Epithelial cancers, including those of the skin and cervix, are the most common type of cancers in humans. Many recent studies have attempted to use Raman spectroscopy to diagnose these cancers. In this paper, Raman spectral markers related to the temporal and spatial effects of cervical and skin cancers are examined through four separate but related studies. Results from a clinical cervix study show that previous disease has a significant effect on the Raman signatures of the cervix, which allow for near 100&#x25; classification for discriminating previous disease versus a true normal. A Raman microspectroscopy study showed that Raman can detect changes due to adjacent regions of dysplasia or HPV that cannot be detected histologically, while a clinical skin study showed that Raman spectra may be detecting malignancy associated changes in tissues surrounding nonmelanoma skin cancers. Finally, results of an organotypic raft culture study provided support for both the skin and the in vitro cervix results. These studies add to the growing body of evidence that optical spectroscopy, in this case Raman spectral markers, can be used to detect subtle temporal and spatial effects in tissue near cancerous sites that go otherwise undetected by conventional histology.

Matthew D. Keller

Elizabeth M. Kanter

Chad A. Lieber

Shovan K. Majumder

Joanne Hutchings

Darrel L. Ellis

Richard B. Beaven

Nicholas Stone

Anita Mahadevan-Jansen

Detecting Temporal and Spatial Effects of Epithelial Cancers with Raman Spectroscopy

We report a pilot study designed to test elastic light-scattering (ELS) spectroscopy for characterizing normal, tumor, and tumor-infiltrated brain tissues. ELS spectra were measured from 393 sites on 36 ex vivo tissue specimen obtained from 29 patients. We employed and compared the performances of three methods of spectral classification for tissue characterization, including spectral slope analysis, principle component analysis (PCA), and artificial neural network (ANN) classification. The ANN classifier yielded the best correlation between spectral pattern and histopathological diagnosis, with a typical sensitivity of 80&#x25; and specificity of 93&#x25; for differentiating tumor from normal brain tissues. We also demonstrate that all three classification methods discriminate between tumor and normal tissue and have the potential to identify and quantitatively characterize tumor-infiltrated brain tissues.

Jianmin Gong

Ji Yi

Vladimir M. Turzhitsky

Kenji Muro

Xu Li

Characterization of Malignant Brain Tumor Using Elastic Light Scattering Spectroscopy

V. Backman

H. K. Roy

Optical Spectroscopic Markers of Cancer

Pancreatic cancer screening has been hampered by the high rate of complications associated with interrogating the pancreas. The closest non-invasively accessible mucosa available for pancreatic cancer screening is the periampullary duodenal tissue. Our earlier report has shown the potential of using optical markers to interrogate this tissue for the presence of pancreatic cancer. In this study, we report a larger data set of low-coherence enhanced backscattering (LEBS) and elastic light scattering fingerprinting (ELF) optical markers from the periampullary duodenal mucosa. Optical measurements from biopsy samples were acquired from a total of 203 patients with varying clinical classification including healthy controls, a family history of pancreatic cancer, pancreatitis, mucinous cystic precursor lesions, pancreatic cancer, and other pancreatic malignancies. Evaluation of the performance of an independent testing set for discriminating healthy control patients from pancreatic cancer patients showed a 95&#x25; sensitivity, 71&#x25; specificity, and 85&#x25; area under the receiver operator characteristic (AUROC) curve. Importantly, this performance was uncompromised for detecting potentially curable stages of the disease. Additionally, optical markers in higher risk populations such as family history and pancreatitis had values between those of healthy control and pancreatic cancer patients, thus allowing for future investigations of screening from these high risk groups.

Vladimir Turzhitsky

Yang Liu

Nahla Hasabou

Michael Goldberg

Hemant K. Roy

Vadim Backman

Randall Brand

Investigating Population Risk Factors of Pancreatic Cancer by Evaluation of Optical Markers in the Duodenal Mucosa

Light scattering spectroscopy measurements can be used to determine the structure of tissue samples. Through refined data acquisition and signal processing techniques, quantitative nuclear morphology measurements may be obtained from light scattering data. These data have been used primarily as a biomarker of neoplastic change in a wide range of settings. Here, we review the application of light scattering to assessing the health status of tissues drawn from animal models of carcinogenesis, in particular, the rat esophagus and the golden Syrian hamster trachea carcinogenesis models. In addition, we present results from ex vivo human tissues to demonstrate the relevance of the use of animal models which are excellent surrogates for several human cancers. These models provide the opportunity to develop biomarkers and test chemopreventive and therapy strategies before application in humans.

Adam Wax

John W. Pyhtila

In Situ Nuclear Morphology Measurements Using Light Scattering as Biomarkers of Neoplastic Change in Animal Models of Carcinogenesis

We have discovered quantitative optical biomarkers unique to cancer by developing a double-differential spectroscopic analysis method for near-infrared (NIR, 650&#x2013;1000 nm) spectra acquired non-invasively from breast tumors. These biomarkers are characterized by specific NIR absorption bands. The double-differential method removes patient specific variations in molecular composition which are not related to cancer, and reveals these specific cancer biomarkers. Based on the spectral regions of absorption, we identify these biomarkers with lipids that are present in tumors either in different abundance than in the normal breast or new lipid components that are generated by tumor metabolism. Furthermore, the O-H overtone regions (980&#x2013;1000 nm) show distinct variations in the tumor as compared to the normal breast. To quantify spectral variation in the absorption bands, we constructed the Specific Tumor Component (STC) index. In a pilot study of 12 cancer patients we found 100&#x25; sensitivity and 100&#x25; specificity for lesion identification. The STC index, combined with other previously described tissue optical indices, further improves the diagnostic power of NIR for breast cancer detection.

Shwayta Kukreti

Albert Cerussi

Bruce Tromberg

Enrico Gratton

Intrinsic Near-Infrared Spectroscopic Markers of Breast Tumors

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Disease Markers publishes papers related to the identification of disease markers, the elucidation of their role and mechanism, as well as their application in the prognosis, diagnosis and treatment of diseases.

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Chief Editor Paola Gazzaniga is an Associate Professor in the Department of Molecular Medicine at Sapienza University of Rome, Italy. Her core research focuses on liquid biopsies in patients with solid tumors.

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Disease Markers publishes papers related to the identification of disease markers, the elucidation of their role and mechanism, as well as their application in the prognosis, diagnosis and treatment of diseases.

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Disease Markers | Hindawi

Disease Markers

This Issue is now open for submissions.
Papers are published upon acceptance, regardless of the Special Issue publication date.

Disease Markers

Optical Spectroscopic Markers of Cancer

Optical Spectroscopic Markers of Cancer

Articles

Detecting Temporal and Spatial Effects of Epithelial Cancers with Raman Spectroscopy

Characterization of Malignant Brain Tumor Using Elastic Light Scattering Spectroscopy

Optical Spectroscopic Markers of Cancer

Investigating Population Risk Factors of Pancreatic Cancer by Evaluation of Optical Markers in the Duodenal Mucosa

In Situ Nuclear Morphology Measurements Using Light Scattering as Biomarkers of Neoplastic Change in Animal Models of Carcinogenesis

Intrinsic Near-Infrared Spectroscopic Markers of Breast Tumors