Citations

SUMMARY Tuberculosis induces diverse lesions, such as necrotic pneumonia, contributing to disease progression and transmission. Despite advances in understanding the role of ATP-gated P2RX7 ion channels in developing severe forms of tuberculosis, the regulation of this important signaling pathway remains unclear. Herein, we show that the ectonucleotidase CD39 plays an essential regulatory role in TB progression by preventing lung tissue damage, bacterial dissemination, and excessive inflammatory responses. Mechanistically, through its enzymatic activity on the cellular surface, CD39 protects infected macrophages from undergoing necrotic death mediated by P2RX7 activation. We proposed that by protecting macrophages from P2RX7-mediated cell death and bacterial dissemination, CD39 prevents the development of necrotic lesions. Altogether, these findings uncover a significant role for CD39 as an essential component of the molecular regulation underlying the development of severe tuberculosis. GRAPHICAL ABSTRACT Brief In tuberculosis, necrotic granuloma-like structures release extracellular ATP (eATP), which triggers P2RX7-mediated immune cell death. CD39 degrades eATP, preventing P2RX7 activation and promoting macrophage survival, thereby limiting inflammation, tissue damage, and bacterial dissemination.

Radiologists are integral members of the interdisciplinary team for patients with mucinous appendiceal neoplasms and can directly affect care by suggesting the diagnosis of pseudomyxoma peritonei, optimizing imaging protocols for evaluating peritoneal implants, and reporting the primary tumor and spilled tumor cells thoroughly.

Background: When missing data are present in clinical outcomes studies, complete-case analysis (CCA) is often performed, whereby patients with missing data are excluded. While simple, CCA analysis may impart selection bias and reduce statistical power, leading to erroneous statistical results in some cases. However, there exist more rigorous statistical approaches, such as single and multiple imputation, which approximate the associations that would have been present in a full dataset and preserve the study’s power. The purpose of this study is to evaluate how statistical results differ when performed after CCA analysis versus imputation methods. Methods: This simulation study analyzed a sample dataset consisting of 2204 shoulders, with complete datapoints from a larger multicenter total shoulder arthroplasty database. From the sampled dataset of demographics, surgical characteristics, and clinical outcomes, we created five test datasets, ranging from 100 to 2000 shoulders, and simulated 10–50% missingness in the postoperative American Shoulder and Elbow Surgeons (ASES) score and range of motion in four planes in missing completely at random (MCAR), missing at random (MAR), and not missing at random (NMAR) patterns. Missingness in outcomes was remedied using CCA, three single imputation techniques, and two multiple imputation techniques. The imputation performance was evaluated relative to the native complete dataset using the root mean squared error (RMSE) and the mean absolute percentage error (MAPE). We also compared the mean and standard deviation (SD) of the postoperative ASES score and the results of multivariable linear and logistic regression to understand the effects of imputation on the study results. Results: The average overall RMSE and MAPE were similar for MCAR (22.6 and 27.2%) and MAR (19.2 and 17.7%) missingness patterns, but were substantially poorer for NMAR (37.5 and 79.2%); the sample size and the percentage of data missingness minimally affected RMSE and MAPE. Aggregated mean postoperative ASES scores were within 5% of the true value when missing data were remedied with CCA, and all candidate imputation methods for nearly all ranges of sample size and data missingness when data were MCAR or MAR, but not when data were NMAR. When data were MAR, CCA resulted in overestimates of the SD. When data were MCAR or MAR, the accuracy of the regression estimate (β or OR) and its corresponding 95% CI varied substantially based on the sample size and proportion of missing data for multivariable linear regression, but not logistic regression. When data were MAR, the width of the 95% CI was up to 300% larger when CCA was used, whereas most imputation methods maintained the width of the 95% CI within 50% of the true value. Single imputation with k-nearest neighbor (kNN) method and multiple imputation with predictive mean matching (MICE-PMM) best-reproduced point estimates and intervariable relationships resembling the native dataset. Availability of correlated outcome scores improved the RMSE, MAPE, accuracy of the mean postoperative ASES score, and multivariable linear regression model estimates. Conclusions: Complete-case analysis can introduce selection bias when data are MAR, and it results in loss of statistical power, resulting in loss of precision (i.e., expansion of the 95% CI) and predisposition to false-negative findings. Our data demonstrate that imputation can reliably reproduce missing clinical data and generate accurate population estimates that closely resemble results derived from native primary shoulder arthroplasty datasets (i.e., prior to simulated data missingness). Further study of the use of imputation in clinical database research is critical, as the use of CCA may lead to different conclusions in comparison to more rigorous imputation approaches.

