Skip to content
2000
Volume 20, Issue 7
  • ISSN: 1573-4129
  • E-ISSN: 1875-676X

Abstract

Introduction

Infrared and Raman spectroscopy have emerged as promising diagnostic tools for gastric and liver cancer, offering significant advantages over traditional histology and biomarker-based methods.

Methods

These spectroscopic techniques provide rapid and highly specific molecular fingerprinting with minimal sample preparation, enabling real-time diagnosis and preserving samples for further analysis. The integration of nanoparticles, particularly in surface-enhanced Raman spectroscopy, enhances the sensitivity and resolution of the method by amplifying signal strengths through localized surface plasmon resonances. This advancement facilitates the detection of subtle molecular changes associated with cancer, even at early stages.

Results

Raman spectroscopy, a non-destructive technique, can differentiate between healthy and malignant cells, aiding in the diagnosis of various gastric cancer forms, including adenocarcinoma and gastrointestinal stromal tumors. Similarly, IR spectroscopy provides insights into the chemical composition of tissues, detecting molecular changes associated with cancer. For liver cancer, including hepatocellular carcinoma, these spectroscopic methods reveal biochemical alterations, facilitating early detection and characterization of the disease. This review explores the application of Raman and IR spectroscopy in diagnosing gastric and liver cancers, emphasizing their potential to enhance diagnostic accuracy and improve patient outcomes by identifying molecular changes linked to malignancies.

Conclusion

Overall, the integration of nanoparticles into spectroscopic techniques holds significant potential for improving the accuracy, speed, and efficacy of cancer diagnostics.

Loading

Article metrics loading...

/content/journals/cpa/10.2174/0115734129322567240821052326
2024-08-28
2025-01-22
Loading full text...

Full text loading...

