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Comparison of hair medulla from esophageal cancer patients and healthy persons using synchrotron radiation infrared microspectroscopy
Infrared Physics and Technology 105 (2020) 103201
Contents lists available at ScienceDirect
Infrared Physics & Technology journal homepage: www.elsevier.com/locate/infrared
Comparison of hair medulla from esophageal cancer patients and healthy persons using synchrotron radiation infrared microspectroscopy Qipeng Wua,1, Chao Lib,c,1, Zeming Qic, Ling Zonga, Chuansheng Huc, Jiarong Lib, Xin Wanga,
T ⁎
a
School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui 230032, China The Second Affiliated Hospital, Anhui Medical University, Hefei, Anhui 230601, China c National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui 230029, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Esophageal cancer Hair medulla SR-IR microspectroscopy IR spectra
This work aimed to investigate the feasibility of distinguishing esophageal cancer patients from healthy persons by IR spectra of hair medulla. SR-IR microspectroscopy was used to compare the differences in hair medulla from esophageal cancer patients and healthy persons. The results demonstrated that esophageal cancer might cause significant change of proteins content/structure in hair medulla. Moreover, combined with discriminant analysis, IR spectra of hair medulla could distinguish between esophageal cancer patients and healthy persons with the sensitivity 89.74%, the specificity 87.50%, the positive predictive value 89.74% and the accuracy 88.73%. Taken together, the results indicated that IR spectra of hair medulla might be helpful for early esophageal cancer diagnosis.
1. Introduction Esophageal cancer is a malignant tumor occuring in esophageal epithelium, and it is a serious threat to global health. For example, about 450,000 people were diagnosed with esophageal cancer while about 400,000 people died of esophageal cancer worldwide in 2012 [1]. Since the early symptoms of esophageal cancer were not obvious, most patients were diagnosed at moderate/advanced stage and lost the optimal time for surgery [2,3]. Therefore, early diagnosis of esophageal cancer is very important. At present, the main diagnostic methods of esophageal cancer include gastroscopy and biopsy, X-ray barium meal examination, chest CT, esophageal exfoliative cytology, etc. Gastroscopy and biopsy are preferred among these methods [4]. However, gastroscopy and biopsy have some limitations as follows [5]: 1. Severe cardiovascular and cerebrovascular disease patients cannot tolerate. 2. Gastroscopy cannot pass through excessively narrow esophagus. 3. The results of gastroscopy and biopsy may be influenced by operators’ experience. Hence it is very urgent to develop new methods for diagnosing esophageal cancer. Since FTIR spectroscopy has the ability of investigating complex tissues’ and cells’ structure and composition [6], it has been applied to cancer research broadly [7,8]. FTIR spectroscopy was also used to
investigate esophageal cancer, for example: Wang et al. compared esophageal cancer tissues’ and normal tissues’ IR spectra, and they found that the differences existed in the regions of proteins, nucleic acids and sugars [9,10]. Maziak et al. compared esophageal cancer tissues’ and normal tissues’ IR spectra, and they found that the nucleito-cytoplasm ratio and the relative DNA content increased while the relative RNA content decreased in malignant tissues [11]. These studies show that FTIR spectroscopy is a powerful tool for distinguishing esophageal cancer tissues from normal tissues. However, the samples were not easy to get since they came from resected specimen. The hair consists of medulla (about 10 μm width), cortex (about 40–80 μm width) and cuticle (about 5 μm width) [12], which can reflect serious diseases of human body [13,14]. FTIR spectroscopy was also used to investigate hair of cancer patients [15]. However, it is impossible to obtain IR spectra of hairs’ three parts spectrately due to the limitation of conventional source brightness. Fortunately, synchrotron radiation (SR) source has advantages of high brightness etc. which enhances spatial resolution of FTIR microspectroscopy largely [16]. SR-IR microspectroscopy can gain IR spectra of hair’s medulla, cortex and cuticle accurately [12]. We also used SR-IR microspectroscopy to compare hair from gastric cancer patients and healthy persons [17]. Compared to surgical and endoscopic samples, hair samples are easier to obtain and non-invasive. The study of hair by SR-IR
Abbreviations: FTIR, Fourier transform infrared; IR, infrared; SR, synchrotron radiation; PCA, principal component analysis ⁎ Corresponding author. E-mail address: [email protected] (X. Wang). 1 Both contributed equally to this work. https://doi.org/10.1016/j.infrared.2020.103201 Received 19 June 2019; Received in revised form 16 December 2019; Accepted 15 January 2020 Available online 17 January 2020 1350-4495/ © 2020 Elsevier B.V. All rights reserved.
