Characterization of wild-type and mutant p53 protein by Raman spectroscopy and multivariate methods Article uri icon

abstract

  • To improve the early and reliable detection of cancer novel methods for the identification of associated biomarkers can suppose a big advantage over most of the techniques nowadays used for diagnosis because these techniques generally have the disadvantages of being laborious, invasive, and dependent on the physician%27s experience. The cancer biomarker wild-type p53 protein is naturally present in the human body and activated when cellular damage is detected. Mutations in p53 are related to the presence of tumors. In this work, Raman spectra of wild-type and mutant p53 were obtained. The spectra were analyzed by multivariate methods. Principal component analysis and support vector machine algorithms showed that it is possible to discriminate between the wild and mutant types of this biomarker with an accuracy of 94%25. An estimation of the limit of the detection of the wild-type p53 protein by means of Raman spectroscopy was performed by partial least squares regression, reaching that it is possible to detect concentration as low as 0.946 μM without additional reagents. This proof-of-concept test shows that it is possible to detect and differentiate among types of p53 and represent the basis for an advanced study where a mechanism of signal amplification can be implemented. Raman spectroscopy in conjunction with multivariate mathematical techniques is projected as a complete tool capable of identifying biomarkers in a noninvasive, simple, and economical way, eliminating the subjective interpretation of the results, and therefore contributing to objective and more reliable diagnoses. © 2019 John Wiley %26 Sons, Ltd.
  • To improve the early and reliable detection of cancer novel methods for the identification of associated biomarkers can suppose a big advantage over most of the techniques nowadays used for diagnosis because these techniques generally have the disadvantages of being laborious, invasive, and dependent on the physician%27s experience. The cancer biomarker wild-type p53 protein is naturally present in the human body and activated when cellular damage is detected. Mutations in p53 are related to the presence of tumors. In this work, Raman spectra of wild-type and mutant p53 were obtained. The spectra were analyzed by multivariate methods. Principal component analysis and support vector machine algorithms showed that it is possible to discriminate between the wild and mutant types of this biomarker with an accuracy of 94%25. An estimation of the limit of the detection of the wild-type p53 protein by means of Raman spectroscopy was performed by partial least squares regression, reaching that it is possible to detect concentration as low as 0.946 μM without additional reagents. This proof-of-concept test shows that it is possible to detect and differentiate among types of p53 and represent the basis for an advanced study where a mechanism of signal amplification can be implemented. Raman spectroscopy in conjunction with multivariate mathematical techniques is projected as a complete tool capable of identifying biomarkers in a noninvasive, simple, and economical way, eliminating the subjective interpretation of the results, and therefore contributing to objective and more reliable diagnoses. © 2019 John Wiley & Sons, Ltd.
  • To improve the early and reliable detection of cancer novel methods for the identification of associated biomarkers can suppose a big advantage over most of the techniques nowadays used for diagnosis because these techniques generally have the disadvantages of being laborious, invasive, and dependent on the physician's experience. The cancer biomarker wild-type p53 protein is naturally present in the human body and activated when cellular damage is detected. Mutations in p53 are related to the presence of tumors. In this work, Raman spectra of wild-type and mutant p53 were obtained. The spectra were analyzed by multivariate methods. Principal component analysis and support vector machine algorithms showed that it is possible to discriminate between the wild and mutant types of this biomarker with an accuracy of 94%25. An estimation of the limit of the detection of the wild-type p53 protein by means of Raman spectroscopy was performed by partial least squares regression, reaching that it is possible to detect concentration as low as 0.946 μM without additional reagents. This proof-of-concept test shows that it is possible to detect and differentiate among types of p53 and represent the basis for an advanced study where a mechanism of signal amplification can be implemented. Raman spectroscopy in conjunction with multivariate mathematical techniques is projected as a complete tool capable of identifying biomarkers in a noninvasive, simple, and economical way, eliminating the subjective interpretation of the results, and therefore contributing to objective and more reliable diagnoses. © 2019 John Wiley %26 Sons, Ltd.

publication date

  • 2019-01-01