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Background: Currently, main treatment strategies for early-stage non-small cell lung cancer (ES-NSCLC) disease are surgery or stereotactic body radiation therapy (SBRT), with successful local control rates for both approaches. However, regional and distant failure remain critical in SBRT, and it is paramount to identify predictive factors of response to identify high-risk patients who may benefit from more aggressive approaches. The main endpoint of the MONDRIAN trial is to identify multi-omic biomarkers of SBRT response integrating information from the individual fields of radiomics, genomics and proteomics., Methods: MONDRIAN is a prospective observational explorative cohort clinical study, with a data-driven, bottom-up approach. It is expected to enroll 100 ES-NSCLC SBRT candidates treated at an Italian tertiary cancer center with well-recognized expertise in SBRT and thoracic surgery. To identify predictors specific to SBRT, MONDRIAN will include data from 200 patients treated with surgery, in a 1:2 ratio, with comparable clinical characteristics. The project will have an overall expected duration of 60 months, and will be structured into five main tasks: (i) Clinical Study; (ii) Imaging/ Radiomic Study, (iii) Gene Expression Study, (iv) Proteomic Study, (v) Integrative Model Building., Discussion: Thanks to its multi-disciplinary nature, MONDRIAN is expected to provide the opportunity to characterize ES-NSCLC from a multi-omic perspective, with a Radiation Oncology-oriented focus. Other than contributing to a mechanistic understanding of the disease, the study will assist the identification of high-risk patients in a largely unexplored clinical setting. Ultimately, this would orient further clinical research efforts on the combination of SBRT and systemic treatments, such as immunotherapy, with the perspective of improving oncological outcomes in this subset of patients., Trial Registration: The study was prospectively registered at clinicaltrials.gov (NCT05974475)., (© 2023. The Author(s).)

Background: Biobanks are vital research infrastructures aiming to collect, process, store, and distribute biological specimens along with associated data in an organized and governed manner. Exploiting diverse datasets produced by the biobanks and the downstream research from various sources and integrating bioinformatics and "omics" data has proven instrumental in advancing research such as cancer research. Biobanks offer different types of biological samples matched with rich datasets comprising clinicopathologic information. As digital pathology and artificial intelligence (AI) have entered the precision medicine arena, biobanks are progressively transitioning from mere biorepositories to integrated computational databanks. Consequently, the application of AI and machine learning on these biobank datasets holds huge potential to profoundly impact cancer research., Methods: In this paper, we explore how AI and machine learning can respond to the digital evolution of biobanks with flexibility, solutions, and effective services. We look at the different data that ranges from specimen-related data, including digital images, patient health records and downstream genetic/genomic data and resulting "Big Data" and the analytic approaches used for analysis., Results: These cutting-edge technologies can address the challenges faced by translational and clinical research, enhancing their capabilities in data management, analysis, and interpretation. By leveraging AI, biobanks can unlock valuable insights from their vast repositories, enabling the identification of novel biomarkers, prediction of treatment responses, and ultimately facilitating the development of personalized cancer therapies., Conclusions: The integration of biobanking with AI has the potential not only to expand the current understanding of cancer biology but also to pave the way for more precise, patient-centric healthcare strategies.

The recent advancements in breast cancer precision medicine have highlighted the urgency for the precise and reproducible characterization of clinically actionable biomarkers. Despite numerous standardization efforts, biomarker testing by conventional methodologies is challenged by several issues such as high inter-observer variabilities, the spatial heterogeneity of biomarkers expression, and technological heterogeneity. In this respect, artificial intelligence-based digital pathology approaches are being increasingly recognized as promising methods for biomarker testing and subsequently improved clinical management. Here, we provide an overview on the most recent advances for artificial intelligence-assisted biomarkers testing in breast cancer, with a particular focus on tumor-infiltrating lymphocytes, programmed death-ligand 1, phosphatidylinositol-3 kinase catalytic alpha, and estrogen receptor 1. Challenges and solutions for this integrative analysis in pathology laboratories are also provided., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