References

  1. NkS. ChandanaG.M.H. VaishnaviG. Pharmaceutical applications and importance of near infrared spectroscopy.MACIJ2020411610.23880/macij‑16000155
    [Google Scholar]
  2. GilbertA.S. Vibrational, rotational and raman spectroscopy, historical perspective.201610.1016/B978‑0‑12‑803224‑4.00308‑3.
    [Google Scholar]
  3. FiniG. Applications of Raman spectroscopy to pharmacy.J. Raman Spectrosc.200435533533710.1002/jrs.1161
    [Google Scholar]
  4. LiuK. ZhaoQ. LiB. ZhaoX. Raman spectroscopy: A novel technology for gastric cancer diagnosis.Front. Bioeng. Biotechnol.20221085659110.3389/fbioe.2022.85659135372295
    [Google Scholar]
  5. WangX.W. ThorgeirssonS.S. The biological and clinical challenge of liver cancer heterogeneity.Hepat. Oncol.20141434935310.2217/hep.14.1830190968
    [Google Scholar]
  6. TehS.K. ZhengW. HoK.Y. TehM. YeohK.G. HuangZ. Diagnosis of gastric cancer using near-infrared Raman spectroscopy and classification and regression tree techniques.J. Biomed. Opt.200813303401310.1117/1.293940618601558
    [Google Scholar]
  7. LochheadP. El-OmarE.M. Gastric cancer.Br. Med. Bull.20088518710010.1093/bmb/ldn00718267927
    [Google Scholar]
  8. TalariA.C.S. MartinezM.A.G. MovasaghiZ. RehmanS. RehmanI.U. Advances in Fourier transform infrared (FTIR) spectroscopy of biological tissues.Appl. Spectrosc. Rev.201752545650610.1080/05704928.2016.1230863
    [Google Scholar]
  9. MinnesR. NissinmannM. MaizelsY. GerlitzG. KatzirA. RaichlinY. Using attenuated total reflection–fourier transform infra-red (ATR-FTIR) spectroscopy to distinguish between melanoma cells with a different metastatic potential.Sci. Rep.201771438110.1038/s41598‑017‑04678‑628663552
    [Google Scholar]
  10. ChenH. LinZ. HegangW. WangL. Diagnosis of colorectal cancer by near-infrared optical fiber spectroscopy and random forest.Spectrochim. Acta A Mol. Biomol. Spectrosc.201513518519110.1016/j.saa.2014.07.00525064501
    [Google Scholar]
  11. Wei-songY. Dian-shengC. ZhiL. Lan-lanW. Ai-guoS. Ji-mingH. Gastric cancer differentiation using Fourier transform nearinfrared spectroscopy with unsupervised pattern recognition. Spectrochim. Acta - A.Mol. Biomol.201310112713110.1016/j.saa.2012.09.037
    [Google Scholar]
  12. SvenssonT. SwartlingJ. TaroniP. TorricelliA. LindblomP. IngvarC. Andersson-EngelsS. Characterization of normal breast tissue heterogeneity using time-resolved near-infrared spectroscopy.Phys. Med. Biol.200550112559257110.1088/0031‑9155/50/11/00815901954
    [Google Scholar]
  13. KondepatiV.R. ZimmermannJ. KeeseM. SturmJ. ManegoldB.C. BackhausJ. Near-infrared fiber optic spectroscopy as a novel diagnostic tool for the detection of pancreatic cancer.J. Biomed. Opt.200510505401610.1117/1.206056816292976
    [Google Scholar]
  14. LipingH. Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning.Nat. Commun.202314110.1038/s41467‑022‑35696‑2
    [Google Scholar]
  15. FengS. ChenR. LinJ. PanJ. WuY. LiY. ChenJ. ZengH. Gastric cancer detection based on blood plasma surface-enhanced Raman spectroscopy excited by polarized laser light.Biosens. Bioelectron.20112673167317410.1016/j.bios.2010.12.02021227679
    [Google Scholar]
  16. MaryamB. A Raman-based serum constituents' analysis for gastric cancer diagnosis: In vitro study.Talanta201920410.1016/j.talanta.2019.06.068
    [Google Scholar]
  17. ShigehiroK. YujiW. YusukeO. Raman spectroscopic analysis for gastric and colorectal cancer in surgical treatment toward molecular-guided surgery.Molecular-Guided Surgery: Molecules, Devices, and Applications (Progress in Biomedical Optics and Imaging - Proceedings of SPIE20181047810.1117/12.2291435
    [Google Scholar]
  18. Mads SylvestB. Fiber-optic Raman spectroscopy probes gastric carcinogenesis in vivo at endoscopy.J. Biophotonics20136110.1002/jbio.201200138
    [Google Scholar]