e18017 Background: Head and neck (H&N) cancers affect the oral cavity, pharynx, larynx, salivary glands, nasal cavity, and sinuses. In Sub-Saharan Africa (SSA), the true burden of H&N cancers remains unclear, with available estimates suggesting approximately 47,000 new cases and 26,000 deaths annually. Limited cancer datasets hinder understanding of disease patterns and outcomes. This study explores patient characteristics, treatments, and outcomes to guide regional cancer control efforts. Methods: A cancer dataset was created and implemented at 4 leading teaching hospitals in Ghana, Kenya, Ethiopia, and Rwanda to systematically collect data on patient demographics, disease characteristics, and treatment patterns. Established through competitive grant funding, the primary objective of the database was to assess the indirect impact of the COVID-19 pandemic on cancer care. The dataset includes all cancer patients seen in consultation and/or treated between 2016 and 2023. In this study, a subset of patients diagnosed with H&N cancers was analyzed using descriptive statistics to assess clinical characteristics, treatments modalities, and patients' outcomes. Results: A total of 1,023 patients with H&N cancer were included in the analysis. The median age at diagnosis was 54 yrs (IQR 41-66), with 37% (n= 374) of the cohort being female. A total of 55% (n= 549) had no health insurance coverage. Of those with staging data, majority presented with advanced disease (89%) on presentation. Regarding treatment modality, 16% (n= 157) underwent surgery, 27% (n=279) received radiotherapy (RT), 14% (n= 143) received chemotherapy (CT), and 56% (n= 572) received no cancer therapy. Of those who received CT the timing was neoadjuvant (12%), concurrent with RT (22%), adjuvant after surgery (8.9%) or as palliative treatment (57%). Platinum-based agents (94%) were the most common CT, followed by Taxol-based (31%), and 5FU-based agents (27%). Regarding RT, planning was performed using 2D (55%) and 3D (45%) techniques. The median delivered dose was 60 Gy in 30 fractions. At a median follow up of 43 months, 1.6% were disease free, 10% (n= 103) were alive, 5.9% (n= 60) were confirmed dead, and 84% (n= 848) were lost to follow up. Conclusions: This study identifies key challenges in managing H&N cancers in SSA, including late-stage presentation, limited access to advanced treatment modalities, and a high lost to follow-up rate (84%). The reliance on older RT techniques such as 2D planning and the limited use of surgery highlight gaps in infrastructure and resource availability. Limited health insurance coverage suggests potential financial barriers to care and disparities in treatment access. Addressing these challenges will require greater investment in cancer care, expansion of the oncology workforce, and improvements in healthcare infrastructure to support better patient outcomes in the region.

TPS1138 Background: The SV-BR-1-GM breast cancer cell line activates anti-tumor immunity by expressing tumor associated antigens and secreting GM-CSF which enhances dendritic cell activation and promotes adaptive (T-cell mediated) and innate (dendritic and NK cell) immune responses. The cells are also engineered to optimize immune recognition through pt specific HLA antigen matching. SV-BR-1-GM acts through direct antigen presentation and CD4+ T-cell activation and, when combined w/ checkpoint inhibitors (CPIs), has demonstrated clinical benefit in 54 heavily pretreated metastatic breast cancer (MBC) pts. In pts w/ disease progression following CPI therapy, similar or improved progression free survival (PFS) compared to their prior treatment regimen. Disease control following antibody drug conjugates was observed in 40%of pts. Clinical benefit was seen in 5 out of 8 pts w/ untreated intracranial metastases. CD8+ Immuno-PET imaging suggests systemic activation, w/ increased CD8+ tumor infiltrating lymphocytes at both primary and metastatic tumor sites, as well as lymphoid organs. Optimized sequencing of CPI w/ SV-BR-1-GM and its latest phase 3 formulation have shown enhanced clinical outcomes, including improved overall survival (OS) (median 13.4 mos), PFS (3.6 mos), and clinical benefit rate (CBR; 61%).These findings have informed refinements to the ongoing pivotal, registration enabling Phase 3 trial, designed to optimize pt selection and treatment sequencing strategies. Methods: This ongoing multicenter, randomized, open label Phase 3 trial evaluates Bria-IMT + CPI vs. Treatment of Physician’s Choice (TPC) in MBC pts lacking approved curative therapies. Pts are randomized 1:1:1 to Bria-IMT + CPI, TPC, or Bria-IMT monotherapy (discontinued after 150 enrollments to prioritize combination arms). The Bria-IMT regimen consists of: Day -2: Cyclophosphamide 300 mg/m², Day 0: 20M irradiated SV-BR-1-GM cells, Day 2/3: 0.1 mcg pegylated α interferon at each inoculation site. CPI infusion is administered Day -3 to 3. Cycles q3w. TPC regimens follow site specific SOC. Imaging q6w (first 2 cycles), then q8w. Eligibility includes all MBC subtypes, including CNS mets, and permits prior CPI therapy ( >21 days pre-treatment). There will be 100 sites across the U.S., Canada, and ex-North America w/ an enrollment target of 404. The trial is currently active at 59 sites with 217 sub investigators. To date, 67 pts screened: 46 randomized (median age 56 yrs [34–83], median 6 [2–13] prior lines of therapy. The primary endpoint is OS, with an interim analysis at 144 events targeting a hazard ratio of 0.6. Secondary endpoints: PFS, overall response rate, CBR, CNS event free survival, and TWiST. Safety analyses ongoing; pt reported outcomes assess subjective treatment impact. Clinical trial information: NCT03328026 .

