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2030 Background: Brain metastases (BM) are common and arise in 30% of lung adenocarcinoma (LUAD) patients. Patients with LUAD that develop BM have significantly poorer outcomes, with a 10-16 month median overall survival. Unfortunately, current clinical practice for BM prediction is limited and so BM are typically detected after they develop and grow to cause neurological symptoms. Once BM are detected, currently neurosurgical tumor biopsies are performed to enable BM diagnosis via neuropathological evaluation. The aims of this study were to develop DNA methylation-based models that predict LUAD BM and non-invasively detect BM in blood to enable early diagnosis and treatment. Methods: DNA methylomes were acquired from 402 tumor tissue and plasma samples in a cohort of 346 LUAD and BM patients. Machine learning models were built using DNA methylation signatures that stratify BM risk in tissue and detect BM in plasma. Models were evaluated in independent validation datasets. A predictive nomogram was developed using the BM prediction model together with clinical factors to provide composite patient-specific scores reflecting BM risk. Results: The methylation-based BM predictor accurately stratified BM risk in a univariable Cox model using validation set data (HR = 5.65, 95%CI 1.85–17.2, p = 0.0023). Model utility was independent of the predictive value of clinical factors in a multivariable Cox model using validation set data (Table 1: HR = 8.92, 95%CI 1.97–40.5, p = 0.0046). The 5-year model accuracy was 0.81 and significantly higher than a similarly built cancer stage-based model (0.65), demonstrating utility over current practice. The combinatorial clinical-methylomic predictive nomogram had enhanced utility with an accuracy of 0.82 univariable Cox HR of 17.2 (95%CI 4.13–71.3, p < 0.0001), demonstrating comprehensive patient-specificity. The plasma-based model accurately classified BM from gliomas and lymphomas (AUROC=0.80), as typical clinical differential diagnoses, in validation set data. The models were validated further in additional external data. Conclusions: DNA methylation-based modeling of BM can accurately predict LUAD patients at risk for BM development and can non-invasively detect BM that develop. Future treatment approaches may tailor initial LUAD treatment and ongoing cancer surveillance to a patient’s BM risk, allowing for the potential to prevent and treat BM early. DNA methylation-based BM prediction is independent of clinical factors in a multivariable Cox proportional hazards model. Variable HR 95% CI p Methylome risk score 8.92 1.97–40.5 0.005 Age Years 0.96 0.92–1.02 0.177 Smoking Pack-years 0.99 0.95–1.03 0.496 EGFR Mutant vs wildtype 0.92 0.25–3.34 0.895 T T2 vs T1 1.58 0.41–6.04 0.505 T3−4 vs T1 1.49 0.28–7.98 0.642 N N1 vs N0 1.05 0.31–3.58 0.943 N2−3 vs N0 1.00 0.27–3.69 0.995 M M1 vs M0 145 12.2–1730 <0.001

e16610 Background: Adrenocortical carcinoma (ACC) is a rare malignancy with an incidence of 1-2 per million per year. The optimal treatment remains unclear as does the benefit of chemotherapy (chemo) in patients (pts) with resectable ACC. Methods: The SEER database (2000–2021) was used to identify ACC pts > 18 years. Variables of interest included age, race, household income, rural-urban classification, stage, chemo, radiation therapy (RT), and surgery. Statistical analyses were conducted using ANOVA, Kruskal-Wallis, and Kaplan-Meier methods to compare survival outcomes according to variables of interest. Results: Of the 2,598 pts identified, 1,564 (60%) were female. The majority of pts (85%) were white, followed by black (9%). Most pts (87%) resided in metropolitan areas. Pts with localized, regional, or distant metastatic disease comprised 25%, 17% and 36% of the group, respectively. 40% of pts underwent radical or total surgical removal of the primary site disease while 9%, 2%, and 1% underwent partial surgical removal, excision, or debulking surgery, respectively, and 30% did not undergo surgery. 34% of pts received chemo and 8% received RT. The median overall survival (mOS) for the entire cohort was 15 months (m) (95% CI: 14–17 m). No significant differences in OS were observed among pts of different races or household incomes. Distant metastatic disease was significantly associated with worse mortality when compared with regional or localized diseases (mOS: 5 m vs. 20 m vs 60.6 m, respectively, p < 0.001). Surgical intervention of any kind was associated with longer survival when compared to those who did not undergo surgery (18 m vs. 3 m, HR 0.33, p < 0.0001). Among the 971 pts with distant metastatic disease, pts who received chemo had a superior mOS compared to those who did not receive chemo or with unknown chemo status (8 m vs. 2 m, p < 0.0001). This OS advantage remained significant even after excluding pts who underwent surgery (5 m vs. 2 m, p < 0.0001). While chemo was also associated with longer mOS (29 m vs. 27 m, p < 0.0001) in localized disease, this survival advantage was not present in pts with localized disease managed with surgery (27 m vs. 27 m, p = 0.061). Although chemo was associated with numerically longer mOS in pts with regional disease, the difference was not significant. Conclusions: ACC with distant metastatic disease carries a poor prognosis yet demonstrates superior survival in pts who receive chemo. Surgery is associated with better survival outcomes, but there is no additive benefit from chemo in those with localized disease managed with surgical resection.

