Åslaug Helland

• Nymoen, Hanne Marte Gjertsen; Zhao, Zhi; Horndalsveen, Henrik; Bjaanæs, Maria Moksnes; Grønberg, Bjørn Henning & Halvorsen, Tarje Onsøien [Show all 20 contributors for this article] (2026). Gut microbiota alterations in patients with non-small-cell lung cancer undergoing chemoradiotherapy. Molecular Oncology. ISSN 1574-7891. doi: 10.1002/1878-0261.70326. Full text in Research Archive Show summary

  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 R 2  = 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.

• Thunold, Solfrid; Hernes, Eivor; Mikalsen, Lars Tore Gyland; Farooqi, Saima; Øjlert, Åsa Kristina & Francis, Roslyn J [Show all 16 contributors for this article] (2026). Dual-time-point [18F]FDG-PET/CT as a prognostic biomarker in patients with pleural mesothelioma undergoing immunotherapy. EJNMMI Research. 16(1). doi: 10.1186/s13550-026-01469-x. Full text in Research Archive
• Berkovska, Olena; Schliemann, Igor; Mermelekas, Georgios; Özkan, Nazlı Ezgi; Nikpour, Mahnaz & Haakensen, Vilde Drageset [Show all 9 contributors for this article] (2026). Mass spectrometry-based proteomics delivers in-depth proteome profiling of FFPE lung cancer biopsies from single glass slides. NPJ precision oncology. 10(1). doi: 10.1038/s41698-026-01517-8. Full text in Research Archive Show summary

  Abstract Clinical proteomics has the potential to add a valuable data layer to genomic and histopathological analyses in precision oncology, but its application to limited clinical material remains challenging. Here, we demonstrate that state-of-the-art mass spectrometry-based proteomics enables in-depth proteomic profiling of formalin-fixed paraffin-embedded (FFPE) clinical samples, including small diagnostic biopsies and single tissue sections mounted on glass slides. Despite minimal input material, single-slide analyses of clinical lung tumor specimens yielded biologically and clinically informative data, supporting detection of actionable proteins, immune-related signatures, and multivariate biomarkers. These results establish the feasibility of proteomics for retrospective FFPE studies and routine clinical practice, expanding opportunities for biomarker discovery and precision medicine from scarce tissue material.

• Horndalsveen, Henrik; Haakensen, Vilde Drageset; Madebo, Tesfaye; Grønberg, Bjørn Henning; Halvorsen, Tarje Onsøien & Bjaanæs, Maria Moksnes [Show all 12 contributors for this article] (2026). ctDNA-Based MRD Detection in Stage III NSCLC Treated With Chemoradiotherapy and Durvalumab. Journal of Thoracic Oncology. ISSN 1556-0864. doi: 10.1016/j.jtho.2026.103992. Full text in Research Archive
• Nakken, Sigve; Edsjö, Anders; Lehtiö, Janne; Nygaard, Vigdis; Roepman, Paul & Rosenquist, Richard [Show all 69 contributors for this article] (2026). Towards an ecosystem of clinical decision support tools for precision cancer medicine. NPJ precision oncology. doi: 10.1038/s41698-026-01551-6. Full text in Research Archive Show summary

  Molecular tumor boards are supported by clinical decision support system (CDSS) tools for the interpretation of complex molecular data towards personalized treatments. Current CDSS tools are genomics-focused and characterized by tight couplings between data ingestion, guideline-based reasoning logic and curated knowledgebases. Next-generation CDSS solutions should integrate multimodal data and learn from outcomes in an interoperable ecosystem, leveraging explainable, trustworthy output from AI models through rigorous clinical validation processes.

• Hektoen, Helga; Tsuruda, Kaitlyn Michiko; Mæhlen, Marthe Thoresen; Helland, Åslaug & Andreassen, Bettina Kulle (2026). Real-world outcomes of immunotherapy in advanced NSCLC patients with comorbidities. British Journal of Cancer. ISSN 0007-0920. doi: 10.1038/s41416-026-03491-1. Full text in Research Archive
• Ross, Elisabeth; Bouissou, Olivier; Helland, Åslaug & Faxvaag, Arild (2026). From documentation to discovery: clinicians’ perspectives on the generation, usability and standardization of real-world data. International Journal of Medical Informatics. ISSN 1386-5056. 217. doi: 10.1016/j.ijmedinf.2026.106501. Full text in Research Archive
• Chen, Chao; Cheng, Jiancheng; Hou, Ruili; Zheng, Xiaoyuan; Su, Li & Bjaanæs, Maria Moksnes [Show all 15 contributors for this article] (2026). DNA methylation and expression of MAPRE3 affect overall survival of early-stage non-small cell lung cancer patients. Molecular Oncology. ISSN 1574-7891. doi: 10.1002/1878-0261.70260. Full text in Research Archive
• Pol, Henk van der; Kringelbach, Tina; Agudo, Maria Martin; Stav, Gabriel Bratseth; Fagereng, Gro Live & Fiocco, Marta [Show all 24 contributors for this article] (2026). Procedures of data merging in precision cancer medicine: the PRIME-ROSE project. Acta Oncologica. ISSN 0284-186X. 65, p. 1–8. doi: 10.2340/1651-226X.2026.44889. Full text in Research Archive
• Slørdahl, Kathinka Schmidt; Puco, Katarina; Falk, Ragnhild Sørum; Dyvik, Ingrid; Brabrand, Sigmund & Niehusmann, Pitt [Show all 19 contributors for this article] (2026). Clinical outcomes of genomically guided trametinib monotherapy across cancer types: results from the IMPRESS-Norway trial. Acta Oncologica. ISSN 0284-186X. 65, p. 90–96. doi: 10.2340/1651-226X.2026.45086. Full text in Research Archive Show summary

  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.

• Sommervoll, Frigg Åslaugsdatter; Horndalsveen, Henrik; Sommervoll, Dag Einar; Koivunen, Jussi; Halvorsen, Tarje Onsøien & Grønberg, Bjørn Henning [Show all 18 contributors for this article] (2026). How does pulmonary function impact QoL in patients with locally advanced NSCLC treated with chemoradiotherapy and durvalumab? Acta Oncologica. ISSN 0284-186X. 65, p. 232–240. doi: 10.2340/1651-226X.2026.45040. Full text in Research Archive Show summary

  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.

• Rakaee, Mehrdad; Nassar, Amin H.; Tafavvoghi, Masoud; Rahim, Falah Jabar; Farhat, Elias Bou & Adib, Elio [Show all 15 contributors for this article] (2026). Ancestry-Associated Performance Variability of Open-Source AI Models for EGFR Prediction in Lung Cancer. JAMA Oncology. ISSN 2374-2437. doi: 10.1001/jamaoncol.2025.6430. Full text in Research Archive Show summary

  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.

• Pol, Henk van der; Kringelbach, Tina; Fagereng, Gro Live; Stav, Gabriel Bratseth; Agudo, Maria Martin & Mohammad, Soemeya Fooziye Haj [Show all 20 contributors for this article] (2025). Procedure for pooling clinical outcome data from DRUP-like clinical trials using the OMOP model. Journal of Clinical Oncology. ISSN 0732-183X. 43, p. e23165–e23165. doi: 10.1200/JCO.2025.43.16_suppl.e23165. Full text in Research Archive
• Solberg, Steinar Kristian; Slørdahl, Kathinka Schmidt; Aanerud, Marianne; Brustugun, Odd Terje; Grønberg, Bjørn Henning & Helbekkmo, Nina [Show all 8 contributors for this article] (2025). Too much or too little? The trajectory of systemic anti-cancer treatment throughout the last year of life of lung cancer patients in Norway. BJC Reports. 3, p. 1–8. doi: 10.1038/s44276-025-00183-w. Full text in Research Archive Show summary

  Abstract 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.

