Toward Precision Medicine: How Far Is the Goal?

Ravegnini, Gloria; Angelini, Sabrina

doi:10.3390/ijms17020245

Cited by 2 publications

(2 citation statements)

References 22 publications

(17 reference statements)

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“…Although an increasing number of measures for cancer prevention and treatment are being implemented, the incidence and mortality of colorectal cancer remain high ( 3 ). The development of precision medicine in recent years is expected to revolutionize the diagnosis and treatment of colorectal cancer ( 4 ). Identifying molecular markers corresponding to tumors and achieving individualized treatment to maximize efficacy and minimize side effects is an important direction for future clinical tumor treatment ( 5 , 6 ).…”

Section: Introductionmentioning

confidence: 99%

Key genes in youth colorectal cancer based on data mining and verification by reverse transcription‑quantitative PCR

et al. 2021

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In recent years, among all patients with colorectal cancer, the proportion of young patients has been gradually increasing. However, the molecular mechanisms involved in colorectal cancer in the young are largely unknown. In the present study the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas datasets were integrated to elucidate the key gene biomarkers in these patients. The GSE41657 and GSE41258 datasets were downloaded from the GEO database. By screening for differentially expressed genes, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein-protein interaction analysis, hub gene screening and survival analysis, two key genes, CXCL8 and VEGFA, which were enriched in cancer pathways, were obtained. Reverse transcription-quantitative (RT-q)PCR was performed to verify the outcome obtained by bioinformatics analysis. In conclusion, the present study identified two key genes using bioinformatics analysis and RT-qPCR validation. These results indicated that the candidate genes may be involved in the progression of colorectal cancer in young people, and these two genes may act as ideal prognostic indicators or therapeutic targets for colorectal cancer in the youth.

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Section: Introductionmentioning

confidence: 99%

Key genes in youth colorectal cancer based on data mining and verification by reverse transcription‑quantitative PCR

et al. 2021

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“…Using this method, doctors will be able to evaluate more precisely which treatment strategies for specific disorders and diseases will work best on individual patients. Given this potential, there is great interest in providing scientific and practical approaches to improving treatment strategies for patients in terms of time, drug efficacy, and cost. − Along with experimental methods, − computational tools are being developed to address several aspects of precision medicine at different levels of complexity, on different scales, and for various human diseases − (e.g., genetic disease, infectious disease, and cancer). For example, machine learning techniques such as support vector machines, neural networks, and naive Bayes, have been used to leverage the available data to analyze human variants. − These algorithms help us connect the molecular details of genome variation for genetic diseases such as hyperammonemia, hypercholesterolemia, and hyperuricemia .…”

Section: Introductionmentioning

confidence: 99%

A Personalized Multiscale Modeling Framework for Dose Selection in Precision Medicine

Toroghi

Cluett

Mahadevan

2020

Ind. Eng. Chem. Res.

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Precision medicine (PM) refers to the use of available genomic information from an individual patient to select the most appropriate therapy for a disease. In this paper, we have developed a mechanistic multiscale modeling framework for the whole human body integrated with human hepatocyte genomic data. The model is validated by estimating the concentrations of several biomarkers in different amino acid inborn errors of metabolism (IEMs). To demonstrate the potential application of our multiscale modeling framework to precision medicine, we present a computational study of a specific disease. In this study, a genetic deficiency called Kelley–Seegmiller syndrome (KSS) is simulated for eight adult patients. Using our approach, we estimate the proper dosage of the drug for each subject needed to prevent hyperuricemia. These in silico results demonstrate that there is a significant difference in the optimal dose of the drug among individuals. In addition, the required dosages for the second and third days are different from those for the first day of treatment in each patient. Both results have important implications in terms of drug efficacy, drug side effects, and cost of the treatment. We also compare the pharmacological effect of available commercial drug tablets with these optimal values on disease progression. The results in this paper highlight the potential of the proposed modeling framework in opening up new opportunities in systems pharmacology and personalized medicine.

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Toward Precision Medicine: How Far Is the Goal?

Abstract: The accomplishment of the Human Genome Project, followed by the availability of high-throughput technologies, has led to an impressive change in biomedical research.[...]

Cited by 2 publications

References 22 publications

Key genes in youth colorectal cancer based on data mining and verification by reverse transcription‑quantitative PCR

Key genes in youth colorectal cancer based on data mining and verification by reverse transcription‑quantitative PCR

A Personalized Multiscale Modeling Framework for Dose Selection in Precision Medicine

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