Early Detection of Lung Cancer: A Call for Novel Biomarkers-Review

Clinical biomarkers for cancer recognition and prevention: A novel approach with optical measurements

Cancer is the most important cause of death worldwide, and early cancer detection is the most fundamental factor for efficacy of treatment, prognosis, and increasing survival rate. Over the years great effort has been devoted to discovering and testing new biomarkers that can improve its diagnosis, especially at an early stage. Here we report the potential usefulness of new, easily applicable, non-invasive and relatively low-cost clinical biomarkers, based on abnormalities of oral mucosa spectral reflectance and fractal geometry of the vascular networks in several different tissues, for identification of hereditary non-polyposis colorectal cancer carriers as well for detection of other tumors, even at an early stage. In the near future the methodology/technology of these procedures should be improved, thus making possible their applicability worldwide as screening tools for early recognition and prevention of cancer.

Imaging mass spectrometry: Towards clinical diagnostics

Imaging MS (IMS) has emerged as a powerful tool for biomarker discovery. A key advantage of this technique is its ability to probe the proteome directly from a tissue section with preservation of the spatial relationships of the sample and minimal sample preparation. This allows for direct correlation of protein expression with histology. Here, we present the latest developments in imaging MS and their relevance to clinical mass spectral analysis. IMS allows for high throughput analysis of tissue samples and is fully compatible with biostatistical analysis without prior knowledge of protein expression. Several studies are presented of applications in which direct tissue mass spectral analysis has provided insight into clinical questions not readily available by other means. Examples include the determination of lymph node status from investigation of primary breast tumors, prediction of response of breast tumors to chemotherapy, classification and prediction of progression of lung lesions, and exploration of 'molecular' margins in invasive disease.