The PDZ domain of the E protein in SARS-CoV induces carcinogenesis and poor prognosis in LUAD.

BACKGROUND: In both lung adenocarcinoma (LUAD) and severe acute respiratory syndrome (SARS), uncontrolled inflammation can be detected in lung tissue. The PDZ-binding motif (PBM) in the SARS-CoV-1 E protein has been demonstrated to be a virulence factor that induces a cytokine storm. METHODS: To identify gene expression fluctuations induced by PBM, microarray sequencing data of lung tissue infected with wild-type (SARS-CoV-1-E-wt) or recombinant virus (SARS-CoV-1-E-mutPBM) were analyzed, followed by functional enrichment analysis. To understand the role of the screened genes in LUAD, overall survival and immune correlation were calculated. RESULTS: A total of 12 genes might participate in the initial and developmental stages of LUAD through expression variation and mutation. Moreover, dysregulation of a total of 12 genes could lead to a poorer prognosis. In addition, the downregulation of MAMDC2 and ITGA8 by PBM could also affect patient prognosis. Although the conserved PBM (-D-L-L-V-) can be found at the end of the carboxyl terminus in multiple E proteins of coronaviruses, the specific function of each protein depends on the entire amino acid sequence. CONCLUSIONS: In summary, PBM containing the SARS-CoV-1 E protein promoted the carcinogenesis of LUAD by dysregulating important gene expression profiles and subsequently influencing the immune response and overall prognosis.

Feasibility of delta radiomics-based pCR prediction for rectal cancer patients treated with magnetic resonance-guided adaptive radiotherapy.

Magnetic resonance-guided adaptive radiotherapy (MRgART) represents the latest frontier in precision radiotherapy. It is distinguished from other modalities by the possibility of acquiring high-contrast soft tissue images, combined with the ability to recalculate and re-optimize the plan on the daily anatomy. The extensive database of available images offers ample scope for using disciplines such as radiomics to try to correlate features and outcomes. This study aimed to correlate the change of radiomics feature along the treatment to pathological complete response (pCR) for locally advanced rectal cancer (LARC) patients. Twenty-eight LARC patients undergoing neoadjuvant chemoradiotherapy (nCRT) with a short course (25 Gy, 5 Gy × 5f) MRgART at 1.5 Tesla MR-Linac were enrolled. The T2-weighted images acquired at each fraction, corresponding target delineation, pCR result of the surgical specimen, and clinical variables were collected. Seven families of features [First Order, Shape, Gray-level Co-occurrence Matrix (GLCM), Gray-level Dependence Matrix (GLDM), Gray-level Run Length Matrix (GLRLM), Gray-level Size Zone Matrix (GLSZM), and Neighborhood Gray Tone Difference Matrix (NGTDM)] were extracted, and delta features were calculated from the ratio of features of each successive fraction to those of the first fraction. Mann-Whitney U test and LASSO were utilized to reduce the dimension of features and select those features that are most significant to pCR. At last, the radiomics signatures were established by linear regression with the final set of features and their coefficients. A total of 581 radiomics features were extracted, and 2,324 delta features were calculated for each patient. Nineteen features and delta features, and one clinical variable (cN) were significant (p< 0.05) to pCR; seven predictive features were further selected and included in the linear regression to construct the radiomics signature significantly discriminating pCR and non-pCR groups (p< 0.05). Delta features based on MRI images acquired during a short course MRgART could potentially be used to predict treatment response in LARC patients undergoing nCRT.

Comprehensive Evaluation of a Deep Learning Model for Automatic Organs-at-Risk Segmentation on Heterogeneous Computed Tomography Images for Abdominal Radiation Therapy.

