Unlocking c-MET: A comprehensive journey into targeted therapies for breast cancer

Jabbarzadeh Kaboli, Parham; Chen, Hsiao-Fan; Babaeizad, Ali; Roustai Geraylow, Kiarash; Yamaguchi, Hirohito; Hung, Mien-Chie

doi:10.1016/j.canlet.2024.216780

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Preprint1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 164 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Fragment-based design and synthesis of coumarin-based thiazoles as dual c-MET/STAT-3 inhibitors for potential antitumor agents

Naguib,

Elsebaie,

Nafie

et al. 2024

Bioorganic Chemistry

View full text Add to dashboard Cite

Fragment-based design and synthesis of coumarin-based thiazoles as dual c-MET/STAT-3 inhibitors for potential antitumor agents

Naguib,

Elsebaie,

Nafie

et al. 2024

Bioorganic Chemistry

View full text Add to dashboard Cite

Comprehensive prediction and analysis of human protein essentiality based on a pre-trained protein large language model

Kang,

Fan,

Cui

et al. 2024

Preprint

View full text Add to dashboard Cite

Human essential genes and their protein products are indispensable for the viability and development of the individuals. Thus, it is quite important to decipher the essential proteins and up to now numerous computational methods have been developed for the above purpose. However, the current methods failed to comprehensively measure human protein essentiality at levels of humans, human cell lines, and mice orthologues. For doing so, here we developed Protein Importance Calculator (PIC), a sequence-based deep learning model, which was built by fine-tuning a pre-trained protein language model. As a result, PIC outperformed existing methods by increasing 5.13%-12.10% AUROC for predicting essential proteins at human cell-line level. In addition, it improved an average of 9.64% AUROC on 323 human cell lines compared to the only existing cell line-specific method, DeepCellEss. Moreover, we defined Protein Essential Score (PES) to quantify protein essentiality based on PIC and confirmed its power of measuring human protein essentiality and functional divergence across the above three levels. Finally, we successfully used PES to identify prognostic biomarkers of breast cancer and at the first time to quantify the essentiality of 617462 human microproteins.

show abstract

Unlocking c-MET: A comprehensive journey into targeted therapies for breast cancer

Cited by 2 publications

References 164 publications

Fragment-based design and synthesis of coumarin-based thiazoles as dual c-MET/STAT-3 inhibitors for potential antitumor agents

Fragment-based design and synthesis of coumarin-based thiazoles as dual c-MET/STAT-3 inhibitors for potential antitumor agents

Comprehensive prediction and analysis of human protein essentiality based on a pre-trained protein large language model

Contact Info

Product

Resources

About