Efgartigimod as a novel FcRn inhibitor for autoimmune disease

Immunoglobulin G (IgG) autoantibodies can lead to the formation of autoimmune diseases through Fab and/or Fc-mediated interactions with host molecules as well as activated T cells. The neonatal Fc receptor (FcRn) binds at acidic pH IgG and albumin, and the mechanism for prolonging serum IgG half-life is making IgG re-entry into circulation by prompting it not to be degraded by lysosomes and back to the cell surface. Given the FcRn receptor's essential role in IgG homeostasis, one of the strategies to promote the quick degradation of endogenous IgG is to suppress the function of FcRn, which is beneficial to the treatment of IgG-driven autoimmune disorders like myasthenia gravis (MG), chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), stiff person syndrome, and immune thrombocytopenia (ITP). We elaborately read the literature about efgartigimod and systematically reviewed the research progress and clinical application of this novel FcRn inhibitor in autoimmune diseases. Efgartigimod is the firstly FcRn antagonist developed and was approved on 17 December 2021 by the United States for the therapy of acetylcholine receptor-positive MG. In January 2022, efgartigimod received its second regulatory approval in Japan. In addition, the market authorization application in Europe was submitted and validated in August 2021. China's National Medical Products Administration officially accepted the marketing application of efgartigimod on July 13, 2022. To suppress the function of FcRn, which is beneficial to the treatment of IgG-driven autoimmune disorders like MG, CIDP, ITP, and stiff person syndrome. We review the rationale, clinical evidence, and future perspectives of efgartigimod for the treatment of autoimmune disease.

Bulk and single-cell RNA sequencing analysis with 101 machine learning combinations reveal neutrophil extracellular trap involvement in hepatic ischemia-reperfusion injury and early allograft dysfunction

BACKGROUND

Hepatic ischaemia-reperfusion injury (HIRI) is a major clinical concern during the perioperative period and is closely associated with early allograft dysfunction (EAD), acute rejection (AR) and long-term graft survival. Neutrophil extracellular traps (NETs) are extracellular structures formed by the release of decondensed chromatin and granular proteins following neutrophil stimulation. There is growing evidence that NETs are involved in the progression of various liver transplantation complications, including ischaemia-reperfusion injury (IRI). This study aimed to comprehensively analyse the expression patterns of NET-related genes (NRGs) in HIRI, identify HIRI subtypes with distinct characteristics, and develop a reliable EAD prediction model.

METHODS

Microarray, bulk RNA-seq, and single-cell sequencing datasets were obtained from the GEO database. Initially, differentially expressed NRGs (DE-NRGs) were identified using differential gene expression analyses. We then utilised a non-negative matrix factorisation (NMF) algorithm to classify HIRI samples. Subsequently, we employed machine learning algorithms to screen the hub NRGs related to EAD and developed an EAD prediction model based on these hub NRGs. Concurrently, we assessed the expression patterns of hub NRGs at the single-cell level using the HIRI. Additionally, we validated C5AR1 expression and its effect on HIRI and NETs formation in a rat orthotopic liver transplantation (OLT) model.

RESULTS

In this study, we identified 11 DE-NRGs in the HIRI context. Based on these 11 DE-NRGs, HIRI samples were classified into two distinct clusters. Cluster1 exhibited a low expression of DE-NRGs, minimal neutrophil infiltration, mild inflammation, and a low incidence of EAD. Conversely, Cluster2 displayed the opposite phenotype, with an activated inflammatory subtype and a higher incidence of EAD. Furthermore, an EAD prediction model was developed using the four hub NRGs associated with EAD. Based on risk scores, HIRI samples were classified into high- and low-risk groups. The OLT model confirmed substantial upregulation of C5AR1 expression in the liver tissue, accompanied by increased formation of NETs. Treatment with a C5AR1 antagonist improved liver function, reduced tissue inflammation, and decreased NETs formation.

CONCLUSIONS

This study distinguished two apparent HIRI subtypes, established a predictive model for EAD, and validated the effect of C5AR1 on HIRI. These findings provide novel perspectives for the development of advanced clinical strategies to enhance the outcomes of liver transplant recipients.

Consistency of Monoenergetic Attenuation Measurements for a Clinical Dual-Source Photon-Counting Detector CT System Across Scanning Paradigms: A Phantom Study

Background: Use of virtual monoenergetic images (VMIs) from multi-energy CT scans can mitigate inconsistencies in traditional attenuation measurements that result from variation in scan-related factors. Photon-counting detector (PCD) CT systems produce VMIs as standard image output under flexible scanning conditions. Objective: To evaluate the consistency of monoenergetic attenuation measurements obtained from a clinical PCD CT scanner across a spectrum of scanning paradigms. Methods: A phantom with ten tissue-simulating inserts was imaged using a clinical dual-source PCD CT scanner. Nine scanning paradigms were obtained across combinations of tube voltages (90, 120, and 140 kVp) and image quality (IQ) levels (80, 145, and 180). Images were reconstructed at VMI levels of 50, 60, 70, and 80 keV. Consistency of attenuation measurements was assessed, using the 120-kVp IQ-145 scanning paradigm as the reference scan. Results: For all scanning paradigms, attenuation measurements showed intraclass correlation ≥0.999 with respect to the reference scan. Across inserts, mean bias relative to the reference scan ranged from -14.9 to 13.6 HU, -2.7 to 1.7 HU, and -3.9 to 3.8 HU at tube voltages of 90, 120, and 140 kVp; and from -14.9 to 13.6 HU, -6.4 to 3.8, -3.7 to 1.4, and -7.2 to 4.3 HU at VMI levels of 50, 60, 70, and 80 keV. Thus, mean bias did not exceed 5 HU for any insert at tube potentials of 120 kVp and 140 kVp, nor for any insert at a VMI level of 70 keV. At a VMI level of 50 keV and tube potential of 90 kVp, mean bias exceeded 5 HU for 14 of 30 possible combinations of inserts and scanning paradigms, and exceeded 10 HU for 4 of 30 such combinations. At VMI levels of both 60 and 80 keV, mean bias exceeded 5 HU for only two combinations of inserts and scanning paradigms, all at a tube potential of 90 kVp. Conclusion: PCD CT generally provided consistent attenuation measurements across combinations of scanning paradigms and VMI levels. Clinical Impact: PCD CT may facilitate quantitative applications of CT data in clinical practice.

Accelerating Sulfur Redox Kinetics by Electronic Modulation and Drifting Effects of Pre-Lithiation Electrocatalysts

Efficient catalyst design is crucial for addressing the sluggish multi-step sulfur redox reaction (SRR) in lithium-sulfur batteries (LiSBs), which are among the promising candidates for the next-generation high-energy-density storage systems. However, the limited understanding of the underlying catalytic kinetic mechanisms and the lack of precise control over catalyst structures pose challenges in designing highly efficient catalysts, which hinder the LiSBs' practical application. Here, drawing inspiration from the theoretical calculations, the concept of precisely controlled pre-lithiation SRR electrocatalysts is proposed. The dual roles of channel and surface lithium in pre-lithiated 1T'-MoS2 are revealed, referred to as the "electronic modulation effect" and "drifting effect", respectively, both of which contribute to accelerating the SRR kinetics. As a result, the thus-designed 1T'-Lix MoS2 /CS cathode obtained by epitaxial growth of pre-lithiated 1T'-MoS2 on cubic Co9 S8 exhibits impressive performance with a high initial specific capacity of 1049.8 mAh g-1 , excellent rate-capability, and remarkable long-term cycling stability with a decay rate of only 0.019% per cycle over 1000 cycles at 3 C. This work highlights the importance of precise control in pre-lithiation parameters and the synergistic effects of channel and surface lithium, providing new valuable insights into the design and optimization of SRR electrocatalysts for high-performance LiSBs.

