Effective cancer care increasingly depends on digital decision support tools (DSTs) to interpret complex clinical, molecular, and genomic data and guide personalised treatment decisions. However, the oncology DST (oncDST) landscape remains fragmented, with limited interoperability, inconsistent standards, and uneven clinical adoption across healthcare systems. This fragmentation hinders routine clinical use and impedes the demonstration of robust clinical benefit. To address these challenges, the CAN.HEAL consortium proposes the EU-oncDST digital framework, a conceptual, harmonised, interoperable, and modular architecture designed to integrate existing oncDSTs across Europe. Developed through consortium-wide consultations, an EU-level survey and comprehensive mapping of both public and private solutions, the framework provides a practical pathway for implementing interoperable oncDSTs while fostering stakeholder collaboration and innovation. It also promotes the improvement of data-driven precision oncology, highlighting the integration of artificial intelligence, enabling continuous patient follow-up, and supporting the development of a learning cancer system. At its core, the framework empowers Molecular Tumour Boards (MTBs) to operate efficiently at institutional, national, and European levels. By offering a harmonised, interoperable, and modular architecture designed to integrate clinical, molecular and genomic data, the framework strengthens evidence-based and personalised treatment recommendations. A phased action plan links MTB deployment to the implementation of oncDSTs. Early phases focus on piloting and validating oncDST use within MTBs, optimising patient-centred consultations, harmonising variant annotation, and enhancing clinical trial matching. Overall, the EU-oncDST digital framework aims to provide a practical and collaborative pathway to strengthen oncology decision-making and accelerate the translation of precision medicine into clinical benefit across Europe.

Unlike many other solid tumors, melanoma cells possess a remarkable ability to dynamically transition between distinct transcriptional states in response to environmental cues or therapeutic pressure. Among the adaptive mechanisms underlying this plasticity, the epithelial-to-mesenchymal transition (EMT) has garnered increasing attention, as it facilitates the shift from a proliferative, epithelial-like phenotype to a more invasive, mesenchymal-like phenotype frequently associated with cellular dormancy, quiescence and resistance to therapy. Despite growing interest in this phenomenon, the characterization of dormant cellular phenotypes and their clinical significance remains incomplete. In this study, we adopted a comprehensive approach integrating patient-derived melanoma cell lines, bulk RNA sequencing from tumor biopsies and analysis of independent bulk and single-cell public datasets. This multi-dimensional strategy enabled the identification of a reproducible dichotomy between “proliferative” and “dormant” phenotypes, characterized by distinct levels of mitotic activity and mesenchymal gene expression profiles. By leveraging an eight-gene transcriptional signature, we constructed a “dormancy score” able to stratify tumors along a dormancy–proliferation axis, revealing strong associations with clinical outcomes such as progression-free survival (PFS), overall survival (OS) and response to immunotherapy. Within the dormant-associated gene module, the surface glycoprotein TACSTD2 (TROP2) emerged as a central hub gene. TROP2 expression was consistently upregulated in the dormant-like transcriptional state. Supporting these findings, single-cell RNA sequencing data confirmed that TROP2 marks a rare subpopulation of malignant cells that may constitute a quiescent, therapy-resistant niche. Besides, results highlight a predominant intracellular expression of TROP2 in the dormant phenotype. Together, these findings define a robust dormant phenotype in melanoma with both molecular and clinical significance and evaluate TROP2 as a potential biomarker and therapeutic target for identifying and eradicating dormant and treatment-refractory tumor cells.

Melanoma remains a highly aggressive malignancy, with immunotherapy playing a pivotal role in its treatment. However, the variability in patient response highlights the need for reliable biomarkers to guide therapeutic decisions. We performed a Bioinformatics meta-analysis on a pooled dataset of 211 patients to identify clinically relevant RNA biomarkers for predicting immunotherapy response in melanoma, using bulk transcriptomics from tissue biopsies. Bulk transcriptomics remains a viable option for several reasons: projected cost per patient, feasibility in clinical settings, and turnaround time. Differential Enrichment showed a significant activation of humoral immunity, interferon-gamma-mediated responses and MHC class I binding factors in Responders. A putative blacklist of confounder genes with high fold changes was built to support future analyses. When building machine-learning-based prediction models, Random Forest Modelling based solely on transcriptomic data can predict ICB response with an AUC of 0.65, without any additional biomolecular information or clinical metadata. When adding basic clinical and technical variables the predictive power reaches an AUC of 0.68, while HLA Evolutionary Divergence brings no value in response prediction. Out-of-fold predicted response classes significantly stratify Progression-Free Survival, while Overall Survival stratification does not reach significance. Differential Deconvolution of Survival Endpoints suggests populations specific to Immune-Checkpoint blockade sensitivity and other general prognostic factors such as M1 Macrophages. Clinical Transcriptomics is herein evaluated as an additional companion biomarker tool for the current and next wave of immunotherapies in Melanoma treatment.