e14008 Background: Lung cancer is the most common cancer to metastasize to the brain. Identifying the EGFR mutation is critical for determining treatment strategies and prognosis. However, 17.26% of patients show EGFR mutation discordance between the primary tumor and CNS metastasis. On the other hand, it is not always feasible to obtain brain samples. Many studies have developed deep learning (DL) models to predict the existence of EGFR mutations using radiomics. In this paper, we aim to measure the accuracy of diagnostic tests in those studies. Methods: PubMed, Scopus, Cochrane Library and Web of Science databases were searched from inception to January 2025, to identify studies measuring the ability of DL models in differentiating between the types of EGFR mutation in patients with lung cancer brain metastases. The quality assessment of the included studies was performed using QUIPS tool. The diagnostic accuracy meta-analysis was conducted using Meta-DiSc software. Results: Nine studies were included in our systematic review and meta-analysis, encompassing 260 patients with EGFR mutant type and 264 patients with EGFR wild type. Our analysis revealed that DL approaches exhibit a high ability to differentiate between EGFR mutation types, with a sensitivity of 0.82 (95% CI: 0.73–0.88) and a specificity of 0.88 (95% CI: 0.78–0.94). Additionally, the positive likelihood ratio and negative likelihood ratio were 6.87 (95% CI: 3.5–13.3) and 0.20 (95% CI: 0.13–0.31), respectively. The diagnostic odds ratio was 33.4 (95% CI: 13.5–82.5), which is indicative of excellent diagnostic accuracy. Conclusions: DL models demonstrate exceptional diagnostic accuracy in detecting EGFR mutations in brain metastases from lung cancer. These findings highlight the potential of AI-driven approaches to enhance personalized treatment strategies and improve outcomes for patients with EGFR-mutant NSCLC brain metastases.

10582 Background: Breast cancer is the most common cancer in young women, with an increasing incidence over the past two decades. This study aims to evaluate the characteristics of young-onset breast cancers among patients aged ≤50 and compare tumor characteristics by germline mutation carrier status. Methods: Patients with breast cancer diagnosis ≤50 years old and evaluated across the Mayo Clinic enterprise between 2000 and 2024 were identified through the prospective Mayo Clinic Breast Cancer Study and the institutional tumor registry. Demographics, tumor characteristics, and clinical outcomes were obtained and described using summary statistics. Germline pathogenic or likely pathogenic variant (PV) carrier status for 5 established breast cancer predisposition genes (BRCA1, BRCA2, ATM, CHEK2 and PALB2) was available in a subset of unselected patients who consented to participation in sequencing studies at Mayo Clinic. Clinical characteristics were compared between PV carriers in each gene and non-carriers utilizing Chi-square test. All tests were two-sided and p-value less than 0.05 was considered statistically significant. Results: Among 8,462 patients (8435 women, 27 men) with breast cancer diagnosis at age ≤50 in the study, the median age of diagnosis of breast cancer was 44 years (range 18 – 49). At diagnosis, 84% had invasive disease, 43% of the tumors were high-grade, 15.8% had triple-negative breast cancer (TNBC), more than two-thirds (67.5%) presented with stage I or II breast cancer, and 3.7% had bilateral breast cancer. Among the 2,527 patients who consented to germline sequencing, 10.1% were found to be carriers of PVs; these included BRCA1 (3.3%), BRCA2 (2.7%), CHEK2 (2.3%), ATM (1.3%), and PALB2 (0.6%). Compared to non-carriers, a significant enrichment (p<0.05) of invasive breast cancer (92.6% vs. 83.3%) and high grade tumors (61.7% vs. 31.4%) were noted in BRCA1 PV carriers, and of bilateral breast cancer (13.4% vs. 3.8%) and high grade tumors (46.4% vs. 31.4%) in BRCA2 PV carriers. After exclusion of in-situ disease, proportion of TNBC was observed to be significantly higher in BRCA1 (61.3%), BRCA2 (15.5%) and PALB2 (30.7%) PV carriers compared to non-carriers (11.2%), whereas >90% of ATM or CHEK2 PV carriers had ER+ breast cancer and none had TNBC. A significant difference in stage at presentation was not observed by germline PV carrier status. Conclusions: The high frequency (>10%) of PVs in young-onset breast cancer underscores the importance for genetic testing in this population. The observed differences in breast cancer phenotypes based on germline PV carrier status among young-women may have significant implications for clinical outcomes and needs to be further explored.

