• Machine learning and data mining frameworks for predicting drug response in cancer: an overview and a novel in silico screening process based on association rule mining

      Vougas, K; Sakellaropoulos, T; Kotsinas, A; Foukas, GP; Ntargaras, A; Koinis, F; Polyzos, A; Myrianthopoulos, V; Zhou, H; Narang, S; et al. (2019)
      A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into effective drug-response models. Machine learning is both an expanding and an evolving computational field that holds promise to cover such needs. Here we provide a focused overview of: 1) the various supervised and unsupervised algorithms used specifically in drug response prediction applications, 2) the strategies employed to develop these algorithms into applicable models, 3) data resources that are fed into these frameworks and 4) pitfalls and challenges to maximize model performance. In this context we also describe a novel in silico screening process, based on Association Rule Mining, for identifying genes as candidate drivers of drug response and compare it with relevant data mining frameworks, for which we generated a web application freely available at: https://compbio.nyumc.org/drugs/. This pipeline explores with high efficiency large sample-spaces, while is able to detect low frequency events and evaluate statistical significance even in the multidimensional space, presenting the results in the form of easily interpretable rules. We conclude with future prospects and challenges of applying machine learning based drug response prediction in precision medicine.
    • The role of E3, E4 ubiquitin ligase (UBE4B) in human pathologies

      Antoniou, N; Lagopati, N; Balourdas, DI; Nikolaou, M; Papalampros, A; Vasileiou, PVS; Myrianthopoulos, V; Kotsinas, A; Shiloh, Y; Liontos, M; et al. (2019)
      The genome is exposed daily to many deleterious factors. Ubiquitination is a mechanism that regulates several crucial cellular functions, allowing cells to react upon various stimuli in order to preserve their homeostasis. Ubiquitin ligases act as specific regulators and actively participate among others in the DNA damage response (DDR) network. UBE4B is a newly identified member of E3 ubiquitin ligases that appears to be overexpressed in several human neoplasms. The aim of this review is to provide insights into the role of UBE4B ubiquitin ligase in DDR and its association with p53 expression, shedding light particularly on the molecular mechanisms of carcinogenesis.