INTRODUCTION:An abnormal immune response at the fetal-maternal interface is expected in 50-60 % of unexplained Recurrent Pregnancy Loss (uRPL) cases. Detected immunophenotypes in uRPL could help in risk assessment, prognosis and therapy. The study of immune mechanisms at the fetal-maternal interface is crucial, but the technique used for research has limitations, including contamination and invasiveness, which can trigger immune responses. Hystero-embryoscopy may provide a precise method for studying the immunological factors involved in RPL at the maternal-fetal interface, reducing bias from sample collection techniques. Our aim is to assess its effectiveness in obtaining high-quality samples to study the immunological basis of RPL. METHODS:This is a multicenter prospective study in which 10 women with a first-trimester ongoing miscarriage were enrolled and received surgical treatment at the University Hospital Federico II in Naples. Embryo-hysteroscopy was used to selectively obtain decidual and chorionic villous tissues separately, from the maternal-fetal interface. Transcriptome sequencing was performed at Regina Elena National Cancer Institute in Rome. RESULTS:RNA integrity numbers (RIN) satisfied the minimum quality requirements (median RIN considering all samples was 8.4 ± 1.1) and RNA sequencing exhibited adequate sequencing depth (the mean of Uniquely Mapped Reads considering all samples was 52.1 ± 7.7), ensuring reliable downstream analysis. The bioinformatics analysis demonstrated the absence of cross-tissue contamination due to the clear separation between the transcriptional profiles of decidual and chorionic villous tissues: CD45 immunostaining and pathological validation confirmed these findings. CONCLUSIONS:These findings demonstrate that hystero-embryoscopy enables precise immunological profiling at the maternal-fetal interface while minimizing sample contamination.

INTRODUCTION:The CAN.HEAL consortium, comprising 47 cancer centers and academic institutions across 17 EU countries, has developed a set of recommendations for Molecular Tumor Boards (MTBs) to address the lack of standardized guidelines in personalized cancer medicine. METHODS:Over the past 2 years, through extensive collaboration and seven dedicated online meetings, CAN.HEAL experts developed consensus-based recommendations across 10 critical domains. RESULTS:The consortium agreed that MTBs' primary role is to perform molecular and clinical assessments for patients requiring care beyond standard treatment. Core MTB composition should include medical oncologists, molecular biologists, pathologists, and bioinformaticians. Patient eligibility criteria should prioritize performance status, with flexibility for rare cases. Shared informed consent is crucial for sample collection, data use, and research. A two-tiered IT workflow, with minimal and maximal datasets, is recommended, along with a comprehensive decision support tool. These recommendations focus on genomic testing, acknowledging diversity of NGS assays and proposing general guidelines. MTB reports should be concise, with technical details provided in the molecular diagnostic report. Innovative approaches like the Drug Rediscovery Protocol support access to off-label therapies. Harmonized training for MTB members is essential to bridging knowledge gaps in this evolving field. Indicators are needed to assess MTB effectiveness over time. Expanding MTB benefits to underserved populations depends on creating a shared European MTB database. CONCLUSION:Standardizing MTB practices represents a key step toward equitable access to personalized medicine and improved cancer care across Europe. Sustainable implementation requires coordinated EU efforts, and dynamic MTBs that continuously refine genomic-driven decisions within real-world contexts.

Federated Search enables data accessibility under privacy-preserving regulations. One of the strategic objectives of the BBMRI-ERIC biobanking infrastructure is to make high-quality samples findable via Federated Search. The main prerequisites for biobanks to join the Federated Network are the conversion of a local database into a Common Data Model and the setup of a server node in which the database is loaded and made accessible for external queries. Data conversion is often the most critical step for institutions, as many of them lack the technical expertise needed to improve the FAIRness of their data. This is achieved through a local Extraction, Transformation and Loading process of data, usually extracted from a Biobank Information Management System. We hereby present a framework for the conversion of minimal information datasets into HL7-FHIR transaction bundles, allowing basic Biobank Interoperability, and enabling biobanks to be connected to the BBMRI-ERIC European Federated Platform. The toolkit consists of several Python modules, creating JSON files, ready to be uploaded to an internal FHIR server connected to the federated network, enabling data sharing and query execution. This tool has been successfully integrated in three BBMRI.it biobanks, allowing them to share their data correctly. In general, this tool will enforce data harmonization and standardization among research infrastructures, integrating the current pipeline into local information systems. The framework is available at https://github.com/bbdataeng/a-small-fire.

