Citations

AbstractMeningeal solitary fibrous tumors (SFT) are rare and have a high frequency of local recurrence and distant metastasis. In a cohort of 126 patients (57 female, 69 male; mean age at surgery 53.0 years) with pathologically confirmed meningeal SFTs with extended clinical follow‐up (median 9.9 years; range 15 days–43 years), we performed extensive molecular characterization including genome‐wide DNA methylation profiling (n = 80) and targeted TERT promoter mutation testing (n = 98). Associations were examined with NAB2::STAT6 fusion status (n = 101 cases; 51 = ex5‐7::ex16‐17, 26 = ex4::ex2‐3; 12 = ex2‐3::exANY/other and 12 = no fusion) and placed in the context of 2021 Central Nervous System (CNS) WHO grade. NAB2::STAT6 fusion breakpoints (fusion type) were significantly associated with metastasis‐free survival (MFS) (p = 0.03) and, on multivariate analysis, disease‐specific survival (DSS) when adjusting for CNS WHO grade (p = 0.03). DNA methylation profiling revealed three distinct clusters: Cluster 1 (n = 38), Cluster 2 (n = 22), and Cluster 3 (n = 20). Methylation clusters were significantly associated with fusion type (p < 0.001), with Cluster 2 harboring ex4::ex2‐3 fusion in 16 (of 20; 80.0%), nearly all TERT promoter mutations (7 of 8; 87.5%), and predominantly an “SFT” histologic phenotype (15 of 22; 68.2%). Clusters 1 and 3 were less distinct, both dominated by tumors having ex5‐7::ex16‐17 fusion (respectively, 25 of 33; 75.8%, and 12 of 18; 66.7%) and with variable histological phenotypes. Methylation clusters were significantly associated with MFS (p = 0.027), but not overall survival (OS). In summary, NAB2::STAT6 fusion type was significantly associated with MFS and DSS, suggesting that tumors with an ex5::ex16‐17 fusion may have inferior patient outcomes. Methylation clusters were significantly associated with fusion type, TERT promoter mutation status, histologic phenotype, and MFS.

Abstract Background: Immune checkpoint inhibitors (ICIs) have significantly improved outcomes for patients with metastatic non-small cell lung cancer (NSCLC). However, clinical management is challenging. The PD-L1 biomarker does not optimally guide the choice between ICI monotherapy and combination ICI-chemotherapy, and there are currently no biomarkers to predict immune-related adverse events (irAEs). Here, we describe a versatile platform based on plasma proteomics and machine learning for generating predictive tools to support treatment decisions. Methods: Pre-treatment plasma samples were collected from 616 NSCLC patients receiving ICI-based therapy (NCT04056247). Clinical benefit (CB) data and irAEs were recorded. Proteomic profiling of plasma samples was performed using the SomaScan® assay, covering ~7000 proteins per sample. Proteins associated with Clinical Benefit (progression-free survival at 12 months) were classified as resistance-associated proteins (RAPs). Proteins associated with grade ≥3 irAEs occurring within the first 100 days of treatment were classified as toxicity-associated proteins (TAPs). RAPs and TAPs were integrated into two separate machine learning-based models, yielding CB and irAE probabilities, respectively. The CB model used a CB probability threshold to assign patients a PROphet-positive or PROphet-negative result. Bioinformatic analysis was performed on RAPs and TAPs. Results: CB and irAE models displayed strong predictive performance with a high correlation between predicted probability and observed CB or irAE rate (CB model: R2=0.98; p-value&lt;0.0001; irAE model: R2= 0.92; p-value &lt;0.0001). In the CB model, patients classified as PROphet-positive achieved significantly longer overall survival (OS) than PROphet-negative patients, with a median OS of 25.9 vs. 10.8 months (hazard ratio, HR = 0.51; p-value&lt;0.001). Furthermore, patients with PD-L1 ≥50% tumors and a PROphet-negative result had significantly longer OS with ICI-chemotherapy in comparison to ICI monotherapy (HR=0.23, p-value = 0.0003), suggesting that combination therapy is preferable for such patients despite high PD-L1 levels. Bioinformatic analysis showed that RAPs related to immune regulation, angiogenesis, chemo-resistance, and other potential resistance mechanisms displayed higher expression levels in patients who did not benefit from treatment. Neutrophil- and inflammation-related proteins were significantly enriched in patients who experienced irAEs. Conclusions: We describe two machine-learning based predictive tools that may be used separately or in combination to inform treatment decisions based on the patient’s likelihood to benefit from ICI therapy and to develop serious irAEs. Our findings also provide biological insights related to treatment resistance and immune-related toxicity. Citation Format: Michal Harel, Petros Christopoulos, Igor Puzanov, Jair Bar, Iris Kamer, Niels Reinmuth, Ina Koch, Mor Moskovitz, Adva Levy-Barda, Alona Zer, Michal Lotem, David Farrugia, Rivka Katzenelson, Gillian Price, Abed Agbarya, Helen Cheley, Adam Hassani, Mahmoud Abu-Amna, Tom Geldart, Anirban Chatterjee, Andreas Polychronis, Maya Gottfried, Yanyan Lou, Tatiana Harkovsky, Alison Brewster, Ido Wolf, Ella Tepper, Ben Yellin, Itamar Sela, Coren Lahav, Yehonatan Elon, Raya Leibowitz, Adam P. Dicker, Young Kwang Chae, Ryan J. Sullivan, David Carbone, David Gandara, Jarushka Naidoo. Plasma proteomics-based models for predicting therapeutic benefit and immune-related adverse events in non-small cell lung cancer patients treated with immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1208.

