Drug development in the era of precision medicine

Dugger, Sarah A.; Platt, Adam; Goldstein, David B.

doi:10.1038/nrd.2017.226

Cited by 367 publications

(263 citation statements)

References 162 publications

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“…To address the question whether long term Her2/neu and CDK4/6 inhibition in advanced HER2positive breast cancer has a sustainable therapeutic effect, we employed the MMTV-neu202 Mul transgenic mouse bearing late-stage mammary tumor (volume > 500mm 3 ) and examined their response to a continuous anti-Her2/neu antibody (Ab) plus CDK4/6 inhibitor Palbociclib (Pal) treatment. Two weeks of Ab+Pal treatment produced pronounced effects, leading to tumor regression with an average volume reduction of 52.74% (Fig.…”

Section: Rapid Emergence Of Resistant Tumors In Vivo To Anti-her2/neumentioning

confidence: 99%

“…Precision medicine is a personalized disease treatment model that tailors the therapeutic regimens for individual patients by considering the genetic heterogeneity of disease 1,2 . Targeted cancer therapy exemplifies the concept of precision medicine through rationally-designed targeted treatment towards a tumor-specific dysregulated genetic event 3,4 . With superior clinical efficacy and less side effects, targeted cancer therapy has become one of the major pillars of modern cancer treatment 5,6 .…”

Section: Introductionmentioning

confidence: 99%

“…Anti-HER2/neu antibody (clone 7.16.4, BE0277), mouse IgG2a Isotype control (Catalog# BE0085), anti-CTLA 4 antibody (clone 9H10, BE0131), anti-PD-1 antibody (clone RMP1-14, BE0146), anti-Ly6G/Ly6C (Gr-1) antibody (clone RBC-8C5, BE0075), anti-CD3ε antibody (clone 145-2C11, BP0001) and polyclonal syrian hamster IgG (Catalog# BE0087) were purchased from BioXcell (West Lebanon, NH). Nulliparous female mice were enrolled for treatment when the spontaneous tumor reached a size of > 500 mm3 . Anti-HER2/neu antibody or the isotype IgG control was intraperitoneally administered at 10 mg/kg body weight in PBS twice weekly.…”

mentioning

confidence: 99%

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Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor resistant HER2-positive breast cancer

Wang

Guldner

Golomb

et al. 2019

Preprint

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Development of acquired resistance to targeted cancer therapy is one of the most significant clinical challenges. Acquiring resistance under drug selection pressure is a result of evolutionary adaptation to a complex and dynamic tumor microenvironment (TME). New therapy regimens combining CDK4/6inhibitor are under active investigation in clinical trials to treat HER2+ breast cancer patients. In parallel with clinical trial settings, in this study, we sought to prospectively model the tumor evolution in response to a targeted therapy regimen in vivo and identify a clinically actionable strategy to combat potential acquired resistance. Notably, despite a promising initial response, acquired resistance emerged rapidly to the anti-Her2/Neu antibody plus CDK4/6 inhibitor Palbociclib combination treatment. By leveraging high-throughput single-cell analyses of the evolving tumors over the course of treatments, we revealed a distinct immunosuppressive immature myeloid cell (IMC) population infiltrated in the resistant TME.Guided by single-cell transcriptome analysis, we demonstrated a combinatorial immunotherapy of IMCtargeting tyrosine kinase inhibitor cabozantinib and immune checkpoint blockades enhanced anti-tumor immunity, and overcame the resistance. Further, sequential combinatorial immunotherapy enabled a sustained control of the rapidly evolving CDK4/6 inhibitor-resistant tumors. Our study demonstrates a translational framework for treating rapidly evolving tumors through preclinical modeling and single-cell analyses. Our findings provide a rationale for an immediate clinical proposition of combinatorial immunotherapy for HER2+ breast cancer as a strategy to mitigate the emergence of resistance. 6 results at the single-cell transcriptome level indicated that CDK4/6 inhibitor treatment elicits antigen presentation and stimulate IFN signaling, supporting and extending previous observations 33 . Given that increased antigen presentation and IFN signaling, which suggested an elevated tumor immunogenicity in Ab+Pal resistant (APR) tumors, we next sought to combine immune checkpoint blockades (ICB, anti-CTLA4 and anti-PD-1 antibodies) to overcome or prevent the resistance to Ab+Pal treatment. However, the addition of ICB to the rebound APR tumors showed only modest effect (Fig. 1H, Ab+Pal+ICB), suggesting neither CTLA4 nor PD-1/L1 axis was the major mediator for the resistance. There were likely other factors contributing to the resistant phenotype. Single-cell RNA-sequencing reveals distinct immune milieu among different phenotypes and immature myeloid cells are enriched in resistant tumorsWe next investigated the TME factors that could potentially mediate the development of resistance.The observation that more CD45 + leukocytes in both APP and APR tumors compared to Ctrl (Supplemental Fig. 3) led us to focus on the immune compartment. CD45 + tumor infiltrated leukocytes (TILs) were isolated by magnetic-activated cell sorting (MACS) from single-cell suspensions of tumors and single-cell RNA sequencing was performed ( ...