PURPOSE: Our purpose was to develop a deep learning model (AbsegNet) that produces accurate contours of 16 organs at risk (OARs) for abdominal malignancies as an essential part of fully automated radiation treatment planning. METHODS AND MATERIALS: Three data sets with 544 computed tomography scans were retrospectively collected. Data set 1 was split into 300 training cases and 128 test cases (cohort 1) for AbsegNet. Data set 2, including cohort 2 (n = 24) and cohort 3 (n = 20), were used to validate AbsegNet externally. Data set 3, including cohort 4 (n = 40) and cohort 5 (n = 32), were used to clinically assess the accuracy of AbsegNet-generated contours. Each cohort was from a different center. The Dice similarity coefficient and 95th-percentile Hausdorff distance were calculated to evaluate the delineation quality for each OAR. Clinical accuracy evaluation was classified into 4 levels: no revision, minor revisions (0% < volumetric revision degrees [VRD] ≤ 10%), moderate revisions (10% ≤ VRD < 20%), and major revisions (VRD ≥20%). RESULTS: For all OARs, AbsegNet achieved a mean Dice similarity coefficient of 86.73%, 85.65%, and 88.04% in cohorts 1, 2, and 3, respectively, and a mean 95th-percentile Hausdorff distance of 8.92, 10.18, and 12.40 mm, respectively. The performance of AbsegNet outperformed SwinUNETR, DeepLabV3+, Attention-UNet, UNet, and 3D-UNet. When experts evaluated contours from cohorts 4 and 5, 4 OARs (liver, kidney_L, kidney_R, and spleen) of all patients were scored as having no revision, and over 87.5% of patients with contours of the stomach, esophagus, adrenals, or rectum were considered as having no or minor revisions. Only 15.0% of patients with colon and small bowel contours required major revisions. CONCLUSIONS: We propose a novel deep-learning model to delineate OARs on diverse data sets. Most contours produced by AbsegNet are accurate and robust and are, therefore, clinically applicable and helpful to facilitate radiation therapy workflow.

Prognostic value of sarcopenia in patients with lung cancer treated with epidermal growth factor receptor tyrosine kinase inhibitors or immune checkpoint inhibitors.

Objectives: It remains controversial whether sarcopenia has any significant impact on the efficacy of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) or immune checkpoint inhibitors (ICIs) in patients with advanced non-small cell lung cancer (NSCLC). Therefore, in this study, we aimed to assess the association between sarcopenia and clinical outcomes in patients with advanced NSCLC receiving EGFR-TKIs or ICIs as a first-line therapy. Methods: We retrospectively enrolled 131 patients with advanced NSCLC treated with first-line EGFR-TKIs or ICIs between 1 March 2019 and 31 March 2021. To estimate sarcopenia, we calculated skeletal muscle index (SMI) as the ratio of skeletal muscle area (cm2) to height squared (m2). Associations between sarcopenia and overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan-Meier method and log-rank tests, respectively. A Cox proportional hazards regression model was used to assess the factors associated with OS and PFS. The Student's t-test or Mann-Whitney U test was used to compare the SMI between patients with or without objective response and disease control. The chi-squared test was used to compare adverse events (AEs) between patients with and without sarcopenia. Results: Among the 131 patients, 35 (26.7%) were diagnosed with sarcopenia. Sarcopenia was an independent predictor of poor OS and PFS (p < 0.05) overall and in the EGFR-TKI- and ICI-treated cohorts. Among all patients, those with sarcopenia showed significantly shorter OS and PFS than those without sarcopenia (median OS and PFS: 13.0 vs. 26.0 months and 6.4 vs. 15.1 months; both p < 0.001). These associations were consistent across the subtypes of most clinical characteristics. Statistically significant differences between the objective response (OR) and non-OR groups were also observed in the mean SMI (OR group, 43.89 ± 7.55 vs. non-OR group, 38.84 ± 7.11 cm2/m2; p < 0.001). In addition, we observed similar results with disease control (DC) and non-DC groups (DC group, 42.46 ± 7.64 vs. non-DCR group, 33.74 ± 4.31 cm2/m2; p < 0.001). The AEs did not differ significantly between the sarcopenia and non-sarcopenia groups. Conclusion: Sarcopenia before treatment might be a significant predictor of poor clinical outcomes (shorter OS and PFS, fewer ORs, less DC) in patients with advanced NSCLC treated with EGFR-TKIs or ICIs as the first-line therapy.