  19. ShuyanZ. YiQ. ShunT. RenzheB. MaliniO. molecular fingerprint detection using raman and infrared spectroscopy technologies for cancer detection: A progress review.Biosensors (Basel)202313510.3390/bios13050557
    [Google Scholar]
  20. ParaskevaidM. Clinical applications of infrared and Raman spectroscopy in the fields of cancer and infectious diseases.Appl. Spectrosc.20215680486810.1080/05704928.2021.1946076
    [Google Scholar]
  21. XienY. QiongrongO. WeiyeY. Diagnosis of liver cancer by FTIR spectra of serum.Spectrochim. Acta A Mol. Biomol. Spectrosc.202126310.1016/j.saa.2021.120181
    [Google Scholar]
  22. StefanoG. Surgical treatment of gastric cancer liver metastases: Systematic review and meta-analysis of long-term outcomes and prognostic factors.Crit. Rev. Oncog.202116310331310.1016/j.critrevonc.2021.103313
    [Google Scholar]
  23. PopescuM-C. ConstantinescuR. PădureanuS.S. 2D IR correlation spectroscopy and chemometric methods in gastric cancer diagnosis.J. Mol. Struct.2020121412821110.1016/j.molstruc.2020.128211
    [Google Scholar]
  24. KatsunoriT. In vivo near-infrared fluorescence imaging of gastric cancer in an MKN-45 gastric cancer xenograft mouse model using intraoperative ureteral identification agent ASP5354.Photochem. Photobiol. Sci.20232271721172910.1007/s43630‑023‑00410‑837010695
    [Google Scholar]
  25. LiQ. WangW. LingX. WuJ.G. Detection of gastric cancer with Fourier transform infrared spectroscopy and support vector machine classification.BioMed Res. Int.201320131410.1155/2013/94242724000331
    [Google Scholar]
  26. LiuZ. LiT. WangZ. LiuJ. HuangS. MinB.H. AnJ.Y. KimK.M. KimS. ChenY. LiuH. KimY. WongD.T.W. HuangT.J. XieY.H. Gold Nanopyramid arrays for non-invasive surface-Enhanced raman spectroscopy-based gastric cancer detection via sEVs.ACS Appl. Nano Mater.202259125061251710.1021/acsanm.2c0198636185166
    [Google Scholar]
  27. KimH.H. Endoscopic raman spectroscopy for molecular fingerprinting of gastric cancer: Principle to implementation.BioMed Res. Int.201520151910.1155/2015/67012126106612
    [Google Scholar]
  28. BergholtM.S. ZhengW. LinK. HoK.Y. TehM. YeohK.G. Yan SoJ.B. HuangZ. In vivo diagnosis of gastric cancer using Raman endoscopy and ant colony optimization techniques.Int. J. Cancer2011128112673268010.1002/ijc.2561820726002
    [Google Scholar]
  29. HuangZ. TehS.K. ZhengW. LinK. HoK.Y. TehM. YeohK.G. In vivo detection of epithelial neoplasia in the stomach using image-guided Raman endoscopy.Biosens. Bioelectron.201026238338910.1016/j.bios.2010.07.12520729057
    [Google Scholar]
  30. BergholtM.S. ZhengW. HoK.Y. TehM. YeohK.G. Yan SoJ.B. ShabbirA. HuangZ. Fiberoptic confocal raman spectroscopy for real-time in vivo diagnosis of dysplasia in Barrett’s esophagus.Gastroenterology20141461273210.1053/j.gastro.2013.11.00224216327
    [Google Scholar]
  31. BergholtM.S. ZhengW. LinK. HoK.Y. TehM. YeohK.G. SoJ.B.Y. HuangZ. Combining near-infrared-excited autofluorescence and Raman spectroscopy improves in vivo diagnosis of gastric cancer.Biosens. Bioelectron.201126104104411010.1016/j.bios.2011.04.00521550225
    [Google Scholar]
  32. Wong Kee SongL.M. WilsonB.C. Endoscopic detection of early upper GI cancers.Best Pract. Res. Clin. Gastroenterol.200519683385610.1016/j.bpg.2005.04.00616338645
    [Google Scholar]
  33. AlmondL.M. HutchingsJ. LloydG. BarrH. ShepherdN. DayJ. StevensO. SandersS. WadleyM. StoneN. KendallC. Endoscopic Raman spectroscopy enables objective diagnosis of dysplasia in Barrett’s esophagus.Gastrointest. Endosc.2014791374510.1016/j.gie.2013.05.02823886354
    [Google Scholar]
  34. WeiY. ZhuY. WangM. Surface-enhanced Raman spectroscopy of gastric cancer serum with gold nanoparticles/silicon nanowire arrays.Optik (Stuttg.)2016127197902790710.1016/j.ijleo.2016.05.146
    [Google Scholar]
