Comprehensive Treatment Uncertainty Analysis and PTV Margin Estimation for Fiducial Tracking in Robotic Liver Stereotactic Body Radiation Therapy.

OBJECTIVE: This study aims to quantify the uncertainties of CyberKnife Synchrony fiducial tracking for liver stereotactic body radiation therapy (SBRT) cases, and evaluate the required planning target volume (PTV) margins. METHODS: A total of 11 liver tumor patients with a total of 57 fractions, who underwent SBRT with synchronous fiducial tracking, were enrolled for the present study. The correlation/prediction model error, geometric error, and beam targeting error were quantified to determine the patient-level and fraction-level individual composite treatment uncertainties. The composite uncertainties and multiple margin recipes were compared for scenarios with and without rotation correction during treatment. RESULTS: The correlation model error-related uncertainty was 4.3±1.8, 1.4±0.5 and 1.8±0.7 mm in the superior-inferior (SI), left-right, and anterior-posterior directions, respectively. These were the primary contributors among all uncertainty sources. The geometric error significantly increased for treatments without rotation correction. The fraction-level composite uncertainties had a long tail distribution. Furthermore, the generally used 5-mm isotropic margin covered all uncertainties in the left-right and anterior-posterior directions, and only 75% of uncertainties in the SI direction. In order to cover 90% of uncertainties in the SI direction, an 8-mm margin would be needed. For scenarios without rotation correction, additional safety margins should be added, especially in the superior-inferior and anterior-posterior directions. CONCLUSION: The present study revealed that the correlation model error contributes to most of the uncertainties in the results. Most patients/fractions can be covered by a 5-mm margin. Patients with large treatment uncertainties might need a patient-specific margin.

FTO Prevents Thyroid Cancer Progression by SLC7A11 m6A Methylation in a Ferroptosis-Dependent Manner.

N6 methyladenosine (m6A) modification serves as a novel epigenetic regulatory mechanism that is heavily implicated in the heredity of tumors. Meanwhile, fat mass and obesity-associated protein (FTO) has the potential to affect the regulation of m6A modification in the mRNA of key oncogenes as well as tumor suppressor genes that facilitate tumor progression. In our study, FTO was downregulated in papillary thyroid carcinoma (PTC) tissues. The role of FTO in PTC was assessed by Cell Counting Kit-8 analysis, cell scratch, migration, invasion experiment, flow cytometry apoptosis analysis, and nude mouse experiment. In addition to RNA-Seq and meRIP-Seq, luciferase reporting and mutation analysis have also identified SLC7A11 as the potential FTO regulatory gene. Moreover, X-ray electron microscopy, glutathione (GSH)/oxidized GSH, GPX, malondialdehyde determination, and western blot helped confirmed that FTO inhibited the development of PTC by downregulating the expression of SLC7A11 through ferroptosis. Finally, a rescue experiment was employed to clarify the relationship between FTO and its specific target gene SLC7A11. FTO is able to inhibit the occurrence of PTC by downregulating SLC7A11 in m6A independently, and it functions as a tumor suppressor gene in PTC. These findings could contribute to our understanding of the tumor malignancy regulated by m6A and might lead to new insights for potential biomarkers and therapeutic targets for the treatment of thyroid papillary carcinoma.

Identification of prognostic biomarkers related to the tumor microenvironment in thyroid carcinoma.

Thyroid Carcinoma (THCA) is the most common endocrine tumor that is mainly treated using surgery and radiotherapy. In addition, immunotherapy is a recently developed treatment option that has played an essential role in the management of several types of tumors. However, few reports exist on the use of immunotherapy to treat THCA. The study downloaded the miRNA, mRNA and lncRNA data for THCA patients from the TCGA database ( https://portal.gdc.cancer.gov/ ). Thereafter, the tumor samples were divided into cold and hot tumors, based on the immune score of the tumor microenvironment. Moreover, the differentially expressed lncRNAs and miRNAs were obtained. Finally, the study jointly constructed a ceRNA network through differential analysis of the mRNA data for cold and hot tumors. The study first assessed the level of immune infiltration in the THCA tumor microenvironment then divided the samples into cold and hot tumors, based on the immune score. Additionally, a total of 568 up-regulated and 412 down-regulated DEGs were screened by analyzing the differences between hot and cold tumors. Thereafter, the study examined the differentially expressed genes for lncRNA and miRNA. The results revealed 629 differentially expressed genes related to lncRNA and 114 associated with miRNA. Finally, a ceRNA network of the differentially expressed genes was constructed. The results showed a five-miRNA hubnet, i.e., hsa-mir-204, hsa-mir-128, hsa-mir-214, hsa-mir-150 and hsa-mir-338. The present study identified the immune-related mRNA, lncRNA and miRNA in THCA then constructed a ceRNA network. These results are therefore important as they provide more insights on the immune mechanisms in THCA. The findings also provides additional information for possible THCA immunotherapy.

Using the Diaphragm as a Tracking Surrogate in CyberKnife Synchrony Treatment.

