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Intelligent Monitoring and Dynamic Regulation Equipment and Software Development for the Equal-Pressure Fully Mechanized Mining Face in the Sandaogou Coal Mine

Impact of salt concentration and free magnesium on human beta-cardiac myosin reveal important details about the conserved mechanochemical mechanism

Therapeutic strategies and reduced drug spending as a signal of early impact of the Enhancing Oncology Model.

1578 Background: Building on lessons learned from the predecessor Oncology Care Model, the Centers for Medicare & Medicaid Services designed the Enhancing Oncology Model (EOM), a voluntary, two-sided risk, episode-based payment model, to incentivize participating practices to provide high-quality, patient-centered oncology care while targeting Medicare spending reductions. At the start of the model, 44 oncology practices voluntarily joined EOM. Practices are held financially accountable for 6-month episodes of care for Medicare Fee-for-Service beneficiaries with 7 high-risk cancers. The objective of this study is to evaluate how practices implemented EOM and whether they were able to reduce Medicare spending during its first six months of implementation. Methods: To identify strategies practices used to meet model goals, we interviewed 93 key informants during site visits at 6 EOM practices from November 2024 through February 2025. We analyzed claims-based impacts on spending using a difference-in-differences approach using a sample of episodes of care from EOM practices and propensity score matched comparison practices during a baseline period (July 1, 2018 – June 30, 2022) and the first performance period of the model (July 1–December 31, 2023). Results: EOM practices reported focusing on reducing drug expenditure. Strategies included (1) substitution to value-based treatment alternatives, such as biosimilars, while mitigating the impact of drug shortages; (2) dose rounding and weight-based dosing to minimize waste and improve efficiency; and (3) avoiding drugs with limited clinical benefit, such as white blood cell growth factors for metastatic tumors. While not statistically significant, we found the model reduced total Medicare spending by $646 per episode (1.1%; 90% confidence interval [CI]: –$1,724, $433), likely driven by reductions in Part B systemic cancer therapy payments of $645 per episode (90% CI: –$1,622, $332). This is consistent with practice reports of implementing value-based prescribing strategies. Conclusions: Early EOM implementation results show emerging evidence of systemic cancer therapy payment reductions. These findings may reflect expanded biosimilar availability and practices' strategic focus on value-based drug substitution and dosing.

Analysis of the results of whole-exome sequencing of paired samples in patients of the Eurasian population with triple-negative breast cancer and their impact on clinical outcomes.

e12605 Background: While standard practice focuses on germline mutations, our study identifies clinically relevant somatic mutations impacting riple-negative breast cancer (TNBC) prognosis, supporting the need for comprehensive exome panels. Using whole-exome sequencing (WES), we analyzed the molecular landscape of Eurasian TNBC patients and its association with clinico-phenotypic features. Methods: We performed WES on paired tumor-blood samples in 80 TNBC patients. The outcome was defined as progression (n = 37, 46%) or remission (n = 43, 54%). Pathological response was assessed using the Residual Cancer Burden (RCB) classification. Detected germline mutations (BRCA1, BRCA2, BARD1, PMS2 and others) and somatic mutations (TP53, PIK3CA, KMT2C and others) were analyzed. Descriptive statistics were calculated for all variables. Categorical variables were compared using the Chi-square or Fisher's exact test; continuous variables using the Mann-Whitney U test. Results: The mean patient age was 53 years. The predominant histological type was invasive ductal carcinoma (91%). Stage distribution: IA (16%), IIA (41%), IIB (16%), IIIA-C (27%). Pathological complete response (pCR, RCB 0) was achieved in 14 of 80 patients (18%). The RCB classification demonstrated a strong association with outcome (p < 0.001): patients with a good response (RCB 0-1) had a progression rate of 5% compared to 58% in patients with a poor response (RCB 2-3). Germline BRCA1 mutation was found in 17/80 patients (21%) and was associated with higher rates of pathological response and a reduced risk of progression. Somatic TP53 mutation was detected in 32/80 patients (40%) and was associated with an increased risk of progression (OR = 3.23, 95% CI: 1.03–10.1, p = 0.044). Our analysis identified patients with the best prognosis (BRCA1+/TP53-: the lowest risk of progression after comprehensive treatment) and the worst prognosis (BRCA1-/TP53+: progression in 67% of cases). Initial group-level analysis of somatic mutations revealed no association (p = 0.7) with disease outcome. Multivariate analysis revealed opposing effects (TP53 mutation was a risk factor for progression, while an opposite effect was observed in patients with somatic PIK3CA mutation), underscoring the importance of analyzing individual mutations. Conclusions: Comprehensive whole-exome analysis in TNBC patients identified clinically significant prognostic factors among both germline (protective BRCA1 mutation) and somatic (TP53 mutation as a risk factor) mutations. Polar prognostic groups were defined: BRCA1+/TP53- (best outcome) and BRCA1-/TP53+ (worst outcome). The results substantiate the necessity of implementing comprehensive genetic profiling that extends beyond the analysis of germline mutations alone for risk stratification and personalization of TNBC therapy.

Breast care outcomes and infectious disease: Insights from COVID-19.