Infrared Physics and Technology 105 (2020) 103201
Q. Wu, et al.
microspectroscopy will be helpful to explore a new method for detecting esophageal cancer non-invasively and rapidly. In this study, we explored the feasibility of differentiating esophageal cancer patients from healthy persons by IR spectra of hair medulla. 2. Materials and methods 2.1. Materials Biomedical Ethics Committee of Anhui Medical University approved this study (Ref. No. 20160222), and all participants agreed to provide hair. Hair samples were collected from 39 preoperative esophageal cancer patients who did not have chemotherapy/radiotherapy. These patients (including 24 males and 15 females) were from The Second Affiliated Hospital of Anhui Medical University, and they were confirmed as esophageal squamous cell cancer by postoperative pathological diagnosis. Hair samples from 32 healthy persons were contributed by healthy volunteers (including 19 males and 13 females). There was no significant age difference between esophageal cancer patients and healthy persons.
Fig. 1. Average IR spectra of hair medulla from esophageal cancer patients and healthy persons.
cancer patients while it was 3070.97 ± 3.84 for healthy persons (P < 0.05), indicating that the form and degree of hydrogen bonding in hair medulla changed after esophageal cancer occurred [23].
2.2. Sample preparation Hair samples were cut at 1 cm length from scalp, and then they were sponged with distilled water and 95% alcohol respectively and vacuumdried. The samples were embedded in OCT, frozen to −25 °C and then sliced with 5 μm thickness by a freezing microtome. The slices were placed onto 1 mm thick BaF2 windows and stored in a vacuum dryer before examination.
3.2. Peak-area ratios In order to distinguish esophageal cancer patients’ hair medulla from healthy persons’ hair medulla, we measured the area of seven peaks (Table 1) and then calculated the values of A3286/A1657, A1657/A3077, A2925/A1467, A1548/A1467, A1548/A1243 and A1467/A1243 (Table 2). A3286/A1657: It may describe the change of proteins content/ structure. The average value of A3286/A1657 was 2.37 for esophageal cancer patients while it was 2.04 for healthy persons, moreover, P value was less than 0.05, indicating A3286/A1657 was significantly different between esophageal cancer patients and healthy persons [24]. A1657/A3077: It may also describe the change of proteins content/ structure. The average value of A1657/A3077 was 30.72 for esophageal cancer patients while it was 36.60 for healthy persons, moreover, P value was less than 0.05, indicating A1657/A3077 was significantly different between esophageal cancer patients and healthy persons [24]. A2925/A1467: It may describe the change of lipids structure. The average value of A2925/A1467 was 1.40 for esophageal cancer patients while it was 1.31 for healthy persons, moreover, P value was higher than 0.05, indicating A2925/A1467 was not significantly different between esophageal cancer patients and healthy persons [24]. A1548/A1467: It may describe the change of proteins content relative to lipids content. The average value of A1548/A1467 was 8.05 for esophageal cancer patients while it was 8.00 for healthy persons, moreover, P value was higher than 0.05, indicating A1548/A1467 was not significantly different between esophageal cancer patients and healthy persons [24]. A1548/A1243: It may describe the change of proteins content relative to nucleic acids content. The average value of A1548/A1243 was
2.3. SR-IR microspectroscopy measurements IR microspectroscopy measurements were carried out at BL01B beamline of National Synchrotron Radiation Laboratory (China). BL01B beamline has a Bruker VERTEX 70v FTIR spectrometer coupled with a Bruker Hyperion 3000 IR microscope. The spectra were collected in transmission mode through the following parameters such as 5 μm * 5 μm aperture, 4 cm−1 resolution and 256 scans. 2.4. Data processing IR spectra were dealt with OPUS5.5 software. They were cut in 3640–1000 cm−1 range, baseline corrected (64 points rubberband correctio) and min-max normalized successively. Then second-derivative IR spectra were obtained by using Savitzky-Golay algorithm (9 smoothing points). The peak-area ratios were analyzed by using Origin6.0 software and expressed as means ± SD. Independent t-test was run by using origin6.0 software. PCA was done by using Unscrambler X10.4 software. Discriminant analysis was carried out by using SPSS16.0 software. 3. Result and discussion 3.1. Analysis of IR spectra of hair medulla Fig. 1 showed the average IR spectra of hair medulla from esophageal cancer patients and healthy persons. The major bands were mainly divided into three groups [18–22]: One group was related with proteins, including the bands around 3286 cm−1, 3077 cm−1, 1657 cm−1, 1548 cm−1 and 1280 cm−1. Another group was related with lipids, including the bands around 2925 cm−1, 2892 cm−1, 1467 cm−1 and 1397 cm−1. The third group was related with nucleic acids, including the bands around 1243 cm−1 and 1115 cm−1. The average IR spectrum of hair medulla from healthy persons was similar to that of esophageal cancer patients. However, the position of the band around 3077 cm−1 (P3077) was 3075.56 ± 3.68 for esophageal
Table 1 Selected peak-areas and their baselines, assignments. Selected peak-areas A3286 A3077 A2925 A1657 A1548 A1467 A1243
2
Baselines 3560–3129 3106–3020 2990–2910 1700–1600 1580–1490 1485–1430 1258–1220
Assignments −1
cm cm−1 cm−1 cm−1 cm−1 cm−1 cm−1
Amide A Amide B CH3 and CH2 asymmetric stretching Amide I Amide II CH2 deformation PO2− asymmetric stretching
Infrared Physics and Technology 105 (2020) 103201
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Table 2 Statistical data.