In maize, co-expression of GAT and GR79-EPSPS provides high glyphosate resistance, along with low glyphosate residues

Herbicide tolerance has been the dominant trait introduced during the global commercialization of genetically modified (GM) crops. Herbicide-tolerant crops, especially glyphosate-resistant crops, offer great advantages for weed management; however, despite these benefits, glyphosate-resistant maize (Zea mays L.) has not yet been commercially deployed in China. To develop a new bio-breeding resource for glyphosate-resistant maize, we introduced a codon-optimized glyphosate N-acetyltransferase gene, gat, and the enolpyruvyl-shikimate-3-phosphate synthase gene, gr79-epsps, into the maize variety B104. We selected a genetically stable high glyphosate resistance (GR) transgenic event, designated GG2, from the transgenic maize population through screening with high doses of glyphosate. A molecular analysis demonstrated that single copy of gat and gr79-epsps were integrated into the maize genome, and these two genes were stably transcribed and translated. Field trials showed that the transgenic event GG2 could tolerate 9000 g acid equivalent (a.e.) glyphosate per ha with no effect on phenotype or yield. A gas chromatography-mass spectrometry (GC-MS) analysis revealed that, shortly after glyphosate application, the glyphosate (PMG) and aminomethylphosphonic acid (AMPA) residues in GG2 leaves decreased by more than 90% compared to their levels in HGK60 transgenic plants, which only harbored the epsps gene. Additionally, PMG and its metabolic residues (AMPA and N-acetyl-PMG) were not detected in the silage or seeds of GG2, even when far more than the recommended agricultural dose of glyphosate was applied. The co-expression of gat and gr79-epsps, therefore, confers GG2 with high GR and a low risk of herbicide residue accumulation, making this germplasm a valuable GR event in herbicide-tolerant maize breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-023-00114-8.

Prostate cancer detection and segmentation on MRI using non-local mask R-CNN with histopathological ground truth

BACKGROUND

Automatic detection and segmentation of intraprostatic lesions (ILs) on preoperative multiparametric-magnetic resonance images (mp-MRI) can improve clinical workflow efficiency and enhance the diagnostic accuracy of prostate cancer and is an essential step in dominant intraprostatic lesion boost.

PURPOSE

The goal is to improve the detection and segmentation accuracy of 3D ILs in MRI by a proposed a deep learning (DL)-based algorithm with histopathological ground truth.

METHODS

This retrospective study included 262 patients with in vivo prostate biparametric MRI (bp-MRI) scans and were divided into three cohorts based on their data analysis and annotation. Histopathological ground truth was established by using histopathology images as delineation reference standard on cohort 1, which consisted of 64 patients and was randomly split into 20 training, 12 validation, and 32 testing patients. Cohort 2 consisted of 158 patients with bp-MRI based lesion delineation, and was randomly split into 104 training, 15 validation, and 39 testing patients. Cohort 3 consisted of 40 unannotated patients, used in semi-supervised learning. We proposed a non-local Mask R-CNN and boosted its performance by applying different training techniques. The performance of non-local Mask R-CNN was compared with baseline Mask R-CNN, 3D U-Net and an experienced radiologist's delineation and was evaluated by detection rate, dice similarity coefficient (DSC), sensitivity, and Hausdorff Distance (HD).

RESULTS

The independent testing set consists of 32 patients with histopathological ground truth. With the training technique maximizing detection rate, the non-local Mask R-CNN achieved 80.5% and 94.7% detection rate; 0.548 and 0.604 DSC; 5.72 and 6.36 95 HD (mm); 0.613 and 0.580 sensitivity for ILs of all Gleason Grade groups (GGGs) and clinically significant ILs (GGG > 2), which outperformed baseline Mask R-CNN and 3D U-Net. For clinically significant ILs, the model segmentation accuracy was significantly higher than that of the experienced radiologist involved in the study, who achieved 0.512 DSC (p = 0.04), 8.21 (p = 0.041) 95 HD (mm), and 0.398 (p = 0.001) sensitivity.

CONCLUSION

The proposed DL model achieved state-of-art performance and has the potential to help improve radiotherapy treatment planning and noninvasive prostate cancer diagnosis.

Develop and Evaluate a Dose Calculation Strategy Using Electron Density Maps from Spectral CT

PURPOSE/OBJECTIVE(S)

The conventional method of estimating relative electron density using Hounsfield Units (HUs) is prone to errors resulting from various factors such as energy spectrum, exposure, scanner/patient conditions, etc. Specific calibration is needed for each acquisition protocol. To overcome these limitations, dual energy CT has been extensively researched for its accuracy in dose calculation using tube potential switching techniques. A dual layer design offers a different approach to acquire spectral images using single data acquisitions. This study aims to develop and evaluate a dose calculation method using electron density maps generated directly from a dual layer detector scanner.

MATERIALS/METHODS

A phantom with tissue equivalent inserts was scanned using different scanner configurations on a dual layer detector scanner. The electron density of 17 inserts ranged from 0.668 - 5.663 × 1023 m-23. The energy dependent attenuation curves were generated and translated into values of Compton and photoelectric components, which were used to calculate ED values. The ED values were compared to normal values provided by the vendor for each insert. The generated ED maps were normalized to the ED of water and used as the input for dose calculations without CT images. Dosimetry plans were generated on the phantom for two different field sizes (10 × 10 cm2 and 3 × 3 cm2) at gantry angles of 0 and 90 degrees using a 6 MV Monte Carlo engine. The dose distributions were compared between the conventional HU to ED calibration approach with CT images and the direct calculation using the calculated ED map.

RESULTS

The results showed that compared to the conventional HU to ED map, the ED map generated from spectral CT had a relative ED that was about 0.02 lower and was more uniform, with smaller standard deviations. The ED map was closer to the nominal value in low-density regions, while the HU converted ED map was closer to the nominal value in high-density regions. The dose distributions between the two ED approaches were almost identical, with a maximum deviation of around 1% for both field sizes at deeper depths.

CONCLUSION

In conclusion, a dual layer detector scanner can provide an accurate estimation of ED maps. We showed that the dose calculation using the generated ED map is highly accurate using a phantom. This method provides an alternative strategy for dose calculation that eliminates the need for HU to ED calibration and enables the use of the ED map directly.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Immune landscape in rejection of renal transplantation revealed by high-throughput single-cell RNA sequencing

Background: The role of the cellular level in kidney transplant rejection is unclear, and single-cell RNA sequencing (scRNA-seq) can reveal the single-cell landscape behind rejection of human kidney allografts at the single-cell level. Methods: High-quality transcriptomes were generated from scRNA-seq data from five human kidney transplantation biopsy cores. Cluster analysis was performed on the scRNA-seq data by known cell marker genes in order to identify different cell types. In addition, pathways, pseudotime developmental trajectories and transcriptional regulatory networks involved in different cell subpopulations were explored. Next, we systematically analyzed the scoring of gene sets regarding single-cell expression profiles based on biological processes associated with oxidative stress. Results: We obtained 81,139 single cells by scRNA-seq from kidney transplant tissue biopsies of three antibody-mediated rejection (ABMR) patients and two acute kidney injury (AKI) patients with non-rejection causes and identified 11 cell types, including immune cells, renal cells and several stromal cells. Immune cells such as macrophages showed inflammatory activation and antigen presentation and complement signaling, especially in rejection where some subpopulations of cells specifically expressed in rejection showed specific pro-inflammatory responses. In addition, patients with rejection are characterized by an increased number of fibroblasts, and further analysis of subpopulations of fibroblasts revealed their involvement in inflammatory and fibrosis-related pathways leading to increased renal rejection and fibrosis. Notably, the gene set score for response to oxidative stress was higher in patients with rejection. Conclusion: Insight into histological differences in kidney transplant patients with or without rejection was gained by assessing differences in cellular levels at single-cell resolution. In conclusion, we applied scRNA-seq to rejection after renal transplantation to deconstruct its heterogeneity and identify new targets for personalized therapeutic approaches.