10512 Background: Polygenic risk scores (PRSs) combine information from single-nucleotide polymorphisms (SNPs) across the genome to explain substantial genetic breast cancer (BC) susceptibility. Previous studies have demonstrated that a multiple-ancestry PRS (MA-385) based on 56 ancestry-informative and 329 BC-associated SNPs is accurate for diverse populations and ranks among the most important known factors affecting the risk of BC development. However, medical guidelines call for more evidence before endorsing the clinical use of PRS, including studies to evaluate possible interactions of SNPs with environmental and hormonal risk factors. Here, we use longitudinal outcomes from the UK Biobank (UKB) to explore interactions of MA-385 and the five most informative individual BC-associated SNPs with the widely used Tyrer-Cuzick (TC) risk model and individual TC risk factors. Methods: The study cohort included 197,509 female UKB participants with no history of cancer at the time of study enrollment. We used Cox proportional hazards models to test associations of MA-385, individual BC SNPs, TC, and individual TC risk factors with BC outcomes. Effect modification of MA-385 and individual SNPs by clinical risk factors was evaluated by including interaction terms in the models. All models were adjusted for age at UKB enrollment and 10 principal components. Hazard ratios (HRs) and 95% confidence intervals (CIs) are reported per standard deviation, and significance tests were performed using two-sided p-values based on likelihood-ratio test statistics. Results: After a median follow-up of 11.8 years, 7,419 (3.8%) participants were diagnosed with BC.In a model including both MA-385 and TC, MA-385 was a significantly better predictor of BC development (HR = 1.56; 95% CI 1.53-1.60, p = 3.2 x 10 -329 ) over the TC model (HR = 1.21; 95% CI 1.18-1.23; p = 5.4 x 10 -69 ). We found no evidence of interaction between MA-385 and TC ( p = 0.31) , nor between individual SNPs and TC. After Bonferroni adjustment for multiple testing (102 tests), we found no evidence of interaction between MA-385 or individual SNPs with clinical TC factors. The strongest evidence for interaction was found between a BC SNP on chromosome 2 (rs13387042) and age at UKB enrollment (unadjusted p = 0.002; Bonferroni adjusted p = 0.23). Conclusions: In a longitudinal analysis of UKB, MA-385 was a highly significant predictor of BC risk and substantially improved prediction over TC. In contrast, interactions of MA-385, and individual BC SNPs, with TC and individual clinical factors in the TC model were not statistically significant. Clinical TC factors have minimal, if any, impact on the strength of the association between MA-385 and BC. These results may help to alleviate concerns expressed in guidelines that SNPs interact with environmental or hormonal risk factors.