e13086 Background: Adverse inpatient outcomes with COVID-19 have been well characterized for aggregations of all cancer types. However, the unique pathophysiology and treatment of breast cancer warrant specific analysis. Therefore, a critical gap exists with regard to breast cancer hospitalizations specifically to better inform clinical decision making and resource planning. We aimed to characterize inpatient mortality, morbidity, and resource utilization among breast cancer patients with concurrent COVID-19 infections to address this gap. Methods: We identified hospitalization cases from the National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality from 2020-2022 that met the inclusion criteria of female adults ≥ 18 years old with hospitalizations containing a primary or secondary ICD-10 code for diagnosis of breast cancer. Non-normally distributed results were compared using Mann-Whitney U test, and categorical variables were compared using Pearson’s chi-square test. Multivariate logistic regression models compared inpatient mortality and COVID-19 and survey-weighted negative binomial regression estimated the association between COVID-19 and inpatient length of stay. All analyses were performed using Stata version 19 (StataCorp LP, College Station, TX). Results: We identified 97,288 hospitalizations meeting inclusion criteria of which 4,933 (5.1%) cases were diagnosed with COVID-19. COVID-19 was independently associated with statistically significantly higher odds of inpatient mortality (11.1% vs 4.9%), septic shock (5.3% vs 2.9%), acute respiratory failure (38.6% vs 10.9%), mechanical ventilation (11.7% vs 5.1%), and longer length of hospital stay (3.0-10.0 days vs 2.0-6.0) (p < 0.001). Increased mortality was additionally associated with age 80 years and older (AOR 2.915, 95% CI 2.209–3.845, p < 0.001), non-Hispanic Black patients (AOR 1.214, 95% CI 1.117-1.320, p < 0.001), metastatic cancer (AOR 3.230, 95% CI 3.032-3.440, p < 0.001), chronic renal failure (AOR 1.309, 95% CI 1.170-1.464, p < 0.001), congestive heart failure (AOR 1.106, 95% CI 1.001-1.223, p = 0.048), and chronic pulmonary disease (AOR 1.169, 95% CI 1.068-1.280, p = 0.001). Conclusions: Breast cancer patients hospitalized with COVID-19 experienced statistically significant higher inpatient mortality, greater morbidity, and longer hospital stays compared with those without COVID-19 even after adjustment for comorbidities and hospital factors, highlighting the increased vulnerability of this population during infectious disease surges. Targeted clinical monitoring, timely prevention strategies, and early intervention may help mitigate these risks, underscoring the need for continued attention to breast cancer–specific outcomes during and beyond public health emergencies.

HLA-A*01 as a biomarker of poor outcome in patients treated with immune checkpoint inhibitors.

e14547 Background: Despite advances in immune checkpoint inhibition, clinical responses remain highly variable, highlighting the need to better understand host-related determinants of immunotherapy outcomes. Human leukocyte antigen (HLA) class I genotype, has emerged as a potential modulator of immune checkpoint inhibitor (ICI) efficacy. A large epidemiological study published in The Lancet Oncology (2025) reported an association between HLA-A*03 carriage and reduced overall survival (OS) following ICI, providing high-level evidence for a role of host HLA variation. In contrast, evidence for other HLA alleles is limited. For HLA-A*01, small studies in non-small cell lung cancer (NSCLC) have reported both improved OS (Shohdy et al., 2025) and inferior OS (Abed et al., 2024). We therefore evaluated the association of HLA-A*01 status with survival and response outcomes in early-phase ICI clinical trials. Methods: We conducted a retrospective analysis of 186 patients with advanced solid tumors treated with ICI within early-phase clinical trials, either as monotherapy or in combination with other agents. High-resolution HLA class I genotyping was performed during clinical trial prescreening, and HLA-A*01 status was classified as carrier or non-carrier. OS, PFS (progression-free survival) and objective response rate (ORR) were analyzed. Results: A total of 186 patients were included, of whom 43 (23%) were HLA-A01 carriers. In the overall cohort, median OS was shorter in HLA-A*01 carriers than in non-carriers (9.2 vs 20.4 months; p < 0.001 ), as was median PFS (4.0 vs 8.1 months; p = 0.003 ). ORR was numerically higher in HLA-A*01–negative patients (38.6% vs 25.6%; p = 0.147 ). In patients with NSCLC, HLA-A*01–positive patients (n = 21) had shorter OS (9.2 vs 17.6 months; p = 0.008 ) and PFS (3.4 vs 6.7 months; p = 0.008 ) than HLA-A*01–negative patients (n = 75). When stratified by treatment strategy, inferior outcomes associated with HLA-A*01 carriage were observed across PD-(L)1- containing regimens. Among patients treated with PD-(L)1 monotherapy (n = 41), median OS and PFS were shorter in HLA-A*01 carriers (n = 9) than in non-carriers (OS: 10.4 vs 27.3 months, p < 0.001 ; PFS: 2.8 vs 17.9 months, p = 0.001 ). Among patients receiving PD-(L)1–based combination therapy (n = 145), HLA-A*01 carriers (n = 34) had shorter median OS (9.0 vs 17.3 months; p = 0.01 ), while median PFS was numerically shorter (5.3 vs 6.9 months; p = 0.073 ). Conclusions: In this early-phase clinical trial cohort, HLA-A*01 status was associated with shorter OS and PFS in patients treated with ICI. Similar associations were observed in the NSCLC subgroup and across PD-(L)1 treatment strategies, including both monotherapy and PD-(L)1–based combination regimens. These findings suggest that HLA-A*01 status may be relevant to clinical outcomes in the context of immune checkpoint inhibition and support further prospective evaluation.

Multi-omic profiling to identify RNA-protein concordance and post-transcriptional dysregulation in HER2+ breast cancer.