e14551 Background: Extracellular vesicles (EVs) are microscopic particles released by all cell types with a distinct fingerprint reflecting the cell of origin. In patients with prostate cancer, PSMA+EVs have been associated with clinical outcomes. In this study, we investigated tumor-derived EVs (tdEVs) using the tumor-specific CD326 marker as a novel biomarker for pancreas ductal adenocarcinoma (PDAC). Methods: The study included patients with localized PDAC treated on a prospective phase 2 clinical trial evaluating a 15-fraction chemoradiation (CRT) regimen. Blood samples were obtained after induction chemotherapy (C) (prior to CRT) and in follow-up. 20 healthy controls were included. High-resolution flow cytometry enumerated levels of fluorescent antibody labelled tumor-specific CD326 (EpCAM)-positive EVs. All samples were de-identified and randomly coded. The technologist responsible for EV analysis was blinded to patient information and clinical data. Each sample was run in triplicate. Flow cytometry data was analyzed with custom-built software to automatically determine and apply gates and generate reports with scatter plots and EV concentrations for each combination of markers and data summaries. Results: tdEV data were analyzed from 70 patients with pre-CRT samples. Patients had mean age 66 years (9.0 standard deviation), with 60% ECOG 0, 43% borderline resectable and 48% locally advanced. Patients had a median 8 cycles of C prior to CRT, and 70% proceeded to surgery after CRT. 2-year overall survival (OS) was 54%. Patient samples showed elevated total CD326 EVs compared to the healthy controls (p = 0.0005). Furthermore, patient CD326 EVs revealed two distinct subpopulations: small (120-1,000nm) and large (1,000-3,000nm) size CD326 EVs. No large CD326 subpopulation was found in healthy donor samples. Higher pre-CRT levels of total CD326 and large CD326 EVs were associated with decreased progression-free survival (PFS) (hazard ratio (HR) = 2.38, p = 0.013 and HR = 2.017, p = 0.021) on multivariable models with surgical resection. Resection was associated with increased PFS (p < 0.0001), and the interaction terms did not meet significance (p = 0.083 and p = 0.21). No differences in pre-CRT total or large CD326 EVs were identified between patients with or without surgical resection (p = 0.72 and p = 0.83). CA19-9 levels were not predictive of clinical outcomes in this trial and showed no association with EV levels. Conclusions: We present an association between clinical outcomes and tdEVs in PDAC, highlighting their potential as a novel, independent biomarker. If validated, tdEVs may offer an opportunity to personalize care and improve risk stratification.

