Growing evidence suggests that gut microbial features may predict-and potentially modulate-responses to cancer therapy, particularly immunotherapy. However, the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota remains less well-understood. This knowledge gap is especially relevant in locally advanced non-small-cell lung cancer (NSCLC), where CRT typically precedes immunotherapy. We therefore investigated whether CRT alters gut microbial composition and whether such changes are associated with survival outcomes. Fecal samples were collected at three time points: prior to CRT (baseline), at completion of CRT, and immediately before initiation of consolidation immunotherapy, from 62 patients with locally advanced NSCLC. Microbiota profiling was performed using a qPCR-based panel (PMP™) targeting 108 prevalent microbial taxa. Within-sample (alpha) and between-sample (beta) bacterial diversity were assessed across time points and clinical subgroups defined by antibiotic exposure and survival outcomes. Alpha diversity remained stable from baseline to completion of CRT (all P > 0.60). Patients who received broad-spectrum antibiotics during CRT had significantly lower alpha diversity compared with those who did not receive antibiotics (P = 0.017), reflecting a transient between-group difference. Beta diversity differed modestly but significantly at baseline between survival groups (progression-free survival ≥ 18 vs < 18 months; PERMANOVA R2 = 0.028, P = 0.045). The gut microbiota appears largely stable during CRT for locally advanced NSCLC but is susceptible to disruption by antibiotic use. Baseline beta diversity differences between survival groups may signal a potential role for gut microbial composition as a future preliminary biomarker and warrant further investigation.

PURPOSE Survival discrepancy between male and female patients in lung cancer is a well-known, but still poorly understood phenomenon. Previous studies have used different patient cohorts and clinical covariates and have not included obesity, which is associated with longer lung cancer survival. We evaluated the relationship between survival, obesity, sex and other covariates using comprehensive, harmonized patient cohorts and a federated analysis approach. MATERIALS AND METHODS Initial analyses were done in a retrospective, real-world cohort of 7,327 patients with lung cancer diagnosed at the Helsinki University Hospital from 2015 to 2024. Patients were stratified by BMI, and univariate and multivariate analyses of survival were performed. External validation of univariate analyses was performed on data from four European university hospitals (n = 12,700). RESULTS Higher BMI was associated with a smaller sex-related survival difference. In the normal BMI cohort (18.5-25 kg/m(2)), the 2-year overall survival was 46% in females and 29% in males (P < .01). In the high BMI cohort, the difference was 51% versus 41% (P < .01). Similar trends were observed in the validation sites, with some variation. The largest effect of high BMI was observed in squamous cell carcinoma. When full multivariate analysis was performed separately for high and normal BMI patients, the effect of male sex on survival was 32% smaller among high BMI patients. CONCLUSION Higher BMI was associated with reduced survival gap between sexes, emphasizing the value of comprehensive covariate reporting in future clinical trials and observational studies.