Efficacy and safety of PLDR-IMRT for the re-irradiation of recurrent NPC: A prospective, single-arm, multicenter trial.

Salvage treatment of locoregionally recurrent nasopharyngeal carcinoma (NPC) requires weighing the benefits of re-irradiation against increased risks of toxicity. Here, we evaluated the outcomes of patients treated with intensity-modulated-based pulsed low-dose-rate radiotherapy (PLDR-IMRT) to enhance the curative effect of salvage treatment and reduce RT-related SAEs. A prospective clinical trial was conducted from March 2018 to March 2020 at multiple institutions. NPC patients who experienced relapse after radical therapy were re-irradiated with a median dose of 60 Gy (50.4-70 Gy)/30 f (28-35 f) using PLDR-IMRT. Thirty-six NPC patients who underwent PLDR-IMRT for locoregional recurrence were identified. With a median follow-up of 26.2 months, the objective response rate (ORR) of the entire cohort was 91.6%. The estimated mPFS duration was 28 months (95% CI: 24.9-31.1), and the estimated mLRFS duration was 30.4 months (95% CI: 25.2-35.5). The overall survival (OS) rate for all patients was 80.6%, the progression-free survival (PFS) rate was 75% and the cancer-specific survival (CSS) rate was 88.9% at 1 year. The LRFS and DMFS rates were 88.9% and 91.7%, respectively, at 1 year. A combination of systematic therapies could provide survival benefits to patients who experience NPC relapse (p < 0.05), and a Karnofsky performance status (KPS) score of ≥90 was a favorable factor for local control (p < 0.05). The incidence of acute SAEs (grade 3+) from PLDR was 22.2%, and the incidence of chronic SAEs was 19.4% among all patients. PLDR-IMRT combined with systematic therapy can effectively treat patients with locoregionally recurrent nasopharyngeal carcinoma and causes fewer adverse events than the rates expected with IMRT.

Ginsenoside Rg5 enhances the radiosensitivity of lung adenocarcinoma via reducing HSP90-CDC37 interaction and promoting client protein degradation.

Ginsenoside Rg5 is a rare ginsenoside showing promising tumor-suppressive effects. This study aimed to explore its radio-sensitizing effects and the underlying mechanisms. Human lung adenocarcinoma cell lines A549 and Calu-3 were used for in vitro and in vivo analysis. Bioinformatic molecular docking prediction and following validation by surface plasmon resonance (SPR) technology, cellular thermal shift assay (CETSA), and isothermal titration calorimetry (ITC) were conducted to explore the binding between ginsenoside Rg5 and 90 kD heat shock protein alpha (HSP90α). The effects of ginsenoside Rg5 on HSP90-cell division cycle 37 (CDC37) interaction, the client protein stability, and the downstream regulations were further explored. Results showed that ginsenoside Rg5 could induce cell-cycle arrest at the G1 phase and enhance irradiation-induced cell apoptosis. It could bind to HSP90α with a high affinity, but the affinity was drastically decreased by HSP90α Y61A mutation. Co-immunoprecipitation (Co-IP) and ITC assays confirmed that ginsenoside Rg5 disrupts the HSP90-CDC37 interaction in a dose-dependent manner. It reduced irradiation-induced upregulation of the HSP90-CDC37 client proteins, including SRC, CDK4, RAF1, and ULK1 in A549 cell-derived xenograft (CDX) tumors. Ginsenoside Rg5 or MRT67307 (an IKKε/TBK1 inhibitor) pretreatment suppressed irradiation-induced elevation of the LC3-II/ß ratio and restored irradiation-induced downregulation of p62 expression. In A549 CDX tumors, ginsenoside Rg5 treatment suppressed LC3 expression and enhanced irradiation-induced DNA damage. In conclusion, ginsenoside Rg5 may be a potential radiosensitizer for lung adenocarcinoma. It interacts with HSP90α and reduces the binding between HSP90 and CDC37, thereby increasing the ubiquitin-mediated proteasomal degradation of the HSP90-CDC37 client proteins.