TPS3644 Background: Currently, there are no biomarkers validated prospectively in randomized studies for resected colon cancer (CC) to determine need for adjuvant chemotherapy (AC). However, circulating tumor DNA (ctDNA) represents a highly specific and sensitive approach (especially with serial monitoring) for identifying minimal/molecular residual disease (MRD) post-surgery in CC patients (pts), and may outperform traditional clinical and pathological features in prognosticating risk for recurrence. CC pts who do not have detectable ctDNA (ctDNA-) are at a much lower risk of recurrence and may be spared the toxicities associated with AC. Furthermore, for CC pts with detectable ctDNA (ctDNA+) who are at a very high risk of recurrence, the optimal AC regimen has not been established. We hypothesize that for pts whose CC has been resected, ctDNA status may be used to risk-stratify for making decisions about AC. Methods: In this prospective phase II/III trial, up to 1,912 pts with resected stage IIB, IIC, and III CC will be enrolled. Based on the post-operative ctDNA status using personalized and tumor-informed assay (Signatera™, bespoke assay), those who are ctDNA- (Cohort A) will be randomized to immediate AC with fluoropyrimidine (FP)+oxaliplatin (Ox) for 3-6 mos per established guidelines v serial ctDNA monitoring. Patients who are ctDNA+ post-operatively, or with serial monitoring (Cohort B), will be randomized to FP+Ox v more intensive AC with addition of irinotecan (I) for 6 mos. One cycle of chemotherapy is allowed while awaiting ctDNA testing results for cohort assignment. The primary endpoints for Cohort A are time to ctDNA+ status (phase II) and disease-free survival (DFS) (phase III) in the immediate v delayed AC arms. The primary endpoint for Cohort B is DFS in the FP+Ox v FP+Ox+I arms for both phase II and phase III portions of the trial. Secondary endpoints include prevalence of detectable ctDNA post-operatively, time-to-event outcomes (overall survival and time to recurrence) by ctDNA status, and the assessment of compliance to adjuvant therapy. Biospecimens including archival tumor tissue, as well as post-operative plus serial matched/normal blood samples, will be collected for exploratory correlative research. Active enrollment across the NCTN started in June 2022 with CCTG sites joining in August 2023. Current accrual (as of 1-27-2025): 647/1,912. NCT: 05174169. Support: U10 CA180868, -180822; -180888; UG1 CA189867; Natera, Inc. Clinical trial information: NCT05174169 .

TPS3634 Background: For patients with oligometastatic colorectal cancer (CRC), aggressive local therapy of isolated metastases, particularly in the liver, has been associated with long-term progression-free and overall survival (OS) primarily based on retrospective evidence. However, in patients with limited metastatic CRC that is deemed inoperable or those with additional disease outside of the liver or lungs, the role of local ablative therapies, including microwave ablation (MWA) and stereotactic body radiation therapy (SBRT), to render patients disease free is less clear. Despite the long history of treating oligometastatic CRC with local therapy, which is largely provider biased, questions remain regarding the benefit of extending the paradigm of metastatic directed therapy to patients with more extensive disease. This trial seeks to use a pragmatic multimodality approach that mirrors the current clinical dilemma. This study is designed to evaluate the safety and efficacy of adding total ablative therapy (TAT) of all sites of disease to standard of care systemic treatment in those with limited metastatic CRC. Methods: A022101/NRG-GI009 is a National Clinical Trials Network randomized phase III study planned to enroll 364 patients with newly diagnosed metastatic CRC (BRAF wild-type, microsatellite stable) without peritoneal metastasis or liver-only disease on baseline imaging. Patients receive first-line systemic therapy for 12-39 weeks. Patients with ≤4 sites of metastatic disease following initial systemic therapy that are amenable to any combination of surgical resection, MWA, and/or SBRT are then randomized 1:1, stratified by number of metastatic organ sites (1-2 vs. 3-4), timing of metastatic disease diagnosis (de novo vs. secondary), and presence of metastatic disease outside the liver/lungs in at least 1 site. Patients in Arm 1 will receive TAT consisting of treatment of all metastatic sites with SBRT, MWA, and/or surgical resection followed by standard of care systemic therapy. Patients in Arm 2 will continue with standard of care systemic therapy alone. The primary endpoint is OS. Secondary endpoints include event-free survival, treatment-related toxicities, and local recurrence with exploratory biomarker analyses. The study needs 346 evaluable patients combined in the 2 arms to demonstrate an improvement in OS with a hazard ratio of 0.7 to provide 80% power with a one-sided alpha of 5%. The trial utilizes a group sequential design with two interim analyses (25% and 50% of events) for futility. The trial activated in January 2023 and recruitment is ongoing. Support: U10CA180821, U10CA180882; https://acknowledgments.alliancefound.org. U10CA180820 (ECOG-ACRIN); U10CA180868 (NRG); U10CA180888 (SWOG); Clinical trial information: NCT05673148 .