Monitoring the Progression of Early Atherosclerosis Using a Fluorescence Nanoprobe for the Detection and Imaging of Phosphorylation and Glucose Levels

Monitoring the early stage of atherosclerosis (AS) without plaque formation is of great significance. Herein, we developed a metal organic framework (MOF)-based fluorescence nanoprobe to analyze the progression of AS by assessing the levels of protein phosphorylation and glucose in blood and tissue. The probe was prepared by post-modification of the MOF with iodine (I3 - )-rhodamine B (RhB) associate, which realizes the specific recognition of target object through the metal joint ZrIV and I3 - -RhB, respectively. We investigated different stages of target object changes in the early non-plaque stage of AS in blood. It was found that the levels of phosphate and glucose in the blood were higher than those of the normal mice. The results of two-photon images showed that early AS mice had higher levels of protein phosphorylation and glucose than that of the normal mice. The present study provides a suitable fluorescence tool for further revealing the pathogenesis and progression of AS.

Evaluation and Use of Organs from Donors Poisoned by Organophosphorus Pesticide

BACKGROUND The aim of this study was to explore the evaluation and use of donor organs from donors with brain death caused by acute severe organophosphorus pesticides and provide a basis for the use of such donor organs. MATERIAL AND METHODS Seven cases of brain dead donors caused by acute organophosphorus pesticide poisoning from January 2014 to December 2018 in the hospital were collected, and a retrospective analysis was made of the donors' age, race, physiological and pathological changes, donor organ function changes and the organ use, liver or kidney function recovery, and complications of the recipients. The 18 recipients were followed up until June 31, 2022. RESULTS We found that 71.42% of organ donors were male, and 71.42% of organ donors were under 50 years old. The main cause of death was respiratory failure caused by organophosphorus pesticide poisoning. The liver and kidney functions of 7 donors were damaged, and 3 livers could not be used due to severe functional damage, but the liver or kidney function of 18 recipients gradually recovered after transplantation. Delayed recovery of graft function occurred after transplantation accounted for 21.43%, and the grafts had good short-term to medium-term performance. CONCLUSIONS Although the function of organs from donor with brain death due to acute severe organophosphorus pesticide poisoning is seriously damaged, most of the organs can still be used for transplantation. Individualized functional maintenance according to the situation of donors is conducive to improving the quality of organs.

Analysis of a Sabin-Strain Inactivated Poliovirus Vaccine Response to a Circulating Type 2 Vaccine-Derived Poliovirus Event in Sichuan Province, China 2019-2021

IMPORTANCE

The Sabin-strain inactivated poliovirus vaccine (IPV) may be a tool for polio outbreak response in certain situations.

OBJECTIVE

To investigate the response to a type 2 vaccine-derived poliovirus (VDPV2) outbreak.

DESIGN, SETTING, AND PARTICIPANTS

This case series was conducted in China after a VDPV2 was detected in stool specimens from a child with acute flaccid paralysis (AFP) in Sichuan Province in 2019, 3 years after the global withdrawal of live, attenuated type 2 oral poliovirus vaccine (OPV). Investigation followed National Health Commission and World Health Organization guidance and included searching hospitals for unreported AFP cases; testing stool specimens from the child, his contacts, and local children; enhanced environmental surveillance for VDPV2s in wastewater; and measuring vaccination coverage. Sabin-strain IPV campaigns were conducted in a wide geographic area.

MAIN OUTCOMES AND MEASURES

Any VDPV2 detection after completion of the supplementary immunization activities.

RESULTS

A 28-nucleotide-change VDPV2 was isolated from a young boy. Three VDPV2s were detected in healthy children; 2 were contacts of the original child, and none had paralysis. A search of 31 million hospital records found 10 unreported AFP cases; none were polio. No type 2 polioviruses were found in wastewater. Prior to the event, polio vaccine coverage was 65% among children younger than 5 years. Sabin-strain IPV campaigns reached more than 97% of targeted children, administering 1.4 million doses. No transmission source was identified. More than 1 year of enhanced poliovirus environmental and AFP surveillance detected no additional VDPVs.

CONCLUSIONS AND RELEVANCE

These findings suggest that the circulating VPDV2 outbreak in 2019 was associated with low vaccine coverage. An investigation discovered 3 infected but otherwise healthy children and no evidence of the virus in wastewater. Following Sabin-strain IPV-only campaigns expanding from county to prefecture, the poliovirus was not detected, and the outbreak response was considered by an expert panel and the World Health Organization to have been successful. This success suggests that the Sabin-strain IPV may be a useful tool for responding to circulating VDPV2 outbreaks when high-quality supplementary immunization activities can be conducted and carefully monitored in settings with good sanitation.

Federated learning enables big data for rare cancer boundary detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey

Reinforcement learning takes sequential decision-making approaches by learning the policy through trial and error based on interaction with the environment. Combining deep learning and reinforcement learning can empower the agent to learn the interactions and the distribution of rewards from state-action pairs to achieve effective and efficient solutions in more complex and dynamic environments. Deep reinforcement learning (DRL) has demonstrated astonishing performance in surpassing the human-level performance in the game domain and many other simulated environments. This paper introduces the basics of reinforcement learning and reviews various categories of DRL algorithms and DRL models developed for medical image analysis and radiation treatment planning optimization. We will also discuss the current challenges of DRL and approaches proposed to make DRL more generalizable and robust in a real-world environment. DRL algorithms, by fostering the designs of the reward function, agents interactions and environment models, can resolve the challenges from scarce and heterogeneous annotated medical image data, which has been a major obstacle to implementing deep learning models in the clinic. DRL is an active research area with enormous potential to improve deep learning applications in medical imaging and radiation therapy planning.

Diagnostic and prognostic value of m5C regulatory genes in hepatocellular carcinoma

Background: A high mortality rate makes hepatocellular carcinoma (HCC) one of the most common types of cancer globally. 5-methylcytosine (m5C) is an epigenetic modification that contributes to the prognosis of several cancers, but its relevance to HCC remains unknown. We sought to determine if the m5C-related regulators had any diagnostic or prognostic value in HCC.

Methods: M5C regulatory genes were screened and compared between HCC and normal tissue from The Cancer Genome Atlas (TCGA)and Gene Expression Omnibus (GEO) databases. Least absolute shrinkage and selection operator method (LASSO) and univariate Cox regression analysis of differentially expressed genes were then performed to identify diagnostic markers. A LASSO prognostic model was constructed using M5C regulatory genes with prognostic values screened by TCGA expression data. HCC patients were stratified based on risk score, then clinical characteristics analysis and immune correlation analysis were performed for each subgroup, and the molecular functions of different subgroups were analyzed using both Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). The prognostic model was evaluated using univariate and multivariate Cox analyses as well as a nomogram. Molecular typing was performed according to m5C regulatory genes and immune checkpoint genes expression respectively, and clinical characterization and immune correlation analysis were performed for each subgroup.

Results: M5C regulatory genes are expressed differently in HCC patients with different clinical and pathological characteristics, and mutations in these genes are frequent. Based on five m5C regulators (NOP2, NSUN2, TET1, YBX1, and DNMT3B), we constructed a prognostic model with high predictive ability. The risk score was found to be an independent prognostic indicator. Additionally, risk scores can also be applied in subgroups with different clinical characteristics as prognostic indicators.