Post-treatment serum triglyceride: An effective biomarker for body fat mass and overall survival in esophageal squamous cell cancer patients treated with chemoradiotherapy.

Objectives: Although lipids have been assessed for their possible roles in cancer survival prediction, studies on the association between serum triglyceride (TG) levels and the prognosis of esophageal squamous cell carcinoma (ESCC) patients are limited. This study aimed to evaluate whether serum TG is associated with outcomes in patients with ESCC and investigate any interaction between serum TG and clinical parameters, especially body fat mass. Materials and methods: We conducted a prospective case study on patients diagnosed with ESCC between March 2012 and November 2018. We measured patients' serum TG levels before and after treatment. The association between serum TG and overall survival (OS) was evaluated using hazard ratios. We sought to determine a threshold point using optimal stratification. Survival analysis was performed using Kaplan-Meier curves and a Cox proportional hazards model. Results: Of the 257 participants diagnosed with ESCC, 200 (77.8%) were men. Median follow-up time was 22.4 months (range 3.3-92.4 months). Using univariate Cox proportional hazard analysis and subsequent multivariate analysis, post-TG levels, Karnofsky performance scores, T stages, and chemotherapy cycles were shown to be independent prognostic factors for OS (p < 0.05). The post-TG cut-off point to best classify patients with respect to time to mortality was 1.47 mmol/L. A post-TG level of ≥ 1.47 mmol/L could independently predict a better OS (hazard ratio: 0.55, 95% confidence interval: 0.37-0.79). The associations were consistent across the subtypes of clinical parameters. Furthermore, the post-body mass index, post-subcutaneous adipose tissue area, post-visceral adipose tissue area, post-total adiposity tissue area, and post-total adipose density exhibited a strong positive association with post-TG levels. Conclusion: Post-TG levels were found to be a significant positive prognostic biomarker for body fat mass and OS in ESCC patients.

Lymph drainage and cervical fascia anatomy-oriented differential nodal CTV delineation at the supraclavicular region for esophageal cancer and nasopharyngeal cancer.

PURPOSE: To determine the differences in supraclavicular lymph node metastasis between esophageal cancer (EC) and nasopharyngeal cancer (NPC) and explore the feasibility of differential supraclavicular clinical target volume (CTV) contouring between these two diseases based on the involvement of different fascial spaces. MATERIALS AND METHODS: One hundred patients with supraclavicular nodes positive for EC or NPC were enrolled, and their pre-treatment images were reviewed. The distribution patterns of nodes between the two diseases were compared in the context of node levels defined by the 2017 Japanese Esophageal Society and 2013 International Consensus on Cervical Lymph Node Level Classification. Grouping supraclavicular nodes based on sub-compartments formed by the cervical fascia was discussed, and the feasibility of differential CTV contouring based on the differences in the involvement of these sub-compartments between EC and NPC was explored. RESULTS: The 2013 Consensus on cervical node levels and 2017 Japanese Esophageal Society node station could not practically guide supraclavicular CTV contouring. We divided the supraclavicular space into six sub-compartments: the para-esophageal space (PES), carotid sheath space (CSS), sub-thyroid pre-trachea space (STPTS), pre-vascular space (PVS), and vascular lateral space (VLS) I and II. EC mainly spread to the PES, STPTS, CSS, and VLS I, whereas NPC tended to spread to the CSS, VLS I, and VLS II. These combinations of sub-compartments may help constitute the supraclavicular CTVs for EC and NPC. CONCLUSIONS: The fascia anatomy-based sub-compartments sufficiently distinguished metastasis to the supraclavicular space between EC and NPC, thus facilitating differential CTV contouring between these two diseases.

