Citations

1106 Background: TNBC, although an aggressive breast cancer (BC) subtype, is highly immunogenic and the only BC subtype where the ICI pembrolizumab is approved. However, predictive biomarkers for pembrolizumab benefit are limited. The chemokines CXCL9 and CXCL10 attract CD8 + T cells into the tumor microenvironment (TME) and are associated with chemotherapy benefit, but little is known about their role in prediciting pembrolizumab benefit in TNBC. We investigated the association of CXCL9 , CXCL10 and their cognate receptor CXCR3 with TME and ICI efficacy. Methods: 3,038 TNBC samples were analyzed via NGS (592-gene panel, NextSeq; WES/WTS, NovaSeq; Caris Life Sciences, Phoenix, AZ). Tumor mutational burden (TMB) totaled somatic mutations per tumor (high > 10 mt/MB). Immune cell fractions were estimated using WTS deconvolution (Quantiseq). CXCL9 / CXCL10 / CXCR3 -high (H) and -low (L) tumors were classified by RNA expression above or below the 50th percentile. Real-world overall survival (OS) was derived from insurance claims and calculated from start of pembrolizumab to last contact using Kaplan-Meier. Statistical significance was assessed using chi-square and Mann-Whitney U with multiple comparison adjustments (q < .05). Results: TNBC expressed higher levels of CXCL9 and CXCL10 (median (TPM): 5.3 and 14.7) compared to N = 1,082 HER2+ (4.8 and 10.3, p < 0.05) and N = 4,918 HR+HER2- (2.7 and 7, q < .05) BC. CXCR3 expression was higher in TNBC compared to HR+HER2- (1.9 vs 1.7, q < .05), but no difference when compared to HER2+ (1.9 vs 2, q = 0.97) BC. CXCL9 / CXCL10 / CXCR3 -H TNBC had higher median OS post pembrolizumab [ CXCL9 -H vs -L: 26.5 vs 15.7 months (mo), HR: 0.65 (95% CI 0.5-0.84); CXCL10 -H vs -L: 26.0 vs 20.6 mo, HR 0.74 (0.57-0.95); CXCR3 -H vs -L: 32.6 vs 18.3 mo, HR 0.68 (0.52-0.88), all p < 0.05 ]. CXCL9 -H, CXCL10 -H and CXCR3 -H had higher PD-L1 positivity (22C3), TMB high, higher T cell inflamed score, TP53 mutations, elevated B and CD8 + T cells infiltration, but not neutrophils, and higher expression of immune checkpoint genes (Table). Conclusions: High CXCL9 / CXCL10 / CXCR3 expression is associated with longer survival in patients with TNBC post pembrolizumab, and characterized by an immune-enriched TME. Further investigation is needed to evaluate this chemokine axis in TNBC and its potential as a therapeutic target to enhance ICI efficacy. TME characteristics by CXCL9, CXCL10 and CXCR3 expression. CXCL9 CXCL10 CXCR3 High Low q-value High Low q-value High Low q-value PD-L1 % 54 14 <.05 54 14.7 <.05 49 19 <.05 TMB high % 14.3 8 <.05 12.6 9.7 <.05 12.4 9.8 <.05 B cell (median %) 4.4 3.5 <.05 4.3 3.6 <.05 5 3.4 <.05 CD8+T cell (median %) 1.2 0 <.05 1 0 <.05 1.3 0 <.05 Neutrophil (median %) 4.2 4.5 <.05 4.2 4.4 <.05 4.2 4.3 0.2 T cell inflamed score 100 -84 <.05 98 -84 <.05 108 -100 <.05 CTLA4 (median TPM) 3.2 0.7 <.05 3 0.8 <.05 3.4 0.7 <.05 LAG3 (median TPM) 6.6 2.1 <.05 6.9 2 <.05 6.8 2 <.05 TP53 mutation % 88 81 <.05 90.5 78.6 <.05 86 83 0.08