Importance:Artificial intelligence (AI) models are emerging as rapid, low-cost tools for predicting targetable genomic alterations directly from routine pathology slides. Although these approaches could accelerate treatment decisions in lung cancer, little is known about whether their performance is consistent across diverse patient populations and tissue contexts. Objective:To evaluate the performance and generalizability of 2 open-source AI pathology models for predicting EGFR mutation status in lung adenocarcinoma (LUAD) across independent cohorts and ancestral subgroups. Design, Setting, and Participants:This cohort study included patients with LUAD from 2 cohorts: Dana-Farber Cancer Institute (DFCI) from June 2013 to November 2023, and a European-based trial (TNM-I) from August 2016 to February 2022. All patients had paired next-generation sequencing data and hematoxylin-eosin-stained whole-slide images. In the DFCI cohort, genetic ancestry was inferred using germline genotype data. Data analyses were performed from July 2025 to September 2025. Main Outcomes:The primary outcome was model performance for predicting EGFR mutation status, measured as the area under the receiver operating characteristic curve (AUC), evaluated overall and across ancestry subgroups and sample types. Results:Overall, 2098 patients with LUAD were included (mean [SD] age, 66.6 [10.3] years; 1315 female individuals [63%] and 783 male individuals [37%]). In the DFCI cohort (n = 1759; 54 African, 101 American, 95 Asian, 1465 European), EGFR mutations were detected in 432 patients (25%). One AI-pathology model achieved an AUC of 0.83 (95% CI, 0.81-0.85) compared with 0.68 (95% CI, 0.65-0.70) for the other model. In the TNM-I cohort (n = 339), EGFR mutations were detected in 50 patients (15%), with AUCs of 0.81 (95% CI, 0.74-0.88) and 0.75 (95% CI, 0.68-0.83), respectively. In ancestry-stratified analyses of the DFCI cohort, AUCs for the higher-performing model were 0.84 (95% CI, 0.81-0.86) in patients of European ancestry, 0.85 (95% CI, 0.72-0.94) in African ancestry, and 0.68 (95% CI, 0.55-0.78) in Asian ancestry. In sample type analyses, performance declined in pleural (AUC, 0.66; 95% CI, 0.56-0.76) compared with lung specimens (AUC, 0.86; 95% CI, 0.83-0.88). AI-guided triage analyses showed a potential 57% reduction in rapid EGFR testing, while maintaining sensitivity of 0.84 and specificity of 0.99. Conclusions:This cohort study found that AI-based pathology tools may serve as preliminary adjuncts for EGFR prediction in lung cancer, though performance differences by ancestry warrant careful interpretation.

The MAPRE3 gene is aberrantly expressed in several cancers. We profiled DNA methylation in tumor tissues from early‐stage non‐small cell lung cancer (NSCLC) patients and assessed associations with overall survival (OS). Significant CpG probes were validated in The Cancer Genome Atlas (TCGA). The methylation level of cg12821679 MAPRE3 showed significant associations with OS in lung squamous cell carcinoma (LUSC) (HR = 0.32, P = 6.55 × 10 −7 ), but it was not observed in lung adenocarcinoma (LUAD). In LUSC, MAPRE3 expression was significantly correlated with cg12821679 MAPRE3 ( r = 0.17, P = 2.96 × 10 −3 ) and potential trans ‐regulated genes were enriched in the Nicotine addiction pathway. Additionally, MAPRE3 expression showed significant associations with OS in both LUAD and LUSC (LUAD: HR low vs high = 2.28, P = 2.40 × 10 −3 ; LUSC: HR low vs high = 1.61, P = 0.0244). The association between smoking cessation and overall survival was significantly modified by MAPRE3 expression (HR interaction = 0.69, P = 0.0282). Smoking cessation improved OS only in patients with high MAPRE3 expression (HR = 0.56, P = 2.82 × 10 −3 ). We conclude MAPRE3 may predict NSCLC prognosis and influence the prognostic benefit of smoking cessation.