e14626 Background: Despite advancements in neoadjuvant therapy and surgical techniques, patients with pancreatic ductal adenocarcinoma (PDAC) often experience high recurrence rates after total neoadjuvant therapy (TNT) and resection. Existing tumor response scoring systems, such as the College of American Pathologists (CAP) guidelines, fail to stratify recurrence risk effectively, emphasizing the need for novel, objective approaches. Methods: This study evaluated spatial characteristics of residual cancer and stroma in a multi-site cohort of 203 patients with resected PDAC following TNT, not having achieved a major pathologic response (CAP 2 or 3). Whole slide images (WSI) of hematoxylin and eosin-stained sections were digitized and analyzed using artificial intelligence to perform tissue segmentation. Metrics quantifying spatial morphology and configuration, inspired by principles of landscape ecology, were computed to explore spatial features of the tumor microenvironment (TME). Statistical models (recursive partitioning and regression tree [RPRT] model and Cox model with backwards eliminations) incorporating these features were developed to stratify recurrence risk. Results: Five metrics were used for risk classification model build. Three models successfully classified patients into high- and low-risk groups based on spatial metrics. Models demonstrated moderate discriminatory power (C-statistics: 0.560–0.566) and showed that increased tumor fragmentation, like stromal patch density and cancer patch shape index, were strongly associated with improved outcomes. Conclusions: Integrating spatial metrics of cancer-stroma configuration enhances risk stratification beyond conventional scoring systems. Given increased tumor fragmentation is associated with improved outcomes, these data indirectly suggest ecological mechanisms of treatment resistance. This approach offers a pathway toward personalized post-operative management strategies to improve outcomes in PDAC. Risk classification models. Model Description Event/n Median DFS (95% CI) HR(95% CI) p-value C-statistics 1(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 87 / 101 8.22(5.72 – 10.1) 1.64(1.20 – 2.25) 0.002 0.562 Low risk: log standard deviation of the stroma shape index ≤ 0.651 71 / 102 11.90(9.24 – 25.1) Ref 2(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 & mean cancer shape index ≤ 1.775 58 / 63 7.23(5.19 – 9.63) 1.82(1.31 – 2.52) 0.0003 0.560 Low risk: (log standard deviation of the stroma shape index > 0.651 & mean cancer shape index > 1.775) or log standard deviation of the stroma shape index ≤ 0.651 100 / 140 11.57(9.24 – 17.92) Ref 3(Backwards elimination) High risk: PI * > median 86 / 101 8.02(6.08 – 9.86) 1.73(1.26 – 2.37) 0.0007 0.566 Low risk:PI * ≤ median 72 / 102 15.72(9.97 – 25.05) Ref *PI: (0.2701 * log mean stroma area) + (0.3905 * log edge density).

Abstract Infection is increasingly recognized as a significant cause of morbidity and mortality in patients with relapsed/refractory (R/R) large B-cell lymphoma (LBCL) receiving CD19 chimeric antigen receptor (CAR) T-cell therapy. The current study analyzed the natural history, risk factors, and outcomes of infection in 3350 patients with R/R LBCL receiving commercial CD19 CAR T-cell therapy (n = 2804 axicabtagene ciloleucel [axi-cel], n = 546 tisagenlecleucel) from December 2017 to June 2022. Infection developed in 834 patients (24.9%) within 100 days after infusion, resulting in an infection density of 0.43 per 100 patient days and a 100-day cumulative incidence of 22%. Bacterial, viral, and fungal infections were recorded in 527 (15.7%), 374 (11.2%), and 108 patients (3.2%), respectively, with corresponding infection densities of 0.23, 0.15, and 0.04 per 100 patient days. After a 24-month median follow-up, 1482 patients (44%) had died, with infection as the primary cause in 173 cases (12%). The 100-day infection-related mortality (IRM) was 1.6% (95% confidence interval, 1.2-2.0). Patients with a Karnofsky performance score of ≤80, infection history before CAR T-cell therapy, axi-cel therapy, severe cytokine release syndrome (grade ≥3), and severe immune effector cell–associated neurotoxicity syndrome (grade ≥3) had increased infection risk. Infections within 100 days were an independent risk factor for inferior overall survival beyond day 100 after CD19 CAR T-cell therapy. In conclusion, study results show a significant incidence of infection and IRM in patients with R/R LBCL treated with CD19 CAR T-cell therapy. Furthermore, results identify patients at a heightened risk of infection, offering insights to guide potential interventions aimed at mitigating infection and improving patient outcomes after CAR T-cell therapy.