10510 Background: The impact of germline pathogenic or likely pathogenic variants (PVs) in cancer predisposition genes on overall survival (OS) after breast cancer diagnosis is not well defined. In particular, unbiased OS estimates from population-based studies accounting for clinical subtypes of breast cancer (based on ER, PR, and HER2 status) and for genes other than BRCA1/2 are lacking. Methods: The study included 25,168 prospectively followed women with locoregional invasive breast cancer within the population-based CARRIERS study. Germline sequencing using a custom multigene amplicon-based panel was performed to identify PVs. OS was compared between germline PV carriers in ATM, BRCA1, BRCA2, CHEK2 and PALB2 and non-carriers (negative for germline PVs in 13 known breast cancer predisposition genes) for each clinical subtype of breast cancer from the time of breast cancer diagnosis to death or last follow up in a multivariable Cox proportional hazard regression analysis adjusting for age at diagnosis, race/ethnicity, histology, TNM stage, type of surgery, use of adjuvant radiation, chemotherapy and endocrine agents. Results: Among 25,168 women with breast cancer, germline PVs in one of the five breast cancer predisposition genes were detected in 5.8% of the women [ ATM : 0.8%, BRCA1 : 1.3%, BRCA2: 1.6%, CHEK2 : 1.5%, and PALB2 : 0.6%]. Among women with ER+ breast cancer, compared to non-carriers, a significantly worse OS was noted for BRCA1 (Hazard Ratio (HR): 1.8, 95% Confidence Interval (CI): 1.1 – 3.0, p=0.02) and BRCA2 (HR: 1.8, 95%CI: 1.4 – 2.4, p<0.001), but not for ATM (HR: 1.2, 95%CI: 0.8 – 1.7, p=0.40) or CHEK2 (HR:1.0, 95%CI: 0.8 – 1.3, p=1.0) PV carriers. Worse OS was noted in PALB2 PV carriers with ER+ breast cancer (HR:1.5, 95%CI: 0.9 – 2.2, p=0.09), although it did not reach statistical significance. Similar HR estimates for OS as with ER+ breast cancer were observed in women with ER+/HER2- breast cancer for BRCA1 , BRCA2 and PALB2 PV carriers, but only BRCA2 results were statistically significant. Among women with ER-negative breast cancer, compared to non-carriers, a significant difference in OS was not observed for PV carriers in ATM (HR:0.8, 95%CI: 0.4 – 1.8, p=0.63), BRCA1 (HR:1.2, 95%CI: 0.8 – 1.7, p=0.35), BRCA2 (HR: 0.8, 95%CI: 0.5 – 1.2, p=0.29), CHEK2 (HR: 0.7, 95%CI: 0.3 – 1.4), or PALB2 (HR: 0.9, 95%CI: 0.5 -1.7, p=0.78). Conclusions: The suggestive differences in OS by ER status of the tumor in BRCA1 and BRCA2 PV carriers warrant further investigation of underlying tumor biology and assessment of endocrine sensitivity of breast cancer in germline PV carriers.

Abstract Superior mesenteric artery (SMA) thrombosis is rare yet critical illness that can result in lethal bowel ischemia and infarction. This report details a case of SMA thrombosis with associated superior mesenteric vein (SMV) narrowing, secondary to mesenteric torsion in a 26-year-old female with history of Roux-en-Y gastric bypass surgery. The patient’s presenting symptoms were severe epigastric pain, vomiting, and significant anemia. Imaging confirmed SMA thrombosis with early signs of bowel ischemia. Interventional radiology promptly performed an SMA angiogram and initiated thrombolysis with a tenecteplase infusion, which led to near-complete resolution of the thrombus. This case draws attention to the necessity for early diagnosis and swift management of SMA thrombosis, particularly in post-surgical patients with altered gastrointestinal anatomy. The resolution of this case demonstrates the value of a collaborative care, combining interventional radiology and general surgery to prevent bowel ischemia.

Abstract Colony stimulating factor-1 receptor (CSF1R) encodes for a tyrosine kinase receptor expressed on microglia. CSF1R related disorder is a devastating autosomal dominant leukoencephalopathy caused by CSF1R with variable penetrance in adults. It remains significantly underdiagnosed or misdiagnosed. We report a case of a 43-year-old woman with an insidious onset of neurocognitive decline, alien limb phenomenon, and personality changes over 1 year. In this report we will discuss the clinical approach, differential diagnosis, investigation, and available treatment options for CSF1R related disorder.

7075 Background: Hepatosplenic T-cell lymphoma (HSTCL) is a rare, aggressive peripheral T-cell lymphoma arising primarily from γδ T-cells. It carries a poor prognosis and resists conventional chemotherapy. Most reports on HSTCL are case-based. This study comprehensively analyzes a large cohort, evaluating treatment strategies and survival outcomes. Methods: This retrospective study included patients (pts) with pathologically confirmed HSTCL diagnosed between 2000-2024, consecutively seen at Mayo Clinic MN. Clinical, pathological, genomic, and treatment-related data were extracted when available. Descriptive statistics were used to summarize baseline characteristics. Time-to-event analyses, including Kaplan-Meier estimates, median overall survival (OS), and survival time estimates were conducted from the date of diagnosis. Results: A total of 20 patients with newly diagnosed HSTCL were included, with a median age of 57 years (range: 35-71). The cohort was predominantly male (70%) and non-Hispanic (93%). Molecular data was available for five patients, revealing abnormalities in STAT5B, MLL3 deletion, TP53, EZH2, TERT, and NF1 E291D . The median follow-up was 27.6 months (m) with a median OS of 17.6 m (95% CI: 11.2 - NA). First-line treatment was anthracycline-based in 68% of pts and non-anthracycline-based in 32%, with higher response rates in the latter group (50% vs.83%). Although non-anthracycline regimens showed a trend toward improved 3-year OS (100% vs. 29%) the difference was not statistically significant (p = 0.16). Achieving a complete response to first-line therapy was also associated with a trend towards a better 3-year OS compared to refractory disease (80% vs. 50%, p = 0.17). Most pts (79%) underwent hematopoietic stem cell transplant (HSCT), primarily allogeneic, with only one receiving autologous HSCT. First-line therapy before HSCT was evenly distributed between anthracycline (55%) and non-anthracycline (45%) regimens. HSCT recipients had significantly higher 3-year OS than non-recipients (83% vs. 33%, p = 0.017). Notably, the patient with a TP53 mutation has remained in remission for over a year post-allogeneic HSCT. Conclusions: HSTCL predominantly affects younger pts, with nearly half dying within a year. Allogeneic HSCT, rarely used in other NHL subtypes, improved survival. Non-anthracycline regimens and achieving CR trended toward better outcomes. Our study, leveraging a sizable cohort, highlights the need for targeted research and novel therapies to improve HSTCL management. Summary of survival outcomes in HSTCL. Characteristics Median OS (y) 3-Year OS (95% CI) 1.48 [0.93- NA] 46% [0.26 - 0.81] Transplant Transplant NA [NA - NA] 83% [0.58 - 1.00] No Transplant 1.02 [0.93 - NA] 33% [0.07 - 1.00] Treatment Anthracycline Based 1.02 [0.36 - NA] 29% [0.11 - 0.73] Non-Anthracycline Based 4.61 [NA- NA] 100% [1.00 - 1.00]