573 Background: Standard HER2 testing relies on single-modality assays, such as immunohistochemistry (IHC) for protein overexpression and in situ hybridization (ISH) for gene amplification. These tests may fail to capture the regulatory complexity underlying HER2 biology, including post-transcriptional modulation, which may result in RNA-protein discordance and potentially drive therapeutic resistance. We performed a multi-omic analysis to characterize functional HER2 biology and uncover regulatory mechanisms not captured by standard diagnostic testing. Methods: We utilized Panakeia’s multi-omics platform to analyze a set of 475 breast cancer samples with a complete set of ERBB2 RNA and protein expression values from the Cancer Genome Atlas (TCGA). HER2+ (n=79) and HER2− (n=396) cohorts were defined using clinical HER2 status assessed via IHC/ISH. Transcriptomic and proteomic over-expression states were binarized by thresholding RNA/protein expression values. RNA-protein concordance was assessed to define four molecular states of the tumor: coordinated activation (RNA+/Protein+), coordinated inactivation (RNA−/Protein−), translation blocks (RNA+/Protein−), or post-transcriptional upregulation (RNA−/Protein+). Results: A strong correlation was measured between RNA and protein over-expression (Pearson's correlation r=0.752, p<0.001) with 93.7% concordance (445/475). Molecular patterns with respect to HER2 clinical status were observed as follows: (1) coordinated activation (n=48, 10.1%) with 95.8% HER2+ concordance (46/48), validating HER2 over-expression; (2) coordinated inactivation (n=397, 83.6%) with 95.2% HER2− concordance (378/397), confirming HER2 inactivity; (3) RNA+/Protein− translation blocks (n=29, 6.1%) where ERBB2 RNA was over-expressed but not translated; (4) RNA−/Protein+ (n=1, 0.2%). Among 79 HER2+ patients, only 46 (58.2%) showed functional translation (RNA+/Protein+), while 19 (24.1%) had complete molecular negativity (both inactive) and 14 (17.7%) exhibited translation blocks. Multi-omics profiling identified actionable changes in 35/475 cases (7.4%): 19 potential over-treatment candidates, 14 potential treatment resistance cases, and 2 potential under-treatment cases that are clinically HER2− but exhibit coordinated molecular activity. Conclusions: Integrative multi-omic analysis of the HER2 molecular landscape enabled assessment beyond standard-of-care assays, identifying non-responders to HER2-targeted therapy by capturing post-transcriptional dysregulation not detected by single-modality testing. Overall, multi-omic profiling can support precision stratification by confirming active HER2 signalling, identifying potential over-treatment, refining patient selection and guiding treatment decisions.

Comparative efficacy of PD-1 versus PD-L1 inhibitors in metastatic colorectal cancer: A real-world propensity score–matched study.

e15599 Background: The treatment of microsatellite instability-high (MSI-H) metastatic colorectal cancers (mCRC) has evolved dramatically in the last decade with the advent of immunotherapy. Despite similar mechanisms, there remains debate regarding the efficacy of PD-L1 vs PD-1 agents in this space. Recent COMMIT results suggest inferior progression-free survival (PFS) with PD-L1 in MSI-H mCRC compared to PD-1 in comparable scenarios (KeyNote-177, CM8HW). Here, we utilize a large national database to demonstrate real-world outcomes for mCRC patients treated with PD-1 vs PD-L1 monotherapy. This highlights a potential difference in the inhibition of the programmed cell death PD-1/PD-L1 axis and contributes to the ongoing debate. Methods: We utilized the TriNetX network, a federated, multicenter, de-identified database. We evaluated adult patients with mCRC who received immunotherapy between 2013 and 2025. Cohorts were defined by first exposure to immune checkpoint inhibitors: anti–PD-1(pembrolizumab/nivolumab) vs anti–PD-L1 (durvalumab/atezolizumab), with a separate comparison vs atezolizumab only. Patients treated with CTLA-4 inhibitors were excluded. Subsequently, propensity score matching was performed for demographics, comorbidities, TNM staging, and dMMR genes. Outcomes were calculated at 3 and 5-year intervals from the index date of initial immunotherapy exposure. Time-to-event outcomes were analyzed using the Kaplan–Meier method, with differences assessed by the log-rank test and Cox proportional hazards. Results: 6235 patients were evaluated for inclusion. After propensity score matching, 1820 patients were included, with 910 patients in each cohort. Over the 5-year follow-up window, Overall survival(OS) favored PD-1 therapy: median OS was 26.4 months in the PD-1 cohort vs 18.3 months in the PD-L1 cohort, HR death = 0.84 (95% CI 0.76 - 0.92, log rank p = 0.003). Landmark survival at 3 years and 5 years also favored PD-1 inhibition over PD-L1 inhibition (41.3 vs 33.9% and 34.2% vs 22.6%, respectively). These findings were confirmed in the secondary analysis with Anti-PD-1 therapy vs Atezolizumab cohort with 547 patients in each cohort. Anti-PD-1 therapy showed improved OS at( HR = 0.73, 95% CI-0.61 - 0.86, log rank P = 0.0002) with 5-year survival probability of 34.5% vs 21.7%, respectively. Conclusions: Treatment with PD-1 monotherapy was associated with improved outcomes compared with PD-L1 monotherapy. Similar differences between PD-1 and PD-L1 blockade have been reported in other tumor types; however, comparative data in mCRC remain limited. In light of recent results from the COMMIT trial, our analysis is timely. One potential explanation is that PD-1 inhibition blocks interactions with both PD-L1 and PD-L2, whereas PD-L1 inhibitors do not disrupt PD-1/PD-L2 signaling. Further prospective studies are needed to confirm and define this difference.

Rapid digital patient-derived organoid testing for guiding therapy in patients with metastatic breast cancer receiving antibody drug conjugates (ADCs).

1033 Background: MBC remains incurable despite recent incorporation of ADCs. The optimal sequencing of FDA-approved ADCs such as trastuzumab deruxtecan (T-DXd) or sacituzumab govitecan (SG) are lacking and real-world data have shown cross resistance between the ADCs. The current study aims to develop a clinical diagnostic assay to guide optimal treatment for patients with MBC using digital patient organoid (DPO) in patients with MBC receiving or progressed on ADCs for a precision tool to guide therapy in post-ADC resistance setting. Methods: An institutional IRB was established for prospective collection of fresh tumor biopsies in patients with MBC undergoing ADC therapy. DPO drug sensitivity tests were conducted and analyzed for association with clinical outcome using progression free survival (PFS). DPO tests include ADCs (T-DXd, SG, Dato-DXd) or single agent chemo dosing experiments to determine drug sensitivities (AUC values calculated from CTG readouts) for downstream correlation analyses. Results: Between 09/2024–01/2026, 41 fresh tumor tissues were collected and processed. 22 samples had sufficient viable cells to pass QC for DPO establishment and were successfully assayed and 12 failed QC, giving a DPO establishment success rate of 64.71%. DPO success rates varies by breast cancer subtypes: 100% in HER2+, 73% in TNBC and 56% in HR+HER2- BC. and sites of metastasis. Sites of metastasis (met) also impacted DPO success rates: lymph node 0%, liver met 33%, skin met 60%, breast/ascites 100%. Organoids typically established and expanded within 7-14 days post-biopsy. The DPO drug assays were conducted for ADCs, payloads, and chemotherapy agents testing. Analysis revealed that prior clinical exposure and progression on an ADC correlated with reduced DPO sensitivity to the same agent, consistent with acquired resistance. The platform was capable of delineating between target- versus payload-based resistance. Notably, DPOs from heavily pretreated patients were often resistant to both ADCs but remained responsive to alternative agents, highlighting potential therapeutic opportunities. Conclusions: The DPO platform shows promise in predicting treatment responses and differentiating resistance mechanisms to ADCs in MBC. This approach provides a foundation for rational treatment selection in patients with MBC with prior ADC resistance.

