Browse Articles

Management of pulmonary nodules across Latin America: A real-world observational study.

8030 Background: Lung cancer is the leading cause of cancer-related mortality globally, with lung cancer accounting for 6.8% of all cancer cases in Latin America and the Caribbean. Despite the availability of guidelines, lung cancer early detection and the management of pulmonary nodules across the region are inconsistent, often hindered by limited resources and fragmented health systems. This study aimed to characterize the diagnostic and treatment journey of pulmonary nodules in patients with lung cancer across Latin America. Methods: This was a non-interventional observational study that captured retrospective (March 2019 to July 2021) and prospective (July 2021 to March 2023) data across 16 health institutions in Latin America. Participants were followed for at least two years or until treatment initiation or withdrawal. Data were collected from patients’ medical records. Patient characteristics and physicians' involvement were summarised descriptively. Median time estimates of receiving diagnostic procedure or examination from nodule identification and estimates on median time of treatment decision from lung cancer diagnosis were analysed descriptively using the Kaplan-Meier (KM) method. Results: Among a total of 546 participants (215 prospective; 331 retrospective), 82 were diagnosed with lung cancer during the study period, most commonly with Stage I lung cancer (5.9%). The majority of referrals to dedicated nodule clinics were made by pulmonologists (44.1%) and prompted by incidentally detected pulmonary nodules (83.9%), which were typically solid and ranged from 8mm to 3cm in size (79.5%). The median time to receiving a diagnostic procedure from nodule identification was 10.83 (prospective) and 12.47 (retrospective) months, while the median time to treatment decision post-diagnosis was 1.20 months across both cohorts. Multidisciplinary teams were involved in only 0.3% of diagnostic procedures, but were involved in at least 40% of treatment decisions across different follow-up visits. Conclusions: This study reveals substantial delays in diagnostic procedures and limited multidisciplinary team involvement during early patient evaluation phases in Latin America. Compared with international studies, the study population experienced considerably longer delays in receiving diagnostic procedures. These findings underscore the need for structured referral pathways and broader implementation of critical tools across the region. In addition, adherence to established guidelines is critical to improve early detection and treatment outcomes of lung cancer patients.

Knowledge distillation for pancreatic cancer diagnosis: EfficientNet-based deep learning for stage stratification with real-world deployment optimization.

4217 Background: Pancreatic cancer is among the most lethal malignancies, with a 5-year survival below 12%. Prognosis is strongly stage dependent, yet early disease is frequently misclassified as chronic pancreatitis or benign cystic lesions, resulting in diagnostic delay and loss of surgical opportunity. Although deep learning models demonstrate high accuracy on cross-sectional imaging, their computational demands limit deployment in resource-constrained settings. Knowledge distillation enables transfer of diagnostic capability from high-capacity teacher models to lightweight student networks while preserving performance. We evaluated whether a distilled EfficientNetB0 model could retain EfficientNetB7-level accuracy for pancreatic cancer stage stratification while enabling real-world deployment. Methods: We analyzed 2,840 contrast-enhanced abdominal CT studies, including pancreatic ductal adenocarcinoma (n = 1,400; 700 early-stage resectable or borderline-resectable, 700 locally advanced or metastatic), chronic pancreatitis (n = 900), and benign pancreatic lesions (n = 540) from multiple international centers. Ground truth was established by multidisciplinary consensus incorporating histopathology, surgical findings, and longitudinal follow-up. A high-capacity EfficientNetB7 teacher model (≈66M parameters; 37 GFLOPs) trained on multiphasic CT served as reference. A lightweight EfficientNetB0 student model (≈5.3M parameters; 0.39 GFLOPs; > 90% parameter reduction) was trained using temperature-scaled knowledge distillation with regularized cross-entropy loss. Performance metrics included accuracy, sensitivity, specificity, F1-score, and AUROC. Deployment feasibility was independently evaluated by abdominal radiologists and oncologists across six continents. Results: The distilled EfficientNetB0 achieved 96.6% accuracy for stage stratification (early vs advanced disease), with sensitivity of 97.4%, specificity of 95.8%, and AUROC of 0.989. Differential diagnosis accuracy was 94.8% for pancreatic cancer versus chronic pancreatitis and 95.6% versus benign lesions. External validation accuracy ranged from 93% to 97%. Mean inference time was 38 ms per image compared with 330 ms for EfficientNetB7. Knowledge distillation preserved 99.1% of teacher performance while reducing computational cost by > 95%. Conclusions: Knowledge distillation enables a lightweight EfficientNetB0 to achieve near–EfficientNetB7 accuracy for pancreatic cancer stage stratification while markedly reducing computational complexity. This scalable approach supports real-time imaging decision support and addresses key barriers to global deployment of AI-assisted pancreatic cancer diagnosis.

Optimization of geospatial oncologist placement: A maximum coverage problem approach.