A3286/A1657 A1657/A3077 A2925/A1467 A1548/A1467 A1548/A1243 A1467/A1243
Esophageal cancer patients
Healthy persons
P
2.37 ± 0.45 30.72 ± 371 1.40 ± 0.29 8.05 ± 1.24 24.56 ± 8.24 3.03 ± 0.82
2.04 ± 0.33 36.60 ± 3.56 1.31 ± 0.52 8.00 ± 1.78 22.79 ± 7.20 2.81 ± 0.45
< 0.05 < 0.05 > 0.05 > 0.05 > 0.05 > 0.05
24.56 for esophageal cancer patients while it was 22.79 for healthy persons, moreover, P value was higher than 0.05, indicating A1548/ A1243 was not significantly different between esophageal cancer patients and healthy persons [24]. A1467/A1243: It may describe the changes of lipids content relative to nucleic acid contents. The average value of A1467/A1243 was 3.03 for esophageal cancer patients while it was 2.81 for healthy persons, moreover, P value was higher than 0.05, indicating A1467/A1243 was not significantly different between esophageal cancer patients and healthy persons [24]. In this section, we compared the differences of A3286/A1657, A1657/A3077, A2925/A1467, A1548/A1467, A1548/A1243 and A1467/A1243 between esophageal cancer patients’ hair and healthy persons’ hair medulla. Among these six ratios, only P values of A3286/ A1657 and A1657/A3077 were less than 0.05, indicating that proteins structure and content of hair medulla may alter significantly with esophageal cancer occurrence.
Fig. 3. The loading plots of PCA model.
independent and basically distinguished. Since PC1 explained 44% total variance while PC2 explained 29% total variance, they could reflect most of hair medulla’s information. To further identify differences in hairs’ medulla chemical composition between esophageal cancer patients and healthy persons, loading factors of PCA model were extracted to draw loading plots. PC1 contributed the most to PCA model, moreover, esophageal cancer samples were well differentiated from normal samples in PC1 direction, hence we paid attention on the loading spectrum for PC1 (Fig. 3). It was observed that the highest positive value and negative value were located at 1650 cm−1 and 1660 cm−1 (both owed to α-helix structure) respectively [28], indicating that esophageal cancer caused significant change of α-helix protein content in hair medulla.
3.3. Principal component analysis PCA is an effective data dimension reduction method which explains most variables in original data using fewer variables, and thus it can simplify analysis steps [25–27]. A PCA model was established to analyze second-derivative IR spectra in the 1700–1000 cm−1 range. Distributions of each data set were presented as first principal component (PC1) and second principal component (PC2), and two-dimensional scatter plot of PC1 and PC2 scores was shown in Fig. 2. It was observed that normal samples were mainly concentrated on the left part (negative PC1) while esophageal cancer samples were mainly concentrated on the right part (positive PC1), indicating that most of esophageal cancer samples and normal samples were relatively
3.4. Discriminant analysis Discriminant analysis is a method for classifying the unclassified data according to certain index when the number of classifications is known [29]. Since the differences of P3077, A3286/A1657 and A1657/ A3077 were singnificant between esophageal cancer patients and healthy persons, we therefore carried out discriminant analysis on basis of these three indicators. The equations were established as below:
Y1 = −92.823X1 − 1.225 ∗ 103X2 + 281.305X3 − 4.297 ∗ 105
Fig. 2. PCA score plots. 3
Infrared Physics and Technology 105 (2020) 103201
