Citations

Background and Aims: Efficacy of chimeric antigen receptor (CAR) T cells for treating solid tumors, including HCC, remains a challenge. Nanobodies are emerging building blocks of CAR T cells due to their small size and high expression. Membrane proximal sites have been shown as attractive epitopes of CAR T cells. However, current CAR formats are not tailored toward nanobodies or targeting membrane distal epitopes. Approach and Results: Using hYP7 Fv (membrane proximal) and HN3 VH nanobody (membrane distal) as GPC3 targeting elements, we sought to determine how hinges and transmembrane portions of varying structures and sizes affect CAR T-cell function. We generated multiple permutations of CAR T cells containing CD8, CD28, IgG4, and Fc domains. We show that engineered HN3 CAR T cells can be improved by 2 independent, synergistic changes in the hinge and transmembrane domains. The T cells expressing the HN3 CAR which contains the hinge region of IgG4 and the CD28 transmembrane domain (HN3-IgG4H-CD28TM) exhibited high cytotoxic activity and caused complete HCC tumor eradication in immunodeficient mice. HN3-IgG4H-CD28TM CAR T cells were enriched for cytotoxic-memory CD8+ T cells and NFAT signals, and reduced β catenin levels in HCC cells. Conclusion: Our findings indicate that altering the hinge and transmembrane domains of a nanobody-based CAR targeting a distal GPC3 epitope, in contrast to a membrane proximal epitope, lead to robust T-cell signaling and induce swift and durable eradication of HCC tumors.

Introduction FDG PET/CT was prospectively studied in 287 cN0 head and neck cancer patients in ACRIN 6685, and additional analysis of neck FDG uptake upon recurrence-free survival (RFS) and overall survival (OS) was performed. Patients and Methods Two hundred eight had analyzable data. Survival analysis was performed to compare RFS and OS based on neck FDG visual assessment (VA) and SUVmax. For SUVmax, the optimal thresholds were calculated using conditional inference trees on a randomly selected 70% training data set and validated using the remaining 30% of data. Kaplan-Meier curves with log-rank tests were generated for the patient groups based on VA and optimal SUVmax thresholds, and the hazards ratios (HRs) and 95% confidence intervals (CIs) were also calculated. Hypothesis testing was set at a significance level of 0.05. Results A total of 73.9% of bilateral cN0 and 50.0% of unilateral cN0 were alive at the end of the study with the remaining being dead or lost to follow-up. Overall survival median follow-up time was 24.0 months (interquartile range, 15.8–25.3; range, 0–37.0). A total of 63.3% of bilateral cN0 and 42.5% of unilateral cN0 patients remained disease free during the study. Recurrence-free survival median follow-up time was 23.9 months (interquartile range, 12.4–25.2; range, 0–35.6). Visual assessment of necks by our panel of radiologists was significantly associated with RFS (HR [95% CI], 2.30 [1.10–4.79]; P = 0.02), but not with OS (HR [95% CI], 1.64 [0.86–3.14]; P = 0.13). The optimal SUVmax thresholds were 2.5 for RFS and 5.0 for OS. For SUVmax assessment, applying the optimal thresholds to the 30% test data yielded HRs (95% CIs) of 2.09 (0.61–7.14; P = 0.23) for RFS and 3.42 (1.03–11.41; P = 0.03) for OS. The SUVmax threshold of 5.0 was significantly associated with RFS (HR [95% CI], 5.92 [1.79–19.57]; P < 0.001). Conclusions Neck FDG uptake by VA is significant for RFS. An SUVmax threshold of 5.0 is significantly associated with OS and RFS.

Purpose: Planning target volume (PTV) expansion for post-prostatectomy radiotherapy is typically ≥5 mm. Recent clinical trials have proved the feasibility of a reduced margin of 2–3 mm for treatments on MRI-linac. We aim to study the minimum PTV margin needed using iterative cone-beam CT (iCBCT) as image guidance on conventional linacs. Materials/Methods: Fourteen patients who received post-prostatectomy irradiation (8 with an endorectal balloon and 6 without a balloon) were included in this study. Treatment was delivered with volumetric modulated radiation therapy (VMAT). Fractional dose delivery was evaluated in 165 treatment fractions. The bladder, rectal wall, femoral heads, and prostate bed clinical tumor volume (CTV) were contoured and verified on daily iCBCT. PTV margins (0 mm, 2 mm, and 4 mm) were evaluated on daily iCBCT. CTV coverage and OAR dose parameters were assessed with each PTV margin. Results: CTV D100% was underdosed with a 0 mm margin in 32% of fractions in comparison with 2 mm (6%) and 4 mm (6%) PTV margin (p ≤ 0.001). CTV D95% > 95% was met in 93–94% fractions for all PTV expansions. CTV D95% > 95% was achieved in more patients with an endorectal balloon than those without: 0 mm—90/91 (99%) vs. 63/74 (85%); 2 mm—90/91 (99%) vs. 65/75 (87%); 4 mm—90/90 (100%) vs. 63/73 (86%). There was no difference in absolute median change in CTV D95% (0.32%) for 0-, 2-, and 4 mm margins. The maximum dose remained under 108% for 100% (0 mm), 97% (2 mm), and 98% (4 mm) of images. Rectal wall maximum dose remained under 108% for 100% (0 mm), 100% (2 mm), and 98% (4 mm) of images. Conclusions: With high-quality iCBCT image guidance, PTV margin accounting for inter-fractional uncertainties can be safely reduced for post-prostatectomy radiotherapy. For fractionated radiotherapy, an isotropic expansion of 2 mm and 4 mm may be considered for margin expansion with and without the endorectal balloon. Future application for margin reduction needs to be further evaluated and considered with the advent of shorter post-prostatectomy radiation courses.