First-in-human PET/CT imaging with 68Ga-AKY-2519, a B7-H3 targeted miniprotein radioconjugate, to demonstrate tumor uptake and normal tissue exposure across various advanced solid tumors.

3098 Background: 68Ga-AKY-2519 is a miniprotein radioconjugate developed by Aktis Oncology that targets B7-H3 (CD276) which is overexpressed in several malignancies and is linked with aggressive histology and poor outcomes. AKY-2519 is a high-affinity binder to B7-H3 that internalizes into tumor cells upon binding and thereby maximizes tumor retention. AKY-2519 is also designed to clear rapidly through the kidneys to minimize exposure to normal tissues. To identify potential utility for clinical development of 225Ac-AKY-2519 across various tumor types, here we report the first-in-human evaluation of 68Ga-AKY-2519 using positron emission tomography (PET) in patients with solid tumors. Methods: In this prospective, observational study, 18 patients with advanced solid tumors, including prostate cancer (n=7), colorectal cancer (n=4), SCLC (n=3) and NSCLC (n=1) underwent PET/CT imaging following intravenous administration of 68Ga-AKY-2519. Safety, normal tissue distribution and tumor uptake were assessed. Imaging findings were correlated with known disease sites in PSMA and FDG reference PET/CTs as well as available clinical and pathological data. Results: 68Ga-AKY-2519 was well tolerated with no adverse events. PET/CT imaging demonstrated favorable tumor uptake, rapid blood pool clearance and low uptake in normal tissues. 68Ga-AKY-2519 uptake (SUVmax) in normal tissues at 120 min post injection (p.i.) was noted in the liver (median 22.9 [interquartile range (IQR) [20.9-30.8]), spleen (9.2 [7.6-10.4]), salivary glands (7.3 [6.4-11.4]), adrenal glands (17.5 [15.9-19.8]) and kidneys (6.7 [6.3-8.7]). No significant bone marrow uptake was noted (median SUVmax 4.1 [3.3-5.1] at 120 min p.i.). High and consistent tumor uptake was observed across various tumor types. The largest cohort was patients with metastatic prostate cancer (n=7), in which the highest 68Ga-AKY-2519 uptake was in bone metastases (median SUVmax 40.4 (120 min p.i.), SUVpeak 25, SUVmean 16.1), followed by lymph node metastases (SUVmax 13.8 (120 min p.i.), SUVpeak 6.5, SUVmean 5.1) and visceral metastases (SUVmax 31.0 (120min p.i.), SUVpeak 22.2, SUVmean 18.7). Conclusions: 68Ga-AKY-2519 PET/CT imaging of various malignancies was safe and demonstrated high tumor-to-background uptake and cancerous lesion detection at 120 min p.i. Normal tissue uptake was low, and robust tumor uptake was noted in patients across different solid tumors indicating therapeutic potential. These data warrant further clinical development of 225Ac-AKY-2519.

Real-world infectious complications and IVIG utilization after teclistamab in relapsed/refractory multiple myeloma.

e19516 Background: Teclistamab, a BCMA×CD3 bispecific antibody, demonstrates significant efficacy in relapsed/refractory multiple myeloma (RRMM). However, infectious complications are common in clinical practice, and optimal supportive care strategies, including intravenous immunoglobulin (IVIG), remain poorly characterized. Methods: We performed a retrospective single-center review of RRMM patients treated with teclistamab between April 2024 and May 2025. Data collected included prior therapy exposure, IVIG utilization, documented infections, hospitalizations, ICU admissions, immunoglobulin levels, and bone marrow assessment of normal plasma cells before and 3–6 months after therapy. Results: 57 patients were included. Patients were heavily pretreated, among which 22.8% had prior BCMA-directed therapy. 36/57 patients (63.2%) received IVIG with Teclistamab. Mean infection rates were ~2 per patient. Hospitalizations occurred in about 58% and ICU admissions in 14% patients. Patients without IVIG support had higher hospitalization (66.7% vs 52.8%) and ICU admissions (19.0% vs 11.1%). Paired bone marrow assessments were available in 26 patients using initial and 3–6 month evaluations of normal plasma cells. Teclistamab was associated with marked depletion of the normal plasma cell compartment (median 5.35% before vs 0.1% at 3–6 months). 21 of 26 patients (80.8%) demonstrated < 1% normal plasma cells after treatment. Patients who had < 1% normal plasma cells had risk of infection, with ~80% of patients experiencing ≥1 infection irrespective of IVIG support. Among patients with preserved normal plasma cells (≥1%), IVIG support was associated with elimination of hospitalization (0% vs 33%). Conclusions: Teclistamab results in profound depletion of the normal plasma cell compartment in most patients, providing a biologic explanation for the high infectious burden observed in practice. While IVIG does not prevent infections in the setting of normal plasma cell depletion in the marrow, it appears to reduce the severity of infectious complications when plasma cell reconstitution is preserved, and these findings warrant confirmation in a larger prospective study. Infection burden and severity in patients receiving Teclistamab and change in normal plasma cell compartment. IVIG support Normal plasma cells at 3–6 mo (%) Δ Normal PCs N=26 Mean number of infections Hospitalization ICU Prior BCMA therapy Median prior lines of therapy No Preserved (≥1) +20.9% 3 1.33 33.3% 0% 0% 8 No Severe depletion (<1) NA * 5 2.20 40.0% 0% 0% 9 Yes Preserved (≥1) 0.0% 2 1.50 0% 0% 50.0% 11 Yes Severe depletion (<1) −8.55% 16 2.50 56.2% 0% 25.0% 10 Δ normal PCs denotes the difference in normal plasma cells before Teclistamab and 3-6 months after Teclistamab treatment. *NA = no paired marrow available in that subgroup.