1609 Background: Rural communities in the United States (US) experience persistent shortfalls accessing oncology care due to an uneven workforce distribution. Non-specific county-level metrics fail to pinpoint precisely where new oncologists can maximize impact. By adapting a maximal coverage algorithm to the ZIP code level, our study aims to provide a data-driven solution to physician placement by identifying high demand areas with significant unserved populations. Methods: We developed a model to simulate capacity-constrained maximal coverage expansion of oncology care with up to 500 oncologist placements per state, 40 kilometer catchment radii, and an assumption that one oncologist could cover up to 6,667 individuals over 55 years old (based on baseline US prevalence of 15 oncologists per 100,000 individuals over 55). We used physician data from the Doctors and Clinicians national downloadable file, geographical data from the US Census, and Rural-Urban Continuum Codes (RUCCs) to measure rurality. Outcomes measured included baseline state-level coverage, number of placements needed to achieve 90% state-level population coverage, and urban-rural placement differences. For continuous variables, the two-sample t-test was used for statistical significance. Results: Nationally, approximately 26 million additional individuals would gain coverage with 5,578 additional placements. 2,912 (52.2%) of the optimal ZIP codes were in rural counties. Placements provided a mean coverage of 4,684 people per physician. Median baseline state coverage was 67.8% (IQR 59.9%-77.1%), with 3 states having >90% coverage at baseline (Rhode Island, Connecticut, and New Jersey). To achieve 90% coverage, states required a median of 40 placements (IQR 18.25-63.25). Coverage gains per state were front-loaded with the first 25 oncologists in a state capturing on average 46.7% of all achievable gains. The states that required the greatest number of additional oncologists to achieve 90% coverage were: California (N=209), Florida (N=174), and Texas (N=163). The top five rural placements per state covered an average of 6,505 individuals while the top five urban placements per state covered an average of 6,220 individuals (p-value = 0.009). Conclusions: Our approach precisely identified underserved ZIP codes where oncologist placement would maximize access to care. Strategic placement of oncologists can lead to increased access to care, particularly for rural residents. These policies should initially be directed toward states and ZIP codes with the largest baseline gaps to maximize coverage and advance equitable healthcare access.

Development and validation of an artificial intelligence–based deep learning imaging model for early lung cancer detection: DAVINCI, a retrospective study of 8,962 patients.

8021 Background: Lung cancer is the leading cause of cancer-related mortality worldwide, primarily due to delayed diagnosis and diagnostic variability in histopathological assessment. Advances in deep learning applied to medical imaging offer the potential to enhance early detection accuracy, reduce interobserver variability, and improve diagnostic efficiency in lung cancer. Methods: In this retrospective study, we evaluated DAVINCI using a dataset of 8,962 patients with confirmed lung malignancies. The model utilizes a specialized architecture combining convolutional neural networks (CNNs) and residual blocks to optimize feature extraction from high-resolution pathological slides. Performance was measured via detection accuracy, recall, specificity, and Area Under the Curve (AUC). Results: A total of 8,962 patients were included in the analysis. The DAVINCI model correctly identified lung cancer in 93% of cases, corresponding to 8,334 of 8,962 patients, with a 95% confidence interval (CI) of 86%–100% (7,707–8,962 patients). Model specificity was also 93% (95% CI, 86%–100%), indicating a high true-negative rate. Sensitivity (recall) was 87%, with correct detection in 7,797 patients and a 95% CI of 80%–94% (7,170–8,425 patients). The model demonstrated strong discriminatory performance, achieving an area under the curve (AUC) of 0.91 (95% CI, 0.84–0.98). In comparison, active pathologists achieved a mean diagnostic accuracy of 83%, corresponding to 7,438 of 8,962 cases, with a 95% CI of 76%–90% (6,811–8,066 cases). In terms of efficiency, DAVINCI processed whole-slide images in 16–19 seconds, substantially faster than conventional manual review, which typically requires several minutes per slide. Conclusions: DAVINCI demonstrated superior accuracy, robust discriminatory performance, and markedly faster processing compared with human review, supporting its potential role in early lung cancer detection at scale.

Are all tumor-agnostic biomarkers equally tissue-independent? Comparative cross-histology efficacy analysis of MSI-H/dMMR versus <i>BRAF</i> V600E.

2649 Background: FDA tumor-agnostic approvals for pembrolizumab/dostarlimab (MSI-H/dMMR) and dabrafenib-trametinib (BRAF V600E) assume uniform cross-histology efficacy. However, MSI-H/dMMR depends on immune checkpoint blockade—potentially influenced by tissue-specific microenvironments—while BRAF V600E represents oncogene addiction with essential MAPK dependencies. We hypothesized these biomarkers differ in tissue independence, with MSI-H/dMMR demonstrating greater histology-dependent response variability. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines. PubMed, Embase, and the Cochrane Central Register owere searched from inception to January 2026 to identify prospective basket trials enrolling adults (≥18 years) with advanced or metastatic solid tumors harboring FDA-approved tumor-agnostic biomarkers. Eligible trials evaluated pembrolizumab or dostarlimab in MSI-H/dMMR tumors, or dabrafenib plus trametinib in BRAF V600E-mutant tumors, and reported objective response rates (ORR) stratified by tumor histology. Studies were required to include ≥3 distinct tumor histologies (not subtypes) with a minimum of 10 patients per histology cohort. Phase I trials, retrospective case series, pediatric-only populations, and studies without histology-specific efficacy data were excluded. Primary outcome was ORR heterogeneity across tumor types within each biomarker platform, quantified using the I² statistic and coefficient of variation (CV). Pooled analyses were performed using random-effects models. Effect estimates are expressed as ORR percentages with 95% confidence intervals. Results: Four trials included: KEYNOTE-158 (pembrolizumab, n=373), GARNET (dostarlimab, n=363), ROAR (dabrafenib-trametinib, n=215), VE-BASKET (vemurafenib, n=62); 1,013 patients across 12 tumor histologies. MSI-H/dMMR platform (n=736, 8 tumor types): mean ORR 35.1% (range 0-57.1%); endometrial 57.1%, gastric 45.8%, colorectal 43.5%, small intestine 42.1%, cholangiocarcinoma 40.9%, ovarian 33.3%, pancreatic 18.2%, brain 0%; CV=0.513. BRAF V600E platform (n=277, 4 tumor types): mean ORR 45.0% (range 37.1-53%); anaplastic thyroid 53%, biliary tract 47%, glioma 42.9%, NSCLC 37.1%; CV=0.149. MSI-H/dMMR demonstrated 3.4-fold greater heterogeneity than BRAF V600E (CV 0.513 vs 0.149). Conclusions: Tumor-agnostic biomarkers exhibit differential tissue independence. MSI-H/dMMR showed 3.4-fold greater response heterogeneity (CV=0.513) than BRAF V600E (CV=0.149), indicating immune checkpoint efficacy remains tissue-dependent while oncogene addiction confers uniform predictivity. These findings challenge the assumption of biomarker-driven tissue-agnostic efficacy and necessitate histology-specific outcome counseling and trial stratification.