• Horndalsveen, Henrik; Haakensen, Vilde Drageset; Madebo, Tesfaye; Grønberg, Bjørn Henning; Halvorsen, Tarje Onsøien & Koivunen, Jussi [Show all 21 contributors for this article] (2025). Blood-based tumor mutational burden as a biomarker in unresectable non-small cell lung cancer treated with chemoradiotherapy and durvalumab. Frontiers in Oncology. 15. doi: 10.3389/fonc.2025.1681420. Full text in Research Archive Show summary

  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.

• Mohammad, S.F. Haj; Pol, H. van der; Vrdoljak, E.; Lassen, U.; Ojamaa, K. & Jalkanen, K. [Show all 19 contributors for this article] (2025). A comprehensive assessment of the existing landscape of personalized cancer medicine in the European Union, on behalf of the PCM4EU consortium. ESMO Open. 10(11), p. 105872–105872. doi: 10.1016/j.esmoop.2025.105872. Full text in Research Archive
• Pagui, Euloge Clovis Kenne; Brant, Simon Boge; Svendsen, Kristian; Frigessi, Arnoldo; Helland, Åslaug & Thoresen, Steinar Østerbø [Show all 7 contributors for this article] (2025). Comparative Effectiveness of Atezolizumab, Nivolumab and Pembrolizumab in Second‐Line Treatment of Advanced Non–Small Cell Lung Cancer. Pharmacoepidemiology and Drug Safety. ISSN 1053-8569. 34(7). doi: 10.1002/pds.70181. Full text in Research Archive Show summary

  ABSTRACT Purpose This observational study aimed to assess the comparative effectiveness of immunotherapy (IO) in the second‐line setting of advanced non–small cell lung cancer (aNSCLC). Methods Population‐based data was obtained from the Cancer Registry of Norway (CRN) and linked with the hospital data from the Norwegian Patient Registry (NPR) and treatment data from the Norwegian Prescribed Drug Registry (NorPD). Adult patients with aNSCLC diagnosis in Norway in 2015–2021 were included. The final cohort included patients using IO in the second‐line setting after first‐line treatment with platinum‐containing doublet chemotherapy. We performed a target trial emulating key eligibility criteria commonly used in aNSCLC randomised clinical trials (RCTs) and constructed three pair‐wise 1:1 propensity score (PS)‐matched comparison cohorts: atezolizumab versus pembrolizumab, atezolizumab versus nivolumab and nivolumab versus pembrolizumab. Age, sex, morphology, ECOG performance status, PD‐L1 expression level, chemoradiation use and comorbidities were included in the PS. The primary outcome was overall survival (OS). Patients were followed until experiencing death, emigration or end of study. A Cox proportional hazards regression model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results Analyses included a total of 447 patients, 206 treated with atezolizumab, 71 nivolumab and 170 pembrolizumab. The median follow‐up time was 8.4 (IQR: 3.4–20.7) months. We found no evidence of significant differences in OS in any of the three pair‐wise comparisons; atezolizumab versus pembrolizumab (HR: 0.86; 95% CI: 0.65–1.12), atezolizumab versus nivolumab (HR: 0.97; 95% CI: 0.68–1.37) and nivolumab versus pembrolizumab (HR: 0.99; 95% CI: 0.67–1.49). Conclusion The study suggests no evidence of significant differences between the three IO drugs atezolizumab, nivolumab and pembrolizumab when used in second‐line aNSCLC. However, wide CIs and moderate sample sizes limit definitive conclusions. These results highlight the need for larger studies to confirm potential equivalence or detect meaningful differences.

• Hermansen, Johanne Uthus; Athanasiadis, Paschalis; Yanping, Yin; Rise, Anne-sofie Forfot; Arribas, Alberto J. & Cascione, Luciano [Show all 13 contributors for this article] (2025). Proteasome inhibition overcomes resistance to targeted therapies in B-cell malignancy models and in an index patient. Cell Death & Disease. 16(1), p. 1–14. doi: 10.1038/s41419-025-07884-7. Full text in Research Archive Show summary

  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 CD56 dim NK-cell populations. Our findings suggest that PIs may overcome resistance to targeted therapies, and warrant further studies to optimize clinical responses.

• Henkel, Pia S.; Aas, Eline; Russnes, Hege Elisabeth Giercksky; Dyvik, Ingrid; Fagereng, Gro Live & Helland, Åslaug [Show all 9 contributors for this article] (2025). Microcosting Study of Genomic Profiling for Precision Cancer Medicine. Application from the National Infrastructure for Precision Diagnostics in Norway. Journal of Molecular Diagnostics. ISSN 1525-1578. 27(10), p. 945–953. doi: 10.1016/j.jmoldx.2025.06.006. Full text in Research Archive Show summary

  Detailed cost analyses of genomic profiling for precision cancer medicine can inform strategic planning and cost-effectiveness analysis. A flexible costing framework was developed in this study to conduct microcosting of genomic profiling in precision cancer medicine using the broad gene panel TruSight Oncology 500 and accounting for its integration into the molecular tumor board within the national Infrastructure for Precision Diagnostics in Norway. The framework enables calculation of costs per sample, by workflow steps and cost categories. Site visits and discussions with staff at Oslo University Hospital informed the diagnostic workflow, validation of the framework, and resource use inputs. Sensitivity analysis addressed alternative resource use estimates, higher batch sizes, and investment costs for automation of the library preparation step. Total costs per sample were $2944 USD, ranging from $2366 to $4307 when considering uncertainties in estimates. Consumables and personnel were the most resource-intensive cost categories across analyses. Automating the resource-intensive library preparation step enabled a higher weekly batch size with slightly lower costs per sample ($2881) despite the additional equipment costs. The dynamic costing framework highlights how the choice of equipment and batch sizes affects sample costs and personnel needs for genomic profiling. Consumables and personnel offer the largest potential for costs savings, but potential personnel bottlenecks need to be considered when further upscaling capacity.

• Garcia-Foncillas, Jesús; Bayle, Arnaud; Arnold, Dirk; Avouac, Bernard; Awada, Ahmad & Cruz-Merino, Luis de la [Show all 13 contributors for this article] (2025). Overcoming barriers to advanced biomolecular technologies that inform treatment of solid tumors: a roadmap to access. Future Oncology. ISSN 1479-6694. 21(14), p. 1745–1752. doi: 10.1080/14796694.2025.2501523. Full text in Research Archive
• Zanti, Maria; O'Mahony, Denise; Parsons, Michael T.; Dorling, Leila; Dennis, Joe & Boddicker, Nicholas J. [Show all 50 contributors for this article] (2025). Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification. Nature Communications. 16(1). doi: 10.1038/s41467-025-59979-6. Full text in Research Archive Show summary

  Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyze germline sequencing data of BRCA1 and BRCA2 from 96,691 female breast cancer cases and 302,116 controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observe 11,207 BRCA1 and BRCA2 variants, with 6909 being coding, covering 23.4% of BRCA1 and BRCA2 VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control likelihood ratio (ccLR) evidence is highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.3% specificity for BRCA1 and 93.3% sensitivity and 86.6% specificity for BRCA2. This approach provides case-control evidence for 787 unclassified variants; these include 579 with strong or moderate benign evidence and 10 with strong pathogenic evidence for which ccLR evidence is sufficient to alter clinical classification.