BACKGROUND In this study, we assessed the usefulness of diaphragm surrogate tracking in the design of a respiratory model for CyberKnife Synchrony treatment of lung tumors. MATERIAL AND METHODS Twenty-four patients with lung cancer who underwent stereotactic body radiotherapy with CyberKnife between April and November 2019 were enrolled. Simulation plans for each patient were designed using Xsight lung tracking (XLT) and diaphragm tracking (DT) methods, and tumor visualization tests were performed. The offset consistency at each respiratory phase was analyzed. The relative distance along the alignment center of the superior-inferior (SI) axis in the 2 projections (dxAB), uncertainty (%), and average standard error (AvgStdErr)/maximum standard error (MAXStdErr) were also analyzed. RESULTS Bland-Altman analyses revealed that the average differences±standard deviation (SD) between XLT and DT tracking methods were 0.4±2.9 mm, 0.3±4.35 mm, and -1.8±6.8 mm for the SI, left-right (LR), and anterior-posterior (AP) directions, respectively. These results indicated high consistency in the SI and LR directions and poor consistency in the AP direction. Uncertainty differed significantly between XLT and DT (22.813±5.721% vs 9.384±3.799%; t=-5.236; P=0.0008), but we found no significant differences in dxAB, AvgStdErr, or MAXStdErr. CONCLUSIONS In the majority of cases, motion tracking by XLT and DT was consistent and synchronized in the SI directions, but not in the LR and AP directions. With a boundary margin of 0.3±4.35 mm and 1.8±6.8 mm for the LR and AP directions, DT may contribute to better implementation of CyberKnife Synchrony treatment in patients with lung tumors near the diaphragm that cannot be seen in tumor visualization tests.

Optimized CyberKnife Lung Treatment: Effect of Fractionated Tracking Volume Change on Tracking Results.

OBJECTIVES: To explore the impact of volume change in the fractionated tracking of stereotactic radiotherapy on the results of synchronous, respiratory tracking algorithm using CyberKnife. METHODS: A total of 38 lung tumor patients receiving stereotactic radiotherapy at our center from March 2018 to October 2019 were counted. Photoshop CS4 image processing software was used to obtain the pixels and the average value of brightness of the tracking volume in the image and calculate the grayscale within the contour of the tracking volume on the real-time X-ray image. At the same time, parameters of the synchronous respiratory tracking algorithm of the fractional CyberKnife were extracted for comparison between the volume of image-guided image tracking and the number of fractions during stereotactic radiotherapy. We also analyzed the relationship between fraction tumor location and characteristics and the calculated results of synchronous respiratory tracking by CyberKnife. RESULTS: There were no significant differences between the first four fractions (p > 0.05) for left lung lesions and no significant differences between the first five fractions for right lung lesions (p ≥ 0.05). For peripheral lung cancer, longer fractional treatment led to greater variation in grayscale (G-A: >4 fractions p < 0.05), while for central lung cancer, longer fractional treatment led to greater variation in parameters of the synchronous respiratory tracking algorithm (Uncertainty A and Uncertainty B: >4 fractions p < 0.05). There was a significant correlation between radiotherapy-graded tumor density and relevant parameters, and the correlation was strong (>0.7, p < 0.05). CONCLUSION: With the increase of treatment fractions, the gray value in the patient tracking volume decreased. Patients of >4 fractions were advised to reevaluate with simulated CT and replan. For tumors with small diameter and low density, the imaging changes of volume should be closely followed during treatment. For left lung and central lung cancer, carefully select the synchronous tracking treatment with 2-view.

[Expression of aurora-A kinase in human lung cancer cell lines PG, A549, and NCI-H460].

BACKGROUND & OBJECTIVE: Recent researches found that Aurora-A overexpresses in various malignancies. This study was to detect the expression of Aurora-A in lung cancer cell lines PG (highly-metastatic giant cell lung cancer), A549 (lung adenocarcinoma), and NCI-H460 (large cell lung cancer) and explore its correlation to DNA content, provide a theoretical basis for screening tumor marker and molecular therapeutic target of lung cancer. METHODS: mRNA and protein levels of Aurora-A in PG, A549, and NCI-H460 cells were detected by reverse transcription-polymerase chain reaction(RT-PCR) and Western blot. Flow cytometry was used to analyze DNA contents in cell cycles of PG, A549, and NCI-H460 cells. RESULTS: mRNA level of Aurora-A was 1.14 in PG cells, 1.16 in A549 cells, and 0.84 in NCI-H460 cells, respectively; protein level of Aurora-A was 8.96 in PG cells, 21.13 in A549 cells, and 6.43 in NCI-H460 cells, respectively. The proportion of cells with tetraploid DNA was 19.88% in PG cells, 14.97% in A549 cells, and 10.6% in NCI-H460 cells, respectively (P<0.01); the proportion of cells with polyploid DNA was 2.66% in PG cells, 3.59% in A549 cells, and 2.30% in NCI-H460 cells, respectively. CONCLUSION: Aurora-A is overexpressed in the 3 lung cancer cell lines, but the mRNA levels are different.