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Y2 = −92.209X1 − 1.223 ∗ 103X2 + 280.821X3 − 4.283 ∗ 105
[7] T.Y. Gao, Y.X. Ci, J. Li, Progress in infrared spectroscopic analysis of tumor cells and tissues, Prog. Chem. 12 (2000) 346–353. [8] A.C.S. Talari, M.A.G. Martinez, Z. Movasaghi, S. Rehman, I.U. Rehman, Advances in Fourier transform infrared (FTIR) spectroscopy of biological tissues, Appl. Spectrosc. Rev. 52 (2017) 456–506. [9] J.S. Wang, J.S. Shi, Y.Z. Xu, X.Y. Duan, L. Zhang, J. Wang, L.M. Yang, S.F. Weng, J.G. Wu, FT-IR spectroscopic analysis of normal and cancerous tissues of esophagus, World J. Gastroenterol. 9 (2003) 1897–1899. [10] J.S. Wang, Y.Z. Xu, J.S. Shi, L. Zhang, X.Y. Duan, L.M. Yang, Y.L. Su, S.P. Weng, D.F. Xu, J.G. Wu, FTIR spectroscopic study on normal and cancerous tissues of esophagus, Spectrosc. Spect. Anal. 23 (2003) 863–865. [11] D.E. Maziak, M.T. Da, F.M. Shamji, S.R. Sundaresan, D.G. Perkins, P.T.T. Wong, Fourier-transform infrared spectroscopic study of characteristic molecular structure in cancer cells of esophagus: an exploratory study, Cancer Detect. 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Novais, P. Dechichi, Fourier transform infrared spectroscopy (FTIR) application chemical characterization of enamel, dentin and bone, Appl. Spectrosc. Rev. 53 (2018) 747–769. [21] H. Liu, Q.L. Su, Q.P. Wu, W.J. Fang, D.C. Yang, W. Zheng, X. Wang, FTIR spectroscopic study on apoptosis of lung cancer cell line A549 induced by arsenic trioxide, Infrared Phys. Tech. 93 (2018) 340–345. [22] G.N. Bosio, J. Parisi, F.S. García Einschlag, D.O. Mártire, Imidazole and beta- carotene photoprotection against photodynamic therapy evaluated by synchrotron infrared microscopy, Spectrochim. Acta A 195 (2018) 53–61. [23] X.D. Ma, S.P. Jiang, W. Wang, L. Chen, C.X. Li, H.Y. Wang, Comparative study on IR spectra of finger nails of normal people and patients with cancer in digestive tract, Anal. Instrum. 8 (2007) 26–29. [24] K. Yano, S. Ohoshima, Y. Gotou, K. Kumaido, T. Moriguchi, H. Katayama, Direct measurement of human lung cancerous and noncancerous tissues by Fourier transform infrared microscopy: Can an infrared microscope be used as a clinical tool? Anal. Biochem. 287 (2000) 218–225. [25] P. Heraud, S. Caine, N. Campanale, T. Karnezis, D. McNaughton, B.R. Wood, M.J. Tobin, C.C.A. Bernard, Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage 49 (2010) 1180–1189. [26] Y.F. Yuan, Z.H. Tao, J.X. Liu, C.H. Tian, G.W. Wang, Y.Q. Li, Identification of Cortex phellodendri by Fourier-transform infrared spectroscopy and principal component analysis, Spectrosc. Spect. Anal. 31 (2011) 1258–1261. [27] P. Plaimee, N. Weerapreeyakul, K. Thumanu, W. Tanthanuch, S. Barusrux, Melatonin induces apoptosis through biomolecular changes, in SK-LU-1 human lung adenocarcinoma cells, Cell Proliferat. 47 (2014) 564–577. [28] Y.X. Ci, T.Y. Gao, J.Q. Dong, X. Kan, Z.Q. Guo, FTIR assessment of the secondary structure of proteins in human breast benign and malignant tissues, Chin. Sci. Bull. 44 (1999) 2215–2221. [29] L.W. Shi, SPSS19.0 Statistical Analysis from Entry to the Master, Tsinghua University Press, 2012. [30] X.Q. Zhang, Y.Z. Xu, Y.F. Zhang, L.X. Wang, C.S. Hou, X.S. Zhou, X.F. Ling, Z. Xu, Intraoperative detection of thyroid carcinoma by Fourier transform infrared spectrometry, J. Surg. Res. 171 (2011) 650–656. [31] H. Liu, Q.L. Su, D.P. Sheng, W. Zheng, X. Wang, Comparison of red blood cells from gastric cancer patients and healthy persons using FTIR spectroscopy, J. Mol. Struct. 1130 (2017) 33–37.