• Nyen, Johanne Elise; Booth, Anja Ødegård; Husby, Øyvind; Bugge, Christoffer; Engebretsen, Ingrid & Oteiza, Francisco [Show all 10 contributors for this article] (2025). Targeted treatment and survival in advanced non-squamous non-small cell lung cancer patients – a nationwide and longitudinal study. Frontiers in Oncology. 15. doi: 10.3389/fonc.2025.1506041. Full text in Research Archive Show summary

  Objectives: We aimed to describe treatment patterns, time on treatment (ToT) and overall survival (OS) for patients with advanced non-squamous, EGFR+, ALK+ and ROS1+ NSCLC in Norway. Materials and methods: We extracted data on patients ≥ 18 years diagnosed with advanced non-squamous NSCLC between 2015 and 2022 from the Cancer Registry of Norway and data on cancer drug therapy from the Norwegian Patient Registry and the Norwegian Prescribed Drug Registry. ToT was measured from the date treatment was collected or administered until the last dispensing was depleted or last hospital drug administration. OS was measured from date of diagnosis until death. Results: In total, 5,279 patients were included, of whom 449 EGFR+, 131 ALK+ and 38 ROS1+. 75% of EGFR+ patients, 88% of ALK+ patients, and 58% of ROS1+ patients received at least one systemic treatment within the first three months after diagnosis. Median follow-up was 13, 19, and 4 months for EGFR+, ALK+, and ROS1+, respectively. The median ToT in first line (1L) for EGFR+ patients was 11 months for osimertinib (CI: 10.1-NA) and 9 months (CI: 8.2-11.2) for afatinib, dacomitinib, erlotinib and gefitinib. For ALK+ patients, median ToT in 1L was 20 months (CI: 14.7-23.7for alectinib, 11 months (CI: 4.7-NA) for brigatinib, and 7 months (CI: 2.9-21.6) for crizotinib. For the five ROS1+ patients treated with crizotinib in 1L, median ToT was 5 months (CI: 2.4-NA). For all patients with a targetable genomic alteration, unadjusted median OS was higher (p-value = 0.025) for patients diagnosed in 2020-2022 (median OS: 23 months, CI: 19.5-NA) compared to patients diagnosed in 2015-2019 (median: 19 months, CI: 16.5-21.2). Conclusions: ToT for targeted therapies was shorter than progression-free survival in clinical trials. However, patients eligible for targeted therapy still had a survival improvement during the study period.

• Brant, Simon Boge; Børø, Siri; Jonasson, Christian; Helland, Åslaug & Thoresen, Steinar Østerbø (2025). Comparative Effectiveness of First-Line Pembrolizumab vs. Chemotherapy in aNSCLC: A Norwegian Population-Based Cohort Study. Clinical Pharmacology and Therapeutics. ISSN 0009-9236. 117(4), p. 1123–1130. doi: 10.1002/cpt.3591. Full text in Research Archive
• Nymoen, Hanne Marte Gjertsen; Alver, Tine Norman; Horndalsveen, Henrik; Eide, Hanne Astrid; Bjaanæs, Maria Moksnes & Brustugun, Odd Terje [Show all 9 contributors for this article] (2024). Thoracic radiation in combination with erlotinib—results from a phase 2 randomized trial. Frontiers in Oncology. 14. doi: 10.3389/fonc.2024.1412716. Full text in Research Archive Show summary

  Background: Radiotherapy (RT) can be used to reduce symptoms and maintain open airways for patients with non-small cell lung cancer when systemic treatment is not sufficient. For some patients, tumor control is not achieved due to radioresistance. Concurrent inhibition of epidermal growth factor receptors has been proposed as a strategy to overcome radioresistance but may increase toxicity. We performed a randomized trial to assess the efficacy, tolerance, and quality of life of concurrent erlotinib and palliative thoracic RT for patients with advanced non-small cell lung cancer. Methods: Patients were randomized 1:1 to RT alone (arm A) or in combination with erlotinib (arm B). A computed tomography (CT) scan at baseline and one at 4–12 weeks after inclusion was used to evaluate treatment response. Adverse events were registered during treatment and the subsequent 30 days. Health-related quality-of-life questionnaires were completed by the patients at baseline, weeks 2, 6, and 20. Results: A total of 114 patients were included. Of the 74 patients with CT scans available for evaluation of treatment effect, there were no significant differences in tumor size reduction between the two groups: median 14.5% reduction in the control arm A and 17.0% in the erlotinib arm B (p = 0.68). Overall survival was not significantly different between the two treatment arms: 7.0 and 7.8 months in arm A and arm B, respectively (log-rank p = 0.32). There was no significant increase in adverse events in the experimental arm, other than what is expected from erlotinib treatment alone. Overall, patients reported similar quality of life in both treatment arms. Conclusion: Concurrent erlotinib and palliative thoracic RT for patients with advanced non-small cell lung cancer was well tolerated but did not improve the efficacy of the RT.

• Thunold, Solfrid; Hernes, Eivor; Farooqi, Saima Jamil; Øjlert, Åsa Kristina; Francis, Roslyn J. & Nowak, Anna K. [Show all 16 contributors for this article] (2024). Outcome prediction based on [18F]FDG PET/CT in patients with pleural mesothelioma treated with ipilimumab and nivolumab +/- UV1 telomerase vaccine. European Journal of Nuclear Medicine and Molecular Imaging. ISSN 1619-7070. doi: 10.1007/s00259-024-06853-0. Full text in Research Archive Show summary

  Purpose The introduction of immunotherapy in pleural mesothelioma (PM) has highlighted the need for efective outcome predictors. This study explores the role of [18F]FDG PET/CT in predicting outcomes in PM treated with immunotherapy. Methods Patients from the NIPU trial, receiving ipilimumab and nivolumab +/- telomerase vaccine in second-line, were included. [18F]FDG PET/CT was obtained at baseline (n = 100) and at week-5 (n = 76). Metabolic tumour volume (MTV) and peak standardised uptake value (SUVpeak) were evaluated in relation to survival outcomes. Wilcoxon rank-sum test was used to assess diferences in MTV, total lesion glycolysis (TLG), maximum standardised uptake value (SUVmax) and SUVpeak between patients exhibiting an objective response, defned as either partial response or complete response according to the modifed Response Criteria in Solid Tumours (mRECIST) and immune RECIST (iRECIST), and non-responders, defned as either stable disease or progressive disease as their best overall response. Results Univariate Cox regression revealed signifcant associations of MTV with OS (HR 1.36, CI: 1.14, 1.62, p < 0.001) and PFS (HR 1.18, CI: 1.03, 1.34, p = 0.02), while multivariate analysis showed a signifcant association with OS only (HR 1.35, CI: 1.09, 1.68, p = 0.007). While SUVpeak was not signifcantly associated with OS or PFS in univariate analyses, it was signifcantly associated with OS in multivariate analysis (HR 0.43, CI: 0.23, 0.80, p = 0.008). Objective responders had signifcant reductions in TLG, SUVmax and SUVpeak at week-5. Conclusion MTV provides prognostic value in PM treated with immunotherapy. High SUVpeak was not associated with inferior outcomes, which could be attributed to the distinct mechanisms of immunotherapy. Early reductions in PET metrics correlated with treatment response.

