Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Interobserver delineation uncertainty in involved-node radiation therapy (INRT) for early-stage Hodgkin lymphoma: on behalf of the Radiotherapy Committee of the EORTC lymphoma group

BACKGROUND AND PURPOSE: In early-stage classical Hodgkin lymphoma (HL) the target volume nowadays consists of the volume of the originally involved nodes. Delineation of this volume on a post-chemotherapy CT-scan is challenging. We report on the interobserver variability in target volume definition and its impact on resulting treatment plans. MATERIALS AND METHODS: Two representative cases were selected (1: male, stage IB, localization: left axilla; 2: female, stage IIB, localizations: mediastinum and bilateral neck). Eight experienced observers individually defined the clinical target volume (CTV) using involved-node radiotherapy (INRT) as defined by the EORTC-GELA guidelines for the H10 trial. A consensus contour was generated and the standard deviation computed. We investigated the overlap between observer and consensus contour [Sørensen-Dice coefficient (DSC)] and the magnitude of gross deviations between the surfaces of the observer and consensus contour (Hausdorff distance). 3D-conformal (3D-CRT) and intensity-modulated radiotherapy (IMRT) plans were calculated for each contour in order to investigate the impact of interobserver variability on each treatment modality. Similar target coverage was enforced for all plans. RESULTS: The median CTV was 120 cm(3) (IQR: 95-173 cm(3)) for Case 1, and 255 cm(3) (IQR: 183-293 cm(3)) for Case 2. DSC values were generally high (>0.7), and Hausdorff distances were about 30 mm. The SDs between all observer contours, providing an estimate of the systematic error associated with delineation uncertainty, ranged from 1.9 to 3.8 mm (median: 3.2 mm). Variations in mean dose resulting from different observer contours were small and were not higher in IMRT plans than in 3D-CRT plans. CONCLUSIONS: We observed considerable differences in target volume delineation, but the systematic delineation uncertainty of around 3 mm is comparable to that reported in other tumour sites. This report is a first step towards calculating an evidence-based planning target volume margin for INRT in HL