Conclusion: The study combined data from TCGA and GEO for the first time to reveal the genetic and prognostic significance of m5C-related regulators in HCC, which provides new directions for identifying predictive biomarkers and developing molecularly targeted therapies for HCC.

Potential value of PRKDC as a therapeutic target and prognostic biomarker in pan-cancer

BACKGROUND

While protein kinase, DNA-activated, catalytic subunit (PRKDC) plays an important role in double-strand break repair to retain genomic stability, there is still no pan-cancer analysis based on large clinical information on the relationship between PRKDC and different tumors. For the first time, this research used numerous databases to perform a pan-cancer review for PRKDC to explore the possible mechanism of PRKDC in the etiology and outcomes in various tumors.

METHODS

PRKDC's expression profile and prognostic significance in pan-cancer were investigated based on various databases and online platforms, including TIMER2, GEPIA2, cBioPortal, CPTAC, and SangerBox. We applied the TIMER to identified the interlink of PRKDC and the immune infiltration in assorted tumors, and the SangerBox online platform was adopted to find out the relevance between PRKDC and immune checkpoint genes, tumor mutation burden, and microsatellite instability in tumors. GeneMANIA tool was employed to create a protein-protein interaction analysis, gene set enrichment analysis was conducted to performed gene enrichment analysis.

RESULTS

Overall, tumor tissue presented a higher degree of PRKDC expression than adjacent normal tissue. Meanwhile, patients with high PRKDC expression have a worse prognosis. PRKDC mutations were present in almost all The Cancer Genome Atlas tumors and might lead to a better survival prognosis. The PRKDC expression level was shown a positive correlation with tumor-infiltrating immune cells. PRKDC high expression cohorts were enriched in "cell cycle" "oocyte meiosis" and "RNA-degradation" signaling pathways.

CONCLUSIONS

This study revealed the potential value of PRKDC in tumor immunology and as a therapeutic target and prognostic biomarker in pan-cancer.

[Combined resection of thoracic and abdominal organ clusters: a series of 50 cases]

Objective: To examine the technique and effect of combined thoracic and abdominal organ clusters resection. Methods: From February 2019 to August 2021, totally 50 cases of combined thoracoabdominal organ cluster resection were completed at Transplant Medical Center, the Second Affiliated Hospital of Guangxi Medical University from donation after brain death donors. There were 47 males and 3 females, aging (34.8±12.3) years (range: 5 to 55 years). The length of hospital stay(M(IQR)) was 4(4) days (range: 2 to 43 days), the length of tube time was 4(2) days (range: 1 to 43 days). Through the midsternal incision and the abdominal grand cross incision, the cold perfusion was performing simultaneously when the perfusion lines of each target organ was established respectively. The combined resection was performed with the diaphragm as the boundary and the organ cluster as the unit. The heart and lung were separated on site and sent to the transplant hospital, and the abdominal organ cluster was directly preserved and returned to our hospital for further separation and repair. Results: Totaly 21 hearts, 47 pairs of lungs, 49 livers, 47 pairs of kidneys and 11 pancreas were harvested by this surgical treatment. The resection time was (32.6±6.5) minutes (range: 19 to 50 minutes), with no hot ischemia time. There was no accidental injury that affected organ quality and function. Heart transplantation was performed in 17 cases, combined heart-kidney transplantation in 2 cases, double lung transplantation in 43 cases, single lung transplantation in 6 cases, liver transplantation in 41 cases, combined liver-pancreas-duodenal cluster transplantation in 1 case, combined liver-kidney transplantation in 3 cases, combined pancreas-kidney transplantation in 9 cases, and kidney transplantation in 74 cases. Conclusion: Simultaneous perfusion and combined resection of thoracic and abdominal organ clusters for donation after brain death donors are feasible and effective.

Abstract 543: Characterization of extravascular extracellular space of rat brain tumors using wavelet-based radiomics analysis of dynamic contrast enhanced MRI

Introduction: Research studies have already shown that tumor aggressiveness and response to chemical and radiation therapies are influenced by the extravascular extracellular space (VEES) of the tumor microenvironment. Assessment of VEES has been reported to be fundamental to understanding tumor response to treatment and probability of recurrence.

Purpose: This pilot study investigates the association between wavelet-based radiomic features extracted from dynamic contrast-enhanced magnetic resonance images (DCE-MRI) of rat brain tumors against VEES estimated by pharmacokinetic modeling.

Methods: Eight immune-compromised-RNU/RNU rats were implanted with human U251n cancer cells to form an orthotopic glioma (IACUC #1509). For each rat, two DCE-MRI studies (multi slice/echo GE, 3 slice(2mm),128x64, FOV:32x32mm2, TR/(TE1-TE2)=24ms/(2ms-4ms), flip angle=18º, 400 acquisitions, 1.55 sec interval, Magnevist was injected at acquisition no. 15) were performed (24h apart) using a 7T Varian (Agilent, 20cm bore) scanner. A single 20Gy stereotactic radiation exposure was performed before the second study. The post treatment MRIs were taken a range of 1-6.5 hrs post radiation. The time trace of relaxivity change (ΔR1) in all the voxels of the animal’s brain for all studies were calculated. Wavelet decomposition analysis was performed on the ΔR1 for each voxel and frequency-based localized approximations with 4 degrees of regularities were estimated. The VEES map was estimated from ΔR1 by the pharmacokinetic (modified Toft’s) model and a nested model selection technique. Finally, the Pearson correlation coefficients between the VEES map and corresponding wavelet coefficient maps in the tumor region were calculated.

Results: The average voxel-wise Pearson correlation coefficients between the VEES maps (averaged for all animals) and their corresponding wavelet-based, radiomics coefficient maps were: r= -0.680, r= -0.802, r= -0.813, and r= -0.791 with p<0.0001 for the 4 wavelet coefficients (from higher to lower frequencies), respectively.

Discussion & Conclusion: This pilot study suggests that wavelet based radiomic analysis has potential to provide information pertinent to the tumor microenvironment, which correlates well with pharmacokinetic modeling. As such, this work represents an important first step toward potentially connecting radiomics with underlying biological mechanisms.

Citation Format: Hassan Bagher-Ebadian, Stephen L. Brown, Olivia Valadie, Julian A. Rey, Ning Wen, Malisa Sarntinoranont, James R. Ewing, Indrin J. Chetty. Characterization of extravascular extracellular space of rat brain tumors using wavelet-based radiomics analysis of dynamic contrast enhanced MRI [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 543.

Large-Scale Synthesis of Spinel Nix Mn3-x O4 Solid Solution Immobilized with Iridium Single Atoms for Efficient Alkaline Seawater Electrolysis

Seawater electrolysis not only affords a promising approach to produce clean hydrogen fuel but also alleviates the bottleneck of freshwater feeds. Here, a novel strategy for large-scale preparing spinel Ni_x Mn_3-x O₄ solid solution immobilized with iridium single-atoms (Ir-SAs) is developed by the sol-gel method. Benefitting from the surface-exposed Ir-SAs, Ir₁ /Ni_1.6 Mn_1.4 O₄ reveals boosted oxygen evolution reaction (OER) performance, achieving overpotentials of 330 and 350 mV at current densities of 100 and 200 mA cm^-2 in alkaline seawater. Moreover, only a cell voltage of 1.50 V is required to reach 500 mA cm^-2 with assembled Ir₁ /Ni_1.6 Mn_1.4 O₄ ‖Pt/C electrode pair under the industrial operating condition. The experimental characterizations and theoretical calculations highlight the effect of Ir-SAs on improving the intrinsic OER activity and facilitating surface charge transfer kinetics, and evidence the energetically stabilized *OOH and the destabilized chloride ion adsorption in Ir₁ /Ni_1.6 Mn_1.4 O₄ . This work demonstrates an effective method to produce efficient alkaline seawater electrocatalyst massively.