• Nilssen, Yngvar; Brustugun, Odd Terje; Fjellbirkeland, Lars; Helland, Åslaug; Møller, Bjørn & Wahl, Sissel Gyrid Freim [Show all 7 contributors for this article] (2024). Distribution and characteristics of malignant tumours by lung lobe. BMC Pulmonary Medicine. 24(1). doi: 10.1186/s12890-024-02918-w. Full text in Research Archive Show summary

  Background The main focus on the characteristics of malignant lung tumours has been the size, position within the lobe, and infiltration into neighbouring structures. The aim of this study was to investigate the distribution and characteristics of malignant tumours between the lung lobes and whether the diagnosis, treatment, and outcome differed based on location. Methods This study is based on 10,849 lung cancer patients diagnosed in 2018–2022 with complete data on the location and characteristics of the tumours. The proportions of tumours in each lobe divided by its volume were termed the relative proportion. Results The right upper lobe comprised 31.2% of the tumours and 17.6% of the lung volume. The relative proportion of 1.77 was higher than in the other lobes (p < 0.001). The right middle lobe had a relative proportion of 0.64 but the highest proportion of neuroendocrine tumours (26.1% vs. 15.3 on average). Surgical resection was more often performed in patients with tumours in the lower lobes, and curative radiotherapy was more often performed in the upper lobes. After adjusting for age, sex, stage, and histology, the location of the tumour was found to be a significant independent predictor for resection but not for survival. Conclusion The main finding of the right upper lobe as a site of predilection for lung cancer is similar to tuberculosis and pneumoconiosis. This may be explained that most of the inhaled air, containing bacilli, inorganic particles or tobacco smoke goes to the upper and right parts of the lung.

• Brativnyk, Anastasia; Ankill, Jørgen; Helland, Åslaug & Fleischer, Thomas (2024). Multi-omics analysis reveals epigenetically regulated processes and patient classification in lung adenocarcinoma. International Journal of Cancer. ISSN 0020-7136. doi: 10.1002/ijc.34915. Full text in Research Archive Show summary

  Aberrant DNA methylation is a hallmark of many cancer types. Despite our knowledge of epigenetic and transcriptomic alterations in lung adenocarcinoma (LUAD), we lack robust multi-modal molecular classifications for patient stratification. This is partly because the impact of epigenetic alterations on lung cancer development and progression is still not fully understood. To that end, we identified disease-associated processes under epigenetic regulation in LUAD. We performed a genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis by integrating DNA methylation and gene expression data from 453 patients in the TCGA cohort. Using a community detection algorithm, we identified distinct communities of CpG-gene associations with diverse biological processes. Interestingly, we identified a community linked to hormone response and lipid metabolism; the identified CpGs in this community were enriched in enhancer regions and binding regions of transcription factors such as FOXA1/2, GRHL2, HNF1B, AR, and ESR1. Furthermore, the CpGs were connected to their associated genes through chromatin interaction loops. These findings suggest that the expression of genes involved in hormone response and lipid metabolism in LUAD is epigenetically regulated through DNA methylation and enhancer-promoter interactions. By applying consensus clustering on the integrated expression-methylation pattern of the emQTL-genes and CpGs linked to hormone response and lipid metabolism, we further identified subclasses of patients with distinct prognoses. This novel patient stratification was validated in an independent patient cohort of 135 patients and showed increased prognostic significance compared to previously defined molecular subtypes.

• Nilssen, Yngvar; Brustugun, Odd Terje; Fjellbirkeland, Lars; Grønberg, Bjørn Henning; Haram, Per Magnus & Helbekkmo, Nina [Show all 10 contributors for this article] (2024). Small Cell Lung Cancer in Norway: Patterns of Care by Health Region and Survival Trends. Clinical Lung Cancer. ISSN 1525-7304. 25(5), p. e221–e228.e3. doi: 10.1016/j.cllc.2024.04.002. Full text in Research Archive Show summary

  Introduction/Background: There has been a marked survival improvement for patients with non–small-cell lung cancer. We describe the national trends in characteristics and survival, and geographical differences in diagnostic workup, treatment, and survival for patients with small-cell lung cancer (SCLC). Materials and Methods: Patients registered with SCLC at the Cancer Registry of Norway in 2002 to 2022 were included. Trends in overall survival were estimated for all SCLC patients, patients with limited stage SCLC, patients undergoing surgery, and by health region. Adjusting for case-mix, a multivariable Cox regression was performed examining the association between health region and death. Results: The study included 8374 patients. The stage distribution remained unchanged during the study period. The 5-year overall survival increased from 7.7% to 22.8% for patients with limited stage. The use of multidisciplinary team meetings varied from 62.5% to 85.7%, and the use of positron emission tomography-computer tomography varied from 70.4% to 86.2% between the health regions. Treatment patterns differed markedly between the health regions, with the proportion dying without any registered treatment ranging from 1.2% to 10.9%. For limited stage patients in 2018 to 2022, the median overall survival ranged from 16.5 to 25.5 months across health regions, and the 5-year overall survival ranged from 18.7% to 28.7% (P = .019). Conclusion: The survival for patients with SCLC remains poor. The use of diagnostic procedures, treatment modalities, and survival differed between regions, warranting investigations to further explore the reasons.

• Farooqi, Saima Jamil; Zhao, Zhi; Øjlert, Åsa Kristina; Thunold, Solfrid; Juul, Hedvig Vidarsdotter & Bjaanæs, Maria Moksnes [Show all 10 contributors for this article] (2024). Serum cytokines as a biomarker for immune checkpoint inhibitor toxicity in patients with pleural mesothelioma. Frontiers in Immunology. 15. doi: 10.3389/fimmu.2024.1480183. Full text in Research Archive Show summary

  Background: Pleural mesothelioma (PM) is a rare cancer with a dismal prognosis. Dual immune checkpoint inhibitors have improved overall survival, but the rate of immune-related adverse events (irAEs) is high. Serum cytokines reflect systemic immune reactions and may serve as biomarkers for irAEs. Patients and methods: Patients with pleural mesothelioma treated with nivolumab and ipilimumab with or without UV1 vaccine in the NIPU study were included. Serum cytokine levels were measured by Bio-Plex Pro Human Cytokine Screening 48-Plex Panel Assay. Correlations between cytokine levels and irAEs were analyzed by generalized linear mixed models to identify potential diagnostic and predictive biomarkers. Results: Higher levels of MIG, eotaxin, MIP-1α, IP-10, TNF-α, MIP-1β, IL-4, MIF, IL-16, IL-2RA, SCGF.β and PDFG-BB at baseline are associated with increased risk of developing one or more irAEs. In particular, higher baseline levels of MIG are positively associated with thyroiditis and hypophysitis, and elevated levels of IP-10 and MIG to dermatitis. During the course of treatment, higher levels of MIG, eotaxin, MIF, TNF-α, MIP-1β, IL-4 and IL-16 are associated with an ongoing irAE. We found both predictive and diagnostic value of MIF with fatigue and of eotaxin with both colitis and pneumonitis. Higher levels of CTACK is associated with a lower risk of developing hepatitis, both before and after treatment. Conclusions: Elevated levels of certain cytokines, both before and after onset of treatment, correlate with specific irAEs in PM patients receiving ICIs. These cytokines may be used as biomarkers to predict and detect irAES.

• Tasken, Kjetil; Mohammad, Soemeya F. Haj; Fagereng, Gro Live; Falk, Ragnhild Sørum; Helland, Åslaug & Doorn-Khosrovani, Sahar van [Show all 25 contributors for this article] (2024). PCM4EU and PRIME-ROSE: Collaboration for implementation of precision cancer medicine in Europe. Acta Oncologica. ISSN 0284-186X. 63, p. 384–392. doi: 10.2340/1651-226X.2024.34791. Full text in Research Archive Show summary

  Background: In the two European Union (EU)-funded projects, PCM4EU (Personalized Cancer Medicine for all EU citizens) and PRIME-ROSE (Precision Cancer Medicine Repurposing System Using Pragmatic Clinical Trials), we aim to facilitate implementation of precision cancer medicine (PCM) in Europe by leveraging the experience from ongoing national initiatives that have already been particularly successful. Patients and methods: PCM4EU and PRIME-ROSE gather 17 and 24 partners, respectively, from 19 European countries. The projects are based on a network of Drug Rediscovery Protocol (DRUP)-like clinical trials that are currently ongoing or soon to start in 11 different countries, and with more trials expected to be established soon. The main aims of both the projects are to improve implementation pathways from molecular diagnostics to treatment, and reimbursement of diagnostics and tumour-tailored therapies to provide examples of best practices for PCM in Europe. Results: PCM4EU and PRIME-ROSE were launched in January and July 2023, respectively. Educational materials, including a podcast series, are already available from the PCM4EU website (http://www.pcm4eu.eu). The first reports, including an overview of requirements for the reimbursement systems in participating countries and a guide on patient involvement, are expected to be published in 2024. Conclusion: European collaboration can facilitate the implementation of PCM and thereby provide affordable and equitable access to precision diagnostics and matched therapies for more patients.

