Yingying Hu

University of Helsinki

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Yinyin Wang

Tsinghua University

Jing Tang

Huazhong University of Science and Technology

Ziaurrehman Tanoli

University of Helsinki

Hongbin Yang

Affiliated Hospital of Southwest Medical University

Jehad Aldahdooh

University of Helsinki

Markus Vähä‐Koskela

University of Helsinki

Daniel Bernabéu

Hospital Universitario La Paz

Andrés Redondo

Cancer Clinic

Jaime Feliú

Hospital Universitario La Paz

Javier Escudero

Hospital La Paz Institute for Health Research

Cooperative Institutions

Hospital Universitario La Paz

Hospital La Paz Institute for Health Research

Universidad Autónoma de Madrid

University of Helsinki

Instituto de Salud Carlos III

Centro de Investigación Biomédica en Red de Cáncer

Institute for Molecular Medicine Finland

Centre for Biomedical Network Research on Rare Diseases

Medical Research Network

Finland University

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Eribulin activity in soft tissue sarcoma monolayer and three-dimensional cell line models: could the combination with other drugs improve its antitumoral effect?

Cancer Cell International (2021)

Javier Escudero Victoria Heredia-Soto Yinyin Wang Patricia Ruíz Yingying Hu

Eribulin has shown antitumour activity in some soft tissue sarcomas (STSs), but it has only been approved for advanced liposarcoma (LPS).In this study, we evaluated the effect of eribulin on proliferation, migration and invasion capabilities in LPS, leiomyosarcoma (LMS) and fibrosarcoma (FS) models, using both monolayer (2D) and three-dimensional (3D) spheroid cell cultures. Additionally, we explored combinations of eribulin with other drugs commonly used in the treatment of STS with the aim of increasing its antitumour activity.Eribulin showed activity inhibiting proliferation, 2D and 3D migration and invasion in most of the cell line models. Furthermore, we provide data that suggest, for the first time, a synergistic effect with ifosfamide in all models, and with pazopanib in LMS as well as in myxoid and pleomorphic LPS.Our results support the effect of eribulin on LPS, LMS and FS cell line models. The combination of eribulin with ifosfamide or pazopanib has shown in vitro synergy, which warrants further clinical research.

Eribulin

Trabectedin

10.1186/s12935-021-02337-5

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Citations (6)

DrugRepo: a novel approach to repurposing drugs based on chemical and genomic features

Scientific Reports (2022)

Yinyin Wang Jehad Aldahdooh Yingying Hu Hongbin Yang Markus Vähä‐Koskela

Abstract The drug development process consumes 9–12 years and approximately one billion US dollars in costs. Due to the high finances and time costs required by the traditional drug discovery paradigm, repurposing old drugs to treat cancer and rare diseases is becoming popular. Computational approaches are mainly data-driven and involve a systematic analysis of different data types leading to the formulation of repurposing hypotheses. This study presents a novel scoring algorithm based on chemical and genomic data to repurpose drugs for 669 diseases from 22 groups, including various cancers, musculoskeletal, infections, cardiovascular, and skin diseases. The data types used to design the scoring algorithm are chemical structures, drug-target interactions (DTI), pathways, and disease-gene associations. The repurposed scoring algorithm is strengthened by integrating the most comprehensive manually curated datasets for each data type. At DrugRepo score ≥ 0.4, we repurposed 516 approved drugs across 545 diseases. Moreover, hundreds of novel predicted compounds can be matched with ongoing studies at clinical trials. Our analysis is supported by a web tool available at: http://drugrepo.org/ .

Drug repositioning

Repurposing

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Drug Development

10.1038/s41598-022-24980-2

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Citations (19)

DrugRepo: A novel approach to repurpose a huge collection of compounds based on chemical and genomic features

bioRxiv (Cold Spring Harbor Laboratory) (2022)

Yinyin Wang Jehad Aldahdooh Yingying Hu Hongbin Yang Markus Vähä‐Koskela

ABSTRACT The drug development process consumes 9-12 years and approximately one billion US dollars in terms of costs. Due to high finances and time costs required by the traditional drug discovery paradigm, repurposing the old drugs to treat cancer and rare diseases is becoming popular. Computational approaches are mainly data-driven and involve a systematic analysis of different data types leading to the formulation of repurposing hypotheses. This study presents a novel scoring algorithm based on chemical and genomic data types to repurpose vast collection of compounds for 674 cancer types and other diseases. The data types used to design the scoring algorithm are chemical structures, drug-target interactions (DTI), pathways, and disease-gene associations. The repurpose scoring algorithm is strengthened by integrating the most comprehensive manually curated datasets for each data type. More than 100 of our repurposed compounds can be matched with ongoing studies at clinical trials ( https://clinicaltrials.gov/ ). Our analysis is supported by a web tool available at: http://drugrepo.org/ .

Drug repositioning

Repurposing

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10.1101/2022.04.21.488995

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Citations (1)