TY - JOUR
T1 - Monitoring of chemotherapy leukemia treatment using Raman spectroscopy and principal component analysis
AU - González-Solís, José Luis
AU - Martínez-Espinosa, Juan Carlos
AU - Salgado-Román, Juan Manuel
AU - Palomares-Anda, Pascual
N1 - Funding Information:
Acknowledgments The authors wish to thank CONACYT for financial support under grant number 45488 and Research Network Soft Condensed Matter. Also, we are thankful to Q. F. B. Olga Leticia Brizuela Gamio for preparation of the serum samples.
PY - 2014/5
Y1 - 2014/5
N2 - In this research, we used the Raman spectroscopy to distinguish between normal and leukemia blood serum and identify the different types of leukemia based on serum biochemistry. In addition, monitoring of patients under chemotherapy leukemia treatment (CHLT) was studied. Blood samples were obtained from seven patients who were clinically diagnosed with three leukemia types and 21 healthy volunteers. In addition, other five leukemia patients were monitored during the CHLT, two patients were declared healthy, one patient suspended it; the health of the other two patients worsened, and no improvement was observed along CHLT. The serum samples were put under an Olympus microscope integrated to the Raman system, and several points were chosen for the Raman measurement. The Horiba Jobin Yvon LabRAM HR800 Raman system is equipped with a liquid nitrogen-cooled detector and a laser of 830 nm with a power irradiation of 17 mW. It is shown that the serum samples from patient with leukemia and from the control group can be discriminated when multivariate statistical methods of principal component analysis (PCA) and linear discriminant analysis (LDA) are applied to their Raman spectra obtaining two large clusters corresponding to the control and leukemia serum samples and three clusters inside the leukemia group associated with the three leukemia types. The major differences between leukemia and control spectra were at 1,338 (Trp, α-helix, phospholipids), 1,447 (lipids), 1,523 (β-carotene), 1,556 (Trp), 1,587 (protein, Tyr), 1,603 (Tyr, Phe), and 1,654 (proteins, amide I, α-helix, phospholipids) cm-1, where these peaks were less intense in the leukemia spectrum. Minor differences occurred at 661 (glutathione), 890 (glutathione), 973 (glucosamine), 1,126 (protein, phospholipid C-C str), 1,160 (β-carotene), 1,174 (Trp, Phe), 1,208 (Trp), 1,246 (amide III), 1,380 (glucosamine), and 1,404 (glutathione) cm-1. Leukemia spectrum showed a peak at 917 cm -1 associated with glutathione, but it was absent in the control spectrum. The results suggest that the Raman spectroscopy and PCA could be a technique with a strong potential of support for current techniques to detect and identify the different leukemia types by using a serum sample. Nevertheless, with the construction of a data library integrated with a large number of leukemia and control Raman spectra obtained from a wide range of healthy and leukemic population, the Raman-PCA technique could be converted into a new technique for minimally invasive real-time diagnosis of leukemia from serum samples. In addition, complementary results suggest that using these techniques is possible to monitor CHLT.
AB - In this research, we used the Raman spectroscopy to distinguish between normal and leukemia blood serum and identify the different types of leukemia based on serum biochemistry. In addition, monitoring of patients under chemotherapy leukemia treatment (CHLT) was studied. Blood samples were obtained from seven patients who were clinically diagnosed with three leukemia types and 21 healthy volunteers. In addition, other five leukemia patients were monitored during the CHLT, two patients were declared healthy, one patient suspended it; the health of the other two patients worsened, and no improvement was observed along CHLT. The serum samples were put under an Olympus microscope integrated to the Raman system, and several points were chosen for the Raman measurement. The Horiba Jobin Yvon LabRAM HR800 Raman system is equipped with a liquid nitrogen-cooled detector and a laser of 830 nm with a power irradiation of 17 mW. It is shown that the serum samples from patient with leukemia and from the control group can be discriminated when multivariate statistical methods of principal component analysis (PCA) and linear discriminant analysis (LDA) are applied to their Raman spectra obtaining two large clusters corresponding to the control and leukemia serum samples and three clusters inside the leukemia group associated with the three leukemia types. The major differences between leukemia and control spectra were at 1,338 (Trp, α-helix, phospholipids), 1,447 (lipids), 1,523 (β-carotene), 1,556 (Trp), 1,587 (protein, Tyr), 1,603 (Tyr, Phe), and 1,654 (proteins, amide I, α-helix, phospholipids) cm-1, where these peaks were less intense in the leukemia spectrum. Minor differences occurred at 661 (glutathione), 890 (glutathione), 973 (glucosamine), 1,126 (protein, phospholipid C-C str), 1,160 (β-carotene), 1,174 (Trp, Phe), 1,208 (Trp), 1,246 (amide III), 1,380 (glucosamine), and 1,404 (glutathione) cm-1. Leukemia spectrum showed a peak at 917 cm -1 associated with glutathione, but it was absent in the control spectrum. The results suggest that the Raman spectroscopy and PCA could be a technique with a strong potential of support for current techniques to detect and identify the different leukemia types by using a serum sample. Nevertheless, with the construction of a data library integrated with a large number of leukemia and control Raman spectra obtained from a wide range of healthy and leukemic population, the Raman-PCA technique could be converted into a new technique for minimally invasive real-time diagnosis of leukemia from serum samples. In addition, complementary results suggest that using these techniques is possible to monitor CHLT.
KW - Chemotherapy leukemia treatment
KW - Leukemia
KW - Principal component analysis
KW - Raman spectroscopy
KW - Serum
UR - http://www.scopus.com/inward/record.url?scp=84902815499&partnerID=8YFLogxK
U2 - 10.1007/s10103-013-1515-y
DO - 10.1007/s10103-013-1515-y
M3 - Artículo
SN - 0268-8921
VL - 29
SP - 1241
EP - 1249
JO - Lasers in Medical Science
JF - Lasers in Medical Science
IS - 3
ER -