Model refinement increases confidence levels and clinical agreement when commissioning a three-dimensional secondary dose calculation system

Purpose

Evaluate custom beam models for a second check dose calculation system using statistically verifiable passing criteria for film analysis, DVH, and 3D gamma metrics.

Methods

Custom beam models for nine linear accelerators for the Sun Nuclear Dose Calculator algorithm (SDC, Sun Nuclear) were evaluated using the AAPM‐TG119 test suite (5 Intensity Modulated Radiation Therapy (IMRT) and 5 Volumetric Modulated Arc Therapy (VMAT) plans) and a set of clinical plans. Where deemed necessary, adjustments to Multileaf Collimator (MLC) parameters were made to improve results. Comparisons to the Analytic Anisotropic Algorithm (AAA), and gafchromic film measurements were performed. Confidence intervals were set to 95% per TG‐119. Film gamma criteria were 3%/3 mm (conventional beams) or 3%/1 mm (Stereotactic Radiosurgery [SRS] beams). Dose distributions in solid water phantom were evaluated based on DVH metrics (e.g., D95, V20) and 3D gamma criteria (3%/3 mm or 3%/1 mm). Film passing rates, 3D gamma passing rates, and DVH metrics were reported for HD MLC machines and Millennium MLC Machines.

Results

For HD MLC machines, SDC gamma film agreement was 98.76% ± 2.30% (5.74% CL) for 6FFF/6srs (3%/1 mm), and 99.80% ± 0.32% (0.83% CL) for 6x (3%/3 mm). For Millennium MLC machines, film passing rates were 98.20% ± 3.14% (7.96% CL), 99.52% ± 1.14% (2.71% CL), and 99.69% ± 0.82% (1.91% CL) for 6FFF, 6x, and 10x, respectively. For SDC to AAA comparisons: HD MLC Linear Accelerators (LINACs); DVH point agreement was 0.97% ± 1.64% (4.18% CL) and 1.05% ± 2.12% (5.20% CL); 3D gamma agreement was 99.97% ± 0.14% (0.30% CL) and 100.00% ± 0.02% (0.05% CL), for 6FFF/6srs and 6x, respectively; Millennium MLC LINACs: DVH point agreement was 0.77% ± 2.40% (5.47% CL), 0.80% ± 3.40% (7.47% CL), and 0.07% ± 2.15% (4.30% CL); 3D gamma agreement was 99.97% ± 0.13% (0.29% CL), 99.97% ± 0.17% (0.36% CL), and 99.99% ± 0.06% (0.12% CL) for 6FFF, 6x, and 10x, respectively.

Conclusion

SDC shows agreement well within TG119 CLs for film and redundant dose calculation comparisons with AAA. In some models (SRS), this was achieved using stricter criteria. TG119 plans can be used to help guide model adjustments and to establish clinical baselines for DVH and 3D gamma criteria.

Nimotuzumab shows an additive effect to inhibit cell growth of ALA-PDT treated oral cancer cells

Oral squamous cell carcinoma (OSCC) is characterized by severe functional impairment and a poor prognosis. The epidermal growth factor receptor (EGFR) is highly expressed in OSCC and is a promising target for cancer therapy. In addition, aminolevulinic acid-induced photodynamic therapy (ALA-PDT) has produced robust clinical effects and showed some advantages over radiotherapy in oral cancer. Here, an EGFR inhibitor, nimotuzumab, was administered to 2 OSCC cell lines, CAL-27 and SCC-25, treated with ALA-PDT. Cell growth, apoptosis, and reactive oxygen species (ROS) generation were used to measure the antitumor activity of the combination therapy. The in vivo effect of nimotuzumab plus ALA-PDT was done using a mouse OSCC xenograft model (SCC-25). EGFR expression was further compared by Western blotting in different groups. We observed that nimotuzumab combined with ALA-PDT could enhance inhibition of OSCC cell growth in vitro and in vivo. We also observed an enhanced effect after combination on cell apoptosis in CAL-27 and SCC-25 cells. Furthermore, combined therapy significantly reduced the protein expression levels of EGFR in vitro. However, we observed that nimotuzumab plus ALA-PDT did not increase ROS generation substantially in OSCC cells compared to the ALA-PDT group alone. These observations indicate that nimotuzumab combined with ALA-PDT has valuable applications for OSCC treatment.

Graphene-containing metal-organic framework nanocomposites for enhanced microwave ablation of salivary adenoid cystic carcinoma

Salivary adenoid cystic carcinoma (SACC), one of the most common malignant tumors in the head and neck region, is characterized by high postoperative recurrence rate and poor prognosis. Microwave (MW) ablation possesses advantages in preserving SACC patients' facial aesthetics and oral function, but unfortunately, it suffers from low therapeutic efficacy due to the limited MW-thermal efficiency. Moreover, the insufficient thermal ablation may aggravate hypoxic state in tumors, which is deleterious to the treatment of residual tumors and aggressive tumors. Hence, MW ablation has been rarely applied in treating head and neck tumors in recent years. To minimize the unfavorable outcomes and maximize the therapeutic effects of MW ablation, a MW sensitizer coupled with a self-sufficient oxygen nanoagent was employed for the first time in MW ablation to treat head and neck tumors. We prepared a graphene-containing metal-organic framework (ZIF67@Gr-PEG), which exhibited excellent MW thermal conversion ability endowed by the incorporated Gr and showed in situ oxygen generation capacity derived from the ZIF67 matrix. In an animal experiment, ZIF67@Gr-PEG-based MW ablation with a temperature up to 66.1 °C exhibited a high tumor ablation rate. More importantly, insufficient MW ablation-induced high expressions of HIF-1α and VEGF were observed in our experiment, whereas the levels of tumor hypoxia and angiogenesis were efficiently decreased in MW ablation with the assistance of ZIF67@Gr-PEG nanocomposites (NCs). Notably, our strategy for MW ablation not only evidences the great potential of ZIF67@Gr-PEG but also promotes the translation of thermotherapeutic graphene from basic research to clinical practice.

Antibacterial and Antioxidant Effects of Magnesium Alloy on Titanium Dental Implants

OBJECTIVES

In this study, a new type of dental implant by covering the surface of the titanium (Ti) implant with zinc-magnesium (Zn-Mg) alloy was designed, to study the antibacterial and antioxidant effects of Mg alloy on titanium (Ti) implants in oral implant restoration.

METHODS

Human gingival fibroblasts (HGFs), S. sanguinis, and F. nucleatum bacteria were used to detect the bioactivity and antibacterial properties of Mg alloy-coated Ti implants. In addition, B6/J mice implanted with different materials were used to further detect their antibacterial and antioxidant properties.

RESULTS

The results showed that Mg alloy could better promote the adhesion and proliferation and improve the alkaline phosphatase (ALP) activity of HGFs, which contributed to better improved stability of implant osseointegration. In addition, Mg alloy could better inhibit the proliferation of S. sanguinis, while no significant difference was found in the proliferation of F. nucleatum between the two implants. In the mouse model, the peripheral inflammatory reaction and oxidative stress of the Mg alloy implant were significantly lower than those of the Ti alloy implant.

CONCLUSIONS

Zn-Mg alloy-coated Ti implants could better inhibit the growth of Gram-positive bacteria in the oral cavity, inhibit oxidative stress, and facilitate the proliferation activity of HGFs and the potential of osteoblast differentiation, thus, better increasing the stability of implant osseointegration.