• Chen, Leyi; Wang, Xiang; Xie, Ning; Zhongwen, Zhang; Xiaowen, Xu & Xue, Maojie [Show all 18 contributors for this article] (2024). A two-phase epigenome-wide four-way gene-smoking interaction study of overall survival for early-stage non-small cell lung cancer. Molecular Oncology. ISSN 1574-7891. 19(1), p. 173–187. doi: 10.1002/1878-0261.13766. Full text in Research Archive
• Rakaee, Mehrdad; Tafavvoghi, Masoud; Ricciuti, Biagio; Alessi, Joao V; Cortellini, Alessio & Citarella, Fabrizio [Show all 24 contributors for this article] (2024). Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer. JAMA Oncology. ISSN 2374-2437. 11(2), p. 109–118. doi: 10.1001/jamaoncol.2024.5356. Full text in Research Archive Show summary

  Importance - Only a small fraction of patients with advanced non−small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment. For optimal personalized NSCLC care, it is imperative to identify patients who are most likely to benefit from immunotherapy.<p> <p>Objective - To develop a supervised deep learning−based ICI response prediction method; evaluate its performance alongside other known predictive biomarkers; and assess its association with clinical outcomes in patients with advanced NSCLC.<p> <p>Design, Setting, and Participants - This multicenter cohort study developed and independently validated a deep learning−based response stratification model for predicting ICI treatment outcome in patients with advanced NSCLC from whole slide hematoxylin and eosin–stained images. Images for model development and validation were obtained from 1 participating center in the US and 3 in the European Union (EU) from August 2014 to December 2022. Data analyses were performed from September 2022 to May 2024.<p> <p>Exposure - Monotherapy with ICIs.<p> <p>Main Outcomes and Measures - Model performance measured by clinical end points and objective response rate (ORR) differentiation power vs other predictive biomarkers, ie, programmed death-ligand 1 (PD-L1), tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs).<p> <p>Results - A total of 295 581 image tiles from 958 patients (mean [SD] age, 66.0 [10.6] years; 456 [48%] females and 502 [52%] males) treated with ICI for NSCLC were included in the analysis. The US-based development cohort consisted of 614 patients with median (IQR) follow-up time of 54.5 (38.2-68.1) months, and the EU-based validation cohort, 344 patients with 43.3 (27.4-53.9) months of follow-up. The ORR to ICI was 26% in the developmental cohort and 28% in the validation cohort. The deep learning model’s area under the receiver operating characteristic curve (AUC) for ORR was 0.75 (95% CI, 0.64-0.85) in the internal test set and 0.66 (95% CI, 0.60-0.72) in the validation cohort. In a multivariable analysis, the deep learning model’s score was an independent predictor of ICI response in the validation cohort for both progression-free (hazard ratio, 0.56; 95% CI, 0.42-0.76; P < .001) and overall survival (hazard ratio, 0.53; 95% CI, 0.39-0.73; P < .001). The tuned deep learning model achieved a higher AUC than TMB, TILs, and PD-L1 in the internal set; in the validation cohort, it was superior to TILs and comparable with PD-L1 (AUC, 0.67; 95% CI, 0.60-0.74), with a 10-percentage point improvement in specificity. In the validation cohort, combining the deep learning model with PD-L1 scores achieved an AUC of 0.70 (95% CI, 0.63-0.76), outperforming either marker alone, with a response rate of 51% compared to 41% for PD-L1 (≥50%) alone.<p> <p>Conclusions and Relevance - The findings of this cohort study demonstrate a strong and independent deep learning−based feature associated with ICI response in patients with NSCLC across various cohorts. Clinical use of this deep learning model could refine treatment precision and better identify patients who are likely to benefit from ICI for treatment of advanced NSCLC.

• Yiangou, Kristia; Mavaddat, Nasim; Dennis, Joe; Zanti, Maria; Wang, Qin & Bolla, Manjeet K. [Show all 50 contributors for this article] (2024). Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction. Breast Cancer Research. ISSN 1465-5411. 26:189(1), p. 1–14. doi: 10.1186/s13058-024-01947-x. Full text in Research Archive Show summary

  Background The 313-variant polygenic risk score (PRS313) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. Methods We explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank. The mean PRS was calculated by country in the BCAC dataset and by country of birth in the UK Biobank. We explored different approaches to reduce the observed heterogeneity in the mean PRS across the countries, and investigated the implications of the distribution variability in risk prediction. Results The mean PRS313 differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS313 distribution to define risk categories, leads to overestimation and underestimation of risk in some individuals from these countries. Adjustment for principal components explained most of the observed heterogeneity in the mean PRS. The mean estimates derived when using an empirical Bayes approach were similar to the predicted means after principal component adjustment. Conclusions Our results demonstrate that PRS distribution differs even within European ancestry populations leading to underestimation or overestimation of risk in specific European countries, which could potentially influence clinical management of some individuals if is not appropriately accounted for. Population-specific PRS distributions may be used in breast cancer risk estimation to ensure predicted risks are correctly calibrated across risk categories.

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• Skaara, Turid Rygh; Puco, Katarina; Dyvik, Ingrid; Slørdahl, Kathinka Schmidt; Falk, Ragnhild Sørum & Brabrand, Sigmund [Show all 32 contributors for this article] (2026). Alteration-matched therapy in advanced lung cancer: results from the IMPRESS-Norway study. Full text in Research Archive
• Bjørgo, Elisa; Ånensen, Nina; Fagereng, Gro Live; Russnes, Hege Elisabeth Giercksky; Smeland, Sigbjørn & Tasken, Kjetil [Show all 7 contributors for this article] (2026). Merging clinical research and standard healthcare – Nordic Precision Cancer Medicine Symposium 2025. Acta Oncologica. ISSN 0284-186X. 65, p. 185–185. doi: 10.2340/1651-226x.2026.45168. Full text in Research Archive
• Tafavvoghi, Masoud; Rahim, Falah Jabar; Berglund, Marte; Nassar, Amin; Blix, Egil Støre & Mortensen, Elin Synnøve [Show all 12 contributors for this article] (2026). Benchmarking histology foundation models to identify Prosigna high-risk breast cancer patients. Journal of Clinical Oncology. ISSN 0732-183X. 44(16_suppl). doi: 10.1200/jco.2026.44.16_suppl.e12572. Full text in Research Archive Show summary