Y1 and Y2 represented esophageal cancer patients and healthy persons respectively, X1, X2 and X3 were A1657/A3077, A3286/A1657 and P3077 respectively. The case would be determined as esophageal cancer patient if Y1 > Y2 while be determined as healthy person if Y1 < Y2 [30,31]. For the esophageal cancer group, 35 cases were determined to be esophageal cancer while 4 cases were determined to be healthy. For the healthy group, 28 people were determined to be healthy while 4 people were determined to be esophageal cancer. Then the sensitivity, the specificity, the positive predictive value and the accuracy were calculated. The sensitivity was 89.74%, the specificity was 87.50%, the positive predictive value was 89.74% and the accuracy was 88.73%. The results indicated that IR spectra of hair medulla combined with discriminant analysis might clearly differentiate esophageal cancer patients from healthy persons. 4. Conclusion In this study, we used SR-IR microspectroscopy to reveal the differences between hair medulla from esophageal cancer patients and healthy persons. Significant differences were observed in the peak position of amide B and the values of A3286/A1657 and A1657/A3077. Moreover, IR spectra of hair medulla combined with PCA discovered the α-helix content change in proteins. These results indicated that the content/structure of proteins in hair medulla changed significantly due to esophageal cancer. In addition, IR spectra of hair medulla combined with discriminant analysis obtained satisfactory result in differentiating esophageal cancer patients from healthy persons. This study shows that chemical compositional changes happen in hair medulla of esophageal cancer patients, indicating that IR spectra of hair medulla combined with statistical method may develop a potential method for screening esophageal cancer early. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement The work was supported by National Natural Science Foundation of China (Grant No. U1632148), BL01B beamline of National Synchrotron Radiation Laboratory. We are grateful for these supports. References [1] M.C.S. Wong, W. Hamilton, D.C. Whiteman, J.Y. Jiang, Y. Qiao, F.D.H. Fung, H.H.X. Wang, P.W.Y. Chiu, E.K.W. Ng, J.C.Y. Wu, J. Yu, F.K.L. Chan, J.J.Y. Sung, Global Incidence and mortality of oesophageal cancer and their correlation with socioeconomic indicators temporal patterns and trends in 41 countries, Sci. Rep. 8 (2018) 4522–4534. [2] H.Y. Wang, Y. Lv, F. Wang, X.D. Ma, S.P. Jiang, W. Wang, C.X. Li, Study on FTIR spectra of finger nails of normal people and patients of esophagus cancer, Spectrosc. Spect. Anal. 28 (2008) 331–334. [3] Z.Q. Fan, Z.H. Wu, R.G. Li, The clinical application of endoscopic ultrasonography on preoperative staging of esophageal carcinoma, J. Xinjiang Med. U. 40 (2017) 596–601. [4] L. Wang, P. Li, Research progress in endoscopic diagnosis of early esophageal carcinoma, Chin. J. Clin. 8 (2014) 4079–4081. [5] D.Y. Fu, Comparative analysis of esophageal carcinoma by barium meal contrast and gastroscopy biopsy, J. Mod. Med. Health 31 (2015) 405–406. [6] X.Y. Fan, Application of Fourier transform infrared spectroscopy in life science, Life Sci. Res. 7 (2003) 83–87.
4
Contents lists available at ScienceDirect
Infrared Physics & Technology journal homepage: www.elsevier.com/locate/infrared
Comparison of hair medulla from esophageal cancer patients and healthy persons using synchrotron radiation infrared microspectroscopy Qipeng Wua,1, Chao Lib,c,1, Zeming Qic, Ling Zonga, Chuansheng Huc, Jiarong Lib, Xin Wanga,
T ⁎
a
School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui 230032, China The Second Affiliated Hospital, Anhui Medical University, Hefei, Anhui 230601, China c National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui 230029, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Esophageal cancer Hair medulla SR-IR microspectroscopy IR spectra
This work aimed to investigate the feasibility of distinguishing esophageal cancer patients from healthy persons by IR spectra of hair medulla. SR-IR microspectroscopy was used to compare the differences in hair medulla from esophageal cancer patients and healthy persons. The results demonstrated that esophageal cancer might cause significant change of proteins content/structure in hair medulla. Moreover, combined with discriminant analysis, IR spectra of hair medulla could distinguish between esophageal cancer patients and healthy persons with the sensitivity 89.74%, the specificity 87.50%, the positive predictive value 89.74% and the accuracy 88.73%. Taken together, the results indicated that IR spectra of hair medulla might be helpful for early esophageal cancer diagnosis.