1553 Background: Despite rapid global adoption of immune checkpoint inhibitors (ICI) for metastatic non–small cell lung cancer (mNSCLC), real-world treatment access, selection, time on treatment and transitions between regimens remain poorly characterized across health systems and patient populations. Whether observed outcomes are consistent across regions, data sources, and age groups is largely unknown. Addressing these gaps at scale requires a federated analytic approach with standardized analyses across sites, enabling reliable and comparable results while preserving patient privacy. Methods: We launched FALCON (Federated Alliance for Large-scale Cancer Observational Network), the largest federated, most diverse oncology network supporting observational cancer research, and its subnetwork FALCON-Lung. FALCON-Lung includes 23 sites (hospitals, registries, public-private) providing longitudinal cancer data from 2015 onwards standardized to OMOP common data model, from 11 countries in Europe, US and Australia. All sites completed data quality assessments and targeted improvements to improve completeness and overall cancer data quality. Analyses were executed locally using shared analytic code without sharing patient-level data. Results: Among 111,574 NSCLC pts included, 62% developed metastatic disease, of whom 59% initiated antineoplastic drugs within three months; 88% received a guideline-recommended 1 st line regimen. ICI uptake rose sharply between 2017 - 2019; by 2022 59% received ICI (± platinum) in 1 st line. ICI monotherapy showed a tendency toward longer overall survival (OS) compared with platinum (±ICI), although no single regimen demonstrated a consistent advantage across all databases. OS decreased with age across sites. Patients aged ≥81 years were less likely to receive systemic therapy and, when treated, more often received ICI monotherapy. No clear or consistent differences in OS were observed between different treatment regimens in this age group. Conclusions: In this global federated study, ICI uptake showed consistent patterns across sites and regions. OS varied across sites and no consistent survival advantage was observed for ICI regimens, either as monotherapy or in combination, although higher OS with ICI monotherapy was observed in some settings. Older patients (aged ≥81 years) were more frequently treated with ICI monotherapy without a corresponding survival advantage, possibly reflecting real-world treatment selection driven by tolerability rather than biomarkers. Total 18-64y 65-81y ≥81y NSCLC 111,574 36,239 62,328 13,007 Metastatic NSCLC 68,678 24,059 36,397 8,222 1st line systemic therapy 40,619 15,226 21,397 3,980 1st line guideline-approved systemic therapy 35,560 13,458 18,725 3,361 1st line in 2022 (%) ICI monotherapy 17 12 18 32 ICI + platinum doublet 42 43 45 26 Other guideline-approved regimen 41 45 37 43

e12572 Background: Currently, a variety of commercial molecular tests, including MammaPrint, Oncotype DX, and Prosigna, are used to guide adjuvant therapy decisions for early-stage breast cancer patients with hormone receptor-positive/HER2-negative phenotypes. Despite their effectiveness, these tests present challenges in terms of complexity, turnaround time, and cost, motivating the development of AI-based digital pathology tools as alternative prognostic methods. Methods: We benchmarked two self-supervised histology foundation models (UNI-v1 and Prov-GigaPath) for prediction of Prosigna-derived recurrence risk (ROR-PT) from paired H&E whole-slide images. Training and testing were performed using more than 7 million image tiles (224 × 224 pixels) derived from 534 breast cancer patients collected at the University Hospital of North Norway. Both models were fine-tuned using end-to-end task adaptation with slide-level supervision to classify patients into high-risk versus intermediate/low-risk groups. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and standard classification metrics. Results: In the overall cohort, molecular subtypes were distributed as follows: luminal A 65% (n = 347), luminal B 32% (n = 173), basal 2% (n = 8), and HER2-enriched 1% (n = 6). The Prosigna ROR-PT scores were dichotomized into low-risk and high-risk groups, comprising 427 (80%) and 107 (20%) patients, respectively. In the hold-out test set (n = 107, 20%), the UNI and Prov-GigaPath models achieved sensitivities of 0.82 and 0.73, specificities of 0.70 and 0.78, and AUCs of 0.79 and 0.81, respectively. While Prov-GigaPath demonstrated slightly higher precision (PPV), the UNI model showed higher sensitivity, suggesting a broader identification of high-risk patients (Table). In addition, model ensembling did not show performance gains over the best unimodal model. Furthermore, a strong correlation (Pearson’s r = 0.65, p < 0.001) was observed between the predictions of both foundation models and the continuous Prosigna ROR scores. Conclusions: The findings of this initial study demonstrate that AI-driven analysis of routine H&E images represents a promising, cost-effective, and rapid surrogate to Prosigna for prediction of recurrence risk in breast cancer. These results will be further validated in independent external cohorts. Model AUC (CI, 95%) Sensitivity Specificity PPV NPV UNI 0.79 (0.65-0.89) 0.82 0.70 0.42 0.94 Prov-GigaPath 0.81 (0.76-0.96) 0.73 0.78 0.46 0.92

