Citations

Abstract High grade gliomas are devastating diseases. In the pediatric population, diffuse midline gliomas with the H3K27M mutation (H3K27M DMG) are the most aggressive primary malignant brain tumors. With no effective therapies available, children typically succumb to disease within one year of diagnosis. In adults, glioblastoma (GBM) remains a death sentence despite standard clinical care. Therefore, effective therapies for these tumors remain one of the most urgent and unmet needs in modern medicine. Interleukin 13 receptor subunit alpha 2 (IL-13Rα2) is a cell-surface transmembrane protein upregulated in H3K27M DMG and GBM versus normal brain tissue, posing a potentially promising therapeutic target for both tumors. In this study, we investigated the pharmacological effects of a novel peptide-toxin conjugate, IL13.E13K-PE4E (also known as GB-13), that contains a targeting moiety designed to bind IL-13Rα2 with high specificity and a point-mutant cytotoxic domain derived from Pseudomonas exotoxin A. We demonstrated that IL13.E13K-PE4E was a potent killer of cultured H3K27M DMG and GBM cells in vitro. Intratumoral administration of IL13.E13K-PE4E via convection-enhanced delivery (CED) decreased tumor burden and prolonged survival in both H3K27M DMG and GBM murine xenograft models. Furthermore, we observed enhanced drug tissue retention and volume of distribution after CED, suggesting IL13.E13K-PE4E is capable of covering the target area and remaining at the site of infusion long enough to impart therapeutic effects. In summary, administration of IL13.E13K-PE4E demonstrated a potent pharmacological response in H3K27M DMG and GBM models both in vitro and in vivo in a manner strongly associated with IL13Rα2 expression, underscoring the potential of IL13Rα2 targeted therapy in a subset of these tumors.

TNF ligation of TNF receptor 1 (TNFR1) promotes either inflammation and cell survival by (a) inhibiting RIPK1’s death-signaling function and activating NF- κ B or (b) causing RIPK1 to associate with the death-inducing signaling complex to initiate apoptosis or necroptosis. The cellular source of TNF that results in RIPK1-dependent cell death remains unclear. To address this, we employed in vitro systems and murine models of T cell–dependent transplant or tumor rejection in which target cell susceptibility to RIPK1-dependent cell death could be genetically altered. We show that TNF released by T cells is necessary and sufficient to activate RIPK1-dependent cell death in target cells and thereby mediate target cell cytolysis independently of T cell frequency. Activation of the RIPK1-dependent cell death program in target cells by T cell–derived TNF accelerates murine cardiac allograft rejection and synergizes with anti-PD1 administration to destroy checkpoint blockade–resistant murine melanoma. Together, the findings uncover a distinct immunological role for TNF released by cytotoxic effector T cells following cognate interactions with their antigenic targets. Manipulating T cell TNF and/or target cell susceptibility to RIPK1-dependent cell death can be exploited to either mitigate or augment T cell–dependent destruction of allografts and malignancies to improve outcomes.

Intra-arterial drug delivery circumvents the first-pass effect and is believed to increase both efficacy and tolerability of primary and metastatic brain tumor therapy. The aim of this update is to report on pertinent articles and clinical trials to better understand the research landscape to date and future directions. Elsevier’s Scopus and ClinicalTrials.gov databases were reviewed in August 2021 for all possible articles and clinical trials of intra-arterial drug injection as a treatment strategy for brain tumors. Entries were screened against predefined selection criteria and various parameters were summarized. Twenty clinical trials and 271 articles satisfied all inclusion criteria. In terms of articles, 201 (74%) were primarily clinical and 70 (26%) were basic science, published in a total of 120 different journals. Median values were: publication year, 1986 (range, 1962–2021); citation count, 15 (range, 0–607); number of authors, 5 (range, 1–18). Pertaining to clinical trials, 9 (45%) were phase 1 trials, with median expected start and completion years in 2011 (range, 1998–2019) and 2022 (range, 2008–2025), respectively. Only one (5%) trial has reported results to date. Glioma was the most common tumor indication reported in both articles (68%) and trials (75%). There were 215 (79%) articles investigating chemotherapy, while 13 (65%) trials evaluated targeted therapy. Transient blood–brain barrier disruption was the commonest strategy for articles (27%) and trials (60%) to optimize intra-arterial therapy. Articles and trials predominately originated in the United States (50% and 90%, respectively). In this bibliometric and clinical trials analysis, we discuss the current state and trends of intra-arterial therapy for brain tumors. Most articles were clinical, and traditional anti-cancer agents and drug delivery strategies were commonly studied. This was reflected in clinical trials, of which only a single study had reported outcomes. We anticipate future efforts to involve novel therapeutic and procedural strategies based on recent advances in the field.