7073 Background: The Optimized HLH Inflammatory (OHI) index (Zoref-Lorenz et al., Blood , 2022), based on serum soluble CD25 (sCD25) and ferritin, is a prognostic tool identifying inflammation in the hemophagocytic lymphohistiocytosis (HLH) spectrum and early mortality risk. Prior studies were retrospective and enriched with HLH-suspected cases. We hypothesized that the OHI index would predict outcomes in unselected diffuse large B-cell lymphoma (DLBCL). Methods: 670 newly diagnosed DLBCL patients from a prospective cohort (2002–2015) were analyzed: 335 for discovery and 335 for validation. Pre-treatment serum sCD25 and ferritin levels were quantified via ELISA, and we evaluated original thresholds (sCD25 ≥ 3,900 U/mL; ferritin ≥ 1,000 ng/mL) and developed DLBCL-optimized thresholds (using receiver operator curves) for predicting 500-day mortality. We also evaluated event-free survival (EFS), EFS at 24 months (EFS24), and overall survival (OS). Results: The median age was 64, and 51% were male. Using original thresholds, 4.2% (n=14) of patients were OHI+, with a 5.6-fold higher risk of 500-day mortality (95% CI 1.6–17; p<0.001). Optimized thresholds identified 23.6% (n=78) as OHI+ with a 9.2-fold higher 500-day mortality risk (95% CI 4.0–24; p<0.001). Optimized OHI+ also had a higher risk of EFS24 failure and inferior EFS and OS (Table). OHI+ patients had higher rates of B symptoms (35% vs. 20%; p=0.027), elevated LDH (76% vs. 34%; p<0.001), worse performance status (ECOG ≥2: 38% vs. 12%; p<0.001), and advanced-stage disease (Stage IV: 57% vs 38%; p<0.001), though IPI scores (3–5) were not significantly different (44% vs 36%; p=0.28). Adjusting for age and IPI, OHI+ independently predicted 500-day mortality (OR=5.0; CI 1.9–13; p=0.001), EFS24 failure (OR=3.2; CI 1.5–6.5; p=0.0018), and inferior long-term EFS (HR=2.2; CI 1.1–4.3; p=0.030) and OS (HR=2.0; CI 1.0–4.0; p=0.040) at a median follow up of 9.8 years in living patients. In validation, optimized OHI predicted 500-day mortality, EFS24 failure, and long-term OS and EFS (Table). Cytokine profiling revealed elevated inflammatory markers in OHI+ patients, including IL1a (p=0.008), CCL2 (p=0.03), CXCL10 (p<0.001), and CXCL9 (p<0.001), reflecting systemic hyperinflammation. Conclusions: The OHI index is a powerful predictor of early and long-term outcomes in DLBCL patients. Optimized thresholds identify a larger OHI+ group, highlighting hyperinflammation’s critical role in poor outcomes. These findings support its use in routine management and clinical trial design for novel therapies. Odds ratios or hazard ratios and p-values for optimized OHI+ and DLBCL prognosis. Outcome Discovery Validation OR for 500-day mortality 9.2; p<0.001 4.0; p=0.002 OR for EFS24 failure 5.2; p <0.001 6.3; p<0.001 HR for OS 2.3; p<0.001 1.8; p=0.006 HR for EFS 2.4; p<0.001 2.5; p<0.001