The process in which locally confined epithelial malignancies progressively evolve into invasive cancers is often promoted by unjamming, a phase transition from a solid-like to a liquid-like state, which occurs in various tissues. Whether this tissue-level mechanical transition impacts phenotypes during carcinoma progression remains unclear. Here we report that the large fluctuations in cell density that accompany unjamming result in repeated mechanical deformations of cells and nuclei. This triggers a cellular mechano-protective mechanism involving an increase in nuclear size and rigidity, heterochromatin redistribution and remodelling of the perinuclear actin architecture into actin rings. The chronic strains and stresses associated with unjamming together with the reduction of Lamin B1 levels eventually result in DNA damage and nuclear envelope ruptures, with the release of cytosolic DNA that activates a cGAS-STING (cyclic GMP-AMP synthase-signalling adaptor stimulator of interferon genes)-dependent cytosolic DNA response gene program. This mechanically driven transcriptional rewiring ultimately alters the cell state, with the emergence of malignant traits, including epithelial-to-mesenchymal plasticity phenotypes and chemoresistance in invasive breast carcinoma., (© 2022. The Author(s).)

One of the most relevant prognostic factors in cancer staging is the presence of lymph node (LN) metastasis. Evaluating lymph nodes for the presence of metastatic cancerous cells can be a lengthy, monotonous, and error-prone process. Owing to digital pathology, artificial intelligence (AI) applied to whole slide images (WSIs) of lymph nodes can be exploited for the automatic detection of metastatic tissue. The aim of this study was to review the literature regarding the implementation of AI as a tool for the detection of metastases in LNs in WSIs. A systematic literature search was conducted in PubMed and Embase databases. Studies involving the application of AI techniques to automatically analyze LN status were included. Of 4584 retrieved articles, 23 were included. Relevant articles were labeled into three categories based upon the accuracy of AI in evaluating LNs. Published data overall indicate that the application of AI in detecting LN metastases is promising and can be proficiently employed in daily pathology practice.