Responses to trastuzumab deruxtecan (T-Dxd) in HER2 IHC spectrum 2+ versus 3+ urothelial carcinoma across lines of therapy.

4581 Background: The role of HER2 as a therapeutically actionable target has been validated with the DESTINY-PanTumor02 trial demonstrating meaningful clinical benefit to T-DXd across HER2-expressing bladder malignancies leading to the FDA approval in the immunohistochemical (IHC) 3+ population. We explore the clinical outcome of real-world patients with urothelial carcinoma (UCa) on T-DXd and its correlation with molecular and pathological findings across all the HER-2 IHC scores (e.g., 0 to 3+). Methods: We reviewed the clinical, pathologic, and molecular data of 29 patients with UCa, who received T-DXd between April 2024 and November 2025. Baseline clinical variables included age, sex, ECOG performance status, visceral metastases, line of therapy, and HER2 IHC score (adapted from gastric cancer scoring). Available genomic data included tumor mutational burden (TMB ≥10 mut/Mb), ERBB2 amplification and mutation, DNA damage response (DDR), FGFR alterations, and microsatellite instability (MSI) status. Outcomes of interest included Objective Response Rate (ORR), Disease Control Rate (DCR), and progression-free survival (PFS) and overall survival (OS) which were estimated using Kaplan–Meier methods and compared across groups using the log-rank test. Cox proportional hazards models were used to estimate hazard ratios. Results: Higher HER2 IHC scores were associated with greater clinical activity and higher ORR in IHC 2+ (n=7; 42.9; 95% CI = 9.9–81.6%) tumors and HER2 IHC 3+ (n=20; 55.0; 95% CI =31.5–76.9%). However, no response was seen in HER2 IHC 1+ (n=2). Median duration of response was 15.6 months in HER2 IHC 2+ and 11.6 months in HER2 IHC 3+ (15/30 patients received T-DXd in ≥3 lines). PFS and OS appeared comparable between HER2 2+ and HER2 3+ tumors, with no statistically significant difference by log-rank test (p = 0.67, p = 0.79 respectively). Elevated TMB was observed in 6/12 cases. ERBB2 amplification was detected in 3/10 of cases and ERBB2 mutation in 5/13 of cases. Alterations in DDR related genes and FGFR were identified in patients 2/11 and 1/12 respectively, while MSI-H was not observed in any case. Responses were numerically higher when T-DXd was given in 2 nd line (53.3%, 95% CI 26.6–78.7%) than in further lines (42.9%, 95% CI 17.7–71.1%) and so was DCR 93% (95% CI 68.1–99.8%) in 2 nd line than 71.4% (95% CI 41-91.6%) in further (≥3) lines. Conclusions: T-DXd demonstrated meaningful clinical activity not only in IHC 3+ but in IHC 2+ tumors as well, which is consistent with the results of the DESTINY-PanTumor02 trial. In this limited sample size, there was no statistically significant association between genomic features and patient outcomes. Larger studies are needed to further find predictors across different levels of IHC expression. HER2 IHC Score n Responders (CR/PR) ORR (%) 95% CI 1+ 2 0 0.0 0.0–84.2% 2+ 7 3 42.9 9.9–81.6% 3+ 20 11 55.0 31.5–76.9%

Real-world treatment patterns and clinical outcomes among cholangiocarcinoma patients treated with futibatinib or pemigatinib.

