Photon radiation therapy is a major curative treatment for cancer. However, the lack of robust predictive biomarkers for radiosensitivity precludes personalized radiation therapy. Clonogenic assays are the gold standard method for measuring the radiosensitivity of cancer cells. Although a large number of publications describe the use of clonogenic assays to measure cancer cell radiosensitivity, the robustness of results from different studies is unclear. To address this, we conducted a comprehensive detailed literature search of 256 common cancer cell lines and identified the eight cell lines most-frequently examined for photon sensitivity using clonogenic assays. Survival endpoints and experimental parameters from all 620 relevant experiments were compiled and analyzed. We found that the coefficients of variation for SF₂ (surviving fraction after 2 Gy irradiation) and for D₁₀ (dose that yields a surviving fraction of 10%) were below 30% for all cell lines, indicating that SF₂ and D₁₀ have acceptable inter-assay precision. These data support further analysis of published data on clonogenic assays using SF₂ and D₁₀ as survival endpoints, which facilitates robust identification of biological profiles representative of cancer cell sensitivity to photons.

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5′ single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4 ⁺ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type–specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type–resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

We aimed to clarify the accuracy of rigid image registration and deformable image registration (DIR) in carbon-ion radiotherapy (CIRT) for pancreatic cancer. Six patients with pancreatic cancer who were treated with passive irradiation CIRT were enrolled. Three registration patterns were evaluated: treatment planning computed tomography images (TPCT) to CT images acquired in the treatment room (IRCT) in the supine position, TPCT to IRCT in the prone position, and TPCT in the supine position to the prone position. After warping the contours of the original CT images to the destination CT images using deformation matrices from the registration, the warped delineated contours on the destination CT images were compared with the original ones using mean displacement to agreement (MDA). Four contours (clinical target volume (CTV), gross tumor volume (GTV), stomach, duodenum) and four registration algorithms (rigid image registration [RIR], intensity-based DIR [iDIR], contour-based DIR [cDIR], and a hybrid iDIR-cDIR ([hDIR]) were evaluated. The means ± standard deviation of the MDAs of all contours for RIR, iDIR, cDIR, and hDIR were 3.40 ± 3.30, 2.2 1± 2.48, 1.46 ± 1.49, and 1.46 ± 1.37 mm, respectively. There were significant differences between RIR and iDIR, and between RIR/iDIR and cDIR/hDIR. For the pancreatic cancer patient images, cDIR and hDIR had better accuracy than RIR and iDIR.

In carbon-ion radiotherapy for pancreatic cancer, altered dose distributions due to changes in the gastrointestinal gas volume and anatomy during irradiation are an unresolved therapeutic issue. We developed and investigated an adaptive strategy involving beam angle selection to improve dose distributions in pancreatic cancer. In the adaptive strategy, multiple beams were prepared with angles similar to those of the conventional strategy, and the beam that best reproduces the dose distribution of the treatment plan was used. The dose distributions of the adaptive strategy were compared with those of the conventional strategy for five patients. Patients underwent computed tomography (CT) before every irradiation. The adaptive strategy was evaluated using the same irradiation schedule as that of the conventional method and an adjusted method based on anatomical changes per fraction. Dose distributions on the pre-treatment CT and accumulated dose distributions on the treatment planning CT were evaluated using the volume receiving ≥95% of the prescription dose (V95) from the clinical target volume (CTV) between strategies. There were significant differences in the CTV V95 values for the pre-treatment CT between all strategies. The median (range) CTV V95 for the conventional strategy was 92.7% (87.1–96.1%), for the proposed adaptive strategy without adjusted schedules was 96.9% (95.1–97.8%), and for the proposed strategy with adjusted schedules was 97.8% (96.5–99.2%). The adaptive strategy can improve target coverage for the pre-treatment CT and accumulated dose distributions for the treatment planning CT without increasing the dose to critical organs.