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The Evolution of Anticancer Therapies
Published in David E. Thurston, Ilona Pysz, Chemistry and Pharmacology of Anticancer Drugs, 2021
Knowledge-based approaches have also been developed to consolidate known information about a particular drug in an attempt to anticipate previously unexplored unidentified targets for old drugs, unknown drug–drug similarities, and new biomarkers. By integrating a large amount of information, the certainty of prediction can be improved. Knowledge-based approaches can be broken down into four categories: bioinformatics (biological data mining), cheminformatics, pathway- or network-based approaches, and signature-based approaches. For bioinformatics, data can be accessed internally (in pharmaceutical companies) or from publicly sourced data bases such as the Biomolecular Interaction Network Database (BIND), the Human Protein Reference Database (HPRD), and the Human Proteome Organization (HUPO). Bioinformatics-based approaches have been used to discover new relationships between biomedical entities such as genes, biological pathways, and diseases. For example, this strategy has been used to study the potential Repurposing of FDA-approved tricyclic antidepressants to treat patients with small-cell lung cancer (SCLC) and other neuroendocrine tumors. In another example, ormeloxifene, a selective estrogen receptor modulator used as a nonsteroidal oral contraceptive and experimentally for dysfunctional uterine bleeding and advanced breast cancer, was recently shown to suppress prostate cancer through a knowledge-based study.
Recent developments in Phos-tag electrophoresis for the analysis of phosphoproteins in proteomics
Published in Expert Review of Proteomics, 2022
Techniques that improve the efficiency and accuracy of shotgun analysis, such as fluorescent-labeled [41] or stable isotope-labeled [42] shotgun analysis, nonlabeled shotgun analysis [43], and data-independent acquisition MS [44], and software necessary for differential protein expression analyses [45] are being developed since 2001. Shotgun analysis has been used to identify many proteins, including disease-related, stress-inducing, and complex-constituting proteins [43,46,47]. It has been mainly used as the essential technique in the large-scale comprehensive analysis of human proteome conducted by Kim et al. [48], Whilhelm et al. [49], Human Proteome Project Team of Human Proteome Organization [50], and Jiang et al. [51]. Furthermore, our laboratory obtained good results with the use of shotgun analysis for the identification of disease diagnostic and prognostic markers [52,53] and determination of the function of new protein complex components [54–56].
The role of proteomics in the multiplexed analysis of gene alterations in human cancer
Published in Expert Review of Proteomics, 2021
Niraj Babu, Mohd Younis Bhat, Arivusudar Everad John, Aditi Chatterjee
With the release of the human genome sequence in 2000, research community has realized the role of gene product proteins in regulating and controlling the phenotype. This led to the emergence of The Human Proteome Project (HPP) an international effort initiated by the Human Proteome Organization (HUPO). HPP directed its efforts to annotate all the proteins called chromosome-centric program (C-HPP) and to characterize role of these proteins in disease biology (B/D-HPP) with mass spectrometry as one of the main pillars of exploration. The aim of B/D-HPP is to create an in-depth repository of expressed protein isoforms/ post-translational modifications and apply this information to unravel molecular mechanisms that lead to cancer development and progression in addition to other disease conditions. The mandate of B/D-HPP is to bring transformation in biomedical research by making possible accurate and precise detection and quantification of all human proteins and their association with disease pathogenesis. This will further enable interrogation of genomics and proteomics data to improve clinical decision making and outcomes.
Working the literature harder: what can text mining and bibliometric analysis reveal?
Published in Expert Review of Proteomics, 2019
Yu Han, Sara A. Wennersten, Maggie P. Y. Lam
Aside from guiding individual research questions, text-mining and bibliometrics can uncover global trends in research activities and inform resource allocation, in so-called meta-research or science of science studies. Extensive bibliometric analyses of the biomedical literature have revealed among other observations the rising prominence of team science, a trend that is however accompanied by inequitable credit allocation [12]. Collaborative networks and research ‘hot topic’ nodes have also been analyzed among proteomics researchers in the American Society for Mass Spectrometry (ASMS) [13]. Analyzing NIH-funded studies, one bibliometrics study showed how both basic and applied research provides immense value to commercial patents [14], whereas another investigation ranked genes by total funding received and shed light on underfunded disease targets [5]. Finally, the Human Proteome Organization (HUPO) has adopted bibliometrics to identify highly published proteins across research fields, as a means to prioritize the development of proteomics assays for promising targets that are more likely to be adopted by domain researchers.