4109 Background: Pemigatinib and futibatinib are FGFR2 inhibitors approved by the US Food and Drug Administration in 2020 and 2022, respectively, for the treatment of advanced cholangiocarcinoma (CCA). This study describes demographic and clinical characteristics, and assesses clinical outcomes of real-world CCA patients treated with futibatinib or pemigatinib. Methods: This study used deidentified data from electronic medical records and claims from the ConcertAI RWD360 oncology dataset. Patients diagnosed with CCA and with evidence of initial treatment with futibatinib or pemigatinib in 2023 or later (index treatment) were included. Real-world outcomes (real-world overall survival [rwOS], time to discontinuation [rwTTD], and time to next treatment or death [rwTTNTD]) from the index date were described using Kaplan-Meier analysis. Cox regression models were used to adjust for patient characteristics. Adverse medical events of interest (MEI) were identified with ICD codes. Results: This study included 122 futibatinib (median age: 64 years; female: 58%; White: 66%) and 93 pemigatinib patients (median age: 66 years; female: 61%; White: 69%). The most common treatment regimen before index was cisplatin + durvalumab + gemcitabine (44% futibatinib and 35% pemigatinib patients). Futibatinib patients had numerically longer median rwOS (10.5 vs. 9.6 months) and median rwTTNTD (6.5 vs. 5.6 months) than pemigatinib patients, though the differences were not statistically significant; median rwTTD was similar in both futibatinib and pemigatinib patients (2.8 vs. 2.8 months); and adjusted hazard ratios were non-significant for all outcomes (Table 1). Futibatinib had numerically higher 6-month rwOS (63% vs. 55%) and 12-month rwOS (42% vs. 36%). Overall, 28% (n=60) of patients experienced MEI during index treatment: 29% (35/122 patients) in the futibatinib group and 27% (25/93) in the pemigatinib group. The most common MEI were (futibatinib vs. pemigatinib) fatigue (8% vs. 16%), diarrhea (10% vs. 5%), and dry eyes (6% vs. 1%). Conclusions: This study represents the largest real-world analysis to date of CCA patients treated with FGFR inhibitors. Overall, patient characteristics and MEI were similar in the two treatment groups. Clinical outcomes were also similar in both groups, suggesting that futibatinib is a promising alternative in this patient population. Outcome results. Futibatinib Patients (n=122) Pemigatinib Patients (n=93) P-Value Median rwOS, months (95% CI) 10.5 (7.3, 14.4) 9.6 (5.2, 10.8) 0.39 Adjusted HR 0.95 Ref. 0.65 Median rwTTD, months (95% CI) 2.8 (1.2, 3.7) 2.8 (1.7, 4.0) 0.51 Adjusted HR 1.10 Ref. 0.47 Median rwTTNTD, months (95% CI) 6.5 (4.8, 8.1) 5.6 (4.1, 7.4) 0.66 Adjusted HR 1.00 Ref. 0.99 HR: hazard ratio. Variables adjusted for in Cox model: age, sex, setting of care, ECOG performance status, and time from diagnosis to index date.

Phase 1 study of VLPONC-01, a novel IL-12–encoding saRNA viral replicon particle, alone and in combination with pembrolizumab in head and neck cancer patients: Protocol summary.

TPS6134 Background: Head and neck squamous cell carcinoma (HNSCC) has high recurrence rates despite standard perioperative treatments such as surgery with adjuvant radiotherapy and/or chemotherapy, with about 35% of patients relapsing. Neoadjuvant immune checkpoint therapy has shown promise: in the Phase III KEYNOTE-689 trial, adding perioperative pembrolizumab to standard care significantly improved median event-free survival (51.8 vs 30.4 months), leading to FDA approval in June 2025. However, only 9.4% of patients achieved a major pathologic response, a key predictor of reduced relapse and a surrogate for long-term benefit in other cancers. This low response rate underscores the need for more effective strategies to expand and deepen durable immune-mediated tumor responses in HNSCC. Our strategy is to develop a combination immunotherapy/gene therapy targeting the immunosuppressive myeloid populations such as tumor-associated macrophages (TAMs) and neutrophils (TANs), which are increasingly recognized as key mediators of immune evasion and poor outcomes. VLPONC-01 is a novel, non-replicating, viral particle-based therapy to target TAMs and TANs. VLPONC-01 efficiently delivers self-amplifying RNA (saRNA) encoding an engineered human Interleukin 12 (IL-12) gene into cells in the tumor microenvironment (TME), leveraging the natural tropism of Venezuelan equine encephalitis virus (VEEV). Within transfected cells, the RNA amplifies itself and directs the cell to produce and secrete IL-12 protein. The released IL-12 is expected to concentrate in the TME, where it activates immune cells and enhances their ability to attack cancer cells. Methods: This is a first-in-human, phase 1, open-label trial evaluating the safety and early efficacy of intratumoral administration of VLPONC-01 in patients with HNSCC, focusing on its ability to reduce tumor burden and lessen surgical morbidity. Furthermore, it will characterize IL-12-driven alterations in the tumor microenvironment and determine the synergistic potential of combining this approach with anti-PD-1 immunotherapy. The study includes two cohorts: Cohort A tests weekly intratumoral injection in recurrent and/or metastatic tumor patients to assess safety and determine dose levels, while Cohort C randomizes patients with resectable tumors into three groups to receive low-dose VLPONC-01 plus pembrolizumab, high-dose VLPONC-01 plus pembrolizumab, or pembrolizumab alone, prior to surgery. Outcomes include dose-limiting toxicities, surgical delays, systemic cytokine responses, and tumor response assessed by imaging and pathology. Clinical trial information: NCT06736379 .