e15003 Background: Antibody-drug conjugates (ADCs) have shown substantial promise as therapies for metastatic breast cancer (mBC). However, direct comparisons of different ADC-based regimens are limited. We assessed survival outcomes in mBC patients treated with ADCs. Methods: Randomized controlled trials (RCTs) published before October 2024 were searched in Medline, Embase, ClinicalTrials.gov, and Cochrane Library. Progression-free survival (PFS) and overall surcvival (OS) outcomes were extracted from the most updated publications. Participants were stratified based on molecular subtypes, hormone receptor (HR) status, duration of cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) treatment, and sensitivity to endocrine therapy (ET). Bayesian frameworks were deployed, presenting the synthesized outcomes of indirect comparisons using the surface under the cumulative ranking curve (SUCRA), hazard ratio (HR), and 95% credible interval (Crl). This study was prospectively registered on the International Platform of Registered Systemic Reviews and Meta-analysis Protocols (INPLASY) (INPLASY2024110021). Results: A total of 6449 patients from 12 RCTs of ADCs ado-trastuzumab emtansine (T-DM1), sacituzumab govitecan (SG), trastuzumab deruxtecan (T-DXd), and datopotamab deruxtecan (Dato-DXd) were included in the analysis. Compared to chemotherapy, T-DXd significantly improved PFS (HR 0.35, 95% Crl 0.15-0.84) and OS (HR 0.56, 95% Crl 0.32-1.0). SG also significantly extended OS (HR 0.65, 95% Crl 0.43-0.97) but not PFS. In HER2+ mBC, pooled analyses revealed T-DXd was the most effective treatment in terms of PFS, with a SUCRA of 94.2%, followed by T-DM1 (58.9%), and chemotherapy with HER2-directed therapy (34.2%). Synthesized outcomes of OS mirrored the PFS outcomes. In HR+/HER2- mBC (some of which was HER2-low), Dato-DXd (76.1%) showed slightly superior efficacy over SG (67.4%) for PFS, while SG (85.1%) was advantageous over Dato-DXd (49.1%) in terms of OS. Among patients with HR+/HER2+ mBC, T-DXd (80.0%), SG (55.5%), and chemotherapy with HER2-directed therapy (53.1%) were the most effective therapies for prolonging PFS. Regarding OS, SG (70.3%) and T-DM1 (60.3%) were the most effective, with comparable efficacy observed between chemotherapy with HER2-directed therapy (52.1%) and T-DXd (52.0%). In HR-/HER2+ mBC, T-DXd (78.1%), SG (56.1%), and T-DM1 (51.5%) significantly prolonged PFS, while SG (69.4%) had the most substantial benefit for OS, followed by T-DXd (62.8%) and chemotherapy with HER2-directed therapy (57.6%). Dato-DXd showed an advantage over SG in mBC patients received CDK4/6i for > 12 months. Conclusions: This network meta-analysis showed prominent survival benefits with ADC-containing regimens for mBC. Our results provide valuable insights into personalized treatment strategies for mBC patients.

With their unique therapeutic properties and amenability to engineering modifications, exosomes are considered a promising tool for treating peripheral nerve injuries. Through genetic engineering or physicochemical modifications, the targeting ability and functionality of exosomes can be further enhanced, enabling efficient delivery of therapeutic molecules and significantly boosting their therapeutic potential. This review aims to explore exosome-based therapies in peripheral nerve repair and their mechanisms and summarizes recent advances in the roles of exosomes in neuroprotection, axonal regeneration, vascular regeneration, and inflammatory modulation. Exosomes act as natural messengers between cells, carrying genetic materials, cytokines, and growth factors that can modulate the local microenvironment and foster peripheral nerve regeneration. Studies have shown that exosomes derived from Schwann cells, macrophages, neurons, and mesenchymal stem cells can all promote axonal regeneration and modulate inflammatory responses through various mechanisms. Compared with cell therapy, exosome therapy offers greater stability and safety, with the ability to traverse biological barriers, presenting new possibilities for regenerative medicine and precision therapy. However, challenges such as the heterogeneity and complexity of exosomes, uncertainty of in vivo distribution and metabolic pathways, and the limitations of targeting remain to be addressed. Future research will focus on the engineering modifications of exosomes to enhance their therapeutic efficiency and targeting precision.

Abstract Background Hospital‐at‐home programs (HaH) in the United States have evolved to include a virtual‐hybrid delivery model, where all physician encounters are virtual and partnered with a home care team. Objective To examine whether a virtual hybrid HaH program enabled by technology has similar clinical outcomes to traditional brick‐and‐mortar (B&M) hospital care. Methods We conducted a pragmatic trial at three hospitals, randomizing 1150 acutely ill patients requiring hospital care between July 10, 2023, and October 31, 2023 one‐to‐one into two groups: intervention (HaH) and control (B&M). The primary analysis was an intention‐to‐treat non‐inferiority analysis of the primary outcome, which was a composite of 30‐day all‐cause mortality and unplanned readmissions. Secondary outcomes included 30‐day readmission, all‐cause mortality, and patient experience. Results The mean age was 67.8 (standard deviation [SD] 16.3) years, and 52.2% were female. The primary outcome occurred in 99 (17.3%) HaH patients and 114 (19.8%) B&M patients (odds ratio [OR] 0.85, 95% confidence interval [CI] 0.63–1.14, p = .28), meeting the non‐inferiority criterion. Thirty‐day unplanned readmission occurred in 84 (14.7%) HaH patients and 101 (17.5%) B&M patients (OR 0.81, 95% CI 0.59–1.11, p = .19). Thirty‐day all‐cause mortality occurred in 25 (4.4%) HaH patients and 19 (3.3%) B&M patients (OR 1.34, 95% CI 0.73–2.46, p = .35). No HaH patients died while receiving their hospital care at home. HaH program was associated with a higher likelihood of patients reporting feeling extremely comfortable or very comfortable (84.4% HaH; 60.9% B&M, p = .001). Conclusion A hybrid HaH model is a safe and comfortable alternative to traditional B&M hospital care.

