[Correlation studies of distinct mutational signatures with common cancer pathological subtyping].

It holds great promises to precisely stratify cancer subtypes to improve cancer diagnosis, therapy and prognosis. In the past, the diagnosis of pathological subtypes mainly relied on hematoxylin-eosin staining and immunohistochemistry. With the development of sequencing technologies, genotype and phenotype analysis of individuals has become possible and precision medicine is on the rise in healthcare. As different tumor subtypes have different cell-of-origin, risk factors and clinical phenotypes, they generate unique combinations of mutation types, termed "Mutational Signatures". Herein, using the exome sequencing data from The Cancer Genome Atlas (TCGA), we evaluated the utility of mutational landscape for differentiating cell-of-origin within three common cancers (kidney, lung and esophageal cancers). We found that mutational signatures predicted histological subtypes of kidney cancers, clear cell renal cell carcinoma (KIRC) vs. chromophobe renal cell carcinoma (KICH), which had different cell-of-origin, with 100% accuracy (95% CI: 0.93-1.00). The mutational signatures also predicted histological subtypes of lung cancers (lung adenocarcinoma vs. lung squamous cell carcinoma) and esophageal cancers (esophageal adenocarcinoma vs. esophageal squamous cell carcinoma) with 78% (95% CI: 0.66-0.86) and 84% accuracy (95% CI: 0.60-0.97), respectively. Collectively, mutational signatures-based subtyping is good at pathological classification, personalized diagnosis, especially early detection for common cancers.

Spatial variation of dosimetric leaf gap and its impact on dose delivery.

PURPOSE: During dose calculation, the Eclipse treatment planning system (TPS) retracts the multileaf collimator (MLC) leaf positions by half of the dosimetric leaf gap (DLG) value (measured at central axis) for all leaf positions in a dynamic MLC plan to accurately model the rounded leaf ends. The aim of this study is to map the variation of DLG along the travel path of each MLC leaf pair and quantify how this variation impacts delivered dose. METHODS: 6 MV DLG values were measured for all MLC leaf pairs in increments of 1.0 cm (from the line intersecting the CAX and perpendicular to MLC motion) to 13.0 cm off axis distance at dmax. The measurements were performed on two Varian linear accelerators, both employing the Millennium 120-leaf MLCs. The measurements were performed at several locations in the beam with both a Sun Nuclear MapCHECK device and a PTW pinpoint ion chamber. RESULTS: The measured DLGs for the middle 40 MLC leaf pairs (each 0.5 cm width) at positions along a line through the CAX and perpendicular to MLC leaf travel direction were very similar, varying maximally by only 0.2 mm. The outer 20 MLC leaf pairs (each 1.0 cm width) have much lower DLG values, about 0.3-0.5 mm lower than the central MLC leaf pair, at their respective central line position. Overall, the mean and the maximum variation between the 0.5 cm width leaves and the 1.0 cm width leaf pairs are 0.32 and 0.65 mm, respectively. CONCLUSIONS: The spatial variation in DLG is caused by the variation of intraleaf transmission through MLC leaves. Fluences centered on the CAX would not be affected since DLG does not vary; but any fluences residing significantly off axis with narrow sweeping leaves may exhibit significant dose differences. This is due to the fact that there are differences in DLG between the true DLG exhibited by the 1.0 cm width outer leaves and the constant DLG value utilized by the TPS for dose calculation. Since there are large differences in DLG between the 0.5 cm width leaf pairs and 1.0 cm width leaf pairs, there is a need to correct the TPS plans, especially those with high modulation (narrow dynamic MLC gap), with 2D variation of DLG.