Integrating metabolic response and circulating tumor biomarkers as early indicators of therapy outcome in locally advanced inoperable rectal cancer.

e15523 Background: The integration of immunotherapy with chemotherapy in locally advanced rectal cancer (LARC) is a standard of care of late and needs predictive biomarkers. We investigated the relationship between tumor PD-L1 expression, metabolic imaging response, circulating biomarkers, and clinical outcomes in LARC patients receiving neoadjuvant chemo-immunotherapy. Methods: Twenty-four patients with T3–T4, N1–N3 rectal adenocarcinoma received six cycles of modified FOLFOX6 plus pembrolizumab (200 mg IV q3w). PD-L1 combined positive score (CPS) was assessed by immunohistochemistry. 18F-FDG PET-CT was performed at baseline and week 9 to quantify percentage SUV reduction. Serial plasma cell-free DNA (cfDNA) and circulating tumor cell (CTC) counts were measured. Morphologic response was evaluated per i RECIST v1.1. Correlations between biomarkers and Pathological CR rates (pCR) were analyzed using Pearson correlation coefficients. Results: Complete response (CR) was achieved in 8 patients (33%), all with CPS &gt;50%; 14 patients (58%) achieved partial response, and 2 (9%) had stable disease. PD-L1 CPS demonstrated the strongest correlation with pCR (r = 0.94, p &lt; 0.001), followed by SUV reduction (r = 0.93, p &lt; 0.001), cfDNA decline (r = 0.87, p &lt; 0.001), and CTC reduction (r = 0.86, p &lt; 0.001). The regimen was well tolerated: Grade 1–2 toxicities included fatigue (42%), nausea (29%), and transaminitis (17%); Grade 3 events were limited to neutropenia (8%) and immune-mediated thyroiditis (4%). No Grade 4–5 toxicities occurred. Conclusions: In LARC treated with neoadjuvant FOLFOX plus pembrolizumab, PD-L1 CPS strongly predicts treatment response (radiological) and pCR. Metabolic imaging and liquid biopsy biomarkers provide complementary predictive value. This multimodal biomarker approach may enable response-adapted therapeutic strategies in rectal cancer chemo-immunotherapy. The favorable safety profile supports further investigation in larger prospective trials. Demographics. Total Participants 24 patients Age (years) Mean: 50.3 (40-60) Sex Male: 12: Female: 12 T Stage T3: 15 (62.5%), T4: 9 (37.5%) N Stage N1: 12 (50%), N2: 8 (33.3%), N3: 4 (16.7%) RECIST Response PR: 14 (58.3%), CR: 8 (33.3%), SD: 2 (8.3%)

Rapid AI-assisted intraoperative diagnosis for biliary tract adenocarcinoma using femtosecond laser label-free microscopy.

e16019 Background: Intraoperative histopathological assessment is crucial in hepatobiliary surgery, particularly for determining resection margins in biliary tract adenocarcinoma (BTA). Conventional frozen-section analysis is limited by time-consuming processing, structural artifacts, and subjective interpretation, potentially impacting surgical decisions. Methods: To address these limitations, we developed an integrated diagnostic platform combining femtosecond laser label-free microscopy (FLI) with artificial intelligence (AI). This system performs rapid, nondestructive imaging of fresh, unprocessed tissue specimens in under three minutes. The AI model was trained and validated to analyze the FLI-derived images. Results: The AI-enhanced FLI system demonstrated high diagnostic accuracy. It effectively differentiated benign from malignant tissue at biliary margins, achieving an area under the curve (AUC) of 0.915-0.940. Beyond binary classification, the platform predicted key prognostic features: perineural invasion (AUC: 0.817), vascular invasion (AUC: 0.900), and Ki-67 proliferation index (AUC: 0.94), while also providing a multiplexed immuno-profile. The entire workflow, from specimen acquisition to a comprehensive diagnostic report, was completed within five minutes. Conclusions: Our AI-FLI platform represents a transformative tool for intraoperative diagnosis. It delivers rapid, accurate, and multifaceted pathological assessment directly from fresh tissue, overcoming major constraints of frozen-section analysis. This technology provides surgeons with critical, real-time guidance to optimize the extent of resection during BTA surgery, potentially improving oncologic outcomes.

Comparative real-world outcomes with talquetamab and teclistamab in relapsed/refractory multiple myeloma: A TriNetX observational study.