Objectives: To evaluate the clinical heterogeneity of sarcomas by examining associations between histological subtypes, metastatic patterns, treatment modalities, and survival outcomes. Methods: We analyzed data from 97,062 adult patients diagnosed with sarcoma between 2000 and 2020, using the Surveillance, Epidemiology, and End Results (SEER) database. Fourteen histological subtypes were included. Propensity score matching (PSM) was employed to adjust for baseline differences, and Cox proportional hazards models were used to identify prognostic variables. Results: The most prevalent subtypes were sarcoma not otherwise specified (31.9%), leiomyosarcoma (17.1%), and liposarcoma (13.9%). Metastatic patterns differed significantly by subtype; liver metastases were most common in sarcomas with small blue round cell (SBRC) features (8.9%) and stromal sarcoma (6.1%), while lung metastases were frequently observed in Ewing sarcoma (10.0%) and rhabdomyosarcoma (9.7%). Median overall survival (mOS) varied widely, ranging from 234 months in chondrosarcoma to 16–20 months in rhabdomyosarcoma and SBRC sarcoma. Overall, patients with primary sarcoma had significantly better survival than those with treatment-related disease (119.0 vs. 45.0 months, p < 0.0001), with this trend consistent across most subtypes. Treatment responses were subtype- and size-dependent. For instance, surgery plus radiotherapy improved outcomes in giant cell sarcoma regardless of tumor size, whereas chemotherapy provided benefit only in tumors larger than 5 cm. Combined surgery and radiotherapy offered additional survival benefit in select subtypes, including chordoma, leiomyosarcoma (>5 cm), and synovial sarcoma (<5 cm). Conclusions: Sarcomas exhibit substantial clinical and prognostic heterogeneity across histological subtypes. These findings underscore the importance of subtype-specific, individualized treatment strategies in optimizing patient outcomes.

ABSTRACTBackgroundDeep learning (DL) models for accurate renal tumor characterization may benefit from multi‐center datasets for improved generalizability; however, data‐sharing constraints necessitate privacy‐preserving solutions like federated learning (FL).PurposeTo assess the performance and reliability of FL for renal tumor segmentation and classification in multi‐institutional MRI datasets.Study TypeRetrospective multi‐center study.PopulationA total of 987 patients (403 female) from six hospitals were included for analysis. 73% (723/987) had malignant renal tumors, primarily clear cell carcinoma (n = 509). Patients were split into training (n = 785), validation (n = 104), and test (n = 99) sets, stratified across three simulated institutions.Field Strength/SequenceMRI was performed at 1.5 T and 3 T using T2‐weighted imaging (T2WI) and contrast‐enhanced T1‐weighted imaging (CE‐T1WI) sequences.AssessmentFL and non‐FL approaches used nnU‐Net for tumor segmentation and ResNet for its classification. FL‐trained models across three simulated institutional clients with central weight aggregation, while the non‐FL approach used centralized training on the full dataset.Statistical TestsSegmentation was evaluated using Dice coefficients, and classification between malignant and benign lesions was assessed using accuracy, sensitivity, specificity, and area under the curves (AUCs). FL and non‐FL performance was compared using the Wilcoxon test for segmentation Dice and Delong's test for AUC (p < 0.05).ResultsNo significant difference was observed between FL and non‐FL models in segmentation (Dice: 0.43 vs. 0.45, p = 0.202) or classification (AUC: 0.69 vs. 0.64, p = 0.959) on the test set. For classification, no significant difference was observed between the models in accuracy (p = 0.912), sensitivity (p = 0.862), or specificity (p = 0.847) on the test set.Data ConclusionFL demonstrated comparable performance to non‐FL approaches in renal tumor segmentation and classification, supporting its potential as a privacy‐preserving alternative for multi‐institutional DL models.Evidence Level4.Technical EfficacyStage 2.