Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms

Abstract

This study aims to characterize and classify serum surface-enhanced Raman spectroscopy (SERS) spectra between bladder cancer patients and normal volunteers by genetic algorithms (GAs) combined with linear discriminate analysis (LDA). Two group serum SERS spectra excited with nanoparticles are collected from healthy volunteers (n = 36) and bladder cancer patients (n = 55). Six diagnostic Raman bands in the regions of 481–486, 682–687, 1018–1034, 1313–1323, 1450–1459 and 1582–1587 cm−1 related to proteins, nucleic acids and lipids are picked out with the GAs and LDA. By the diagnostic models built with the identified six Raman bands, the improved diagnostic sensitivity of 90.9% and specificity of 100% were acquired for classifying bladder cancer patients from normal serum SERS spectra. The results are superior to the sensitivity of 74.6% and specificity of 97.2% obtained with principal component analysis by the same serum SERS spectra dataset. Receiver operating characteristic (ROC) curves further confirmed the efficiency of diagnostic algorithm based on GA-LDA technique. This exploratory work demonstrates that the serum SERS associated with GA-LDA technique has enormous potential to characterize and non-invasively detect bladder cancer through peripheral blood.

Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4–10 ng/mL

“…40 Glycogen content was observed to decrease in esophageal and bladder cancer blood samples, compared to that in the blood samples of healthy subjects. 29,41 There was also a relative intensity decrease in peak 1,208 cm −1 , indicating a reduction of tryptophan in blood, which is in agreement with a report on the Raman signal change in malignant gastric tissues. 42 The abnormal changes in the constitutes of PCa are in good agreement with biochemical analysis' results of blood serum detection.…”

“…38,39 On this basis, SERS has been extensively used to detect various cancers with a high accuracy in recent years. [27][28][29] In the present study, the SERS spectra of serum revealed significant differences between cancer patients and BPH patients, implying biomolecular component differences in blood. The Raman peak of 492 cm −1 is related to glycogen, while 1,445 cm −1 is related to CH 2 bending, collagen/lipids.…”

“…26 In recent years, SERS has been used to diagnose various cancers with a high accuracy, such as breast cancer, colorectal cancer and bladder cancer. [27][28][29] An investigation into diagnosing PCa in 2015 reported that by analyzing the Raman spectra of serum separated from a peripheral blood sample and applying SVM techniques, PCa could be diagnosed with an accuracy of up to 98.1%. 24 While this study offered extremely promising results, it focused on developing the methodology for using SERS in PCa diagnosis and thus did not study the method in a clinically relevant situation.…”

Biomedical optical spectroscopy for the early diagnosis of gastrointestinal neoplasms

“…120 A variety of studies have been conducted to evaluate the diagnostic performance of OS techniques in blood samples. Lualdi et al 121 found that a blood fluorescence emission peak around 615-635 nm significantly differed between 172 patients with CRC and 169 health donors, with an AUROC of 0.724.…”

Clinical instrumentation and applications of Raman spectroscopy

“…By combining the sensitivity of SERS with advanced machine learning genetic algorithms, the researchers were able to achieve 94% diagnostic accuracy in a cohort of 91 patients. 198 Zeng et al have likewise investigate SERS techniques for blood plasma analysis aimed at improved gastric cancer detection. 199 Samples from 65 patients were analyzed with polarized illumination of SERS particles and multivariate techniques.…”