Detection of nucleated red blood cells using the Mindray BC-6800Plus hematology analyzer: a clinical performance evaluation

BACKGROUND

With the development of instrument technology, the functions and detection methods of automatic blood cell analyzers have become more complex. To ensure optimal clinical applicability, it is crucial to select an automatic blood cell analyzer with excellent clinical detection performance. This study evaluated the latest Mindray BC-6800Plus automatic blood cell analyzer and assessed its performance in the detection of nucleated red blood cells (NRBCs).

METHODS

A total of 490 clinical blood samples were used to assess the performance of the instrument, including parameters such as precision, linearity, conformity rate of manual microscopic examination, carryover, and limit of quantitation.

RESULTS

The instrument showed a small carryover (≤0.02) and excellent linearity (R2≥0.9986). The reproducibility of the sample tests was satisfactory, and the coefficient of variation (CV) of the test results [0.98-1.72% and 0.62-6.97% for white blood cells (WBCs) and NRBCs, respectively] were significantly lower than that declared by the manufacturer (2.5% and 20% for WBCs and NRBCs, respectively). Thus, the BC-6800Plus satisfies the requirements of clinical testing. Two separate Mindray BC-6800Plus machines were tested and found to be in good agreement with each other and with manual microscopy methods. Furthermore, WBC and NRBC counts were highly consistent with results obtained using the XN-9100 blood analyzer.

CONCLUSIONS

The Mindray BC-6800Plus is an excellent analyzer that can provide timely and accurate reports for clinical laboratory detection of NRBC.

The overexpression of insect endogenous microRNA in transgenic rice inhibits the pupation of Chilo suppressalis and Cnaphalocrocis medinalis

BACKGROUND

Chilo suppressalis and Cnaphalocrocis medinalis are destructive rice pests co-occurring in major rice-growing areas in China. RNA interference (RNAi)-based insect-resistant genetically engineered (IRGE) crops provide a promising approach for pest management by suppressing gene expression or translation. A microRNA (miRNA)-mediated IRGE rice line expressing endogenous Chilo suppressalis miRNA Csu-novel-260, showing significant resistance against Chilo suppressalis, provides an attractive control strategy for Chilo suppressalis by suppressing the expression of the disembodied (dib) gene expression. However, whether this transgenic line also shows the resistance against Cnaphalocrocis medinalis remains unknown.

RESULTS

A spatiotemporal expression analysis of Csu-novel-260 in the transgenic rice line was performed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) to determine the paddy field pest exposure dose. In diet feeding assays, a chemically synthesized Csu-novel-260 agomir at 200 fmol g^-1 significantly inhibited Chilo suppressalis pupation. However, larval development, survival and pupal weight were not significantly affected. Additionally, the transgenic line significantly affected Cnaphalocrocis medinalis pupation but not larval survival. The qRT-PCR showed that Csdib and Cmdib expression levels were significantly suppressed when the two pests fed on the transgenic line. Additionally, the transgenic line significantly decreased Cry1C-resistant and Cry1C-susceptible Chilo suppressalis larval survival in detached rice tissue feeding assays, indicating that Cry1C-resistant Chilo suppressalis was not cross-resistant to Csu-novel-260 expressed in miRNA-mediated IRGE rice.

CONCLUSION

Our study demonstrated that miRNA-mediated IRGE rice significantly inhibited Chilo suppressalis and Cnaphalocrocis medinalis pupation. The results provide a new viewpoint for the application of RNAi-based plants and the inspiration for environmental risk assessment.

Nanoengineered biomimetic Cu-based nanoparticles for multifunational and efficient tumor treatment

The microwave dynamic therapy (MDT) mediated by cytotoxic reactive oxygen species (ROS) is a promising anticancer therapeutic method. However, the therapeutic efficiency of MDT is restricted by several limitations including insufficient ROS generation, strong proangiogenic response, and low tumor-targeting efficiency. Herein, we find that Cu-based nanoparticles can produce oxygen under microwave (MW) irradiation to raise the generation of ROS, such as •O₂, •OH and ¹O₂, especially •O₂. On this basis, a nanoengineered biomimetic strategy is designed to improve the efficiency of MDT. After intravenous administration, the nanoparticles accumulate to the tumor site through targeting effect mediated by biomimetic modification, and it can continuously produce oxygen to raise the levels of ROS in tumor microenvironment under MW irradiation for MDT. Additionally, Apatinib is incorporated as antiangiogenic drug to downregulate the expression of vascular endothelial growth factor (VEGF), which can effectively inhibit the tumor angiogenesis after MDT. Hence, the tumor inhibition rate is as high as 96.79%. This study provides emerging strategies to develop multifunctional nanosystems for efficient tumor therapy by MDT.

Abstract 186: Gleason grade group predictions from mp-MRI of prostate cancer patients using auto deep learning

Gleason Grade Group Predictions from mp-MRI of Prostate Cancer Patients using Automated Deep Learning

Though histopathology remains the gold standard, there have been significant interests in predicting Gleason Grade using noninvasive imaging such as mp-MRI. Most studies simplify the task into binary classification for the high uncertainty at each group. Handcrafted radiomic features were heavily investigated but prone to errors from the definition of region of interest, feature extraction variations, etc. We proposed an automated deep learning framework (auto-Keras) to predict the group directly based on the 3D data of the whole prostate gland. The training cohort A consisted of 96 PCa patients from SPIE-AAPM-NCI Challenge. The number of patients in each Group was 30, 35, 18, 7, and 6. The testing cohort B consisted of 34 PCa patients from our institute (10, 14, 4, 3, 3). We resampled and rigidly registered ADC and T2WI. N4-bias correction was applied to correct the non-uniformity. For each slice, we performed Gaussian blurring followed by prostate cropping from contour delineated by two clinicians.We tested five scenarios, including input of T2WI, ADC, both, two parallel inputs followed by feature concatenation, and prediction ensemble. The search space of augmentation included translation, flip, rotation, zooming, and contrast. The search space of the architectures had vanilla, ResNet, and Xception. With ADC alone, the model detected 75% of patients in Group 3. Using T2WI and ADC as input, 46% of Group 2 and 40% of Group 1 were identified. Since GG 2 is less aggressive and has a favorable outcome, we further studied the performance of classifying 1 VS. 2-5 and 1-2 VS. 3-5. The models' precision and recall were 91% and 72% for 1-2, 60% and 24% for 3-5. We separated 1 VS. 2-5, with a 96% precision and 73% recall for 2-5. The model had a better performance to predict lower GG when the input contained both T2WI and AD, and better at higher GG when the features were concatenated at the output level.

Table 1.Performance of Precision and recall for Gleason Grade Group on the testing cohort.1 VS. 2 VS. 3 VS. 4 VS. 51-2 VS. 3-51 VS. 2-5ADC-onlyGroup 1Group 2Group 3Group 4Group 5Group 1-2Group 3-5Group 1Group 2-5Precision0.100.230.75000.300.500.300.50Recall0.250.380.14--0.580.240.580.24Input MergePrecision0.400.460.25000.910.200.400.61Recall0.310.380.25--0.720.500.310.70Feature MergePrecision0.200.080.250.3300.130.600.200.96Recall0.670.250.250.0600.430.230.670.73PredictionEnsemblePrecision0.200.080.750.3300.170.600.200.91Recall0.500.250.200.10-0.500.240.500.72

Citation Format: Weiwei Zong, Eric Carver, Aharon Feldman, Joon Lee, Zhen Sun, Lanyu Xu, Ali Dabaja, Ning Wen. Gleason grade group predictions from mp-MRI of prostate cancer patients using auto deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 186.

Abstract 221: Develop a pathway level classifier to identify clinically relevant subtypes of glioblastoma

Introduction: Glioblastoma Multiforme (GBM) is a malignant Grade IV brain tumor. With standard treatment, the median survival for adults with GBM, IDH-wildtype, is approximately 11-15 months. We aim at identifying clinically relevant GBM subtypes based on cell signaling pathways information to facilitate personalized medicine.

