two identified the relevant theoretical framework, and phase three included a two-year work process including focus group interviews and think aloud interviews with users. Through the steps of literature review, theoretical framework, and an iterative development process with users and other stakeholders, a six-week program was developed. The program included psychoeducational information, multimedia, exercises, and weekly telephone follow-up with a dedicated nurse. This Internet-delivered intervention can be a novel method for addressing the gap in the provision of follow-up for women after treatment for gynecological cancer

Tumor Targeting by αvβ3-Integrin-Specific Lipid Nanoparticles Occurs via Phagocyte Hitchhiking

Although the first nanomedicine was clinically approved more than two decades ago, nanoparticles’ (NP) in vivo behavior is complex and the immune system’s role in their application remains elusive. At present, only passive-targeting nanoformulations have been clinically approved, while more complicated active-targeting strategies typically fail to advance from the early clinical phase stage. This absence of clinical translation is, among others, due to the very limited understanding for in vivo targeting mechanisms. Dynamic in vivo phenomena such as NPs’ real-time targeting kinetics and phagocytes’ contribution to active NP targeting remain largely unexplored. To better understand in vivo targeting, monitoring NP accumulation and distribution at complementary levels of spatial and temporal resolution is imperative. Here, we integrate in vivo positron emission tomography/computed tomography imaging with intravital microscopy and flow cytometric analyses to study αvβ3-integrin-targeted cyclic arginine-glycine-aspartate decorated liposomes and oil-in-water nanoemulsions in tumor mouse models. We observed that ligand-mediated accumulation in cancerous lesions is multifaceted and identified “NP hitchhiking” with phagocytes to contribute considerably to this intricate process. We anticipate that this understanding can facilitate rational improvement of nanomedicine applications and that immune cell–NP interactions can be harnessed to develop clinically viable nanomedicine-based immunotherapies

Tumor Targeting by αvβ3-Integrin-Specific Lipid Nanoparticles Occurs via Phagocyte Hitchhiking.

Although the first nanomedicine was clinically approved more than two decades ago, nanoparticles' (NP) in vivo behavior is complex and the immune system's role in their application remains elusive. At present, only passive-targeting nanoformulations have been clinically approved, while more complicated active-targeting strategies typically fail to advance from the early clinical phase stage. This absence of clinical translation is, among others, due to the very limited understanding for in vivo targeting mechanisms. Dynamic in vivo phenomena such as NPs' real-time targeting kinetics and phagocytes' contribution to active NP targeting remain largely unexplored. To better understand in vivo targeting, monitoring NP accumulation and distribution at complementary levels of spatial and temporal resolution is imperative. Here, we integrate in vivo positron emission tomography/computed tomography imaging with intravital microscopy and flow cytometric analyses to study αvβ3-integrin-targeted cyclic arginine-glycine-aspartate decorated liposomes and oil-in-water nanoemulsions in tumor mouse models. We observed that ligand-mediated accumulation in cancerous lesions is multifaceted and identified "NP hitchhiking" with phagocytes to contribute considerably to this intricate process. We anticipate that this understanding can facilitate rational improvement of nanomedicine applications and that immune cell-NP interactions can be harnessed to develop clinically viable nanomedicine-based immunotherapies.This work was supported by the Central Norway Regional Health Authority ‘Helse Midt-Norge’ [AMS: PhD stipend (90062100) and travel grant (90284100); SH: researcher grant (90262100)], the National Institutes of Health (WJMM: R01 CA220234, TR: P30 CA00574), the American Heart Association (CPM: 16SDG31390007), the Norwegian Research Council (SH: 230788/F20), and the Tromsø Research Foundation and Trond Mohn Foundation (SH: 180 °N project).S