INTRODUCTION:The benefit of durvalumab after chemoradiotherapy (CRT) varies widely in unresectable stage III NSCLC. Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) detection may help identify patients at high risk of early treatment failure during and after durvalumab. METHODS:In this prospective multicenter study, patients with unresectable stage III NSCLC received CRT followed by durvalumab. Plasma samples were collected at screening, after CRT, at predefined time points during durvalumab, and during post-treatment follow-up. A tumor-agnostic, hybrid-capture ctDNA MRD assay personalized to each patient classified samples as ctDNA detected (MRD positive) or not detected (MRD negative). RESULTS:A total of 659 plasma samples from 84 patients were analyzed. Detectable ctDNA before the seventh cycle of durvalumab (after 6 mo of treatment) and 3 months after treatment completion was strongly associated with inferior progression-free survival (PFS) (hazard ratio [HR]: 2.45, 95% confidence interval [CI]: 1.18-5.11, p = 0.013 and HR: 5.37, 95% CI: 1.93-14.93, p < 0.001, respectively). Detection of ctDNA after CRT but before durvalumab initiation was not prognostic (HR: 1.38, 95% CI: 0.78-2.41, p = 0.269). In a multivariable time-dependent Cox model incorporating all post-CRT samples, detectable ctDNA was associated with a nearly threefold higher risk of progression (HR: 2.95, 95% CI: 1.69-5.15, p < 0.001). CONCLUSIONS:Detectable ctDNA during and after durvalumab was associated with markedly shorter PFS in unresectable stage III NSCLC. Serial ctDNA-based MRD assessment may help identify patients at high risk of relapse who could benefit from alternative or intensified treatment strategies, ideally within prospective clinical trials. CLINICALTRIALS: GOV IDENTIFIER:NCT04392505.

149 Background: YOCRC, defined as CRC diagnosis before age 50, is rising globally. Driving causes remain incompletely understood. We report interim results from IMPRESS-Norway, focusing on genomic profiles, drug matching rates, and outcomes in YOCRC vs average-onset CRC. Methods: IMPRESS-Norway (NCT04817956) is a prospective, non-randomized, nationwide precision oncology trial. Patients with advanced, inoperable cancers undergo gene panel sequencing (TruSight Oncology 500). Those with actionable alterations are offered matched therapies available within the trial. Primary endpoints include the proportion of screened patients receiving on-trial treatment and disease control rate at 16 weeks. This interim analysis includes all CRC patients enrolled from September 2021 to August 2025. Results: Among 465 CRC patients profiled, median age was 58 years (range, 27-82), 183 (39%) were females, and 218 (47%) had RAS/RAF alterations. Owing to trial priority for young patients, 118 (25%) were YOCRC, among whom 50 (42%) women. Median YOCRC age was 43 years. The age, tumor mutational burden (median 8), and RAS/RAF alteration rates (52%) were comparable between men and women. Of the 118 YOCRC cases, one was microsatellite instable and one had POLE V411L mutation. Ten cases (8%) had mutations that met the criteria for targeted therapies in the IMPRESS-Norway trial, significantly lower than the trial overall average of 16%. Six patients initiated targeted treatment, which included MEK inhibitor for NRAS Q61 alterations (3 patients), immunotherapy (2 patients), and PIK3CA inhibitor (1 patient). Of these, 3 patients achieved stable disease as the best overall response, while another 3 experienced immediate progression. Among the 347 average-onset CRC patients (50 years or older), 52 (15%) possessed actionable biomarkers eligible for the IMPRESS-Norway trial. Of these, 22 began treatment with responses categorized as partial response (3 patients), stable disease (8 patients), or progressive disease (8 patients). Two patients exited the study prior to the first response assessment, while one commenced treatment only recently. Conclusions: The IMPRESS-Norway trial has included a significant number of YOCRC patients, yet these individuals possess fewer actionable biomarkers for targeted therapies compared to the average-onset CRC population. Further research is essential to broaden the treatment options available for YOCRC patients. Clinical trial information: NCT04817956 .