Objective Digitalization is a pillar of reproducible research and a mandatory requirement for Research Infrastructures. Biobanks must ensure a fully engineered and digitalized process towards data FAIRification. To this aim, the first step is to assess the current level of digitalization using quantitative metrics, which is particularly challenging given the multi-faceted regulatory and logistical nature of biobanking. Methods We developed a Biobanking digital assessment maturity framework, BB4FAIR, comprising a survey divided into three macro areas, namely IT infrastructure, personnel, and data annotation richness. Furthermore, we implemented an automated R/Shiny system to analyse survey responses and generate visual data representations. We piloted the tool on 46 Italian biobanks that in 2023 had signed the partner charter with BBMRI. A scoring table facilitated the tiering of digital maturity, highlighting areas requiring corrective action. Results The assessment revealed significant heterogeneity across the three macro-areas of digitalization: almost half of the biobanks feature adequate IT infrastructure and personnel, and a smaller proportion have robust data annotation capabilities. Notably, most biobanks reported having a Biobank IT Management System (BIMS) or an alternative that serves their purposes, yet they still collect the consent to biobanking for future purposes in paper format; the digitalization of informed consent is generally lacking. These findings highlight the need for targeted improvements in Biobank digitalization to enhance overall data FAIRness. Conclusion The survey results underscore a pressing need for enhanced IT training and improved data annotation resources within the BBMRI.it. Corrective actions on many lacking features and desiderata are ongoing in the context of the #NextGenerationEu “Strengthening BBMRI.it” project.

Scientific literature supports the evidence that cancer stem cells (CSCs) retain inside low reactive oxygen species (ROS) levels and are, therefore, less susceptible to cell death, including ferroptosis, a type of cell death dependent on iron-driven lipid peroxidation. A collection of lung adenocarcinoma (LUAD) primary cell lines derived from malignant pleural effusions (MPEs) of patients was used to obtain 3D spheroids enriched for stem-like properties. We observed that the ferroptosis inducer RSL3 triggered lipid peroxidation and cell death in LUAD cells when grown in 2D conditions; however, when grown in 3D conditions, all cell lines underwent a phenotypic switch, exhibiting substantial resistance to RSL3 and, therefore, protection against ferroptotic cell death. Interestingly, this phenomenon was reversed by disrupting 3D cells and growing them back in adherence, supporting the idea of CSCs plasticity, which holds that cancer cells have the dynamic ability to transition between a CSC state and a non-CSC state. Molecular analyses showed that ferroptosis resistance in 3D spheroids correlated with an increased expression of antioxidant genes and high levels of proteins involved in iron storage and export, indicating protection against oxidative stress and low availability of iron for the initiation of ferroptosis. Moreover, transcriptomic analyses highlighted a novel subset of genes commonly modulated in 3D spheroids and potentially capable of driving ferroptosis protection in LUAD-CSCs, thus allowing to better understand the mechanisms of CSC-mediated drug resistance in tumors.

Background Multicenter precision oncology real-world evidence requires a substantial long-term investment by hospitals to prepare their data and align on common Clinical Research processes and medical definitions. Our team has developed a self-assessment framework to support hospitals and hospital networks to measure their digital maturity and better plan and coordinate those investments. From that framework, we developed PRISM for Cancer Outcomes: PRagmatic Institutional Survey and bench Marking. Objectives The primary objective was to develop PRISM as a tool for self-assessment of digital maturity in oncology hospitals and research networks; a secondary objective was to create an initial benchmarking cohort of >25 hospitals using the tool as input for future development. Methods PRISM is a 25-question semiquantitative self-assessment survey developed iteratively from expert knowledge in oncology real-world study delivery. It covers four digital maturity dimensions: (1) Precision oncology, (2) Clinical digital data, (3) Routine outcomes, and (4) Information governance and delivery. These reflect the four main data types and critical enablers for precision oncology research from routine electronic health records. Results During piloting with 26 hospitals from 19 European countries, PRISM was found to be easy to use and its semiquantitative questions to be understood in a wide diversity of hospitals. Results within the initial benchmarking cohort aligned well with internal perspectives. We found statistically significant differences in digital maturity, with Precision oncology being the most mature dimension, and Information governance and delivery the least mature. Conclusion PRISM is a light footprint benchmarking tool to support the planning of large-scale real-world research networks. It can be used to (i) help an individual hospital identify areas most in need of investment and improvement, (ii) help a network of hospitals identify sources of best practice and expertise, and (iii) help research networks plan research. With further testing, policymakers could use PRISM to better plan digital investments around the Cancer Mission and European Digital Health Space.

