The emerging discipline of proteogenomics arose from the combination of two molecular biology fields –mass spectrometry (MS)-based proteomics and next-generation sequencing (NGS) based genomics. The fusion of these two methods has enabled improvements in the annotation of newly sequenced non-model organisms, genome re-annotation, mainly in the correction of misannotated genes and the detection of pseudogenes, short open reading frames (sORFs) and other non-coding RNA genes, and the discovery of so-called ‘missing proteins’ –the undiscovered complementary proteins for annotated genes (Low et al., 2019).
Furthermore, by applying in silico methods –the computer-based experiments and simulations that combine biological data with expertise to model biological products and processes –additional genetic variants, post-transcriptional modifications, splice proteoforms and alternative frames of translation initiation and termination can be found and assessed at the peptide level (Koch et al., 2014).
Proteogenomics is only one facet that facilitates further development of precision medicine, which is especially prevalent in the oncology field, contributing to the advancement of onco-proteogenomics. Clinical genome sequencing has provided information for the clinicians in precision oncology, where genome sequencing data are used for diagnosis, management of patients according to their cancer sub-type, guidance in the selection of therapeutic agents and regimes and development of novel targeted therapies (Ang et al., 2019).
The implementation of proteomics data relating to the protein modification, signalling pathways and the microbiome of an individual in this process would allow for further stratification of patients and better tailoring of their treatment. Currently, most proteogenomics studies are focused on cancer research, with the potential to extend to other prevalent non-transmittable diseases, such as cardiovascular diseases or metabolic syndrome, and/or transmittable diseases, with the main focus being battling the antibiotic resistance development in multi-and pan-resistant bacteria (Blumenthal, Mansfieldand Pazdur, 2016).
egSEQ library preparation and targeted sequencing solutions, including specific panels with maximised coverage on oncology-related targets and full bioinformatics solutions with reporting offer a customisable solution for researchers and clinicians to realise the potential of personalised medicine for patients with rare diseases and cancer by helping to predict the future development of diseases, to make accurate diagnoses and to identify treatments.
Ang, M. Y. et al. (2019) ‘Proteogenomics: From next-generation sequencing (NGS) and mass spectrometry-based proteomics to precision medicine’, Clinica Chimica Acta. Elsevier, 498(August), pp. 38–46. doi: 10.1016/j.cca.2019.08.010.
Blumenthal, G. M., Mansfield, E. and Pazdur, R. (2016) ‘Next-Generation Sequencing in Oncology in the Era of Precision Medicine’, JAMA Oncology, 2(1), p. 13. doi: 10.1001/jamaoncol.2015.4503.
Koch, A. et al. (2014) ‘A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiencyof protein identification and enables the discovery of alternative translation start sites’, PROTEOMICS, 14(23–24), pp. 2688–2698. doi: 10.1002/pmic.201400180.
Low, T. Y. et al. (2019) ‘Connecting Proteomics to Next-Generation Sequencing: Proteogenomics and Its Current Applications in Biology’, Proteomics, 19(10), pp. 1–10. doi: 10.1002/pmic.2018002.
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