Background: Impaired pulmonary function is common among patients with lung cancer and may negatively affect health-related quality of life (HRQoL). The primary objective of the present sub-study of the DART-trial was to assess the overall quality of life changes during treatment and stratified by the presence of Chronic Obstructive Pulmonary Disease (COPD). Methods: The investigator-initiated DART trial (NCT04392505) included patients with unresectable stage III non-small cell lung cancer (NSCLC) treated with chemoradiotherapy followed by durvalumab. Baseline pulmonary function was measured by spirometry, and patients were stratified by FEV1/FVC <70% (COPD) or ≥70% (non-COPD). HRQoL was assessed regularly using the EORTC QLQ-C30 and QLQ-LC13 questionnaires at screening and during treatment. A difference in mean score of ≥10 was defined as clinically significant. Results: A total of 86 patients initiated durvalumab and completed at least one HRQoL assessment; pulmonary function data were available for 64 patients. For the overall cohort, quality of life scores remained stable throughout treatment. Patients with COPD consistently reported lower global health scores than those with preserved lung function. The global health score among patients with COPD was not significantly different at end of treatment compared to baseline, however significantly lower than patients without COPD. Symptom trajectories across QLQ-C30 scales were stable in both groups. Dyspnoea was more prevalent among patients with COPD. In the LC13 module, no clinically significant differences were observed except for dyspnoea, which was consistently higher among patients with COPD. Interpretation: The HRQoL remained stable during chemoradiotherapy and durvalumab treatment in stage III NSCLC patients. Impaired lung function was associated with modestly lower HRQoL, though larger studies are needed to confirm subgroup effects.

[18F]FDG PET/CT provides a non-invasive assessment of tumour glucose metabolism. While conventional PET/CT captures a single time point, dual-time-point PET/CT (DTP-PET) evaluates metabolic dynamics by acquiring images at two defined times after injection. This study investigated whether the change in [18F]FDG uptake between 60 and 120 min—retention index (RI)—predicts clinical outcomes in patients with pleural mesothelioma (PM) receiving immunotherapy. Patients from the NIPU trial (NCT04300244) underwent DTP-PET at baseline (n = 50) and/or week-5 (n = 45), with 42 completing both. Peak SUV was measured in a 2-cm spherical volume of interest centred on the most avid lesion at 60 and 120 min, and RI was calculated as the percentage change between the two. Survival (OS, PFS) was analysed using Kaplan–Meier curves and Cox proportional hazards models based on tertiles of RI and SUV60min. Objective response and disease control were defined by mRECIST and iRECIST. Group comparisons used the Wilcoxon rank-sum test. At week-5, RI tertiles showed stepwise separation for both OS (p = 0.038) and PFS (p = 0.031), with the lowest tertile associated with the most favourable outcomes. SUV60min tertiles were also significantly associated with OS (p = 0.042) and PFS (p = 0.043), though OS exhibited a non-monotonic pattern in which the middle tertile had the poorest survival. Objective responders displayed significantly lower RI and SUV60min at week-5. Baseline RI tertiles were not associated with OS or PFS. Week-5 [18F]FDG DTP-PET suggests prognostic value in PM patients receiving immunotherapy. Both RI and SUV60min were associated with objective response. RI showed a consistent stepwise association with survival, whereas SUV60min showed a non-monotonic relationship for OS. These findings are exploratory and require validation in larger cohorts. Further studies are warranted to explore underlying biological mechanisms. ClinicalTrials.gov NCT04300244. Registered 2020-03-09. https://clinicaltrials.gov/study/NCT04300244