PURPOSE Current guidelines for the management of metastatic non–small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247 ) of patients undergoing PD-1/PD-L1 inhibitor–based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor–based treatments, evidenced by high concordance between predicted and observed CB ( R 2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION Plasma proteome–based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor–based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Abstract Single case studies of extraordinary disease resilience may provide therapeutic insight into conditions for which no definitive treatments exist. An otherwise healthy 35-year-old man (patient-R) with the canonical pathogenic ACVR1R206H variant and the classic congenital great toe malformation of fibrodysplasia ossificans progressiva (FOP) had extreme paucity of post-natal heterotopic ossification (HO) and nearly normal mobility. We hypothesized that patient-R lacked a sufficient post-natal inflammatory trigger for HO. A plasma biomarker survey revealed a reduction in total matrix metalloproteinase-9 (MMP-9) compared to healthy controls and individuals with quiescent FOP. Whole exome sequencing identified compound heterozygous variants in MMP-9 (c.59C &gt; T, p.A20V and c.493G &gt; A, p.D165N). Structural analysis of the D165N variant predicted both decreased MMP-9 secretion and activity that were confirmed by enzyme-linked immunosorbent assay and gelatin zymography. Further, human proinflammatory M1-like macrophages expressing either MMP-9 variant produced significantly less Activin A, an obligate ligand for HO in FOP, compared to wildtype controls. Importantly, MMP-9 inhibition by genetic, biologic, or pharmacologic means in multiple FOP mouse models abrogated trauma-induced HO, sequestered Activin A in the extracellular matrix (ECM), and induced regeneration of injured skeletal muscle. Our data suggest that MMP-9 is a druggable node linking inflammation to HO, orchestrates an existential role in the pathogenesis of FOP, and illustrates that a single patient’s clinical phenotype can reveal critical molecular mechanisms of disease that unveil novel treatment strategies.