Abstract Understanding the function of non-coding genomic sequence variants represents a challenge for biomedicine. Many diseases are products of gene-by-environment interactions with complex mechanisms. This study addresses these themes by mechanistic characterization of non-coding variants that influence gene expression only after drug or hormone exposure. Using glucocorticoid signaling as a model system, we integrated genomic, transcriptomic, and epigenomic approaches to unravel mechanisms by which variant function could be revealed by hormones or drugs. Specifically, we identified cis-regulatory elements and 3D interactions underlying ligand-dependent associations between variants and gene expression. One-quarter of the glucocorticoid-modulated variants that we identified had already been associated with clinical phenotypes. However, their affected genes were ‘unmasked’ only after glucocorticoid exposure and often with function relevant to the disease phenotypes. These diseases involved glucocorticoids as risk factors or therapeutic agents and included autoimmunity, metabolic and mood disorders, osteoporosis and cancer. For example, we identified a novel breast cancer risk gene, MAST4, with expression that was repressed by glucocorticoids in cells carrying the risk genotype, repression that correlated with MAST4 expression in breast cancer and treatment outcomes. These observations provide a mechanistic framework for understanding non-coding genetic variant-chemical environment interactions and their role in disease risk and drug response.

AbstractAlternative polyadenylation (APA) is a common genetic regulatory mechanism that generates distinct 3′ ends for RNA transcripts. Changes in APA have been associated with multiple biological processes and disease phenotypes. However, the role of hormones and their drug analogs in APA remains largely unknown. In this study, we investigated transcriptome‐wide the impact of glucocorticoids on APA in 30 human B‐lymphoblastoid cell lines. We found that glucocorticoids could regulate APA for a subset of genes, possibly by changing the expression of 142 RNA‐binding proteins, some with known APA‐regulating properties. Interestingly, genes with glucocorticoid‐mediated APA were enriched in viral translation‐related pathways, while genes with glucocorticoid‐mediated expression were enriched in interferon and interleukin pathways, suggesting that glucocorticoid‐mediated APA might result in functional consequences distinct from gene expression. For example, glucocorticoids, a pharmacotherapy for severe COVID‐19, were found to change the APA but not the expression of LY6E, an important antiviral inhibitor in coronavirus diseases. Glucocorticoid‐mediated APA was also cell‐type‐specific, suggesting an action of glucocorticoids that may be unique to immune regulation. We also observed evidence for genotype‐dependent glucocorticoid‐mediated APA (referred to as pharmacogenomic‐alterative polyadenylation quantitative trait loci), providing potential functional mechanisms for a series of common genetic variants that had previously been associated with immune disorders, but without a clear mechanism. In summary, this study reports a series of observations regarding the impact of glucocorticoids on APA, raising the possibility that this mechanism might have implications for both disease pathophysiology and drug therapy.

Background Phase-contrast cine magnetic resonance imaging (PC-MRI) has been used to measure cerebrospinal fluid (CSF) flow dynamics, but the influence of the area of the aqueduct and region of interest (ROI) on quantification of stroke volume (SV) has not been assessed. Purpose To assess the influence of the area of the ROI in quantifying the aqueductal SV measured with PC-MRI within the cerebral aqueduct. Material and Methods Nine healthy volunteers (mean age = 29.6 years) were enrolled in the study, and brain MRI examinations were performed on a 3.0-T system. Quantitative analysis of the aqueductal CSF flow was performed using manual ROI placement. ROIs were separately drawn for each of the 12 phases of the cardiac cycle, and changes in aqueduct size during the cardiac cycle were determined. The SV was calculated using 12 different aqueductal ROIs and compared with the SV calculated using a fixed ROI size. Results There was variation in the size of the aqueduct during the cardiac cycle. In addition, the measured SV increased with a greater area of the ROI. A significant difference in the calculated SVs with the 12 variable ROIs was observed compared with that using a fixed ROI throughout the cardiac cycle. Conclusion To establish reliable reference values for the SV in future studies, a variable ROI should be considered.

Abstract The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a ‘landing pad’ system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.

Anti-retroviral therapy (ART) has greatly improved the quality and length of life for people living with HIV, but immune activation does not normalize during ART, and persistent immune activation has been linked to increased morbidity and mortality. We report a comparison of assays of two potential sources of immune activation during ART: rare cells producing HIV and the virus’ major viral protein, p24, benchmarked on a cell model of active and latent infections and a method to visualize HIV-producing cells.