  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

• Brabrand, Sigmund; Steinskog, Eli Sihn Samdal; Blix, Egil Støre; Flobak, Åsmund; Puco, Katarina & Fagereng, Gro Live [Show all 20 contributors for this article] (2025). 3137O IMPRESS-Norway: A nationwide precision-oncology study for off-label targeted therapies - Results from the first 1,740 patients. doi: 10.1016/j.annonc.2025.08.1609. Full text in Research Archive
• Helland, Åslaug; Tasken, Kjetil; Lindemann, Kristina Yvonne Kathe; Blix, Egil Støre & Haakensen, Vilde Drageset (2025). ESMO-kongressen 2025 – dette ser de norske onkologene frem til. [Journal]. Dagens Medisin. doi: https:/www.dagensmedisin.no/esmo-esmo-2025-forskning/esmo-kongressen-2025-dette-ser-de-norske-onkologene-frem-til/710408. Full text in Research Archive
• Waaler, Per Niklas Benzler; Robertsen, Magdalena Solveig; Paulsen, Erna-Elise; Andersen, Sigve; Richardsen, Elin & Helland, Åslaug [Show all 12 contributors for this article] (2025). 21P Integration of genomic and clinical data for relapse prediction in early-stage non-small cell lung cancer. ESMO Real World Data and Digital Oncology. 10, p. 100220–100220. doi: 10.1016/j.esmorw.2025.100220. Full text in Research Archive
• Tafavvoghi, Masoud; Rahim, Falah Jabar; Andersen, Sigve; Paulsen, Erna-Elise; Cortellini, A. & Lombardi, P. [Show all 18 contributors for this article] (2025). 219P Benchmarking state-of-the-art deep learning models for tumor-infiltrating lymphocytes (TILs) quantification. ESMO Real World Data and Digital Oncology. 10, p. 100415–100415. doi: 10.1016/j.esmorw.2025.100415. Full text in Research Archive
• Rakaee, Mehrdad; Waaler, Per Niklas Benzler; Rahim, Falah Jabar; Giannikou, Krinio; Adib, Elio & Andersen, Sigve [Show all 19 contributors for this article] (2025). Abstract 5366: DRAGEN pipeline validation for somatic variant detection in diagnostics using TSO500 panel. Cancer Research. ISSN 0008-5472. 85(8_Supplement_1), p. 5366–5366. doi: 10.1158/1538-7445.am2025-5366. Full text in Research Archive Show summary

  Abstract Background: 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. Methods: 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). Results: In the DRAGEN pipeline output, 4328 exonic and nonsynonymous variants with a variant allele fraction (VAF) &gt;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 &gt;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 &gt;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. Conclusion: 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. Citation Format: 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.

• Tafavvoghi, Masoud; Adib, Elio; Farhat, Elias Bou; Rahim, Falah Jabar; Nassar, Amin & Helland, Åslaug [Show all 12 contributors for this article] (2025). Single-slide histology-based deep learning model for mismatch repair deficiency prediction in colorectal cancer. Journal of Clinical Oncology. ISSN 0732-183X. 43(16_suppl), p. 3567–3567. doi: 10.1200/jco.2025.43.16_suppl.3567. Full text in Research Archive Show summary

  3567 Background: Mismatch repair deficiency (dMMR) is a critical predictive biomarker for determining eligibility and response to immunotherapy in colorectal cancer (CRC). The current gold standards for detecting dMMR include next-generation sequencing (NGS) for microsatellite instability (MSI) detection and immunohistochemistry (IHC) for mismatch repair protein expression. However, discrepancies between these techniques have been observed, potentially impacting clinical decisions and patient outcomes. To address this, we developed a histology-based deep learning (DL) model to predict MMR status, with a specific focus on resolving cases of discordance. Methods: Paired hematoxylin and eosin (H&E) slides from 974 CRC tumors were retrospectively collected from the Dana-Farber Cancer Institute, all of which had NGS Oncopanel and IHC MMR reports available. Using NGS-determined MMR status as the training reference, we developed a multi-instance deep learning model to predict MMR status from single H&E slides. Feature extraction employed various pathology foundation models (FMs). The dataset was split into training and tuning sets. A hold-out test set (n = 52, 65% dMMR) was curated including patients treated with immune checkpoint inhibitors or those with NGS-dMMR/IHC-proficient discordance. Results: Among the overall cohort, NGS/IHC concordance identified 82 dMMR patients (9%), 881 proficient MMR (pMMR) patients (90%), and 11 cases (1%) with NGS-dMMR/IHC-proficient discordance. In the hold-out test set, the fine-tuned CTransPath FM demonstrated the highest performance, achieving an area under the curve (AUC) of 0.88 (95% CI 0.77–0.98), a positive predictive value of 0.93, and correctly classifying 8 of 11 discordant cases (73%) as dMMR. Comparative FMs, CONCH and UNI, exhibited slightly lower AUCs (0.86 and 0.85, respectively) and lower accuracy in classifying discordant cases (Table). Conclusions: Our histology-based DL model shows promise as a complementary tool for IHC in predicting dMMR status in CRC. The single-slide approach offers a rapid, robust and cost-effective method to prioritize IHC-proficient cases for further validation by NGS. Cohort expansion and validation in an external dataset are underway. Test set (n=52, 65% dMMR). Model AUC (CI,95%) Sensitivity Specificity PPV NPV Accuracy NGS+/IHC- CTransPath 0.88 (0.77-0.98) 0.85 0.89 0.93 0.76 8/11 CONCH 0.86 (0.76-0.96) 0.88 0.76 0.67 0.93 5/11 UNI 0.85 (0.74-0.96) 0.78 0.82 0.70 0.87 6/11

• Rakaee, Mehrdad; Thunold, Solfrid; Tafavvoghi, Masoud; Öjlert, Åsa Kristina; Giannikou, Krinio & Adib, Elio [Show all 12 contributors for this article] (2025). Multiomics profiling for prediction of immunotherapy response in advanced pleural mesothelioma: Sub-study of the NIPU trial. Journal of Clinical Oncology. ISSN 0732-183X. 43(16_suppl), p. 8086–8086. doi: 10.1200/jco.2025.43.16_suppl.8086. Full text in Research Archive Show summary

  8086 Background: The combination of ipilimumab and nivolumab (IPI/NIVO) is a standard treatment for unresectable pleural mesothelioma. However, the objective response rate (ORR) is relatively low, and serious toxicity necessitating treatment cessation with or without steroid treatment is seen in 20%. Predictive biomarkers for IPI/NIVO in mesothelioma are needed to personalize treatment decisions. Methods: In the NIPU trial, 118 patients progressing after first-line chemotherapy were included in the study and were randomly assigned to IPI/NIVO alone or in combination with the telomerase UV1 vaccine. Whole-slide tumor tissues were available from 99 patients and analyzed using multiplex immunofluorescence (mIF) with a panel including CD8, CD20, CD66b, FoxP3, Granzyme-B, and pan-cytokeratin. Machine learning algorithms (XGBoost) were utilized and trained for immune cell subset classification and tissue subregion segmentation (tumor vs. stroma). Bulk RNA-sequencing (RNA-seq) was performed on 25 matched baseline fresh frozen tissues, followed by differential expression analysis (DESeq2), gene set enrichment analysis (GSEA) and immune cell deconvolution. Radiological evaluation was done by local assessment of immune version of the mesothelioma modified RECIST criteria. Disease control rate (DCR) was defined as the fraction of patients with partial response (PR) or stable disease (SD) compared to those with progressive disease (PD). Results: The DCR and ORR were 69% and 20%, respectively. From mIF analysis, stromal CD66b, CD20, and tumoral CD66b showed the highest area under the curve (AUC = 0.60 ± 0.1) for differentiating DCR groups. For ORR, tumoral CD8+FoxP3+ T-cells demonstrated the highest AUC (0.58) for identifying PR. Patients with tumoral CD66b% scores above the median (>0) had significantly longer progression-free survival (6.2 vs. 4.2 months; HR: 0.63, 95% CI: 0.42–0.97, P = 0.04) and showed a trend toward improved overall survival (HR: 0.65, 95% CI: 0.41–1.0, P = 0.07). These findings were consistent with RNA-seq-derived immune fraction scores. Lasso Cox regression identified natural killer cells, neutrophils, and CD4+ T cells as top predictive features for DCR groups. Additionally, GSEA hallmark analysis revealed significant enrichment of interferon-γ and -α pathways in the DCR PR/SD group (Q < 0.001) compared to PD. Conclusions: High/positive levels of tumoral CD66b+ neutrophils show promise as predictive biomarkers for immunotherapy efficacy in advanced pleural mesothelioma. Larger, independent studies are needed to confirm these findings and validate their clinical utility. Clinical trial information: NCT04300244 .

