Raman based hepatocellular carcinoma biomarker detection

M. A. Santiago-Cordoba; P. R. Romano; A. MacKay; M. C. Demirel

doi:10.1109/IEMBS.2011.6090620

Raman based hepatocellular carcinoma biomarker detection

M. A. Santiago-Cordoba
, P. R. Romano
, A. MacKay
, M. C. Demirel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

Highly sensitive and selective biomarker detection is required for early detection of hepatocellular carcinoma (HCC). Disease progression has been shown to correlate with specific fucosylation of a validated HCC serum glycoprotein biomarker, alpha-fetoprotein (AFP) Carbohydrate binding proteins, such as lectins, can be used as diagnostic indicators for monitoring glycosylation changes during disease progression in hepatitis B virus (HBV) or hepatitis C virus (HCV) infected patients. We prepared surface-enhanced Raman spectroscopy (SERS) substrates, which provide controllable, well-organized nanoparticles on the surface, for the analysis of a fucose binding lectin AAL. The SERS based assay provides fast (10 s), and reproducible (5% variation) detection.

Original language	English (US)
Title of host publication	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages	3672-3675
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2011.6090620
State	Published - 2011
Event	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States Duration: Aug 30 2011 → Sep 3 2011

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Other

Other	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/Territory	United States
City	Boston, MA
Period	8/30/11 → 9/3/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/IEMBS.2011.6090620

Cite this

Santiago-Cordoba, M. A., Romano, P. R., MacKay, A., & Demirel, M. C. (2011). Raman based hepatocellular carcinoma biomarker detection. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 3672-3675). Article 6090620 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6090620

@inproceedings{1d418db497714e429d07610af4e6661e,

title = "Raman based hepatocellular carcinoma biomarker detection",

abstract = "Highly sensitive and selective biomarker detection is required for early detection of hepatocellular carcinoma (HCC). Disease progression has been shown to correlate with specific fucosylation of a validated HCC serum glycoprotein biomarker, alpha-fetoprotein (AFP) Carbohydrate binding proteins, such as lectins, can be used as diagnostic indicators for monitoring glycosylation changes during disease progression in hepatitis B virus (HBV) or hepatitis C virus (HCV) infected patients. We prepared surface-enhanced Raman spectroscopy (SERS) substrates, which provide controllable, well-organized nanoparticles on the surface, for the analysis of a fucose binding lectin AAL. The SERS based assay provides fast (10 s), and reproducible (5\% variation) detection.",

author = "Santiago-Cordoba, \{M. A.\} and Romano, \{P. R.\} and A. MacKay and Demirel, \{M. C.\}",

year = "2011",

doi = "10.1109/IEMBS.2011.6090620",

language = "English (US)",

isbn = "9781424441211",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

pages = "3672--3675",

booktitle = "33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011",

note = "33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 ; Conference date: 30-08-2011 Through 03-09-2011",

}

Santiago-Cordoba, MA, Romano, PR, MacKay, A & Demirel, MC 2011, Raman based hepatocellular carcinoma biomarker detection. in 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011., 6090620, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 3672-3675, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA, United States, 8/30/11. https://doi.org/10.1109/IEMBS.2011.6090620

Raman based hepatocellular carcinoma biomarker detection. / Santiago-Cordoba, M. A.; Romano, P. R.; MacKay, A. et al.
33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 3672-3675 6090620 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Raman based hepatocellular carcinoma biomarker detection

AU - Santiago-Cordoba, M. A.

AU - Romano, P. R.

AU - MacKay, A.

AU - Demirel, M. C.

PY - 2011

Y1 - 2011

N2 - Highly sensitive and selective biomarker detection is required for early detection of hepatocellular carcinoma (HCC). Disease progression has been shown to correlate with specific fucosylation of a validated HCC serum glycoprotein biomarker, alpha-fetoprotein (AFP) Carbohydrate binding proteins, such as lectins, can be used as diagnostic indicators for monitoring glycosylation changes during disease progression in hepatitis B virus (HBV) or hepatitis C virus (HCV) infected patients. We prepared surface-enhanced Raman spectroscopy (SERS) substrates, which provide controllable, well-organized nanoparticles on the surface, for the analysis of a fucose binding lectin AAL. The SERS based assay provides fast (10 s), and reproducible (5% variation) detection.

AB - Highly sensitive and selective biomarker detection is required for early detection of hepatocellular carcinoma (HCC). Disease progression has been shown to correlate with specific fucosylation of a validated HCC serum glycoprotein biomarker, alpha-fetoprotein (AFP) Carbohydrate binding proteins, such as lectins, can be used as diagnostic indicators for monitoring glycosylation changes during disease progression in hepatitis B virus (HBV) or hepatitis C virus (HCV) infected patients. We prepared surface-enhanced Raman spectroscopy (SERS) substrates, which provide controllable, well-organized nanoparticles on the surface, for the analysis of a fucose binding lectin AAL. The SERS based assay provides fast (10 s), and reproducible (5% variation) detection.

UR - https://www.scopus.com/pages/publications/84863577508

UR - https://www.scopus.com/pages/publications/84863577508#tab=citedBy

U2 - 10.1109/IEMBS.2011.6090620

DO - 10.1109/IEMBS.2011.6090620

M3 - Conference contribution

C2 - 22255136

AN - SCOPUS:84863577508

SN - 9781424441211

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 3672

EP - 3675

BT - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011

T2 - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011

Y2 - 30 August 2011 through 3 September 2011

ER -

Santiago-Cordoba MA, Romano PR, MacKay A, Demirel MC. Raman based hepatocellular carcinoma biomarker detection. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. 2011. p. 3672-3675. 6090620. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/IEMBS.2011.6090620

Raman based hepatocellular carcinoma biomarker detection

Abstract

Publication series

Other

UN SDGs

All Science Journal Classification (ASJC) codes

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