Development and testing of an ex vivo, live tumor fragment platform for the prediction of immune checkpoint inhibitor response and relationship to approved biomarkers.

2646 Background: Immune checkpoint inhibitors (ICIs) have transformed the management of many advanced cancers but identifying patients who are likely or unlikely to benefit from ICI treatment remains a critical challenge. Biomarkers, such as PD-L1, mismatch repair deficiency, and tumor mutational burden, capture only static, unidimensional features of the complex tumor microenvironment, and therefore inadequately predict response to immunotherapy in patients. In contrast, live tumor fragments (LTFs) preserve the full complexity of the tumor microenvironment and enable functional ex vivo assessments of ICI activity. Previous efforts have had limited clinical applicability because they required larger resection specimens often collected at a single academic center. Here, the predictive capability of an ex vivo platform using core needle and forceps biopsies from multiple clinical sites was assessed and compared to approved biomarkers. Methods: Patients with eligible solid tumors (where ICI has an indication, including renal, non-small cell lung, bladder, colorectal, and triple-negative breast cancer, and others) were enrolled in ongoing, prospective observational trials (NCT05478538, NCT05520099, NCT06349642). Biopsies were cut into LTFs, encapsulated in hydrogel, and treated sequentially with IgG antibody followed by ICI (αPD-[L]1 with or without αCTLA-4). Cytokine production was assessed by a multiplexed bead-based immunoassay at multiple time points during ex vivo treatment. Using receiver operating characteristic and precision recall analyses, we identified 9 predictive cytokines (including IFN-γ, granzyme B, and CXCL9/10), which were used to develop the Elephas score (ELP-score) to assess cytokine response to ex vivo ICI treatment. Results: Of 167 eligible patient specimens, 85% (n = 142) passed quality control metrics and 130 were used for model development. Hierarchical clustering of cytokine production revealed that 27% (n = 35) of patient specimens exhibited a cytokine response to ICI. In a validation set of 20 tumors, collected from patients who were subsequently treated with ICI, ELP-score positivity correctly identified 9 of 11 patients (82%) who had an objective response (PR/CR) to ICI, including 2 patients who were negative for FDA-approved standard-of-care ICI biomarkers. Furthermore, 5 of 5 patients (100%) with clinical progressive disease were correctly characterized as ELP-score negative. Conclusions: Using routine biopsy specimens, the ex vivo live tumor platform accurately identifies patients with clinical response to ICI therapy, including those incorrectly identified by conventional biomarkers. Ongoing efforts will test these findings in an additional validation set. If confirmed, the ex vivo LTF platform could enable the identification of patients likely to benefit from ICI therapy. Clinical trial information: NCT05478538 , NCT05520099 , NCT06349642 .

Oral selective estrogen receptor degrader monotherapy versus standard endocrine therapy in estrogen receptor-positive, HER2-negative advanced breast cancer with ESR1 mutations: A meta-analysis of randomized trials.

e13061 Background: Resistance to endocrine therapy remains a major clinical challenge in estrogen receptor–positive (ER+), human epidermal growth factor receptor 2–negative (HER2–) advanced breast cancer. Oral selective estrogen receptor degraders (SERDs) have been developed to overcome limitations of intramuscular fulvestrant and resistance associated with ESR1 mutations. However, the comparative efficacy and safety of oral SERD monotherapy versus standard endocrine therapy or physician’s choice endocrine therapy (SOC/PCET) remain incompletely defined. Methods: meta-analysis of randomized controlled trials was performed comparing oral SERD monotherapy with SOC/PCET in patients with ER+/HER2– advanced breast cancer. Outcomes included progression-free survival (PFS), overall survival (OS), objective response rate (ORR), clinical benefit rate (CBR), and safety endpoints. Prespecified subgroup analyses were conducted in patients with ESR1-mutant tumors. Hazard ratios (HRs) were pooled for time-to-event outcomes and risk ratios (RRs) for binary outcomes using fixed- or random-effects models based on statistical heterogeneity. Results: Three randomized trials comprising more than 1,400 patients were included. Oral SERD monotherapy significantly improved PFS compared with SOC/PCET in the overall population (HR 0.80, 95% CI 0.70–0.91; P = 0.001), with low heterogeneity (I² = 2%). A statistically significant OS benefit was also observed (HR 0.72, 95% CI 0.57–0.91; P = 0.005). ORR was higher with oral SERDs (RR 1.64, 95% CI 1.12–2.39; P = 0.01), while improvement in CBR did not reach statistical significance (RR 1.22, 95% CI 0.95–1.56; P = 0.11). In patients with ESR1-mutant disease, oral SERD monotherapy was associated with a pronounced PFS benefit (HR 0.65, 95% CI 0.51–0.82; P = 0.0003), with no heterogeneity detected. Although ORR and CBR numerically favored SERDs in this subgroup, these differences were not statistically significant. Safety analyses showed no significant differences between oral SERDs and SOC/PCET in grade ≥3 adverse events (RR 1.13, 95% CI 0.79–1.62), treatment discontinuation due to adverse events (RR 1.72, 95% CI 0.80–3.69), grade ≥3 nausea, or grade ≥3 alanine aminotransferase elevation. Conclusions: Oral SERD monotherapy provides significant improvements in progression-free and overall survival compared with SOC/PCET in ER+/HER2– advanced breast cancer, with the greatest benefit observed in patients with ESR1-mutant tumors. These efficacy gains are achieved without a meaningful increase in serious toxicity, supporting oral SERDs as an effective and well-tolerated endocrine treatment option in this setting.