Background: Previous studies have provided a comprehensive picture of genomic alterations in primary and metastatic Hormone Receptor (HR)-positive, Human Epidermal growth factor Receptor 2 (HER2)-negative breast cancer (HR+ HER2- BC). However, the evolution of the genomic landscape of HR+ HER2- BC during adjuvant endocrine therapies (ETs) remains poorly investigated., Methods and Findings: We performed a genomic characterization of surgically resected HR+ HER2- BC patients relapsing during or at the completion of adjuvant ET. Using a customized panel, we comprehensively evaluated gene mutations and copy number variation (CNV) in paired primary and metastatic specimens. After retrieval and quality/quantity check of tumor specimens from an original cohort of 204 cases, 74 matched tumor samples were successfully evaluated for DNA mutations and CNV analysis. Along with previously reported genomic alterations, including PIK3CA, TP53, CDH1, GATA3 and ESR1 mutations/deletions, we found that ESR1 gene amplification (confirmed by FISH) and MAP3K mutations were enriched in metastatic lesions as compared to matched primary tumors. These alterations were exclusively found in patients treated with adjuvant aromatase inhibitors or LHRH analogs plus tamoxifen, but not in patients treated with tamoxifen alone. Patients with tumors bearing MAP3K mutations in metastatic lesions had significantly worse distant relapse-free survival (hazard ratio [HR] 3.4, 95% CI 1.52-7.70, p value 0.003) and worse overall survival (HR 5.2, 95% CI 2.10-12.8, p-value < 0.001) independently of other clinically relevant patient- and tumor-related variables., Conclusions: ESR1 amplification and activating MAP3K mutations are potential drivers of acquired resistance to adjuvant ETs employing estrogen deprivation in HR+ HER2- BC. MAP3K mutations are associated with worse prognosis in patients with metastatic disease., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Giancarlo Pruneri reports honoraria from Novartis, Roche, Lilly and Exact Science. Gabriele Zoppoli reports travel grants from Novartis and Pfizer, and reagents for research from Citiva and ThermoFisher Scientific. Andrea Vingiani reports honoraria from Roche and Lilly. Marco Colleoni reports Research Grant from Roche. Elisabtta Munzone reports travel grants from Roche, Pfizer, Lilly and Novartis and reports receiving consultancy fees from Eisai, Exact Sciences, MSD Oncology, Daiichi Sankyo/Astra Zeneca, Pfizer and Seagen. Giuseppe Viale has received grants from Roche/Genentech and Astra Zeneca for his institution; consulting fees from Roche/Genentech, Astra Zeneca, MDS Oncology and Daiichi Sanyko; honoraria for lectures from Roche/Genentech, Astra Zeneca and Daiichi Sanyko; support for attending meetings from Roche/Genentech; and has served on Advisory Boards for Roche/Genentech, Astra Zeneca, Pfizer, MDS Oncology and Novartis. Lorenzo Ferrando, Anna Garuti, Claudio Vernieri, Antonino Belfiore, Luca Agnelli, Gianpaolo Dagrada, Diana Ivanoiu, Giuseppina Bonizzi, Luana Lippolis, Martina Dameri, Francesco Ravera, Luca Magnani and Alberto Ballestrero have no conflict of interest to disclose., (Copyright: © 2023 Ferrando et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Biobanks are key research infrastructures aimed at the collection, storage, processing, and sharing of high-quality human biological samples and associated data for research, diagnosis, and personalized medicine. The Biobank for Translational and Digital Medicine Unit at the European Institute of Oncology (IEO) is a landmark in this field. Biobanks collaborate with clinical divisions, internal and external research groups, and industry, supporting patients' treatment and scientific progress, including innovative diagnostics, biomarker discovery, and clinical trial design. Given the central role of biobanks in modern research, biobanking standard operating procedures (SOPs) should be extremely precise. SOPs and controls by certified specialists ensure the highest quality of samples for the implementation of science-based, diagnostic, prognostic, and therapeutic personalized strategies. However, despite numerous efforts to standardize and harmonize biobanks, these protocols, which follow a strict set of rules, quality controls, and guidelines based on ethical and legal principles, are not easily accessible. This paper presents the biobank standard operating procedures of a large cancer center.

Somatic mutations in PIK3CA are present in ~40% breast cancers (BC); their detection in hormone receptor (HR)+/HER2- tumors allows for selecting patients with advanced disease eligible for PIK3CA targeting with alpelisib. The choice of what type of PIK3CA testing approach to adopt and which tissue sample to analyze is a new task in breast pathology. In this methodological study, we sought to assess the performance of next-generation sequencing (NGS) and RT-PCR for PIK3CA testing on archival formalin-fixed paraffin-embedded (FFPE) primary tumors and corresponding metastases. Sixteen HR+/HER2- BC with known PIK3CA -mutated status (ex. 7, 9, and 20) on metastatic samples by means of amplicon-based targeted NGS were selected, and n = 13 of these samples were re-tested with a commercially available CE-IVD RT-PCR assay. All available primary tumors ( n = 8) were tested with both methods. NGS detected mutations in all samples, while RT-PCR in n = 2 sample-pairs and overall, in n = 5/8 (62.5%) primary tumors and 7/13 (53.8%) metastases (κ = 0.09; 95% CI, -0.69-0.87). Slight agreement (κ = 0; 95% CI, -0.59-0.59) was observed between NGS and RT-PCR, with the former being generally more sensitive in cases with low DNA quality and quantity. Post hoc visual inspection of the RT-PCR data increased the concordance to 76.9%. Targeted NGS offers reliable and robust PIK3CA testing on both tumor and metastasis FFPE samples; the accuracy of RT-PCR depends on the DNA quantity and quality. In HR+/HER2- BC, both the selection of the PIK3CA testing strategy of FFPE tissues and which sample to analyze should consider several technical parameters and should be tailored for each case.