Level Ib CTV delineation in nasopharyngeal carcinoma based on lymph node distribution and topographic anatomy.

BACKGROUND AND PURPOSE: To analyze the distribution pattern of lymph nodes (LNs) metastasis of level Ib in nasopharyngeal cancer (NPC) and propose shrinkage of clinical target volume (CTV) boundaries to avoid unnecessary radiation for some space with very low-risk of involvement. MATERIALS AND METHODS: Pretreatment images of pathologically proven NPC patients were reviewed and those with positive level Ib LN metastasis was enrolled. The geometric center of each level Ib LN in the neck was marked on a template CT. The spatial relationship of nodes with key structures in level Ib was analyzed. Modified level Ib CTV according to the 2013 International CTV consensus was proposed based on the LN distribution pattern. A PlanIQ Feasibility DVH module was implemented to evaluate the feasibility analysis of the best possible sparing of organs at risk (OAR) with modified Ib CTV. RESULTS: A total of 1518 NPC patients were reviewed and 54 with positive level Ib nodes were enrolled. Four sub-level anatomical regions were defined within the gross area of level Ib. Of 106 positive nodes identified, none, one, 88, and 17 were found in the intraglandular (IG), medial mandibular (MM), supra perivascular (SP), and infra perivascular (IP) sub-level, respectively. This study proposes sparing the IG and MM sub-level and including the area within a specified distance from the submandibular gland (11 mm for SP, 17 mm for IP) for CTV coverage. Compared with planning based on CTV-consensus, planning based on CTV-proposed results in a significantly reduced CTV volume, and mean dose (Dmean) of both the ipsilateral SMG and bilateral SLG. CONCLUSIONS: Based on detailed analysis of the relationship between positive node distribution and several important anatomical structures, modified level Ib CTV for prophylactic irradiation was proposed to reduce the dose of OAR irradiation.

Automatic Delineation of Gross Tumor Volume Based on Magnetic Resonance Imaging by Performing a Novel Semisupervised Learning Framework in Nasopharyngeal Carcinoma.

PURPOSE: We aimed to validate the accuracy and clinical value of a novel semisupervised learning framework for gross tumor volume (GTV) delineation in nasopharyngeal carcinoma. METHODS AND MATERIALS: Two hundred fifty-eight patients with magnetic resonance imaging data sets were divided into training (n = 180), validation (n = 20), and testing (n = 58) cohorts. Ground truth contours of nasopharynx GTV (GTVnx) and node GTV (GTVnd) were manually delineated by 2 experienced radiation oncologists. Twenty percent (n = 36) labeled and 80% (n = 144) unlabeled images were used to train the model, producing model-generated contours for patients from the testing cohort. Nine experienced experts were invited to revise model-generated GTV in 20 randomly selected patients from the testing cohort. Six junior oncologists were asked to delineate GTV in 12 randomly selected patients from the testing cohort without and with the assistance of the model, and revision degrees were compared under these 2 modes. The Dice similarity coefficient (DSC) was used to quantify the accuracy of the model. RESULTS: The model-generated contours showed a high accuracy compared with ground truth contours, with an average DSC score of 0.83 and 0.80 for GTVnx and GTVnd, respectively. There was no significant difference in DSC score between T1-2 and T3-4 patients (0.81 vs 0.83; P = .223), or between N1-2 and N3 patients (0.80 vs 0.79; P = .807). The mean revision degree was lower than 10% in 19 (95%) patients for GTVnx and in 16 (80%) patients for GTVnd. With assistance of the model, the mean revision degree for GTVnx and GTVnd by junior oncologists was reduced from 25.63% to 7.75% and from 21.38% to 14.44%, respectively. Meanwhile, the delineating efficiency was improved by over 60%. CONCLUSIONS: The proposed semisupervised learning-based model showed a high accuracy for delineating GTV of nasopharyngeal carcinoma. It was clinically applicable and could assist junior oncologists to improve GTV contouring accuracy and save contouring time.