Background: Several factors are associated with an increased risk of anterior cruciate ligament (ACL) reconstruction revision. However, the ability to accurately translate these factors into a quantifiable risk of revision at a patient-specific level has remained elusive. We sought to determine if machine learning analysis of the Norwegian Knee Ligament Register (NKLR) can identify the most important risk factors associated with subsequent revision of primary ACL reconstruction and develop a clinically meaningful calculator for predicting revision of primary ACL reconstruction. Methods: Machine learning analysis was performed on the NKLR data set. The primary outcome was the probability of revision ACL reconstruction within 1, 2, and/or 5 years. Data were split randomly into training sets (75%) and test sets (25%). Four machine learning models were tested: Cox Lasso, survival random forest, generalized additive model, and gradient boosted regression. Concordance and calibration were calculated for all 4 models. Results: The data set included 24,935 patients, and 4.9% underwent a revision surgical procedure during a mean follow-up (and standard deviation) of 8.1 ± 4.1 years. All 4 models were well-calibrated, with moderate concordance (0.67 to 0.69). The Cox Lasso model required only 5 variables for outcome prediction. The other models either used more variables without an appreciable improvement in accuracy or had slightly lower accuracy overall. An in-clinic calculator was developed that can estimate the risk of ACL revision (Revision Risk Calculator). This calculator can quantify risk at a patient-specific level, with a plausible range from near 0% for low-risk patients to 20% for high-risk patients at 5 years. Conclusions: Machine learning analysis of a national knee ligament registry can predict the risk of ACL reconstruction revision with moderate accuracy. This algorithm supports the creation of an in-clinic calculator for point-of-care risk stratification based on the input of only 5 variables. Similar analysis using a larger or more comprehensive data set may improve the accuracy of risk prediction, and future studies incorporating patients who have experienced failure of ACL reconstruction but have not undergone subsequent revision may better predict the true risk of ACL reconstruction failure. Level of Evidence: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Abstract Background and Aims Patient-reported outcomes are recommended endpoints in Crohn’s disease [CD] trials. The association between patient-reported general well-being relative to symptoms of diarrhoea and abdominal pain [AP] in patients with moderate to severe CD was explored. Methods Patients from three randomized, placebo-controlled, double-blind adalimumab or upadacitinib studies with average daily very soft/liquid stool frequency [SF] ≥4 and/or AP score ≥2 at baseline were included. Using electronic diaries, patients reported general well-being [seven-point Likert scale; 1 = worst; 7 = best] in item 10 of the Inflammatory Bowel Disease Questionnaire [IBDQ]. Changes in well-being and clinical outcomes of SF and AP from baseline to week 12 or 16, and the relationship between well-being and clinical outcomes were evaluated using cumulative distribution function and probability density function curves. Results In total, 858 patients with CD were included [adalimumab, n = 695; upadacitinib, n = 163]. Patients who achieved clinical remission [SF ≤2.8, AP score ≤1.0, neither worse than baseline] were more likely than those not in clinical remission to report IBDQ item 10 response in the 6–7 group category but not IBDQ categories ≤5. Higher IBDQ score for item 10 [6–7] was associated with lower SF and AP score. Greater point increases in IBDQ item 10 were associated with a greater percentage decrease in clinical parameters; a ≥25–30% decrease in SF or AP was associated with a ≥1-point improvement in IBDQ. Conclusions An association between improvements in patient-reported general well-being and clinical remission/response was observed using outcomes of SF and AP, supporting the clinical remission/response endpoint definitions used in clinical studies of CD. Clinical Trial Registrations [ClinicalTrials.gov]: NCT00077779 [CHARM]; NCT00348283 [EXTEND]; NCT02365649 [CELEST].