1. Introduction Esophageal cancer is a malignant tumor occuring in esophageal epithelium, and it is a serious threat to global health. For example, about 450,000 people were diagnosed with esophageal cancer while about 400,000 people died of esophageal cancer worldwide in 2012 [1]. Since the early symptoms of esophageal cancer were not obvious, most patients were diagnosed at moderate/advanced stage and lost the optimal time for surgery [2,3]. Therefore, early diagnosis of esophageal cancer is very important. At present, the main diagnostic methods of esophageal cancer include gastroscopy and biopsy, X-ray barium meal examination, chest CT, esophageal exfoliative cytology, etc. Gastroscopy and biopsy are preferred among these methods [4]. However, gastroscopy and biopsy have some limitations as follows [5]: 1. Severe cardiovascular and cerebrovascular disease patients cannot tolerate. 2. Gastroscopy cannot pass through excessively narrow esophagus. 3. The results of gastroscopy and biopsy may be influenced by operators’ experience. Hence it is very urgent to develop new methods for diagnosing esophageal cancer. Since FTIR spectroscopy has the ability of investigating complex tissues’ and cells’ structure and composition [6], it has been applied to cancer research broadly [7,8]. FTIR spectroscopy was also used to
investigate esophageal cancer, for example: Wang et al. compared esophageal cancer tissues’ and normal tissues’ IR spectra, and they found that the differences existed in the regions of proteins, nucleic acids and sugars [9,10]. Maziak et al. compared esophageal cancer tissues’ and normal tissues’ IR spectra, and they found that the nucleito-cytoplasm ratio and the relative DNA content increased while the relative RNA content decreased in malignant tissues [11]. These studies show that FTIR spectroscopy is a powerful tool for distinguishing esophageal cancer tissues from normal tissues. However, the samples were not easy to get since they came from resected specimen. The hair consists of medulla (about 10 μm width), cortex (about 40–80 μm width) and cuticle (about 5 μm width) [12], which can reflect serious diseases of human body [13,14]. FTIR spectroscopy was also used to investigate hair of cancer patients [15]. However, it is impossible to obtain IR spectra of hairs’ three parts spectrately due to the limitation of conventional source brightness. Fortunately, synchrotron radiation (SR) source has advantages of high brightness etc. which enhances spatial resolution of FTIR microspectroscopy largely [16]. SR-IR microspectroscopy can gain IR spectra of hair’s medulla, cortex and cuticle accurately [12]. We also used SR-IR microspectroscopy to compare hair from gastric cancer patients and healthy persons [17]. Compared to surgical and endoscopic samples, hair samples are easier to obtain and non-invasive. The study of hair by SR-IR
Abbreviations: FTIR, Fourier transform infrared; IR, infrared; SR, synchrotron radiation; PCA, principal component analysis ⁎ Corresponding author. E-mail address: [email protected] (X. Wang). 1 Both contributed equally to this work. https://doi.org/10.1016/j.infrared.2020.103201 Received 19 June 2019; Received in revised form 16 December 2019; Accepted 15 January 2020 Available online 17 January 2020 1350-4495/ © 2020 Elsevier B.V. All rights reserved.
Infrared Physics and Technology 105 (2020) 103201
Q. Wu, et al.
microspectroscopy will be helpful to explore a new method for detecting esophageal cancer non-invasively and rapidly. In this study, we explored the feasibility of differentiating esophageal cancer patients from healthy persons by IR spectra of hair medulla. 2. Materials and methods 2.1. Materials Biomedical Ethics Committee of Anhui Medical University approved this study (Ref. No. 20160222), and all participants agreed to provide hair. Hair samples were collected from 39 preoperative esophageal cancer patients who did not have chemotherapy/radiotherapy. These patients (including 24 males and 15 females) were from The Second Affiliated Hospital of Anhui Medical University, and they were confirmed as esophageal squamous cell cancer by postoperative pathological diagnosis. Hair samples from 32 healthy persons were contributed by healthy volunteers (including 19 males and 13 females). There was no significant age difference between esophageal cancer patients and healthy persons.
Fig. 1. Average IR spectra of hair medulla from esophageal cancer patients and healthy persons.
cancer patients while it was 3070.97 ± 3.84 for healthy persons (P < 0.05), indicating that the form and degree of hydrogen bonding in hair medulla changed after esophageal cancer occurred [23].
2.2. Sample preparation Hair samples were cut at 1 cm length from scalp, and then they were sponged with distilled water and 95% alcohol respectively and vacuumdried. The samples were embedded in OCT, frozen to −25 °C and then sliced with 5 μm thickness by a freezing microtome. The slices were placed onto 1 mm thick BaF2 windows and stored in a vacuum dryer before examination.