Geographic disparities in hepatocellular carcinoma incidence in the United States, 2001–2022.

e16281 Background: Hepatocellular carcinoma (HCC) incidence in the United States has recently stabilized or declined; however, substantial geographic variation in underlying risk factors may result in heterogeneous state-level trends and rural-urban disparities. We evaluated recent state-level and rural–urban trends in HCC incidence across the United States. Methods: We analyzed incident HCC cases from the National Program of Cancer Registries and the Surveillance, Epidemiology, and End Results program, covering all 50 states and the District of Columbia from 2001–2022. HCC was identified using ICD-O-3 site code C22.0 and histology codes 8170–8175. Annual age-adjusted incidence rates (per 100,000 persons), standardized to the 2000 U.S. population, were estimated using SEER*Stat v9.0.42.0. Temporal trends were assessed using Joinpoint regression (v5.4.0) to estimate annual percent changes (APCs). Data from 2020 were excluded due to COVID-19–related reporting disruptions. Results: A total of 264,633 HCC cases were identified; 77% occurred among men and 87% were diagnosed in urban counties. Overall incidence was 5.6 per 100,000 (95% CI, 5.40–5.76) in men and 1.5 per 100,000 (95% CI, 1.42–1.50) in women. Among men, incidence declined in metropolitan counties by 1.4% annually (95% CI, −1.7 to −1.1) from 2008 to 2022, while increasing in non-metropolitan counties by 1.1% annually (95% CI, 0.6–1.6) during 2007-2022, state-level incidence ranged from 3.6 per 100,000 in South Dakota to 9.0 per 100,000 in Texas and recent declines were observed in 22 states (APC range, −1.2% to −12.6%), whereas increasing trends were identified in Kentucky, Texas, Utah and West Virginia. Among women, incidence declined in metropolitan counties by 1.0% annually (95% CI, −1.4 to −0.6) during 2009-2022 but increased in non-metropolitan counties by 1.7% annually (95% CI, 1.2–2.3) from 2001 to 2022, state-level incidence ranged from 1.1 per 100,000 in Wyoming to 3.1 per 100,000 in New Mexico and decreasing trends in recent years were also observed in 7 states (APC range, −0.9% to −3.4%), whereas increasing trends were observed in Arkansas and Kansas. Conclusions: Despite a recent decline in national HCC incidence, we reported that state-level and rural–urban disparities persist. Particularly, increasing incidence in nonmetropolitan areas and select states highlights the need for rural- and state-specific strategies for risk reduction and early detection. Future studies are needed to investigate the factors contributing to disparities in these states and rural areas.

Effects of yttrium-90 radioembolization on epigenomic immune remodeling in hepatocellular carcinoma: Profiled by blood-based 3D genome conformation assay.

e16273 Background: Yttrium-90 (Y-90) radioembolization for intermediate-stage hepatocellular carcinoma (HCC) has been shown to modulate the tumor immune microenvironment. However, noninvasive biomarkers capable of capturing treatment-induced immune remodeling and informing potential responsiveness to immune checkpoint inhibitors (ICIs) remain limited. We sought to characterize peripheral immune remodeling following Y-90 using Checkpoint Inhibitor Response Test (CiRT) to evaluates three-dimensional (3D) genome conformation signatures in circulating immune cells associated with ICI response. Methods: Peripheral blood samples were collected at baseline and approximately 4 weeks after Y-90 radioembolization in patients with BCLC-B HCC treated in a real-world clinical setting. Paired samples were analyzed using the EpiSwitch CiRT platform, which quantifies epigenomic 3D genome conformations linked to immune checkpoint regulation, interferon signaling, and cytotoxic effector function. A mathematical model classified patients as High or Low probability of response to ICIs. Longitudinal changes in immune-associated loci were assessed using the Wilcoxon signed-rank test. Results: Ten evaluable patients (median age 73.5 years) were included. At baseline, 6 patients were classified as High Probability and 4 as Low Probability for ICI response. Following Y-90, 6 patients were classified as High Probability, including one conversion from Low to High. Epigenomic signal increased across immune checkpoint-associated loci (CTLA4, LAG3, TIGIT), interferon and immune activation markers (STAT1, CXCL9, IRF1), and the cytotoxic effector marker GZMB. LAG3 demonstrated the largest post-treatment increase (P < 0.05). Conclusions: Y-90 radioembolization was associated with detectable epigenomic immune remodeling in peripheral blood, favoring response to ICIs. Circulating 3D genome conformation profiling may provide a complementary, noninvasive approach to assess treatment-induced immune modulation and potential ICI responsiveness following locoregional therapy in HCC. Larger studies are warranted to define clinical implications. Paired pre- and post-Y90 changes in immune-associated epigenomic markers detected in peripheral whole blood. Values reflect three-dimensional (3D) genome conformation signatures rather than transcript or protein abundance. Marker Median Δ (Post–Pre) Wilcoxon p PD-1 +0.75 0.182 CTLA4 +1.25 0.091 LAG3 +3.5 0.018 TIGIT +1.25 0.049 CXCL9 +1.5 0.083 STAT1 +0.75 0.217 IRF1 +0.75 0.156 GZMB +0.75 0.041

Biomarkers to predict anthracycline-induced cardiotoxicity in adult hematologic malignancies: A systematic review.