• Thunold, Solfrid; Rakaee, Mehrdad; Giannikou, K.; Hernes, Eivor; Farooqi, Saima Jamil & Öjlert, Å.K. [Show all 11 contributors for this article] (2025). 2977P Dual-time-point [18F] FDG PET/CT and tumour microenvironment features in pleural mesothelioma patients receiving immunotherapy. Annals of Oncology. ISSN 0923-7534. 36. doi: 10.1016/j.annonc.2025.08.3590. Full text in Research Archive
• Robertsen, M.S.; Waaler, Per Niklas Benzler; Andersen, Sigve; Paulsen, Erna-Elise; Kilvær, Thomas Karsten & Wahl, Sissel Gyrid Freim [Show all 20 contributors for this article] (2025). 1802P Tissue tumor mutational burden and risk of recurrence in early-stage non-small cell lung cancer. Annals of Oncology. ISSN 0923-7534. 36. doi: 10.1016/j.annonc.2025.08.2428. Full text in Research Archive
• Rakaee, Mehrdad; Tafavvoghi, Masoud; Cortellini, A.; Andersen, Sigve; Rahim, Falah Jabar & Brunetti, L. [Show all 28 contributors for this article] (2025). P1.11.62 Deep Learning Histopathology Model for PD-L1 (TPS) and Immunotherapy Outcome Prediction in Non-Small Cell Lung Cancer. Journal of Thoracic Oncology. ISSN 1556-0864. 20(10). doi: 10.1016/j.jtho.2025.09.362. Full text in Research Archive
• Helland, Åslaug (2025). ctDNA-based MRD detection in unresectable NSCLC undergoing curatively intended chemoradiotherapy and durvalumab. doi: https:/www.dagensmedisin.no/dmarena/dagens-medisin-inviterte-til-dm-arena-post-asco-12-juni-se-opptaket-her/669612. Full text in Research Archive
• Horndalsveen, Henrik; Haakensen, Vilde Drageset; Madebo, Tesfaye; Grønberg, Bjørn Henning; Halvorsen, Tarje Onsøien & koivunen, jussi [Show all 18 contributors for this article] (2025). ctDNA-based MRD detection in unresectable NSCLC undergoing curatively intended chemoradiotherapy and durvalumab. doi: https:/ascopubs.org/doi/10.1200/JCO.2025.43.16_suppl.8011. Full text in Research Archive
• Helland, Åslaug (2025). A Hands-On Case Study of a pan-European Cancer Research Project Using OMOP. doi: https:/invitepeople.com/public/events/bd0a6002b4/seminars/bbc1c86cf1. Full text in Research Archive
• Helland, Åslaug (2025). Real world data use in precision cancer medicine: EHDS implications in separating primary and secondary use of data. doi: https:/invitepeople.com/public/events/bd0a6002b4/seminars/ae8da53fbf. Full text in Research Archive
• Helland, Åslaug (2025). Gentesting. [TV]. NRK. doi: https:/tv.nrk.no/serie/dagsrevyen/sesong/202503/episode/NNFA19031625. Full text in Research Archive
• Helland, Åslaug (2025). Kayas kreftsvulst: Fra kokosnøtt til klinkekule. [Internet]. Kreftforeningen. doi: https:/kreftforeningen.no/innsamlingsaksjonen/kayas-kreftsvulst-fra-kokosnott-til-klinkekule/. Full text in Research Archive
• Helland, Åslaug (2025). Panelsamtale om kliniske studier. Full text in Research Archive
• Helland, Åslaug (2025). Gentesting av kreftsvulster. Full text in Research Archive
• Helland, Åslaug (2025). IMPRESS-Norway. Full text in Research Archive
• Nyen, Johanne Elise; Booth, Anja Ødegård; Husby, Øyvind; Bugge, Christoffer; Engebretsen, Ingrid & Oteiza, Francisco [Show all 10 contributors for this article] (2025). Corrigendum: Targeted treatment and survival in advanced non-squamous non-small cell lung cancer patients – a nationwide and longitudinal study (Frontiers in Oncology, (2025), 15, (1506041), 10.3389/fonc.2025.1506041). Frontiers in Oncology. 15. doi: 10.3389/fonc.2025.1595028. Full text in Research Archive
• Helland, Åslaug (2024). Ongoing clinical studies in precision medicine. Full text in Research Archive
• Helland, Åslaug (2024). Precision cancer medicine in Norway. Full text in Research Archive
• Helland, Åslaug (2024). Presisjonsmedisin innen kreft - IMPress-studien. Full text in Research Archive
• Helland, Åslaug (2024). Strukturerte data - til bruk i forskning og kvalitetssikring. Full text in Research Archive
• Helland, Åslaug (2024). Digitalt samtykke. Full text in Research Archive
• Helland, Åslaug (2024). Nasjonal screening for lungekreft. Full text in Research Archive
• Helland, Åslaug & Lilleeng, Sverre (2024). Stående applaus for kreftbehandling: – Det er sjelden. [Internet]. NRK. Full text in Research Archive
• Helland, Åslaug (2024). The Dynatsi Protocol. Full text in Research Archive
• Helland, Åslaug (2024). Molecular Tumor Boards in clinical practice. Full text in Research Archive
• Fagereng, Gro Live; Russnes, Hege Elisabeth Giercksky; Tasken, Kjetil; Smeland, Sigbjørn & Helland, Åslaug (2024). Presisjonsmedisin innen kreft. [Journal]. Aftenposten (Persontilpasset Behandling – Addendum to AP). Full text in Research Archive
• García-Foncillas, J.; Arnold, D.; Avouac, B.; Lassen, U.; Laurent-Puig, P. & Taieb, J. [Show all 8 contributors for this article] (2024). Overcoming barriers in biomarker testing. Letter to the Editor regarding: ‘ESMO study on the availability and accessibility of biomolecular technologies in oncology in Europe’, by A. Bayle et al. Annals of Oncology. ISSN 0923-7534. 35(7), p. 677–678. doi: 10.1016/j.annonc.2024.04.008. Full text in Research Archive
• Eriksen, Kjersti Flugstad & Helland, Åslaug (2024). Kreftforsker Åslaug Helland har forventninger til presisjonsmedisin i 2024. [Journal]. Dagens Medisin. Full text in Research Archive
• Helland, Åslaug & Zerener, Anders B (2024). Ny lungekreft-behandling: – Resultatene er enestående. [Journal]. Nettavisen. Full text in Research Archive
• Helland, Åslaug (2024). Lungekreft: målrettet behandling og screening. Full text in Research Archive
• Helland, Åslaug (2024). MPRESS-Norway og Presisjonsmedisin. Full text in Research Archive
• Helland, Åslaug (2024). NorTrials, IMPRESS-Norway and MATRIX. Full text in Research Archive
• Helland, Åslaug (2024). Endepunkter I kliniske studier (Debatt). Full text in Research Archive
• Helland, Åslaug (2024). Prioriteringer & Presisjonsmedisin (Debatt). Full text in Research Archive
• Helland, Åslaug (2024). NorTrials Kreft - aktivitet og planer. Full text in Research Archive
• Helland, Åslaug (2024). Lungekreftscreening. Full text in Research Archive
• Helland, Åslaug (2024). IMPRESS-Norway 3 years. Full text in Research Archive
• Helland, Åslaug (2024). Presisjonsmedisin innen kreft: IMPRESS-Norway og MATRIX. Full text in Research Archive
• Helland, Åslaug (2024). Lung cancer treatment Stage III. Full text in Research Archive
• Helland, Åslaug & Zerener, Anders B (2024). Ny kreftbehandling lanseres i Norge: – En milepæl. [Journal]. Gudbrandsdølen. Full text in Research Archive
• Helland, Åslaug; Zerener, Anders B & Ross, Ingrid Stenstadvold (2024). Ny kreftbehandling lanseres i Norge: – En milepæl. [Journal]. NEttavisen. Full text in Research Archive
• Vebenstad, Marit Aaby & Helland, Åslaug (2024). Hver fjerde norske kreftpasient i IMPRESS-studien får tilbud om eksperimentell behandling. [Journal]. Onkologisk Tidsskrift. Full text in Research Archive
• Helland, Åslaug (2024). IMPRESS-Norway 3 år. Full text in Research Archive
• Helland, Åslaug (2024). Medikamentell kreftbehandling. Full text in Research Archive
• Dyvik, Ingrid; Fagereng, Gro Live; Lien, Tonje; Nygaard, Vigdis; Silwal-Pandit, Laxmi & Noon, J Christopher [Show all 20 contributors for this article] (2024). Comprehensive genomic profiling of circulating tumor DNA for treatment recommendation: A sub-project of the IMPRESS-Norway trial. Full text in Research Archive
• Helland, Åslaug (2024). Nobelpris for bittesmå RNA-fragmenter. Tidsskrift for Den norske legeforening (Tidsskriftet). ISSN 0029-2001. 144(15), p. 1–3. doi: 10.4045/tidsskr.24.0603. Full text in Research Archive
• Tasken, Kjetil; Fagereng, Gro Live; Abel, Edvard; Baltruskeviciene, Edita; Carlsson, Katarina Steen & Falk, Ragnhild Sørum [Show all 20 contributors for this article] (2024). Single point of entry to the European precision cancer medicine trial network PRIME-ROSE. Full text in Research Archive
• Kringelbach, Tina Marie; Fagereng, Gro Live; Mohammad, Soemeya F. Haj; Verbeek, Florentine; Timmer, Hans & Juslin, Tanja [Show all 17 contributors for this article] (2024). PRIME-ROSE: Merging clinical outcome data from DRUP-like clinical trials. Full text in Research Archive
• Helland, Åslaug (2024). Presisjonsmedisin innen kreft. Full text in Research Archive
• Helland, Åslaug (2024). Presisjonsmedisin innen kreft: IMPRESS-Norway and MATRIX. Full text in Research Archive
• Helland, Åslaug (2024). Added value of Liquid Biopsy testing in advanced cancer – IMPRESS NORWAY​. Full text in Research Archive
• Helland, Åslaug (2024). Video: Highlighting the role of CGP in cancer treatment at ESMO 2024. [Internet]. YouTube. Full text in Research Archive
• Mahon, Piers; Chatzitheofilou, Ismini; Dekker, Andre; Fernandez, Xose; Hall, Geoff & Helland, Åslaug [Show all 11 contributors for this article] (2024). A federated learning system for precision oncology in Europe: DigiONE. Nature Medicine. ISSN 1078-8956. 30, p. 334–337. doi: 10.1038/s41591-023-02715-8. Full text in Research Archive
• Helland, Åslaug (2024). Precision medicine and clinical trials in Norway. Full text in Research Archive
• Jakobsen, Siw Ellen & Helland, Åslaug (2024). Første vaksine mot lungekreft er satt. [Internet]. Forskning.no. Full text in Research Archive
• Helland, Åslaug; Steinskog, Eli Sihn Samdal; Blix, Egil Støre; Flobak, Åsmund; Brabrand, Sigmund & Puco, Katarina [Show all 20 contributors for this article] (2024). Hever kvaliteten på behandling av kreft. Tidsskrift for Den norske legeforening (Tidsskriftet). ISSN 0029-2001. 144(1), p. 52–53. doi: 10.4045/tidsskr.23.0740. Full text in Research Archive Show summary