11086 Background: Precision Cancer Medicine (PCM) is limited by increasingly small patient subgroups defined by tumor type and biomarker, producing rare cohorts even within common cancers. This is demonstrated by several European national PCM platform trials like DRUP (NL), IMPRESS-Norway (NO) and ProTarget (DK). From our experiences, we identify four essential requirements for successful, scalable PCM implementation: i) integration of platform trials with national healthcare systems via molecular tumor boards for efficient screening by comprehensive molecular profiling and accrual; ii) cross-national data merging; iii) scalable networks to onboard new countries; and iv) clear decision pathways linked to outcome data for reimbursement. Methods: PRIME-ROSE links national PCM implementation platforms through a robust data sharing framework that retains national/regional data governance while enabling harmonised statistical analyses and standardised endpoints for decision-makers. Predictable implementation pathways provide multiple, pre-defined decision points for industry, health technology assessment (HTA) bodies and payers, and integrate risk-sharing and responder-only reimbursement options with existing data collection. A scalable, transparent network facilitates rapid expansion to additional European partners. Results: We have developed and tested an operational data-sharing framework, with defined protocols for minimal datasets and harmonised merging procedures. Patient-level data from multiple national cohorts (1100 patients in 400 cohorts) have been aggregated, and analyses of five filled cohorts are in progress. PRIME-ROSE uses a staged implementation model to detect initial efficacy signals (industry-financed drugs) to confirm and expand on prior evidence, facilitating predictable scale-up. Risk-sharing is operationalised via responder-only reimbursement after 16 weeks of treatment and a defined transition from trial to commercial supply. In 2025, PRIME-ROSE expanded partnerships, secured the first and second multi-trial industry access contracts, and expanded payer commitment to make reimbursement decisions after Stage III. Conclusions: PRIME-ROSE translates lessons from platform trials into a practical, scalable blueprint that preserves national governance, accelerates evidence generation and reduces payer uncertainty – thereby lowering barriers to equitable, continent-wide PCM adoption. Aligned with initiatives such as Basket of Baskets and ROME, PRIME-ROSE is positioned for further scale-up through member state collaboration under the Joint Action on Personalised Cancer Medicine.

BACKGROUND:Real-world data (RWD) are increasingly recognized as essential for understanding patient populations underrepresented in clinical trials and for supporting data-driven learning in healthcare. For smaller subgroups, the value of RWD depends on standardization and interoperability that enable meaningful reuse across institutions. This study examines how clinicians perceive the reuse and standardization of RWD within a federated Learning Health System (LHS), with emphasis on data quality, clinical relevance, and implications for continuous learning. METHODS:A qualitative case study was conducted at Oslo University Hospital, informed by Learning Health System theory. Ten oncologists representing seven cancer subspecialties participated in focused, semi structured interviews. Data were analyzed using the stepwise deductive inductive (SDI) method to support empirically grounded conceptual development. The study was situated in the hospital's implementation of the OMOP Common Data Model (CDM) for oncology data. RESULTS:Clinicians highlighted the value of RWD for capturing patient groups often excluded from clinical trials. They described substantial variation in documentation practices, noting that clinically relevant information is frequently unstructured or inconsistently recorded. Time constraints and uncertainty about documentation requirements were identified as barriers to data quality. When reviewing data transformed into the OMOP CDM, participants generally found the mappings accurate but expressed concerns about loss of nuance and semantic drift. Across interviews, there was strong support for involving domain experts in validation and for using standardized data to enable collaboration and learning across institutions. CONCLUSIONS:RWD can strengthen oncology practice by supporting insights into diverse patient populations and enabling continuous learning. Standardization through models such as OMOP CDM facilitates reuse and cross institutional collaboration, but success depends on structured documentation, semantic fidelity, clinician engagement, and robust technical infrastructure. These findings underscore the sociotechnical conditions required to realize the potential of RWD within emerging frameworks such as the European Health Data Space.

Background and purpose: Molecular profiling guides cancer treatment, by identifying actionable genomic alterations. The IMPRESS-Norway trial (NCT04817956) is a nation-wide precision medicine trial evaluating the efficacy of approved cancer drugs on a novel indication in patients with advanced cancers harbouring potentially actionable alterations. Trametinib, a selective MEK1/2 inhibitor targeting the Mitogen-Activated Protein Kinase (MAPK) signalling pathway, is approved for BRAF V600 mutant melanoma but may also show activity in tumours with other alterations. This sub-study aimed to assess the efficacy of trametinib monotherapy across tumour types with alterations activating the MAPK signalling pathway. Patient/material and methods: In the IMPRESS-Norway trial patients are screened with the TruSight Oncology 500 panel or circulating tumour DNA profiling. Eligible patients are offered biomarker matched targeted therapies. In this subgroup analysis, we identified patients treated with trametinib monotherapy. Primary endpoints were disease control rate (DCR) after 16 weeks and safety. Secondary endpoints included progression-free survival (PFS) and overall survival (OS). Results: DCR after 16 weeks of treatment was 39% in 52 response evaluable patients, with four patients (8%) experiencing partial response, and 16 (31%) stable disease. Responses were seen in tumours harbouring BRAF fusions, GNA11, GNAQ, KRAS, NF1, and NRAS alterations, most frequently in low-grade serous ovarian cancer, central nervous system tumours, and uveal melanoma. Forty-eight percent of patients experienced treatment-related adverse events, including two treatment related deaths. Median PFS and OS were 4 and 9 months, respectively. Interpretation: Trametinib monotherapy achieved a 39% DCR in patients lacking standard options, supporting further studies to confirm efficacy and identify predictive biomarkers for treatment response.