e19519 Background: Talquetamab (GPRC5D) and teclistamab (BCMA) are bispecific antibodies for relapsed/refractory multiple myeloma (RRMM), but comparative real-world evidence is limited. We compared 1-year effectiveness and safety outcomes between talquetamab and teclistamab. Methods: We conducted a retrospective cohort study in the TriNetX US Collaborative Network. Adults (≥18 years) with RRMM treated with talquetamab or teclistamab from October 2022–November 2025 were included. Patients with solitary plasmacytoma, plasma cell leukemia, or clinical trial–only monitoring codes were excluded. Cohorts were propensity score matched 1:1 on demographics and comorbidities (198 per group). Outcomes through 365 days post-index included all-cause mortality, remission, immune/hematologic toxicities, infections, and organ complications. Effect estimates included risk difference (RD), risk ratio (RR), hazard ratio (HR), 95% confidence intervals (CI), and log-rank p values. Results: Among 1,626 eligible RRMM patients, 402 received talquetamab and 1,224 received teclistamab prior to matching. After matching, baseline characteristics were balanced (mean age 66.8 years; 42% female; similar comorbidity profiles). Grade 3 neutropenia was more common with talquetamab (25.8%) than teclistamab (19.7%) (RD 0.061, 95% CI −0.014 to 0.136; RR 1.31, 95% CI 0.96–1.79; HR 1.46, 95% CI 0.99–2.15; log-rank p=0.054). Grade 3 lymphopenia incidence was similar (5.6% vs 5.1%) (RD 0.005, 95% CI −0.034 to 0.044; RR 1.10, 95% CI 0.55–2.20; HR 1.28, 95% CI 0.63–2.61; log-rank p=0.49). Acute kidney injury was numerically higher with teclistamab (29.3% vs 22.2%) (RD −0.071, 95% CI −0.154 to 0.012; RR 0.76, 95% CI 0.56–1.04; HR 0.77, 95% CI 0.54–1.10; log-rank p=0.15). Mortality (18.2% vs 20.7%; HR 0.91; log-rank p=0.61) and remission (29.1% vs 31.6%; HR 0.95; log-rank p=0.74) were similar between talquetamab and teclistamab. Cytokine release syndrome occurred more often with talquetamab (20.2% vs 14.6%; HR 1.49; log-rank p=0.17). Neurotoxicity was comparable (9.6% vs 7.9%; HR 1.24; log-rank p=0.52). Pneumonia (16.2% vs 20.3%) and sepsis (10.6% vs 13.1%) were numerically lower with talquetamab; thrombocytopenia and hepatotoxicity were similar. Conclusions: In this real-world propensity-matched RRMM cohort, talquetamab and teclistamab had comparable 1-year mortality and remission, with differing toxicity profiles. Talquetamab was associated with higher grade 3 neutropenia and numerically higher cytokine release syndrome, whereas teclistamab showed a signal toward more acute kidney injury and higher infection rates. These data may support individualized treatment selection based on toxicity risk.

YL205, a novel anti-Napi2b antibody drug conjugate (ADC), in patients with ovarian cancer: Preliminary result from a first-in-human trial.

5551 Background: Sodium-dependent phosphate transport protein 2b (NaPi2b) is a rapidly internalizing sodium-phosphate transporter which is highly overexpressed in ovarian cancer (OC). The prognosis of patients (pts) with heavily pretreated ovarian cancer remains poor, highlighting a significant unmet need. YL205 is a unique antibody-drug conjugate comprising a NaPi2b-directed antibody conjugated to a potent topoisomerase 1 inhibitor payload developed with TMALIN platform. The preliminary safety and efficacy of YL205 monotherapy in ovarian cancer from a multi-center, open-label, phase I/II trial are presented. Methods: Pts with advanced solid tumors, mainly OC, who had failed standard therapy or no available standard therapy were enrolled in the trial YL205-CN-101-01. It consists of dose-escalation (BF-BOIN design), followed by dose-expansion. Pts received YL205 IV at 1.0~3.0 mg/kg once every 3 weeks. Primary objectives were to assess safety and tolerability. Results: As of the data cut-off on Dec. 12, 2025, 48 OC pts were dosed with YL205 monotherapy in China and United States with median follow up time of 5.5 months (range 0.2-17.2). Pts had median age of 54.2 yo (range 32-70), 68.8% with ECOG PS 1, 37.5% with ≥ 4 prior lines of therapy. Previous therapies included bezacizumab (89.6%), PARP inhibitors (43.8%), and mirvetuximab soravtansine (2.1%). No maximum tolerated dose (MTD) was defined. Grade 3 TRAEs occurred in 27.1% of pts. 14.6% of pts developed SAEs related to tx. The most common TRAEs were neutropenia (60.4%; G≥3: 12.5%), anaemia (60.4%, G≥3: 4.2%), nausea (47.9%, G≥3: 0), vomiting (33.3%, G≥3: 0), decreased appetite (27.1%, G≥3: 0) and thrombocytopenia (25.0%, G≥3: 6.3%) across all dose levels. Among 43 efficacy evaluable pts, confirmed ORR was 46.5% (95% CI: 31.2 – 62.3), and DCR was 95.3% (95% CI: 84.2 – 99.4). At the date cutoff, the median progression-free survival (PFS) data was immature, 62.5% (15/24) of patients with a response remain on treatment. NaPi2b expression as evaluated by H-score was found to be low (0-100) in 1 pt, medium (101-201) in 11 pts (101-200) and high (201-300) in 35 pts whose tumor tissues available at baseline. No correlation trend was observed between NaPi2b expression and response. Conclusions: YL205 demonstrated a manageable safety profile in heavily pretreated ovarian cancer patients, with preliminary efficacy observed irrespective of NaPi2b expression intensity. The promising clinical data supports further investigation of this ADC in OC. Clinical trial information: NCT06459973 .