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Section: Rapid Emergence Of Resistant Tumors In Vivo To Anti-her2/neumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor resistant HER2-positive breast cancer

Wang

Guldner

Golomb

et al. 2019

Preprint

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“…Drug discovery and development is the process of finding new pharmaceutical candidates and bringing them to market, and includes identifying new drug molecules, pre-clinical research, clinical trials, and the task of obtaining relevant regulatory approvals. 1,2 Recent estimates put the average cost of this research and development in the region of 10's of millions to billions USD. 3 Historically this R&D has focused on small organic molecule new chemical entities, but has now expanded to recent biotech drugs, such as, peptides, proteins, antibodies, and nucleic acids.…”

Section: Introductionmentioning

confidence: 99%

Branched and Dendritic Polymer Architectures: Functional Nanomaterials for Therapeutic Delivery

Cook

Perrier

2019

Adv Funct Materials

129

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Barriers to therapeutic transport in biological systems can prevent accumulation of drugs at the intended site, thus limiting the therapeutic effect against various diseases. Advances in synthetic chemistry techniques have recently increased the accessibility of complex polymer architectures for drug delivery systems, including branched polymer architectures. This article first outlines drug delivery concepts, and then defines and illustrates all forms of branched polymers including highly branched polymers, hyperbranched polymers, dendrimers, and branched–linear hybrid polymers. Many new types of branched and dendritic polymers continue to be reported; however, there is often confusion about how to accurately describe these complex polymer architectures, particularly in the interdisciplinary field of nanomedicine where not all researchers have in‐depth polymer chemistry backgrounds. In this context, the present review describes and compares different branched polymer architectures and their application in therapeutic delivery in a simple and easy‐to‐understand way, with the aim of appealing to a multidisciplinary audience.

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“…This problem can be solved as easily as solving Eqn. (1). The reason is that one only needs to know how to compute the inner product f (u) · f (v) of image vectors to solve the optimization problem.…”

Section: Kernel Ridge Regression (Krr)mentioning

confidence: 99%

A Survey and Systematic Assessment of Computational Methods for Drug Response Prediction

Chen

Zhang

2019

Preprint

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Drug response prediction arises from both basic and clinical research of personalized therapy, as well as drug discovery for cancer and other diseases. With gene expression profiles and other omics data being available for over 1000 cancer cell lines and tissues, different machine learning approaches have been applied to solve drug response prediction problems. These methods appear in a body of literature and have been evaluated on different datasets with only one or two accuracy metrics. We systematically assessed 17 representative methods for drug response prediction, which have been developed in the past five years, on four large public datasets in nine metrics. This study provides insights and lessons for future research into drug response prediction.

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Drug development in the era of precision medicine

Cited by 367 publications

References 162 publications

Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor resistant HER2-positive breast cancer

Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor resistant HER2-positive breast cancer

Branched and Dendritic Polymer Architectures: Functional Nanomaterials for Therapeutic Delivery

A Survey and Systematic Assessment of Computational Methods for Drug Response Prediction

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