Treatment of B-cell malignancies with the PI3K inhibitor (PI3Ki) idelalisib often results in high toxicity and resistance, with limited treatment alternatives for relapsed/refractory patients since idelalisib is recommended as a later or last line therapy. To investigate resistance mechanisms and identify alternative treatments, we studied functional phenotypes of idelalisib-resistant B-cell malignancy models. The idelalisib-resistant KARPAS1718 model remained sensitive to Bcl-2 inhibitors (Bcl-2i), whereas the resistant VL51 model showed reduced sensitivity compared to parental cells. Sensitivity correlated with phosphorylation and expression of the Bcl-2 family members Bcl-2 and Bim. Target addiction scoring revealed high dependence on the proteasome, and proteasome inhibitors (PI) were effective across models and in primary chronic lymphocytic leukemia (CLL) cells, independently of their PI3Ki- or Bcl-2i-sensitivities. PI treatment consistently upregulated Bim and Mcl-1, while Bcl-2 increased in KARPAS1718 and CLL cells. Bcl-2i plus PI combinations led to an additive effect in these models. A multi-refractory CLL patient in the IMPRESS-Norway trial (NCT04817956) treated with Bcl-2i plus PI showed initial clinical improvement but relapsed within four months. Treatment induced Bim and Mcl-1 upregulation and reduced cytotoxic CD8+ T-cell and CD56dim NK-cell populations. Our findings suggest that PIs may overcome resistance to targeted therapies, and warrant further studies to optimize clinical responses.

Introduction:Chemoradiotherapy followed by durvalumab is a potentially curative treatment for unresectable, locally advanced non-small cell lung cancer (NSCLC), but clinical outcomes remain highly variable. Identifying robust biomarkers is essential to refine treatment selection and enable risk-adapted strategies. Methods:In this multicenter, prospective cohort study, 86 patients with unresectable stage III NSCLC were treated with chemoradiotherapy followed by durvalumab. Baseline plasma samples underwent genomic profiling and blood tumor mutational burden (bTMB) assessment using targeted next-generation sequencing. Associations between bTMB, circulating tumor DNA (ctDNA) alterations, PD-L1 expression, and progression-free survival (PFS) were evaluated using a one-sided significance threshold of p < 0.10. Results:Median PFS was 18.9 months (95% CI: 14.7-not reached), and median bTMB was 6.6 mutations/megabase. In univariable analysis, high bTMB was associated with longer PFS using both the prespecified 8.5 mut/Mb cut-off (HR: 0.65; p = 0.088) and the median 6.6 mut/Mb cut-off (HR: 0.52; p = 0.016). PD-L1 ≥ 1% was associated with longer PFS (HR: 0.38; p = 0.0003), while STK11, KEAP1, or NFE2L2 mutations in ctDNA were linked to shorter PFS (HR: 1.84; p = 0.040). In multivariable analysis, PD-L1 remained significantly associated with PFS in both models, while bTMB and STK11/KEAP1/NFE2L2 mutations were significant using the 6.6 mut/Mb cut-off. Conclusion:High bTMB, PD-L1 expression ≥ 1%, and absence of STK11/KEAP1/NFE2L2 mutations were associated with longer PFS. These findings support integrating multiple biomarkers to improve risk stratification and personalize treatment in unresectable stage III NSCLC. Clinical Trial Registration:The study is registered on www.clinicaltrials.gov (ClinicalTrials.gov identifier: NCT04392505).