Structural insights into CeO2 nanoparticle and Ag/CeO2 nanocomposite through various XRD models: Rapid ultrasound-assisted synthesis and photocatalytic applications

A prioritization framework for large-scale cancer screening under resource constraints: three ‘not all’ principles

Water‐Triggered Structural Transformation in a Silver Chalcogenolate Cluster‐Based MOF (SCC‐MOF) Enables Visually Readable Trace Water Sensing

ABSTRACT Monitoring trace water is vital for chemical processes and moisture‐sensitive materials, but conventional electrical humidity sensors require complex instrumentation and lack intuitive visual readout. Luminescent metal‐organic frameworks (MOFs) offer optically driven water sensing; however, most existing systems still rely on traditional node‐linker structures, whereas cluster‐assembled frameworks may have potential due to their multisite existence and remain largely unexplored. Here, we introduce a silver chalcogenolate cluster‐based framework (SCC‐MOF), Ag 12 ‐TCNB 3D‐3D ( TCNB, 1,2,4,5‐tetracyanobenzene ) that exhibits a striking orange‐to‐yellow luminescence transition upon water exposure, enabling rapid, naked‐eye detection within relative humidity (RH) &lt;1.26%. The atomically precise Ag 12 cluster node ( Ag 12 ‐TCNB 0D ), bridged by the electron‐deficient TCNB linker, forms a 2D network that achieve coordination with water molecules ( Ag 12 ‐TCNB 2D‐H 2 O ). Single‐crystal X‐ray diffraction (SCXRD) and powder X‐ray diffraction (PXRD) reveal that water induces lattice displacement and perturbs the cluster‐centered excited states, a conclusion further supported by electronic structure calculations. This work establishes cluster‐based MOFs as a promising platform for optically readable water‐vapor sensing.

Cardiometabolic multimorbidity prevalence and its socio-demographic determinants among Iranian adults: insights from the nationwide STEPS 2021

Abstract Cardiometabolic multimorbidity—typically defined as the presence of two or more cardiometabolic morbidities simultaneously—has emerged as a critical public health challenge both globally and in Iran. We analyzed data from the 2021 WHO STEPwise approach to NCD risk factor surveillance (STEPS) to determine its national prevalence and associated socio-demographic factors. Cardiometabolic multimorbidity was defined as having ≥ 2 of: hypertension (HTN), type 2 diabetes (T2DM), or history of MI/stroke. Multivariable stepwise logistic regression was employed to identify the potential socio-demographic associated factors. Of total 16,453 participants aged 25–75 years (75.43% from urban areas, 54.67% women), 58.01% (confidence interval (CI): 56.92–59.09) had no morbidity, 27.56% (26.59–28.55) had only one morbidity (HTN: 19.78%, T2DM: 6.02%, MI/Stroke: 1.76%), 11.73% (11.07–12.45) had two morbidities, and 2.68% (2.31–3.11) had all three morbidities. In total, the prevalence of cardiometabolic multimorbidity was 14.43% (13.67–15.22); and while being employed, wealthy, and having high educational level were negatively associated with the prevalent cardiometabolic multimorbidity, aging, urban residency, physical inactivity, central and general obesity, positive family history of MI/Stroke, positive family history of diabetes, and history of COVID-19 hospitalization had positive associations (all p-values &lt; 0.05). Moreover, sex-stratified analyses showed similar results. As a limitation, history of MI/stroke was based on self-reported data. In conclusion, 14.43% of Iranian adults experience cardiometabolic multimorbidity with comparable prevalence between men and women, posing a considerable burden on public health and underscoring the necessity for pragmatic and multicomponent preventive strategies in both sexes.

Genome-wide CRISPR interference screen identifies Clip2 as a novel regulator of osteocyte maturation and morphology

Outcomes of combined HCC-cholangiocarcinoma with adjuvant chemotherapy: An NCDB cohort.

4166 Background: Combined (or mixed) hepatocellular carcinoma-cholangiocarcinomas (cHCC-CCA) are rare liver tumors that are associated with poor prognosis. Patients (pts) presenting with limited disease are candidates for curative intent surgery. However, the role of adjuvant chemotherapy is not established. Methods: This retrospective review was based on the National Cancer Data Base (NCDB) participant user file (PUF) from 2014 to 2022. Patients were identified using International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) topography (C22.0–22.1) and histology code 8180 for cHCC-CCA. Adjuvant chemotherapy was defined as chemotherapy administered on or after 6 weeks from surgery. Patients who had neoadjuvant chemo were excluded. Analytical stage variable captures data from pathological stage, and if pathological stage is missing, then clinical stage is captured. Pathological stage data were available only for 13% of pts. Hence, analytical stage was used with about 31% data available. Frequency and proportions were reported for categorical variables. Median overall survival (mOS) and corresponding 95% confidence intervals were reported using Kaplan-Meier (KM) estimates. Cox’s proportional hazard model was used to report the adjusted and unadjusted analysis of OS. Hazard ratio (HR) and 95% confidence intervals were reported. All statistical analysis were performed using SAS version 9.4 software. Analysis of the NCDB PUF is exempt from IRB review. Results: 2815 pts with cHCC-CCA were identified, of which 2174 pts data were used for final analysis. 394 (18.1%) pts received adjuvant chemotherapy and 1780 (81.9%) did not receive any chemotherapy. 90% were above age 50 years; 76.2% were Caucasians and 67.7% were Male. Of those who received adjuvant chemotherapy, 162 (41.1%) received chemotherapy as single agent and 203 (51.5%) received chemotherapy as multiple agents. Among 668 data on analytic stage, 28.3% were stage 1, 36.8% were stage 2, 20.9% were stage 3 and 14.1% were stage 4. LVI data was also available for 549 patients. Of these, 38.1% had LVI present. Adjuvant chemotherapy was associated with improved OS compared to no chemotherapy (HR = 0.87 (95% CI: 0.77 – 0.99) p = 0.0296) in the entire population. Adjusted OS analysis for adjuvant chemotherapy with analytical stage showed significant survival benefit with adjuvant chemotherapy (HR = 0.73 (9%% CI: 0.56 – 0.96), p = 0.0261). Further adjustment for LVI was not performed due to large missing data. Conclusions: Adjuvant chemotherapy is not currently a standard for pts with cHCC-CCA after curative intent surgery. However, it appears to be associated with improved survival. Prospective studies evaluating the role of adjuvant therapy in this pt population are needed.

