A dual role for A-type lamins in DNA double-strand break repair.

A-type lamins are emerging as regulators of nuclear organization and function. Changes in their expression are associated with cancer and mutations are linked to degenerative diseases -laminopathies-. Although a correlation exists between alterations in lamins and genomic instability, the molecular mechanisms remain largely unknown. We previously found that loss of A-type lamins leads to degradation of 53BP1 protein and defective long-range non-homologous end-joining (NHEJ) of dysfunctional telomeres. Here, we determined how loss of A-type lamins affects the repair of short-range DNA double-strand breaks (DSBs) induced by ionizing radiation (IR). We find that lamins deficiency allows activation of the DNA damage response, but compromises the accumulation of 53BP1 at IR-induced foci (IRIF), hindering the fast phase of repair corresponding to classical-NHEJ. Importantly, reconstitution of 53BP1 is sufficient to rescue long-range and short-range NHEJ. Moreover, we demonstrate an unprecedented role for A-type lamins in the maintenance of homologous recombination (HR). Depletion of lamins compromises HR by a mechanism involving transcriptional downregulation of BRCA1 and RAD51 by the repressor complex formed by the Rb family member p130 and E2F4. In line with the DNA repair defects, lamins-deficient cells exhibit increased radiosensitivity. This study demonstrates that A-type lamins promote genomic stability by maintaining the levels of proteins with key roles in DNA DSBs repair by NHEJ and HR. Our results suggest that silencing of A-type lamins by DNA methylation in some cancers could contribute to the genomic instability that drives malignancy. In addition, lamins-deficient tumor cells could represent a good target for radiation therapy.

A novel PET tumor delineation method based on adaptive region-growing and dual-front active contours.

To more accurately and precisely delineate a tumor in a 3D PET image, we proposed a novel, semi-automatic, two-stage method by utilizing an adaptive region-growing algorithm and a dual-front active contour model. First, a rough region of interest (ROI) is manually drawn by a radiation oncologist that encloses a tumor. The voxel having the highest intensity in the ROI is chosen as a seed point. An adaptive region growing algorithm successively appends to the seed point all neighboring voxels whose intensities > = T of the mean of the current region. When T varies from 100% to 0%, a sharp volume increase, indicating the transition from the tumor to the background, always occurs at a certain T value. A preliminary tumor boundary is determined just before the sharp volume increase, which is found to be slightly outside of the known tumor in all tested phantoms. A novel dual-front active contour model utilizing region-based information is then applied to refine the preliminary boundary automatically. We tested the two-stage method on six spheres (0.5-20 ml) in a cylindrical container under different source to background ratios. Comparisons between the two-stage method and an iterative threshold method demonstrate its higher detection accuracy for small tumors (less than 6 ml). One patient study was tested and evaluated by two experienced radiation oncologists. The study illustrated that this two-stage method has several advantages. First, it does not require any threshold-volume curves, which are different and must be calibrated for each scanner and image reconstruction method. Second, it does not use any iso-threshold lines as contours. Third, the final result is reproducible and is independent of the manual rough ROIs. Fourth, this method is an adaptive algorithm that can process different images automatically.

18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate?

UNLABELLED: PET with (18)F-FDG has been used in radiation treatment planning for non-small cell lung cancer (NSCLC). Thresholds of 15%-50% the maximum standardized uptake value (SUV(max)) have been used for gross tumor volume (GTV) delineation by PET (PET(GTV)), with 40% being the most commonly used value. Recent studies indicated that 15%-20% may be more appropriate. The purposes of this study were to determine which threshold generates the best volumetric match to GTV delineation by CT (CT(GTV)) for peripheral NSCLC and to determine whether that threshold can be generalized to tumors of various sizes. METHODS: Data for patients who had peripheral NSCLC with well-defined borders on CT and SUV(max) of greater than 2.5 were reviewed. PET/CT datasets were reviewed, and a volume of interest was determined to represent the GTV. The CT(GTV) was delineated by using standard lung windows and reviewed by a radiation oncologist. The PET(GTV) was delineated automatically by use of various percentages of the SUV(max). The PET(GTV)-to-CT(GTV) ratios were compared at various thresholds, and a ratio of 1 was considered the best match, or the optimal threshold. RESULTS: Twenty peripheral NSCLCs with volumes easily defined on CT were evaluated. The SUV(max) (mean +/- SD) was 12 +/- 8, and the mean CT(GTV) was 198 cm(3) (97.5% confidence interval, 5-1,008). The SUV(max) were 16 +/- 5, 13 +/- 9, and 3.0 +/- 0.4 for tumors measuring greater than 5 cm, 3-5 cm, and less than 3 cm, respectively. The optimal thresholds (mean +/- SD) for the best match were 15% +/- 6% for tumors measuring greater than 5 cm, 24% +/- 9% for tumors measuring 3-5 cm, 42% +/- 2% for tumors measuring less than 3 cm, and 24% +/- 13% for all tumors. The PET(GTV) at the 40% and 20% thresholds underestimated the CT(GTV) for 16 of 20 and 14 of 20 lesions, respectively. The mean difference in the volumes (PET(GTV) minus CT(GTV) [PET(GTV) - CT(GTV)]) at the 20% threshold was 79 cm(3) (97.5% confidence interval, -922 to 178). The PET(GTV) at the 20% threshold overestimated the CT(GTV) for all 4 tumors measuring less than 3 cm and underestimated the CT(GTV) for all 6 tumors measuring greater than 5 cm. The CT(GTV) was inversely correlated with the PET(GTV) - CT(GTV) at the 20% threshold (R(2) = 0.90, P < 0.0001). The optimal threshold was inversely correlated with the CT(GTV) (R(2) = 0.79, P < 0.0001). CONCLUSION: No single threshold delineating the PET(GTV) provides accurate volume definition, compared with that provided by the CT(GTV), for the majority of NSCLCs. The strong correlation of the optimal threshold with the CT(GTV) warrants further investigation.