e24012 Background: Anthracyclines are a mainstay of treatment in hematologic malignancies, particularly in lymphomas and acute leukemias. However, they can also cause dose- and duration-dependent cancer therapy-related cardiac dysfunction (CTRCD), including left ventricular dysfunction. Guidelines regarding the use of cardiac biomarkers in monitoring for CTRCD are equivocal, with the European Society of Cardiology 2022 recommending routine monitoring of troponin and natriuretic peptides, while the American Society of Clinical Oncology 2017 guidelines only provide a moderate recommendation to obtain serum biomarkers. Given that cumulative anthracycline dosages tend to be higher in the management of hematologic malignancies, this systematic review seeks to characterize the relationship between cardiac biomarkers and the detection of anthracycline-induced cardiotoxicity (AIC) in hematologic cancer patients. Methods: A comprehensive search was conducted on PubMed, SCOPUS, and Dissertations and Theses. The search encompassed a broad range of terms related to hematologic malignancies, anthracyclines, and biomarkers. Inclusion criteria included articles that obtained biomarker levels and documented cardiotoxic events. Excluded articles included data from non-hematologic malignancies in which the data from hematologic cancers could not be separated. Results: 1764 articles were screened, including 78 full-text screens. 21 articles were included in the review. The biomarkers investigated were troponin-I in 9 (42.9%) articles, pro-BNP in 8 (38.1%), troponin-T in 7 (33.3%), BNP in 6 (28.6%), ANP in 3 (14.3%), and pro-ANP in 1 (4.8%). A correlation between cardiotoxicity and biomarkers was identified in 12 (57.1%) of the studies. 6 (28.6%) studies utilized multivariate analyses, and all 6 found biomarkers to be predictive of CTRCD when part of a multivariate analysis or included in an algorithm. 3 of these 6 studies incorporated echocardiography. Conclusions: As outlined in this review, changes in biomarker concentrations have been associated with cardiotoxic events, but the utility of individual markers as predictors of CTRCD appears to be limited. Investigators have yet to identify a consistent threshold or monitoring strategy to aid clinicians in risk management for anthracycline therapy. However, our review provides evidence that incorporating multiple biomarkers into multivariate algorithms may hold more promise than the use of any one marker alone. The authors recommend further validation of biomarker-based multivariate prediction models, especially for resource-limited settings in which laboratory monitoring may be more accessible than imaging.

Shifting dietary drivers of colorectal cancer mortality in the United States: A 33-year Global Burden of Disease analysis.

3663 Background: Early-onset colorectal cancer (EOCRC; ages 15–49 years) mortality is increasing in the United States. However, temporal changes in diet-attributable risk factors contributing to EOCRC mortality remain poorly characterized. Using three decades of Global Burden of Disease (GBD) data, we examined shifts in dietary risk factors contributing to EOCRC mortality to identify emerging targets for primary prevention. Methods: We conducted a retrospective population-based analysis of U.S. estimates from the GBD 2023 study (1990–2023). Age-standardized death rates (ASDR), years of life lost (YLLs), and disability-adjusted life years (DALYs) attributable to major dietary risk factors (high processed meat, high red meat, low whole grain, low fiber, low calcium, and low milk intake) were assessed among EOCRC. Period-specific percent changes (1990–1999, 2000–2009, 2010–2019, 2020–2023), rank-order transitions, and sex-stratified patterns were examined. All estimates were derived using GBD cause-of-death ensemble modeling and include 95% uncertainty intervals. Results: In 1990, low whole grain intake was the leading diet-attributable risk factor for ASDR (0.44 per 100,000), followed by red meat (0.40) and processed meat (0.34). Although dietary inadequacy–related risks increased early (low whole grain DALYs +338.9% and YLLs +311.1% in 1990–1999), these burdens declined substantially after 2000. In contrast, processed meat consumption demonstrated persistent and increasingly dominant associations with mortality, with DALYs rising by +430.8%, +223.1%, +94.8%, and +15.9% across successive periods. By 2023, processed meat accounted for the highest ASDR (0.55), surpassing low whole grain (0.53) and red meat (0.49). Sex-stratified analyses showed processed meat emerged as the leading diet-attributable risk among males by 2010 and rose from third to second among females, narrowing the gap with low whole grain intake. Conclusions: Over 33 years, diet-attributable EOCRC mortality in the US has undergone a rank-order transition from dietary inadequacy toward processed meat consumption, particularly among males and increasingly among females. The persistence and dominance of processed meat-attributable burden highlight a critical, modifiable lifestyle risk factor and underscore an urgent opportunity for targeted, age- and sex-specific primary prevention strategies aligned with colorectal cancer prevention recommendations. Age-standardized early-onset colorectal cancer death rates (per 100,000 population) attributable to dietary risk factors in the United States, 1990–2023. 1990 2000 2010 2020 2023 Red Meat 0.40 0.48 0.47 0.50 0.49 Processed Meat 0.34 0.46 0.50 0.55 0.55 Low Fiber 0.02 0.03 0.02 0.02 0.02 Low grain 0.44 0.53 0.52 0.54 0.53 Low Ca 0.09 0.09 0.09 0.10 0.09 Low milk 0.26 0.31 0.31 0.29 0.28

Molecular remission after tyrosine kinase inhibitor cessation in chronic myeloid leukemia (CML): A systematic review and meta-analysis.

e18601 Background: Tyrosine kinase inhibitors (TKIs) have transformed the management of chronic myeloid leukemia (CML), enabling many patients to achieve deep molecular responses. Discontinuation of TKIs with the goal of treatment-free remission (TFR) is now an important therapeutic consideration, but relapse rates remain variable across studies. Methods: We systematically searched PubMed, Embase, and Scopus from inception to August 31, 2025, for prospective and observational studies reporting TFR outcomes in adults with chronic-phase CML following TKI cessation. Proportions of patients in TFR at 6, 12, 24, and 36 months were pooled using random-effects meta-analysis. Heterogeneity was assessed with the I² statistic. Risk of bias was evaluated with the Newcastle–Ottawa Scale (NOS), and certainty of evidence was graded using GRADE. Meta-regression was performed to examine the association between TKI duration and TFR outcomes. The review protocol was registered on PROSPERO (CRD420251143733). Results: Sixteen studies comprising 2,156 patients were included. The pooled TFR rates were 60% (95% CI, 54–65%) at 6 months, 55% (95% CI, 49–60%) at 12 months, 54% (95% CI, 48–59%) at 24 months, and 52% (95% CI, 45–59%) at 36 months, with substantial heterogeneity (I² >80%). Most relapses occurred within the first 12 months. Meta-regression showed a positive association between longer TKI duration and higher 6-month TFR rates (TFR6mo = 0.0835 + 0.2744×log10[median TKI duration, months]). The certainty of evidence for all outcomes was rated as moderate. Conclusions: Approximately half of patients with chronic-phase CML who discontinue TKI therapy sustain long-term TFR. Longer TKI exposure is associated with improved success, supporting guideline recommendations to ensure durable deep molecular remission before discontinuation. These findings reinforce the feasibility of TFR as a treatment goal while highlighting the importance of careful patient selection and close monitoring.