Global cancer mortality attributable to armed conflict: A GBD 1990–2021 analysis.

e23239 Background: Armed conflict disrupts cancer prevention, diagnosis, and treatment continuity, yet its contribution to global cancer mortality has not been systematically quantified using standardized population-level data. We leveraged Global Burden of Disease (GBD) estimates to evaluate the association between armed conflict exposure and cancer mortality across countries and over time. Methods: We conducted a longitudinal, country-level analysis using GBD 2021 estimates (1990–2021) for all-cancer mortality, age-standardized cancer death rates, years of life lost (YLLs), and disability-adjusted life years (DALYs). Armed conflict exposure was operationalized using GBD estimates for mortality due to conflict and terrorism, treated as a time-varying proxy for conflict intensity. Countries were categorized annually into conflict-intensity strata (none, low, moderate, high) based on conflict-related death rates. We assessed associations between conflict intensity and cancer outcomes using mixed-effects regression models with country-level random intercepts, adjusting for calendar year and sociodemographic index (SDI). Excess cancer mortality attributable to conflict was estimated by comparing observed cancer mortality in conflict-exposed country-years with model-predicted counterfactual mortality under a no-conflict reference stratum. Results: Across the 1990–2021 study period, increasing conflict intensity was consistently associated with higher age-standardized cancer death rates and greater cancer-related YLLs. The association demonstrated a dose–response pattern, with the largest excess cancer mortality observed in high-intensity conflict settings and in lower-SDI regions. Temporal analyses showed that sustained conflict exposure was associated with persistently elevated cancer mortality burden compared with non-conflict periods. Patterns were broadly consistent across sexes and major world regions. Conclusions: Using standardized GBD estimates, armed conflict intensity is associated with excess cancer mortality and premature cancer death at the population level. These findings support conceptualizing armed conflict as a structural determinant of cancer outcomes and underscore the need for resilient oncology care delivery, continuity-of-treatment strategies, and targeted cancer control interventions in conflict-affected settings.

A large prospective patient-advocacy assessment of fears, concerns, and challenges in patients diagnosed with lung cancer in the United States.

8073 Background: Studies have been conducted assessing patient (pt) experiences with lung cancer, but minimal data is available on how fears and challenges differ by age, region, and disease stage. Through a pt advocacy organization, we performed a prospective analysis to capture pt and caregiver perceptions. Methods: 2055 surveys were sent out by non-profit organizations to US pts diagnosed with lung cancer and caregivers. 46% of the surveys (n = 956) were returned. Respondents included 63% (N = 603) pts (included in this abstract), 35.5% caregivers, and 1.5% medical professionals. Demographics included: ethnicity, time from diagnosis, gender, stage, region of country, age, role, and current disease status. Of 36 survey questions, 27 were multiple choice, 9 were open-ended and analyzed for recurring themes. Results were analyzed by region, stage, and age to determine if these influenced perspectives about living with lung cancer, and challenges with medical care or treatment. Chi-square test was used to assess differences in responses to survey questions across participant groups. Additional analysis was conducted using Fisher's exact test. Responses to each survey question were categorized, and the proportions of the topics were compared between participant groups. Results: Overall challenges reported by pts varied significantly by disease stage—both at the time of diagnosis (p &lt; 0.001) and during treatment (p &lt; 0.001). The fear cited most was disease progression or recurrence, in stage I (25.8%) or stage IV (27%) disease. Significant differences were observed across age groups relating to challenges with medical care or treatment (p &lt; 0.001), and fears of living with lung cancer. (p &lt; 0.001). Pts older than 45 were more concerned with side effects at diagnosis than younger than 45 (55.1% vs 33%, p &lt; 0.0001) and were less concerned with financial issues (25.7% vs 44.7%, p &lt; 0.0001) at treatment. Care costs and transportation challenges varied regionally, peaking in the Midwest (60.4%) and Southwest (56.5%). Conclusions: Fears, concerns and challenges faced by pts with lung cancer vary significantly by age, disease stage at diagnosis, and during treatment. The findings reveal an opportunity to deliver better support to pts throughout their journey and to allocate resources to address specific concerns. Survey Question Topic Age: &lt;/= 44 (N=219)* Age: &gt;/= 45 (N=321)* Fisher’s Exact Test Fears Progression &amp; Recurrence 10% (21) 29% (94) p &lt; 0.0001 " Emotional &amp; Psychological 18% (40) 10% (33) p &lt; 0.01 " Inadequate Information 5% (11) 10% (33) p &lt; 0.05 Challenges at Diagnosis Varied opinions 34% (75) 20% (63) p &lt; 0.001 " Financial 40% (88) 24% (78) p &lt; 0.0001 " Depression 32% (70) 53% (169) p &lt; 0.0001 Challenges at Treatment Side Effects 33% (73) 55% (177) p &lt; 0.0001 " Varied opinions 28% (62) 12% (39) p &lt; 0.0001 " Financial 45% (98) 26% (82) p &lt; 0.0001 *63 patients did not respond to the question on age.