Exploring the efficacy and cellular uptake of sorafenib in colon cancer cells by Raman micro-spectroscopy.

In recent years, many subcellular proteins have emerged as promising therapeutic targets in oncology. One crucial target is the epidermal growth factor receptor. Inhibition of this receptor has significantly improved the survival rate of patients for many cancers. However, oncogenic mutations such as B-RAFV600E have rendered tumours resistant to this therapeutic approach. Therefore, this mutation has emerged as a potential target for cancer therapy. Sorafenib is developed to overcome the B-RAFV600E mutation and restore the response of the mutated tumour to therapy. Here, we explore the efficacy and distribution of sorafenib at a cellular level using colon cancer cell lines with B-RAFV600E or K-RASG12V mutations. The Raman results detected significant sorafenib-induced spectral differences in both cell lines. In addition, the western blot and real-time cell analysis in vitro assays revealed that the ERK phosphorylation and the cellular proliferation of cells are inhibited, respectively, in the sorafenib-treated cells. Thus, the observed Raman spectral changes illustrate the potent effect of sorafenib on cells despite the presence of the B-RAFV600E or K-RASG12V mutations. These results are in agreement with the clinical studies, where patients with the B-RAFV600E mutation respond to sorafenib. Furthermore, the Raman spectral imaging results have shown the uptake and the distribution of sorafenib in colon cancer cells with the B-RAFV600E mutation through its label-free marker bands in the fingerprint region. The present results of sorafenib efficacy and distribution in cells demonstrate the potential of Raman micro-spectroscopy as the in vitro assay for the assessment of drugs, which is important in drug discovery.

Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach.

Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.

Virtual staining of colon cancer tissue by label-free Raman micro-spectroscopy.

The great capability of the label-free classification of tissue via vibrational spectroscopy, like Raman or infrared imaging, is shown in numerous publications (review: Diem et al., J. Biophotonics, 2013, 6, 855-886). Herein, we present a new approach, virtual staining, that improves the Raman spectral histopathology (SHP) images of colorectal cancer tissue by combining the integrated Raman intensity image in the C-H stretching region (2800-3050 cm-1) with the pseudo-colour Raman image. This allows the display of fine structures such as the filamentous composition of muscle tissue. The morphology of the virtually stained images is in agreement with the gold standard in medical diagnosis, the haematoxylin-eosin staining. The virtual staining image also represents the whole biochemical fingerprint, and several tissue components including carcinoma were identified automatically with high sensitivity and specificity. For fast tissue classifications, a similar approach was applied on coherent anti-Stokes Raman scattering (CARS) spectral data that is faster and therefore potentially more suitable for clinical applications.