Loss of HER2 in previously HER2-positive breast tumors is not rare, occurring in up to 50% of breast cancers; however, clinical research and practice underestimate this issue. Many studies have reported the loss of HER2 after neoadjuvant therapy and at metastatic relapse and identified clinicopathological variables more frequently associated with this event. Nevertheless, the biological mechanisms underlying HER2 loss are still poorly understood. HER2 downregulation, intratumoral heterogeneity, clonal selection, and true subtype switch have been suggested as potential causes of HER2 loss, but translational studies specifically investigating the biology behind HER2 loss are virtually absent. On the other side, technical pitfalls may justify HER2 loss in some of these samples. The best treatment strategy for patients with HER2 loss is currently unknown. Considering the prevalence of this phenomenon and its apparent correlation with worse outcomes, we believe that correlative studies specifically addressing HER2 loss are warranted., Competing Interests: Curigliano G received honoraria for consulting/advisory role/speaker bureau and/or travel funding from Roche, Lilly, Bristol-Myers Squibb, Pfizer, Novartis, and Seagen; Criscitiello C received honoraria for consulting/advisory role/speaker bureau from Novartis, Eli-Lilly, Pfizer, MSD, Seagen and Roche; Fusco N from Merck Sharp and Dohme (MSD), Boehringer Ingelheim, Novartis, AstraZeneca, and Daiichi Sankyo. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© The Author(s) 2022.)

Digital Pathology is becoming more and more important to achieve the goal of precision medicine. Advances in whole-slide imaging, software integration, and the accessibility of storage solutions have changed the pathologists' clinical practice, not only in terms of laboratory workflow but also for diagnosis and biomarkers analysis. In parallel with the pathology setting advancement, translational medicine is approaching the unprecedented opportunities unrevealed by artificial intelligence (AI). Indeed, the increased usage of biobanks' datasets in research provided new challenges for AI applications, such as advanced algorithms, and computer-aided techniques. In this scenario, machine learning-based approaches are being propose in order to improve biobanks from biospecimens collection repositories to computational datasets. To date, evidence on how to implement digital biobanks in translational medicine is still lacking. This viewpoint article summarizes the currently available literature that supports the biobanks' role in the digital pathology era, and to provide possible practical applications of digital biobanks., Competing Interests: The authors declare that they have no conflicts of interest to report regarding the present study., (© 2021 Bonizzi.)

Biobanks are biorepositories that collect, process, store, catalog, and distribute human biological samples, and record the associated data. The role and action field of these strategic infrastructures for implementing precision medicine in translational research is continuously evolving. To ensure the optimal quality at all stages of biobanking, specific protocols are required and should be elaborated according to updated guidelines, recommendations, laws, and rules. This article illustrates the standard operating procedures, including protocols, troubleshooting, and quality controls, of a fully certified biobank in a referral Cancer Center. This model involves all clinical departments and research groups to support the dual mission of academic cancer centers, i.e. to provide high-quality care and high-quality research. All biobanking activities based on the type of biological specimens are detailed and the most tricky methodological aspects are discussed, from patients' informed consent to specimen management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bonizzi, Zattoni, Capra, Cassi, Taliento, Ivanova, Guerini-Rocco, Fumagalli, Monturano, Albini, Viale, Orecchia and Fusco.)