Methods: We rebuilt a MultiPLIER model for GBM using the recount2 compendium with updated V7.0 canonical pathways from the MSigDB database. The MultiPLIER is a machine learning model based on pathway-level information extractor (PLIER), a matrix factorization approach to identify specific pathways that regulate gene expression using a large public dataset and prior biological knowledge from multiple tissues and biological conditions. It has two inputs, the gene expression matrix, and the prior knowledge. PLIER constructed eigengene like latent variables (LVs) to approximate relevant pathways by decomposing gene expression data and a sparse matrix to specify prior information gene sets and pathways in each LV. The MultiPLIER is an unsupervised transfer learning framework to transfer the PLIER model to a specific dataset or disease with smaller sample sizes. Knowledge learned in an extensive collection of datasets can be transferred to a target domain to discover unseen patterns. We used 2315 gene sets, which have 12604 genes as prior biological information in the PLIER training. We produced a decomposition of 903 LVs with 200 LVs with high confidence (area under curve (AUC) of >0.7, false discovery rate (FDR) of <0.05). We then projected the TCGA GBM HT_HG-U133A dataset with 526 primary solid tumor samples and ten solid tissue normal samples to the MultiPLIER 903-dimension space to get a GBM-MultiPLIER model.

Results: We used the univariate Cox model to select 169 survival-related LVs specific to GBM subtype studies (p <0.05). Then we used an unsupervised clustering method, consensus clustering (Monti et al., 2003), to discover GBM subtypes. Five subtypes were obtained with the p value 0.00009 of the log-rank test of survival analysis. We also performed Silhouette width, the statistical significance of clustering, and differential expression tests with the Bioconductor package, CancerSubtypes in R. We found the differentially expressed LVs (adjusted p-value<0.01) patterns between each subtype and normal samples. There are also 37 shared LVs among these five subtypes relative to normal samples (adjusted p-value<0.01). The subtype three, which is the best survival subtype, has one LV that has an estimated AUC (Area under the ROC Curve) 0.81, with a 95% confidence interval (0.75,0.86) when subtype 3 compared to other tumor samples.

Conclusions: The GBM MultiPLIER model can reveal a consistent pathway or gene set differences across subtypes and capture subtype-specific patterns. These findings provide an opportunity to untangle the underlying biologic meaning further.

Citation Format: Xuelian Xu, Zhen Sun, Ning Wen. Develop a pathway level classifier to identify clinically relevant subtypes of glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 221.

Clinical utility of Gafchromic film in an MRI-guided linear accelerator

Background

The purpose of this study is to comprehensively evaluate the suitability of Gafchromic EBT3 and EBT-XD film for dosimetric quality assurance in 0.35 T MR-guided radiotherapy.

Methods

A 0.35 T magnetic field strength was utilized to evaluate magnetic field effects on EBT3 and EBT-XD Gafchromic films by studying the effect of film exposure time within the magnetic field using two timing sequences and film not exposed to MR, the effect of magnetic field exposure on the crystalline structure of the film, and the effect of orientation of the film with respect to the bore within the magnetic field. The orientation of the monomer crystal was qualitatively evaluated using scanning electron microscopy (SEM) compared to unirradiated film. Additionally, dosimetric impact was evaluated through measurements of a series of open field irradiations (0.83 × 0.83-cm² to 19.92 × 19.92-cm²) and patient specific quality assurance measurements. Open fields were compared to planned dose and an independent dosimeter. Film dosimetry was applied to twenty conventional and twenty stereotactic body radiotherapy (SBRT) patient specific quality assurance cases.

Results

No visual changes in crystal orientation were observed in any evaluated SEM images nor were any optical density differences observed between films irradiated inside or outside the magnetic field for both EBT3 and EBT-XD film. At small field sizes, the average difference along dose profiles measured in film compared to the same points measured using an independent dosimeter and to predicted treatment planning system values was 1.23% and 1.56%, respectively. For large field sizes, the average differences were 1.91% and 1.21%, respectively. In open field tests, the average gamma pass rates were 99.8% and 97.2%, for 3%/3 mm and 3%/1 mm, respectively. The median (interquartile range) 3%/3 mm gamma pass rates in conventional QA cases were 98.4% (96.3 to 99.2%), and 3%/1 mm in SBRT QA cases were 95.8% (95.0 to 97.3%).

Conclusions

MR exposure at 0.35 T had negligible effects on EBT3 and EBT-XD Gafchromic film. Dosimetric film results were comparable to planned dose, ion chamber and diode measurements.

Immunogenicity of two-dose and three-dose vaccination schedules with Sabin inactivated poliovirus vaccine in China: An open-label, randomized, controlled trial

BACKGROUND

We assessed immunogenicity of three-dose and two-dose immunization schedules with a Sabin-strain inactivated poliovirus vaccine (sIPV) produced by one Chinese vaccine manufacturer.

METHODS

This was an open label, randomized, controlled trial conducted in 16 vaccination clinics in Shandong province. Infants were allocated randomly to either a 3-dose study arm (sIPV administered at 2, 3, and 4 months of age) or a 2-dose arm (sIPV administered at 4 and 8-11 months of age). Poliovirus neutralizing antibodies were measured in sera collected prior to the first sIPV dose and one month after the last dose.

FINDINGS

We enrolled 560 infants; 536 (95.7%) completed the study. Final seropositivity rates were >98% for all three serotypes in both study arms. There were no statistically significant differences in seropositivity between the 2-dose and the 3-dose schedule. Final median reciprocal titres of polio antibodies were high overall (>1:768 for all serotypes) and statistically significantly higher in 2-dose recipients compared with 3-dose recipients (p < 0.001).

INTERPRETATION

This study offers evidence that two doses of sIPV administered at 4 and 8-11 months of age and three doses of sIPV administered at 2, 3, and 4 months of age both provide serological protection against poliomyelitis. Median reciprocal titres of polio antibodies were high overall, and were more related to the interval between doses than the number of doses, with the longer interval of the 2-dose schedule producing higher reciprocal titres than the shorter-interval 3-dose schedule. The protection provided by the 3-dose schedule is achieved earlier in life than the protection with the 2-dose schedule. Countries planning to use an IPV-only schedule in the post-eradication era can consider this 2-dose sIPV option as an immunogenic and dose-sparing strategy.

FUNDING

World Health Organization (from a grant from International PolioPlus Committee, Rotary International, Evanston, IL, USA).

Dosimetric Evaluation of Fractionated Stereotactic Radiation Therapy for Skull Base Meningiomas Using HyperArc and Multicriteria Optimization

Purpose

Treatment planning of skull based meningiomas can be difficult due to the irregular shaped target volumes and proximity to critical optic structures. This study evaluated the use of HyperArc (HA) radiosurgery optimization and delivery in conjunction with multicriteria optimization (MCO) to create conformal and efficient treatment plans for conventionally fractionated radiation therapy to difficult base-of-skull (BOS) lesions.

Methods and Materials

Twelve patients with BOS meningioma were retrospectively planned with HA-specific optimization algorithm, stereotactic normal tissue objective (SRS-NTO), and conventional automatic normal tissue objective to evaluate normal brain sparing (mean dose and V20 Gy). MCO was used on both SRS-NTO and automatic normal tissue objective plans to further decrease organ-at-risk doses and target dose maximum to within clinically acceptable constraints. Delivery efficiency was evaluated based on planned monitor units.

Results

The SRS-NTO in HA can be used to improve the mid- and low-dose spread to normal brain tissue in the irradiation of BOS meningiomas. Improvement in normal brain sparing can be seen in larger, more irregular shaped lesions and less so in smaller spherical targets. MCO can be used in conjunction with the SRS-NTO to reduce target dose maximum and dose to organ at risk without sacrificing the gain in normal brain sparing.