3.2. Peak-area ratios In order to distinguish esophageal cancer patients’ hair medulla from healthy persons’ hair medulla, we measured the area of seven peaks (Table 1) and then calculated the values of A3286/A1657, A1657/A3077, A2925/A1467, A1548/A1467, A1548/A1243 and A1467/A1243 (Table 2). A3286/A1657: It may describe the change of proteins content/ structure. The average value of A3286/A1657 was 2.37 for esophageal cancer patients while it was 2.04 for healthy persons, moreover, P value was less than 0.05, indicating A3286/A1657 was significantly different between esophageal cancer patients and healthy persons [24]. A1657/A3077: It may also describe the change of proteins content/ structure. The average value of A1657/A3077 was 30.72 for esophageal cancer patients while it was 36.60 for healthy persons, moreover, P value was less than 0.05, indicating A1657/A3077 was significantly different between esophageal cancer patients and healthy persons [24]. A2925/A1467: It may describe the change of lipids structure. The average value of A2925/A1467 was 1.40 for esophageal cancer patients while it was 1.31 for healthy persons, moreover, P value was higher than 0.05, indicating A2925/A1467 was not significantly different between esophageal cancer patients and healthy persons [24]. A1548/A1467: It may describe the change of proteins content relative to lipids content. The average value of A1548/A1467 was 8.05 for esophageal cancer patients while it was 8.00 for healthy persons, moreover, P value was higher than 0.05, indicating A1548/A1467 was not significantly different between esophageal cancer patients and healthy persons [24]. A1548/A1243: It may describe the change of proteins content relative to nucleic acids content. The average value of A1548/A1243 was
2.3. SR-IR microspectroscopy measurements IR microspectroscopy measurements were carried out at BL01B beamline of National Synchrotron Radiation Laboratory (China). BL01B beamline has a Bruker VERTEX 70v FTIR spectrometer coupled with a Bruker Hyperion 3000 IR microscope. The spectra were collected in transmission mode through the following parameters such as 5 μm * 5 μm aperture, 4 cm−1 resolution and 256 scans. 2.4. Data processing IR spectra were dealt with OPUS5.5 software. They were cut in 3640–1000 cm−1 range, baseline corrected (64 points rubberband correctio) and min-max normalized successively. Then second-derivative IR spectra were obtained by using Savitzky-Golay algorithm (9 smoothing points). The peak-area ratios were analyzed by using Origin6.0 software and expressed as means ± SD. Independent t-test was run by using origin6.0 software. PCA was done by using Unscrambler X10.4 software. Discriminant analysis was carried out by using SPSS16.0 software. 3. Result and discussion 3.1. Analysis of IR spectra of hair medulla Fig. 1 showed the average IR spectra of hair medulla from esophageal cancer patients and healthy persons. The major bands were mainly divided into three groups [18–22]: One group was related with proteins, including the bands around 3286 cm−1, 3077 cm−1, 1657 cm−1, 1548 cm−1 and 1280 cm−1. Another group was related with lipids, including the bands around 2925 cm−1, 2892 cm−1, 1467 cm−1 and 1397 cm−1. The third group was related with nucleic acids, including the bands around 1243 cm−1 and 1115 cm−1. The average IR spectrum of hair medulla from healthy persons was similar to that of esophageal cancer patients. However, the position of the band around 3077 cm−1 (P3077) was 3075.56 ± 3.68 for esophageal
Table 1 Selected peak-areas and their baselines, assignments. Selected peak-areas A3286 A3077 A2925 A1657 A1548 A1467 A1243
2
Baselines 3560–3129 3106–3020 2990–2910 1700–1600 1580–1490 1485–1430 1258–1220
Assignments −1
cm cm−1 cm−1 cm−1 cm−1 cm−1 cm−1
Amide A Amide B CH3 and CH2 asymmetric stretching Amide I Amide II CH2 deformation PO2− asymmetric stretching
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Table 2 Statistical data.
A3286/A1657 A1657/A3077 A2925/A1467 A1548/A1467 A1548/A1243 A1467/A1243
Esophageal cancer patients
Healthy persons
P
2.37 ± 0.45 30.72 ± 371 1.40 ± 0.29 8.05 ± 1.24 24.56 ± 8.24 3.03 ± 0.82
2.04 ± 0.33 36.60 ± 3.56 1.31 ± 0.52 8.00 ± 1.78 22.79 ± 7.20 2.81 ± 0.45
< 0.05 < 0.05 > 0.05 > 0.05 > 0.05 > 0.05
24.56 for esophageal cancer patients while it was 22.79 for healthy persons, moreover, P value was higher than 0.05, indicating A1548/ A1243 was not significantly different between esophageal cancer patients and healthy persons [24]. A1467/A1243: It may describe the changes of lipids content relative to nucleic acid contents. The average value of A1467/A1243 was 3.03 for esophageal cancer patients while it was 2.81 for healthy persons, moreover, P value was higher than 0.05, indicating A1467/A1243 was not significantly different between esophageal cancer patients and healthy persons [24]. In this section, we compared the differences of A3286/A1657, A1657/A3077, A2925/A1467, A1548/A1467, A1548/A1243 and A1467/A1243 between esophageal cancer patients’ hair and healthy persons’ hair medulla. Among these six ratios, only P values of A3286/ A1657 and A1657/A3077 were less than 0.05, indicating that proteins structure and content of hair medulla may alter significantly with esophageal cancer occurrence.
Fig. 3. The loading plots of PCA model.
independent and basically distinguished. Since PC1 explained 44% total variance while PC2 explained 29% total variance, they could reflect most of hair medulla’s information. To further identify differences in hairs’ medulla chemical composition between esophageal cancer patients and healthy persons, loading factors of PCA model were extracted to draw loading plots. PC1 contributed the most to PCA model, moreover, esophageal cancer samples were well differentiated from normal samples in PC1 direction, hence we paid attention on the loading spectrum for PC1 (Fig. 3). It was observed that the highest positive value and negative value were located at 1650 cm−1 and 1660 cm−1 (both owed to α-helix structure) respectively [28], indicating that esophageal cancer caused significant change of α-helix protein content in hair medulla.