BACKGROUND:The use of systemic anti-cancer treatment (SACT) at the end of life (EOL) is controversial. The evidence and detailed description of the dynamics of its use are deficient, especially after the introduction of targeted therapies and immunotherapy. METHODS:Clinical information about lung cancer patients dying in the years 2020-2023 was extracted from the Cancer Registry of Norway. Available data on intravenous and oral SACT enabled the calculation of the proportion of patients who received SACT each of the 360 days before death. RESULTS:A total of 8953 patients were eligible for this study. At day 30, 7, and 1 before death, 8.9%, 1.3%, and 0.4% respectively, received SACT. The reduction was mainly caused by reduced use of chemotherapy and immunotherapy closer to death. Independent predictors for receiving SACT at day 30 before death were young age, male sex, small-cell lung cancer, short time from diagnosis to death, and good performance status. CONCLUSION:The presented low use of SACT at EOL has been achieved in a population where good survival has been documented. Patients with poor performance status and older age received less SACT than patients with good performance status and younger age.

The DRAGEN pipeline has recently been released for the analysis of whole genome and exome sequencing data (PMID:39455800). However, its performance in detecting clinically relevant alterations for routine diagnostic practice remains unknown. This study includes 108 lung cancer patients consecutively collected from the TNM-I trial (NCT03299478). Tumor-only sequencing of FFPE DNA was performed using the TruSight Oncology 500 (TSO500) panel. Alignment and variant calling were conducted with DRAGEN (TSO500 v2.5.2) and Mutect2-GATK (v2.2), with subsequent annotation and classification using PCGR (v2.1.2) and OncoKB (v3.4.1). In the DRAGEN pipeline output, 4328 exonic and nonsynonymous variants with a variant allele fraction (VAF) >0.01 and a minimum supporting read count of 5 (normalized by depth) were analyzed. Among these, 214 variants met actionability tiers 1-3 (AMP/ASCO/CAP) and oncogenicity score >3 based on ClinGen/CGC/VICC Oncogenicity Guidelines, with the highest calls observed for TP53 (44%, n=48) and KRAS (34%, n=37). DRAGEN and Mutect2 showed 100% concordance in detecting level 1 variants (OncoKB classifications), distributed as follows: KRAS (16 variants), EGFR (2 variants), and BRAF (1 variant). The median VAF difference between the two pipelines was 0.017, indicating strong alignment in allele frequency for high-confidence variants. Additionally, 174 variants (84%) showed a VAF difference within ±3.0%, suggesting minor VAF calculation variability in a subset of cases. Across all matched variants, DRAGEN reported consistently lower read depth values than Mutect2, with a median depth of 275 for DRAGEN versus 375 for Mutect2. DRAGEN also demonstrated a lower standard deviation in read depth (188 vs. 320 for Mutect2), indicating tighter depth distribution. This depth discrepancy was particularly pronounced in variants with a >3% VAF difference, suggesting that depth differences may contribute to VAF variability between the pipelines. No level-2 OncoKB classifications were detected by either pipeline. These findings demonstrate DRAGEN concordance with GATK for detecting clinically significant Tier 1 variants, supporting its reliability in routine diagnostics despite read depth inconsistencies. Future studies should further explore DRAGEN performance in detecting copy number variants and fusion calls. Mehrdad Rakaee, Per Niklas Waaler, Falah Jabar, Krinio Giannikou, Elio Adib, Sigve Andersen, Erna-Elise Paulsen, Thomas K.Kilvaer, Elisabeth Jarhelle, Kristin Åberg, Espen Mikal Robertsen, Ane Yde Schmidt, Christina Westmose Yde, Christian Baudet, Åslaug Helland, Mette Pøhl, Lill-Tove R. Busund, David J. Kwiatkowski, Tom Donnem. DRAGEN pipeline validation for somatic variant detection in diagnostics using TSO500 panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5366.