Background: Late distant recurrence is a challenge for the treatment of invasive lobular carcinoma (ILC) of the breast. Despite in-depth characterisation of primary ILC, the molecular landscape of metastatic ILC is still only partially understood., Methods: We retrospectively identified 38 ILC patients from the tissue banks of six European institutions. DNA extracted from patient matched primary and metastatic FFPE tissue blocks was whole genome sequenced to compute somatic copy number aberrations. This, in turn, was used to infer the evolutionary history of these patients., Findings: The data show different metastatic seeding patterns, with both an early and late divergence of the metastatic lineage observed in ILC. Additionally, cascading dissemination from a metastatic precursor was a dominant rule. Alterations in key cancer driver genes, such as TP53 or CCND1, were acquired early while additional aberrations were present only in the metastatic branch. In about 30% of the patients, the metastatic lineage harboured less aberrations than the primary tumour suggesting a period of tumour dormancy or prolonged adaptation at the distant site. This phenomenon was mostly observed in tumours from de novo metastatic patients., Interpretation: Our results provide insights into ILC evolution and offer potential paths for optimised ILC care., Funding: This work has received financial support from Les Amis de l'Institut Bordet, MEDIC, the Breast Cancer Research Foundation (BCRF) and the Belgian Fonds National de la Recherche Scientifique (F.R.S-FNRS)., Competing Interests: Declaration of interests C.S.: advisory board (receipt of honoraria or consultations fees): Astellas, Cepheid, Vertex, Seattle genetics, Puma, Amgen. Participation in company sponsored speaker's bureau: Eisai, Prime Oncology, Teva, Foundation Medicine. Other support (travel, accommodation expenses): Roche, Genentech, Pfizer (outside the submitted work). C.M. has received personal consultancy fees from Bayer, Roche, AstraZeneca, Daiichi Sankyo outside the scope of the submitted work; Grants from Italian Association for Cancer Research (AIRC); honoraria for lectures, presentations from Novartis. R.S. reports funding for research not related to the current manuscript from Breast Cancer Research Foundation; honoraria for lectures unrelated to the current manuscript from Bristol Myers Squibb; congress registration and travel not related to the current manuscript from Merck and Bristol Myers Squibb; participation on advisory boards unrelated to the current manuscript from Roche and Bristol Myers Squibb. R.S. has no conflicts of interests related to this project. G.E. reports consulting fees as general medical affairs consultancy from Thermofisher; role as secretary on the board of the scientific working group of the Belgian Society of Pathology and board member of the Belgian Society of Pathology not reimbursed. All other authors have no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Breast cancer during pregnancy (PrBC) is a rare tumor with only a little information on its immune landscape. Here, we sought to characterize the cellular composition of the tumor microenvironment (TME) of PrBC and identify its differences from early-onset breast cancer (EOBC) in non-pregnant women. A total of 83 PrBC and 89 EOBC were selected from our Institutional registry and subjected to tumor-infiltrating lymphocytes (TILs) profiling and immunohistochemistry for CD4, CD8, forkhead box P3 (FOXP3), and programmed death-ligand 1 (PD-L1) (clone 22C3). A significantly lower frequency of hormone receptor (HR)-positive tumors was observed in PrBC. The prevalence of low/null PD-L1 and CD8+TILs was higher in PrBC than in the controls, specifically in HR+/HER2- breast cancers. PrBC had a significantly higher risk of relapse and disease-related death, compared to EOBC. The presence of TILs and each TIL subpopulation were significantly associated with disease relapse. Moreover, the death rate was higher in PrBC with CD8+ TILs. The TME of PrBC is characterized by specific patterns of TIL subpopulations with significant biological and prognostic roles. Routine assessment of TILs and TILs subtyping in these patients would be a valid addition to the pathology report that might help identify clinically relevant subsets of women with PrBC.

The term "biobanking" is often misapplied to any collection of human biological materials (biospecimens) regardless of requirements related to ethical and legal issues or the standardization of different processes involved in tissue collection. A proper definition of biobanks is large collections of biospecimens linked to relevant personal and health information (health records, family history, lifestyle, genetic information) that are held predominantly for use in health and medical research. In addition, the International Organization for Standardization, in illustrating the requirements for biobanking (ISO 20387:2018), stresses the concept of biobanks being legal entities driving the process of acquisition and storage together with some or all of the activities related to collection, preparation, preservation, testing, analysing and distributing defined biological material as well as related information and data. In this review article, we aim to discuss the basic principles of biobanking, spanning from definitions to classification systems, standardization processes and documents, sustainability and ethical and legal requirements. We also deal with emerging specimens that are currently being generated and shaping the so-called next-generation biobanking, and we provide pragmatic examples of cancer-associated biobanking by discussing the process behind the construction of a biobank and the infrastructures supporting the implementation of biobanking in scientific research., (© 2021. The Author(s).)