Epidemiology of sarcoma in Syria: A retrospective study from the national referral center.

e23504 Background: The Syrian conflict has devastated healthcare infrastructure, creating a critical data gap in cancer epidemiology. This study presents the first analysis of sarcoma from Syria's main oncology center, characterizing patient demographics to establish baseline data for conflict-affected settings. Methods: This is a retrospective study at Al-Bairouni University Hospital – Syria’s national cancer center serving 65-70% of the country’s cancer patients. We included patients > 18 diagnosed with Sarcoma between 1 January 2024 and 31 December 2025. Data extracted from hospital records included sex, age at diagnosis, cancer stage, grade, smoking status, and the governorate of residence. Institutional ethical approval was obtained to perform the study. Results: A total of 500 patients were diagnosed with sarcoma during the study period: 250 in 2024 and 250 in 2025 (Table 1). Across all years, a consistent male predominance was observed 55.5%. The average age at diagnosis was 46.9 years, 35.6% of patients were smokers, 55.5% were high grade and 51% of all cases had advanced/metastatic disease at diagnosis. The highest patient loads originated from Damascus (23.4%) and Rural Damascus (11.6%), followed by central governorates such as Homs and Hama (17.6%). Notably, patients from more distant and underserved governorates such as Deir ez-Zor (7.6%), Aleppo (12.2%), and Al-Hasakeh with Raqqa (9.8%) accounted for a significant proportion of the Sarcoma presenting to our center. Smoking status predicted high-grade histology (OR: 2.34, 95% CI:1.42–3.87, p = 0.008). Patient age was not associated with advanced disease diagnosis (β = 0.03, 95% CI:-0.05–0.11, p = 0.32). Controlling for age and sex, sarcoma subtype independently predicted metastatic presentation (OR:3.15, 95% CI: 1.89–5.24, p < 0.001). Conclusions: Syria's first nationwide sarcoma analysis reveals widespread smoking and late diagnoses as critical challenges, calling for urgent prevention and early detection efforts. This provides essential evidence for health planning in conflict settings. Diagnosis 2024 Cases 2025 Cases Total cases Average Age Male Sex (%) Smokers (%) High grade Advanced/Metastatic at diagnosis Angiomyosarcoma 4 3 7 54.7 28.5% 28.7% 50% 50% Ewing 23 18 41 32.5 75% 43.9% 50% 43% Dermatofibrosarcoma 3 13 16 61.3 56.2% 37% 33.3% 57% fibrosarcoma 18 13 31 38.8 51.6% 32.2% 61.1% 50% giant cell 3 8 11 27.7 63.6% 27.2% 33.3% 43% gist 21 - 21 55.3 68.1% 31.8% 50% 68% Kaposi 6 13 19 67.3 68.4% 36.8% 41% 50% liposarcoma 27 24 52 57.5 57.6% 34.6% 52% 34.7% leiomyosarcoma 26 21 47 50.6 23.4% 36.1% 58% 68.1% chondrosarcoma 12 16 28 42.9 64.2% 25% 57% 42% osteosarcoma 14 16 30 33.7 75.8% 40% 46% 53% rhabdomyosarcoma 11 7 18 37.5 66.6% 33.3% 67% 60% Spindle cell sarcoma 16 18 34 50.5 45.7% 31.4% 70% 55% Synovial 17 20 37 39.7 43.2% 45.9% 64% 52% undifferentiated 30 21 51 47.5 47% 39.2% 77% 47.8% MFH 12 13 25 54.8 48% 40% 67% 33.3% Others 7 26 33 45.4 58% 41.9% 52% 63%

Impact of consensus-based feature selection on machine learning performance for metastatic lung cancer prediction in resource-limited settings.

e20519 Background: In low- and middle-income countries (LMICs), lung cancer is frequently diagnosed at advanced or metastatic stages due to limited early detection infrastructure. Conventional logistic regression provides interpretability but limited predictive performance in high-dimensional settings, whereas penalized regression and machine-learning models can capture complex, non-linear relationships. Comparative evaluation of these approaches in LMIC metastatic cohorts remains scarce. We assessed regression-based and machine-learning models to predict metastatic lung cancer risk and identify key determinants, emphasizing the trade-off between predictive accuracy and clinical interpretability. Methods: We analyzed 4,480 lung cancer patients treated at the National Institute of Cancer Research and Hospital, Bangladesh (2021–2023) using 29 demographic, clinical, symptom-related, and laboratory variables. Missing binary and categorical data were imputed using observed-proportion sampling. Models evaluated included conventional logistic regression, LASSO-penalized logistic regression, ridge regression, Random Forest, and XGBoost. Feature importance was derived for each model and aggregated into a consensus ranking. The top 15 consensus-ranked features were used to re-train all models, with performance compared to full-feature models. Evaluation metrics included ROC–AUC, F1-score, sensitivity (metastatic recall), specificity, calibration plots, and decision curve analysis. Results: Among the top 15 consensus-ranked features, habitual factors emerged as the strongest predictors of metastatic disease, followed by poor performance status (ECOG ≥2), respiratory symptoms including breathlessness with chest pain, and multiple concurrent symptoms. After consensus-based feature selection, tree-based models demonstrated notable performance gains. Random Forest achieved a 3.6% increase in F1-score and 1.8% improvement in metastatic recall. XGBoost showed the largest relative gains: metastatic recall increased by 15.8%, F1-score by 8.3%, with modest improvements in discrimination. In contrast, regression models showed declines in F1-score (LASSO −7.9%, ridge −41.4%) despite stable or slightly improved specificity. Consensus-ranked features preferentially enhanced clinically relevant detection in tree-based models, demonstrating their superiority over regression approaches in this LMIC real-world dataset. Conclusions: Tree-based models achieved superior predictive accuracy and balanced sensitivity–specificity compared with conventional regression. Consensus-ranked features improved metastatic case detection despite dataset limitations inherent to LMIC settings. External validation is required to confirm generalizability in LMIC, real-world clinical environments.