  35. Kalyan KumarK. AnandA. ChowdaryM.V.P. Keerthi KurienJ. Murali KrishnaC. MathewS. Discrimination of normal and malignant stomach mucosal tissues by Raman spectroscopy: A pilot study.Vib. Spectrosc.200744238238710.1016/j.vibspec.2007.03.007
    [Google Scholar]
  36. YaoH. TaoZ. AiM. PengL. WangG. HeB. LiY. Raman spectroscopic analysis of apoptosis of single human gastric cancer cells.Vib. Spectrosc.200950219319710.1016/j.vibspec.2008.11.003
    [Google Scholar]
  37. ChenY. DaiJ. ZhouX. LiuY. ZhangW. PengG. Raman spectroscopy analysis of the biochemical characteristics of molecules associated with the malignant transformation of gastric mucosa.PLoS One201494e9390610.1371/journal.pone.009390624710050
    [Google Scholar]
  38. KawabataT. MizunoT. OkazakiS. HiramatsuM. SetoguchiT. KikuchiH. YamamotoM. HiramatsuY. KondoK. BabaM. OhtaM. KamiyaK. TanakaT. SuzukiS. KonnoH. Optical diagnosis of gastric cancer using near-infrared multichannel Raman spectroscopy with a 1064-nm excitation wavelength.J. Gastroenterol.200843428329010.1007/s00535‑008‑2160‑218458844
    [Google Scholar]
  39. FengS. PanJ. WuY. LinD. ChenY. XiG. LinJ. ChenR. Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis.Sci. China Life Sci.201154982883410.1007/s11427‑011‑4212‑821809036
    [Google Scholar]
  40. XuM. MaJ. QuY. MaoW. ZhengR. Recognition of gastric cancer by raman spectroscopy.Proc. SPIE2009751975191H10.1117/12.845421
    [Google Scholar]
  41. IkedaH. ItoH. HikitaM. YamaguchiN. UragamiN. YokoyamaN. HirotaY. KushimaM. AjiokaY. InoueH. Raman spectroscopy for the diagnosis of unlabeled and unstained histopathological tissue specimens.World J. Gastrointest. Oncol.2018101143944810.4251/wjgo.v10.i11.43930487955
    [Google Scholar]
  42. GuoL. LiY. HuangF. DongJ. LiF. YangX. ZhuS. YangM. Identification and analysis of serum samples by surface-enhanced Raman spectroscopy combined with characteristic ratio method and PCA for gastric cancer detection.J. Innov. Opt. Health Sci.2019122195000310.1142/S1793545819500032
    [Google Scholar]
  43. QuanhongO. Based on serum Raman and Fluorescence spectra to diagnose liver cancer.202110.21203/rs.3.rs‑1118522/v1
    [Google Scholar]
  44. LinK. XuJ. LiL. LiaoF. DongX. LinJ. Label-free detection of liver cancer based on silver nanoparticles coated tissue surface-enhanced Raman spectroscopy.Laser Phys. Lett.2018151212560110.1088/1612‑202X/aae13c
    [Google Scholar]
  45. AndreouC. NeuschmeltingV. TschaharganehD.F. HuangC.H. OseledchykA. IaconoP. KarabeberH. ColenR.R. MannelliL. LoweS.W. KircherM.F. Imaging of liver tumors using surface-enhanced raman scattering nanoparticles.ACS Nano20161055015502610.1021/acsnano.5b0720027078225
    [Google Scholar]
  46. YuY. LinY. XuC. LinK. YeQ. WangX. XieS. ChenR. LinJ. Label-free detection of nasopharyngeal and liver cancer using surface-enhanced Raman spectroscopy and partial lease squares combined with support vector machine.Biomed. Opt. Express20189126053606610.1364/BOE.9.00605331065412
    [Google Scholar]
  47. XiaoR. ZhangX. RongZ. XiuB. YangX. WangC. HaoW. ZhangQ. LiuZ. DuanC. ZhaoK. GuoX. FanY. ZhaoY. JohnsonH. HuangY. FengX. XuX. ZhangH. WangS. Non-invasive detection of hepatocellular carcinoma serum metabolic profile through surface-enhanced Raman spectroscopy.Nanomedicine20161282475248410.1016/j.nano.2016.07.01427520725
    [Google Scholar]
  48. PoojariR. BhujbalM. HoleA. Murali KrishnaC. Distinct stratification of normal liver, hepatocellular carcinoma (HCC), and anticancer nanomedicine-treated- tumor tissues by Raman fingerprinting for HCC therapeutic monitoring.Nanomedicine20213310235210.1016/j.nano.2020.10235233418135
    [Google Scholar]
  49. ZhangK. HaoC. ManB. ZhangC. YangC. LiuM. PengQ. ChenC. Diagnosis of liver cancer based on tissue slice surface enhanced Raman spectroscopy and multivariate analysis.Vib. Spectrosc.201898828710.1016/j.vibspec.2018.07.010