Conclusions

HA can be beneficial both in treatment planning by using the SRS-NTO and in delivery efficiency through the decrease in monitor units and automated delivery.

Therapeutic enhancement of radiation and immunomodulation by gold nanoparticles in triple negative breast cancer

Gold nanoparticles (AuNPs) have been shown to enhance cancer radiotherapy (RT) gain by localizing the absorption of radiation energy in the tumor while sparing surrounding normal tissue from radiation toxicity. Previously, we showed that AuNPs enhanced RT induced DNA damage and cytotoxicity in MCF7 breast cancer cells. Interestingly, we found that cancer cells exhibited a size-dependent AuNPs intracellular localization (4 nm preferentially in the cytoplasm and 14 nm in the nucleus). We extended those studies to an in vivo model and examined the AuNPs effects on RT cytotoxicity, survival and immunomodulation of tumor microenvironment (TME) in human triple negative breast cancer (TNBC) xenograft mouse model. We also explored the significance of nanoparticle size in these AuNPs’ effects. Mice treated with RT and RT plus 4 nm or 14 nm AuNPs showed a significant tumor growth delay, compared to untreated animals, while dual RT plus AuNPs treatment exhibited additive effect compared to either RT or AuNPs treatment alone. Survival log-rank test showed significant RT enhancement with 14 nm AuNP alone; however, 4 nm AuNPs did not exhibit RT enhancement. Both sizes of AuNPs enhanced RT induced immunogenic cell death (ICD) that was coupled with significant macrophage infiltration in mice pretreated with 14 nm AuNPs. These results showing significant AuNP size-dependent RT enhancement, as evident by both tumor growth delay and overall survival, reveal additional underlying immunological mechanisms and provide a platform for studying RT multimodal approaches for TNBC that may be combined with immunotherapies, enhancing their effect.

Improvement of Multiparametric MR Image Segmentation by Augmenting the Data With Generative Adversarial Networks for Glioma Patients

Every year thousands of patients are diagnosed with a glioma, a type of malignant brain tumor. MRI plays an essential role in the diagnosis and treatment assessment of these patients. Neural networks show great potential to aid physicians in the medical image analysis. This study investigated the creation of synthetic brain T1-weighted (T1), post-contrast T1-weighted (T1CE), T2-weighted (T2), and T2 Fluid Attenuated Inversion Recovery (Flair) MR images. These synthetic MR (synMR) images were assessed quantitatively with four metrics. The synMR images were also assessed qualitatively by an authoring physician with notions that synMR possessed realism in its portrayal of structural boundaries but struggled to accurately depict tumor heterogeneity. Additionally, this study investigated the synMR images created by generative adversarial network (GAN) to overcome the lack of annotated medical image data in training U-Nets to segment enhancing tumor, whole tumor, and tumor core regions on gliomas. Multiple two-dimensional (2D) U-Nets were trained with original BraTS data and differing subsets of the synMR images. Dice similarity coefficient (DSC) was used as the loss function during training as well a quantitative metric. Additionally, Hausdorff Distance 95% CI (HD) was used to judge the quality of the contours created by these U-Nets. The model performance was improved in both DSC and HD when incorporating synMR in the training set. In summary, this study showed the ability to generate high quality Flair, T2, T1, and T1CE synMR images using GAN. Using synMR images showed encouraging results to improve the U-Net segmentation performance and shows potential to address the scarcity of annotated medical images.

Correlation of carbonic anhydrase 9 (CA9) with pathological T-stage and prognosis in patients with oral tongue squamous cell carcinoma

Background

We explored the mechanisms underlying tumorigenesis in oral tongue squamous cell carcinoma (OTSCC) with the goal of uncovering prognostic molecular biomarkers.

Methods

An mRNA sequencing dataset was obtained from The Cancer Genome Atlas (TCGA) database, and differentially expressed genes (DEGs) were selected using R language software packages. Functional enrichment analysis was conducted with DAVID software and protein-protein interaction (PPI) networks were constructed using the STRING database. The relationship between hub genes and overall survival (OS) was evaluated by Kaplan-Meier analysis and Cox proportional hazard regression models. Expression of the candidate gene, carbonic anhydrase 9 (CA9), was verified by real-time RT-PCR, western blotting, and immunohistochemistry.

Results

DEGs (n=581) were obtained from 11 OTSCC samples and corresponding adjacent non-tumor tissues. Gene ontology (GO) analysis revealed that most DEGs were implicated in anterior/posterior pattern specification, embryonic skeletal system morphogenesis, and multicellular organism development, and pathway analysis suggested that DEGs were associated with neuroactive ligand-receptor interaction, calcium signaling pathway and transcriptional misregulation in the cancer. A PPI network consisting of 301 nodes and 2011 edges was constructed and 71 hub genes, with high degrees of connectivity in the network, were identified. Kaplan-Meier analysis of the hub genes indicated that high expression of CA9, LHX1, and KISS1R and low expression of CCKAR were associated with poor OS in OTSCC; however, only CA9 was a significant prognostic factor influencing survival in OTSCC on multivariate analysis. High expression of CA9 was associated with poor pathological T-stage. CA9 tumor specificity was confirmed using the Gene Expression Omnibus (GEO) database and further molecular tests.

Conclusions

We identified key DEGs that may assist in the molecular understanding of OTSCC. CA9 warrants further exploration as potential prognostic biomarker and therapeutic target in OTSCC.

Technical Note: Comparison of the internal target volume (ITV) contours and dose calculations on 4DCT, average CBCT, and 4DCBCT imaging for lung stereotactic body radiation therapy (SBRT)

PURPOSE

To investigate the differences between internal target volumes (ITVs) contoured on the simulation 4DCT and daily 4DCBCT images for lung cancer patients treated with stereotactic body radiotherapy (SBRT) and determine the dose delivered on 4D planning technique.

METHODS

For nine patients, 4DCBCTs were acquired before each fraction to assess tumor motion. An ITV was contoured on each phase of the 4DCBCT and a union of the 10 ITVs was used to create a composite ITV. Another ITV was drawn on the average 3DCBCT (avgCBCT) to compare with current clinical practice. The Dice coefficient, Hausdorff distance, and center of mass (COM) were averaged over four fractions to compare the ITVs contoured on the 4DCT, avgCBCT, and 4DCBCT for each patient. Planning was done on the average CT, and using the online registration, plans were calculated on each phase of the 4DCBCT and on the avgCBCT. Plan dose calculations were tested by measuring ion chamber dose in the CIRS lung phantom.

RESULTS

The Dice coefficients were similar for all three comparisons: avgCBCT-to-4DCBCT (0.7 ± 0.1), 4DCT-to-avgCBCT (0.7 ± 0.1), and 4DCT-to-4DCBCT (0.7 ± 0.1); while the mean COM differences were also comparable (2.6 ± 2.2mm, 2.3 ± 1.4mm, and 3.1 ± 1.1mm, respectively). The Hausdorff distances for the comparisons with 4DCBCT (8.2 ± 2.9mm and 8.1 ± 3.2mm) were larger than the comparison without (6.5 ± 2.5mm). The differences in ITV D95% between the treatment plan and avgCBCT calculations were 4.3 ± 3.0% and -0.5 ± 4.6%, between treatment plan and 4DCBCT plans, respectively, while the ITV V100% coverages were 99.0 ± 1.9% and 93.1 ± 8.0% for avgCBCT and 4DCBCT, respectively.

CONCLUSION

There is great potential for 4DCBCT to evaluate the extent of tumor motion before treatment, but image quality challenges the clinician to consistently delineate lung target volumes.