  Alle norske sykehus med kreftavdeling deltar i en nasjonal kreftbehandlingsstudie. Den er aktuell for pasienter med avansert kreftsykdom etter standard behandling.

• Bjørgo, elisa; Fagereng, Gro Live; Russnes, Hege Elisabeth Giercksky; Smeland, Sigbjørn; Tasken, Kjetil & Helland, Åslaug (2024). Acta Oncologica Nordic Precision Cancer Medicine Symposium 2023 – merging clinical research and standard healthcare. Acta Oncologica. ISSN 0284-186X. 63, p. 487–490. doi: 10.2340/1651-226X.2024.24954. Full text in Research Archive
• Torkildsen, Cecilie Fredvik; Lindemann, Kristina Yvonne Kathe; Bischof, Katharina; Aune, Guro; Vistad, Ingvild & Ingebrigtsen, Vibeke Anett [Show all 20 contributors for this article] (2024). 456 Molecular characteristics of gynaecological cancer patients in the IMPRESS-Norway trial – a national prospective, non-randomized clinical trial evaluating the efficacy of anti-cancer drugs on new indications. International Journal of Gynecological Cancer. ISSN 1048-891X. 34, p. A563–A564. doi: 10.1136/ijgc-2024-ESGO.1105. Full text in Research Archive
• Miceli, Rosalba; Eriksson, Hanna; Russo, Giuseppe Lo; Alfieri, Salvatore; Bjaanæs, Maria Moksnes & Pietrantonio, Filippo [Show all 19 contributors for this article] (2024). Gender Difference in sidE eFfects of ImmuNotherapy: a possible clue to optimize cancEr tReatment (G-DEFINER): study protocol of an observational prospective multicenter study. Acta Oncologica. ISSN 0284-186X. 63, p. 213–219. doi: 10.2340/1651-226X.2024.24179. Full text in Research Archive Show summary

  Background: Immune checkpoint inhibitors (ICIs) have significantly improved outcomes in various cancers. ICI treatment is associated with the incidence of immune-related adverse events (irAEs) which can affect any organ. Data on irAEs occurrence in relation to sex- differentiation and their association with gender-specific factors are limited. Aims: The primary objective of the G-DEFINER study is to compare the irAEs incidence in female and male patients who undergo ICI treatment. Secondary objectives are: to compare the irAEs incidence in pre- and postmenopausal female patients; to compare the irAEs incidence in female and male patients according to different clinical and gender-related factors (lifestyle, psychosocial, and behavioral factors). Exploratory objectives of the study are to compare and contrast hormonal, gene-expression, SNPs, cytokines, and gut microbiota profiles in relation to irAEs incidence in female and male patients. Methods and Results: The patients are recruited from Fondazione IRCCS Istituto Nazionale dei Tumori, Italy, St Vincent’s University Hospital, Ireland, Oslo University Hospital, Norway, and Karolinska Insitutet/Karolinska University Hospital, Sweden. The inclusion of patients was delayed due to the Covid pandemic, leading to a total of 250 patients recruited versus a planned number of 400 patients. Clinical and translational data will be analyzed. Interpretation: The expected outcomes are to improve the management of cancer patients treated with ICIs, leading to more personalized clinical approaches that consider potential toxicity profiles. The real world nature of the trial makes it highly applicable for timely irAEs diagnosis.

• Adib, Elio; jabar, falah; Tafavvoghi, Masoud; Nassar, Amin; Busund, Lill-Tove Rasmussen & Dønnem, Tom [Show all 9 contributors for this article] (2024). Artificial Intelligence-powered analysis of the tumor immune microenvironment in primary and metastatic colorectal cancer. Annals of Oncology. ISSN 0923-7534. 35, p. S455–S455. doi: https:/www.annalsofoncology.org/article/S0923-7534(24)02135-5/fulltext. Full text in Research Archive

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