    [Google Scholar]
  50. StaritzbichlerR. HunoldP. Estrela-LopisI. HildebrandP.W. IsermannB. KaiserT. Raman spectroscopy on blood serum samples of patients with end-stage liver disease.PLoS One2021169e025604510.1371/journal.pone.025604534492024
    [Google Scholar]
  51. WangQ. WangS. CuiS. YangD. HuangZ. XieS. Multivariate analysis of serum surface-enhanced Raman spectroscopy of liver cancer patients.J. Innov. Opt. Health Sci.2022155225003210.1142/S1793545822500328
    [Google Scholar]
  52. LiQ.B. SunX.J. XuY.Z. YangL.M. ZhangY.F. WengS.F. ShiJ.S. WuJ.G. Diagnosis of gastric inflammation and malignancy in endoscopic biopsies based on Fourier transform infrared spectroscopy.Clin. Chem.200551234635010.1373/clinchem.2004.03798615637129
    [Google Scholar]
  53. BunaciuA.A. HoangV.D. Aboul-EneinH.Y. Applications of FT-IR spectrophotometry in cancer diagnostics.Crit. Rev. Anal. Chem.201545215616510.1080/10408347.2014.90473325558776
    [Google Scholar]
  54. YiW. CuiD. LiZ. WuL. ShenA. HuJ. Gastric cancer differentiation using Fourier transform near-infrared spectroscopy with unsupervised pattern recognition.Spectrochim. Acta A Mol. Biomol. Spectrosc.201310112713110.1016/j.saa.2012.09.03723099170
    [Google Scholar]
  55. GulekenZ. BulutH. GültekinG.İ. ArıkanS. Yaylımİ. HakanM.T. SönmezD. TarhanN. DepciuchJ. Assessment of structural protein expression by FTIR and biochemical assays as biomarkers of metabolites response in gastric and colon cancer.Talanta202123112235310.1016/j.talanta.2021.12235333965021
    [Google Scholar]
  56. WangX. QiZ. LiuX. WangS. LiC. LiuG. XiongY. LiT. TaoJ. TianY. The comparison of hair from gastric cancer patients and from healthy persons studied by infrared microspectroscopy and imaging using synchrotron radiation.Cancer Epidemiol.201034445345610.1016/j.canep.2010.03.01620430715
    [Google Scholar]
  57. KM.G. BarzegariS. HajianP. ZhamH. MirzaeiH.R. ShiraziF.H. Diagnosis of normal and malignant human gastric tissue samples by FTIR spectra combined with mathematical models.J. Mol. Struct.2021122912949310.1016/j.molstruc.2020.129493
    [Google Scholar]
  58. ChenZ. ButkeR. MillerB. HitchcockC.L. AllenH.C. PovoskiS.P. MartinE.W.Jr CoeJ.V. Infrared metrics for fixation-free liver tumor detection.J. Phys. Chem. B201311741124421245010.1021/jp4073087
    [Google Scholar]
  59. Le NaourF. BraletM.P. DeboisD. SandtC. GuettierC. DumasP. BrunelleA. LaprévoteO. Chemical imaging on liver steatosis using synchrotron infrared and ToF-SIMS microspectroscopies.PLoS One2009410e740810.1371/journal.pone.000740819823674
    [Google Scholar]
  60. Diagnosis of liver cancer from blood sera using FTIR microspectroscopy: A preliminary study.J Biophotonics.201473-42223110.1002/jbio.201300183
    [Google Scholar]
  61. HuriB. Assessment of oxidative stress effects in serum determined by FT-IR spectroscopy in Cholangiocarcinoma patients.Biointerface Res. Appl. Chem.202213215110.33263/BRIAC132.151
    [Google Scholar]
  62. WangK. LiC. LiY. WangJ. MaA. RETRACTED: The application of hierarchy MoS 2 particles for NIR induced drug delivery towards liver cancer treatment.Mater. Res. Express202071010501410.1088/2053‑1591/abc21d
    [Google Scholar]
  63. LiuY. GaoB. FangC. SuS. YangX. TianJ. LiB. Application of near-infrared fluorescence imaging technology in liver cancer surgery.Surg. Innov.2021155335062199777710.1177/155335062199777733634713
    [Google Scholar]
  64. ChaotingZ. Intraoperative identification of liver cancer microfoci using a targeted near-infrared fluorescent probe for imaging-guided surgery.Sci. Rep.201610.1038/srep21959
    [Google Scholar]
/content/journals/cpa/10.2174/0115734129322567240821052326
Loading
/content/journals/cpa/10.2174/0115734129322567240821052326
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test