Surface-enhanced Raman spectroscopy of urine for prostate cancer detection: a preliminary study

Mistro, Greta Del; Cervo, Silvia; Mansutti, Elena; Spizzo, Riccardo; Colombatti, Alfonso; Belmonte, Pietro; Zucconelli, Renzo; Steffan, Agostino; Sergo, Valter; Bonifacio, Alois

doi:10.1007/s00216-015-8610-9

Cited by 92 publications

(61 citation statements)

References 13 publications

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“…To extract such meaningful information and use it for diagnostic purposes, we used multivariate statistical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA) [23,24], developing a predictive model and estimating its performance with cross-validation. A similar approach combining SERS of a biofluid (i.e., urine) and PCA-LDA has been recently reported by our group as a promising approach for the diagnosis of prostate cancer [25].…”

Section: Introductionmentioning

confidence: 97%

SERS analysis of serum for detection of early and locally advanced breast cancer

et al. 2015

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In this contribution, we investigated whether surface-enhanced Raman scattering (SERS) of serum can be a candidate method for detecting "luminal A" breast cancer (BC) at different stages. We selected three groups of participants aged over 50 years: 20 healthy women, 20 women with early localized small BC, and 20 women affected by BC with lymph node involvement. SERS revealed clear spectral differences between these three groups. A predictive model using principal component analysis (PCA) and linear discriminant analysis (LDA) was developed based on spectral data, and its performance was estimated with cross-validation. PCA-LDA of SERS spectra could distinguish healthy from BC subjects (sensitivity, 92 %; specificity, 85 %), as well as subjects with BC at different stages, with a promising diagnostic performance (sensitivity and specificity, ≥80 %; overall accuracy, 84 %). Our data suggest that SERS spectroscopy of serum, combined with multivariate data analysis, represents a minimally invasive, easy to use, and fast approach to discriminate healthy from BC subjects and even to distinguish BC at different clinical stages.

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Section: Introductionmentioning

confidence: 97%

SERS analysis of serum for detection of early and locally advanced breast cancer

et al. 2015

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“…On the contrary, the serum spectra detection adopted in this study need no more than a wee bit of blood sampled from patients when taking routine body examination. For urine Raman spectra detection, 45 a pilot trial for PCa diagnosis seemed to be much more invasive and safer than using serum; however, its accuracy and specificity were inferior to serum detection. This study shows a high diagnostic accuracy of serum SERS detection for PCa, and the accuracy is believed to be high enough to take the place of biopsy in PCa diagnosis to some extent, thus lessening much pain and suffering for patients.…”

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confidence: 99%

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

Chen

Rong

Shao

et al. 2017

IJN

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The surface-enhanced Raman spectroscopy (SERS) of blood serum was investigated to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in males with a prostate-specific antigen level of 4–10 ng/mL, so as to reduce unnecessary biopsies. A total of 240 SERS spectra from blood serum were acquired from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, were used to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa. Similarly, this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%. The results suggest that analyzing blood serum using SERS combined with PCA–LDA diagnostic algorithms is a promising clinical tool for PCa diagnosis and assessment.

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“…LDA was a well-known method which found a linear transformation such that feature clusters were most seperable after the transformation [29]. The PCA combined with LDA were employed to classify and diagnose the different disease successfully based on the Raman spectral features [18, 23, 26, 32]. Rekha et al [21] used PCA-LDA to yield a diagnostic sensitivity of 91.2% and a specificity of 96.7% in the classification of normal from oral malignant group.…”

Section: Discussionmentioning

confidence: 99%

Surface-enhanced Raman spectroscopy of blood serum based on gold nanoparticles for the diagnosis of the oral squamous cell carcinoma

et al. 2017

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BackgroundOral squamous cell carcinoma (OSCC) is becoming more common across the globe. The prognosis of OSCC is largely dependent on the early detection. But the routine oral cavity examination may delay the diagnosis because the early oral malignant lesions may be clinically indistinguishable from benign or inflammatory diseases. In this study, the new diagnostic method is developed by using the surface enhanced Raman spectroscopy (SERS) to detect the serum samples from the cancer patients.MethodThe blood serum samples were collected from the OSCC patients, MEC patients and the volunteers without OSCC or MEC. Gold nanoparticles(NPs) were then mixed in the serum samples to obtain the high quality SERS spectra. There were totally 135 spectra of OSCC, 90 spectra of mucoepidermoid carcinoma (MEC) and 145 spectra of normal control group, which were captured by SERS successfully. Compared with the normal control group, the Raman spectral differences exhibited in the spectra of OSCC and MEC groups, which were assigned to the nucleic acids, proteins and lipids. Based on these spectral differences and features, the algorithms of principal component analysis(PCA) and linear discriminant analysis (LDA) were employed to analyze and classify the Raman spectra of different groups.ResultsCompared with the normal groups, the major increased peaks in the OSCC and MEC groups were assigned to the molecular structures of the nucleic acids and proteins. And these different major peaks between the OSCC and MEC groups were assigned to the special molecular structures of the carotenoids and lipids. The PCA-LDA results demonstrated that OSCC could be discriminated successfully from the normal control groups with a sensitivity of 80.7% and a specificity of 84.1%. The process of the cross validation proved the results analyzed by PCA-LDA were reliable.ConclusionThe gold NPs were appropriate substances to capture the high-quality SERS spectra of the OSCC, MEC and normal serum samples. The results of this study confirm that SERS combined PCA-LDA had a giant capability to detect and diagnosis OSCC through the serum sample successfully.

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Surface-enhanced Raman spectroscopy of urine for prostate cancer detection: a preliminary study

Cited by 92 publications

References 13 publications

SERS analysis of serum for detection of early and locally advanced breast cancer

SERS analysis of serum for detection of early and locally advanced breast cancer

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

Surface-enhanced Raman spectroscopy of blood serum based on gold nanoparticles for the diagnosis of the oral squamous cell carcinoma

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Surface-enhanced Raman spectroscopy of urine for prostate cancer detection: a preliminary study

Cited by 92 publications

References 13 publications

SERS analysis of serum for detection of early and locally advanced breast cancer

SERS analysis of serum for detection of early and locally advanced breast cancer

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

Surface-enhanced Raman spectroscopy of blood serum based on gold nanoparticles for the diagnosis of the oral squamous cell carcinoma

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