Triple negative breast cancer (TNBC) is an aggressive disease which currently has no effective therapeutic targets and prominent biomarkers. The Sperm Associated antigen 5 (SPAG5) is a mitotic spindle associated protein with oncogenic function in several human cancers. In TNBC, increased SPAG5 expression has been associated with tumor progression, chemoresistance, relapse, and poor clinical outcome. Here we show that high SPAG5 expression in TNBC is regulated by coordinated activity of YAP, mutant p53 and MYC. Depletion of YAP or mutant p53 proteins reduced SPAG5 expression and the recruitment of MYC onto SPAG5 promoter. Targeting of MYC also reduced SPAG5 expression and concomitantly tumorigenicity of TNBC cells. These effects of MYC targeting were synergized with cytotoxic chemotherapy and markedly reduced TNBC oncogenicity in SPAG5-expression dependent manner. These results suggest that mutant p53-MYC-SPAG5 expression can be considered as bona fide predictors of patient’s outcome, and reliable biomarkers for effective anticancer therapies.

Background The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. Methods 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. Results The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan–Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. Conclusions The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research.

We assessed the impact of DNA damage response and repair (DDR) biomarker expressions in 222 node-positive early breast cancer (BC) patients from a previous Phase III GOIM 9902 trial of adjuvant taxanes. At a median follow-up of 64 months, the original study showed no disease-free survival (DFS) or overall survival (OS) differences with the addition of docetaxel (D) to epirubicine-cyclophosphamide (EC). Immunohistochemistry was employed to assess the expression of DDR phosphoproteins (pATM, pATR, pCHK1, γH2AX, pRPA32, and pWEE1) in tumor tissue, and their association with clinical outcomes was evaluated through the Cox elastic net model. Over an extended follow-up of 234 months, we confirmed no significant differences in DFS or OS between patients treated with EC and those receiving D → EC. A DDR risk score, inversely driven by ATM and ATR expression, emerged as an independent prognostic factor for both DFS (HR = 0.41, p < 0.0001) and OS (HR = 0.61, p = 0.046). Further validation in a public adjuvant BC cohort was possible only for ATM, confirming its protective role. Overall, our findings confirm the potential role of the DDR pathway in BC prognostication and in shaping treatment strategies advocating for an integrated approach, combining molecular markers with clinical–pathological factors.

BackgroundFew data are available about the durability of the response, the induction of neutralizing antibodies, and the cellular response upon the third dose of the anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in hemato-oncological patients.ObjectiveTo investigate the antibody and cellular response to the BNT162b2 vaccine in patients with hematological malignancy.MethodsWe measured SARS-CoV-2 anti-spike antibodies, anti-Omicron neutralizing antibodies, and T-cell responses 1 month after the third dose of vaccine in 93 fragile patients with hematological malignancy (FHM), 51 fragile not oncological subjects (FNO) aged 80–92, and 47 employees of the hospital (healthcare workers, (HW), aged 23-66 years. Blood samples were collected at day 0 (T0), 21 (T1), 35 (T2), 84 (T3), 168 (T4), 351 (T pre-3D), and 381 (T post-3D) after the first dose of vaccine. Serum IgG antibodies against S1/S2 antigens of SARS-CoV-2 spike protein were measured at every time point. Neutralizing antibodies were measured at T2, T3 (anti-Alpha), T4 (anti-Delta), and T post-3D (anti-Omicron). T cell response was assessed at T post-3D.ResultsAn increase in anti-S1/S2 antigen antibodies compared to T0 was observed in the three groups at T post-3D. After the third vaccine dose, the median antibody level of FHM subjects was higher than after the second dose and above the putative protection threshold, although lower than in the other groups. The neutralizing activity of antibodies against the Omicron variant of the virus was tested at T2 and T post-3D. 42.3% of FHM, 80,0% of FNO, and 90,0% of HW had anti-Omicron neutralizing antibodies at T post-3D. To get more insight into the breadth of antibody responses, we analyzed neutralizing capacity against BA.4/BA.5, BF.7, BQ.1, XBB.1.5 since also for the Omicron variants, different mutations have been reported especially for the spike protein. The memory T-cell response was lower in FHM than in FNO and HW cohorts. Data on breakthrough infections and deaths suggested that the positivity threshold of the test is protective after the third dose of the vaccine in all cohorts.ConclusionFHM have a relevant response to the BNT162b2 vaccine, with increasing antibody levels after the third dose coupled with, although low, a T-cell response. FHM need repeated vaccine doses to attain a protective immunological response.