3.3. Principal component analysis PCA is an effective data dimension reduction method which explains most variables in original data using fewer variables, and thus it can simplify analysis steps [25–27]. A PCA model was established to analyze second-derivative IR spectra in the 1700–1000 cm−1 range. Distributions of each data set were presented as first principal component (PC1) and second principal component (PC2), and two-dimensional scatter plot of PC1 and PC2 scores was shown in Fig. 2. It was observed that normal samples were mainly concentrated on the left part (negative PC1) while esophageal cancer samples were mainly concentrated on the right part (positive PC1), indicating that most of esophageal cancer samples and normal samples were relatively
3.4. Discriminant analysis Discriminant analysis is a method for classifying the unclassified data according to certain index when the number of classifications is known [29]. Since the differences of P3077, A3286/A1657 and A1657/ A3077 were singnificant between esophageal cancer patients and healthy persons, we therefore carried out discriminant analysis on basis of these three indicators. The equations were established as below:
Y1 = −92.823X1 − 1.225 ∗ 103X2 + 281.305X3 − 4.297 ∗ 105
Fig. 2. PCA score plots. 3
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Y2 = −92.209X1 − 1.223 ∗ 103X2 + 280.821X3 − 4.283 ∗ 105
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Y1 and Y2 represented esophageal cancer patients and healthy persons respectively, X1, X2 and X3 were A1657/A3077, A3286/A1657 and P3077 respectively. The case would be determined as esophageal cancer patient if Y1 > Y2 while be determined as healthy person if Y1 < Y2 [30,31]. For the esophageal cancer group, 35 cases were determined to be esophageal cancer while 4 cases were determined to be healthy. For the healthy group, 28 people were determined to be healthy while 4 people were determined to be esophageal cancer. Then the sensitivity, the specificity, the positive predictive value and the accuracy were calculated. The sensitivity was 89.74%, the specificity was 87.50%, the positive predictive value was 89.74% and the accuracy was 88.73%. The results indicated that IR spectra of hair medulla combined with discriminant analysis might clearly differentiate esophageal cancer patients from healthy persons. 4. Conclusion In this study, we used SR-IR microspectroscopy to reveal the differences between hair medulla from esophageal cancer patients and healthy persons. Significant differences were observed in the peak position of amide B and the values of A3286/A1657 and A1657/A3077. Moreover, IR spectra of hair medulla combined with PCA discovered the α-helix content change in proteins. These results indicated that the content/structure of proteins in hair medulla changed significantly due to esophageal cancer. In addition, IR spectra of hair medulla combined with discriminant analysis obtained satisfactory result in differentiating esophageal cancer patients from healthy persons. This study shows that chemical compositional changes happen in hair medulla of esophageal cancer patients, indicating that IR spectra of hair medulla combined with statistical method may develop a potential method for screening esophageal cancer early. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement The work was supported by National Natural Science Foundation of China (Grant No. U1632148), BL01B beamline of National Synchrotron Radiation Laboratory. We are grateful for these supports. References [1] M.C.S. Wong, W. Hamilton, D.C. Whiteman, J.Y. Jiang, Y. Qiao, F.D.H. Fung, H.H.X. Wang, P.W.Y. Chiu, E.K.W. Ng, J.C.Y. Wu, J. Yu, F.K.L. Chan, J.J.Y. Sung, Global Incidence and mortality of oesophageal cancer and their correlation with socioeconomic indicators temporal patterns and trends in 41 countries, Sci. Rep. 8 (2018) 4522–4534. [2] H.Y. Wang, Y. Lv, F. Wang, X.D. Ma, S.P. Jiang, W. Wang, C.X. Li, Study on FTIR spectra of finger nails of normal people and patients of esophagus cancer, Spectrosc. Spect. Anal. 28 (2008) 331–334. [3] Z.Q. Fan, Z.H. Wu, R.G. Li, The clinical application of endoscopic ultrasonography on preoperative staging of esophageal carcinoma, J. Xinjiang Med. U. 40 (2017) 596–601. [4] L. Wang, P. Li, Research progress in endoscopic diagnosis of early esophageal carcinoma, Chin. J. Clin. 8 (2014) 4079–4081. [5] D.Y. Fu, Comparative analysis of esophageal carcinoma by barium meal contrast and gastroscopy biopsy, J. Mod. Med. Health 31 (2015) 405–406. [6] X.Y. Fan, Application of Fourier transform infrared spectroscopy in life science, Life Sci. Res. 7 (2003) 83–87.
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