Fibrodysplasia ossificans progressiva (FOP; MIM# 135100) is an ultra-rare congenital disorder caused by gain-of-function point mutations in the Activin receptor A type I (ACVR1, also known as ALK2) gene. FOP is characterized by episodic heterotopic ossification (HO) in skeletal muscles, tendons, ligaments, or other soft tissues that progressively causes irreversible loss of mobility. FOP mutations cause mild ligand-independent constitutive activation as well as ligand-dependent bone morphogenetic protein (BMP) pathway hypersensitivity of mutant ACVR1. BMP signaling is also a key pathway for mediating acquired HO. However, HO is a highly complex biological process involving multiple interacting signaling pathways. Among them, the hypoxia-inducible factor (HIF) and mechanistic target of rapamycin (mTOR) pathways are intimately involved in both genetic and acquired HO formation. HIF-1α inhibition or mTOR inhibition reduces HO formation in mouse models of FOP or acquired HO in part by de-amplifying the BMP pathway signaling. Here, we review the recent progress on the mechanisms of the HIF-1α and mTOR pathways in the amplification of HO lesions and discuss the future directions and strategies to translate the targeting of HIF-1α and the mTOR pathways into clinical interventions for FOP and other forms of HO.

Abstract During the 20th century, inflammatory bowel disease (IBD) was considered a disease of early-industrialized regions in North America, Europe, and Oceania. At the turn of the 21st century, incidence of IBD increased in newly-industrialized and emerging regions in Africa, Asia, and Latin America, while prevalence in early-industrialized regions started to grow steadily. Changes in incidence and prevalence denote evolution of IBD across four epidemiologic stages: Stage 1 (Emergence), characterized by low incidence and prevalence; stage 2 (Acceleration in Incidence), characterized by rapidly rising incidence and low prevalence; and stage 3 (Compounding Prevalence), characterized by decelerating, plateauing, or declining incidence and steadily rising prevalence. A fourth stage (Prevalence Equilibrium) has been proposed where the slope of prevalence plateaus due to shifting demographics of an aging IBD population, but it has not yet been evidenced. To date, these stages have been theoretical without specific incidence/prevalence indicators defining transition points. Using real-world data from 490 population-based studies comprising 80 global regions and spanning over a century (1920–2023), we show spatiotemporal transitions across stages 1–3 and model transition towards stage 4. Understanding the evolution of IBD across epidemiologic stages allows healthcare systems to better prepare for the future worldwide burden of IBD.

On June 3, 2023, the American Society of Transplant Surgeons convened a meeting in San Diego, California to (1) develop a consensus statement with supporting data on the ethical tenets of thoracoabdominal normothermic regional perfusion (NRP) and abdominal NRP; (2) provide guidelines for the standards of practice that should govern thoracoabdominal NRP and abdominal NRP; and (3) develop and implement a central database for the collection of NRP donor and recipient data in the United States. National and international leaders in the fields of neuroscience, transplantation, critical care, NRP, Organ Procurement Organizations, transplant centers, and donor families participated. The conference was designed to focus on the controversial issues of neurological flow and function in donation after circulatory death donors during NRP and propose technical standards necessary to ensure that this procedure is performed safely and effectively. This article discusses major topics and conclusions addressed at the meeting.

AbstractAxenfeld‐Rieger Syndrome (ARS) type 1 is a rare autosomal dominant condition characterized by anterior chamber anomalies, umbilical defects, dental hypoplasia, and craniofacial anomalies, with Meckel's diverticulum in some individuals. Here, we describe a clinically ascertained female of childbearing age with ARS for whom clinical targeted sequencing and deletion/duplication analysis followed by clinical exome and genome sequencing resulted in no pathogenic variants or variants of unknown significance in PITX2 or FOXC1. Advanced bioinformatic analysis of the genome data identified a complex, balanced rearrangement disrupting PITX2. This case is the first reported intrachromosomal rearrangement leading to ARS, illustrating that for patients with compelling clinical phenotypes but negative genomic testing, additional bioinformatic analysis are essential to identify subtle genomic abnormalities in target genes.

Abstract Purpose: The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial. Patients and Methods: I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy “graduates” if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction. Results: There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%–99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease. Conclusions: The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority &gt;90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.