Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of molecular biology"
DOI: 10.1016/j.jmb.2022.167569
Abstract: Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift… read more here.
Keywords: allosteric cancer; innovative allosteric; allosteric drugs; drivers innovative ... See more keywords
Genetic analysis of cancer drivers reveals cohesin and CTCF as suppressors of PD-L1
Sign Up to like & getrecommendations! Published in 2022 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2120540119
Abstract: Significance The PD-1/PD-L1 immunoinhibitory axis plays a key role in immune evasion of cancer cells, and therapies targeting PD-1/PD-L1 show high efficacy in certain cancer types. Understanding how cancer drivers regulate immune surveillance will enable… read more here.
Keywords: cohesin; immune evasion; biology; cancer drivers ... See more keywords
Dynamic cancer drivers: a causal approach for cancer driver discovery based on bio-pathological trajectories.
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in functional genomics"
DOI: 10.1093/bfgp/elac030
Abstract: The traditional way for discovering genes which drive cancer (namely cancer drivers) neglects the dynamic information of cancer development, even though it is well known that cancer progresses dynamically. To enhance cancer driver discovery, we… read more here.
Keywords: driver; cancer drivers; cancer driver; dynamic cancer ... See more keywords
Abstract 5333: Combining chemoproteomics with machine learning identifies functionally active covalent fragments for hard-to-drug cancer drivers
Sign Up to like & getrecommendations! Published in 2023 at "Cancer Research"
DOI: 10.1158/1538-7445.am2023-5333
Abstract: a) Many cancer drivers are considered “undruggable” and without targeted treatments because they lack binding sites for conventional small molecules. Here, we introduce The FRONTIER™ Platform applying machine learning (ML), chemoproteomics and covalent chemistry to… read more here.
Keywords: cancer; machine learning; covalent; cancer drivers ... See more keywords
Ranking cancer drivers via betweenness-based outlier detection and random walks
Sign Up to like & getrecommendations! Published in 2021 at "BMC Bioinformatics"
DOI: 10.1186/s12859-021-03989-w
Abstract: Background Recent cancer genomic studies have generated detailed molecular data on a large number of cancer patients. A key remaining problem in cancer genomics is the identification of driver genes. Results We propose BetweenNet, a… read more here.
Keywords: drivers via; cancer drivers; ranking cancer; random ... See more keywords
CRISPR and transposon in vivo screens for cancer drivers and therapeutic targets
Sign Up to like & getrecommendations! Published in 2020 at "Genome Biology"
DOI: 10.1186/s13059-020-02118-9
Abstract: Human cancers harbor substantial genetic, epigenetic, and transcriptional changes, only some of which drive oncogenesis at certain times during cancer evolution. Identifying the cancer-driver alterations amongst the vast swathes of “passenger” changes still remains a… read more here.
Keywords: crispr transposon; cancer drivers; vivo screens; screens cancer ... See more keywords