In recent years, a growing interest has been directed towards oligometastatic prostate cancer (OMPC), as patients with three to five metastatic lesions have shown a significantly better survival as compared with those harboring a higher number of lesions. The efficacy of local ablative treatments directed on metastatic lesions (metastases-directed treatments) was extensively investigated, with the aim of preventing further disease progression and delaying the start of systemic androgen deprivation therapies. Definitive diagnosis of prostate cancer is traditionally based on histopathological analysis. Nevertheless, a bioptic sample-static in nature-inevitably fails to reflect the dynamics of the tumor and its biological response due to the dynamic selective pressure of cancer therapies, which can profoundly influence spatio-temporal heterogeneity. Furthermore, even with new imaging technologies allowing an increasingly early detection, the diagnosis of oligometastasis is currently based exclusively on radiological investigations. Given these premises, the development of minimally-invasive liquid biopsies was recently promoted and implemented as predictive biomarkers both for clinical decision-making at pre-treatment (baseline assessment) and for monitoring treatment response during the clinical course of the disease. Through liquid biopsy, different biomarkers, commonly extracted from blood, urine or saliva, can be characterized and implemented in clinical routine to select targeted therapies and assess treatment response. Moreover, this approach has the potential to act as a tissue substitute and to accelerate the identification of novel and consistent predictive analytes cost-efficiently. However, the utility of tumor profiling is currently limited in OMPC due to the lack of clinically validated predictive biomarkers. In this scenario, different ongoing trials, such as the RADIOSA trial, might provide additional insights into the biology of the oligometastatic state and on the identification of novel biomarkers for the outlining of true oligometastatic patients, paving the way towards a wider ideal approach of personalized medicine. The aim of the present narrative review is to report the current state of the art on the solidity of liquid biopsy-related analytes such as CTCs, cfDNA, miRNA and epi-miRNA, and to provide a benchmark for their further clinical implementation. Arguably, this kind of molecular profiling could refine current developments in the era of precision oncology and lead to more refined therapeutic strategies in this subset of oligometastatic patients.

Epigenetic aberrations have been recognized as important contributors to cancer onset and development, and increasing evidence suggests that linker histone H1 variants may serve as biomarkers useful for patient stratification, as well as play an important role as drivers in cancer. Although traditionally histone H1 levels have been studied using antibody-based methods and RNA expression, these approaches suffer from limitations. Mass spectrometry (MS)-based proteomics represents the ideal tool to accurately quantify relative changes in protein abundance within complex samples. In this study, we used a label-free quantification approach to simultaneously analyze all somatic histone H1 variants in clinical samples and verified its applicability to laser micro-dissected tissue areas containing as low as 1000 cells. We then applied it to breast cancer patient samples, identifying differences in linker histone variants patters in primary triple-negative breast tumors with and without relapse after chemotherapy. This study highlights how label-free quantitation by MS is a valuable option to accurately quantitate histone H1 levels in different types of clinical samples, including very low-abundance patient tissues.

Although antibody response to SARS-CoV-2 can be detected early during the infection, several outstanding questions remain to be addressed regarding the magnitude and persistence of antibody titer against different viral proteins and their correlation with the strength of the immune response. An ELISA assay has been developed by expressing and purifying the recombinant SARS-CoV-2 Spike Receptor Binding Domain (RBD), Soluble Ectodomain (Spike), and full length Nucleocapsid protein (N). Sera from healthcare workers affected by non-severe COVID-19 were longitudinally collected over four weeks, and compared to sera from patients hospitalized in Intensive Care Units (ICU) and SARS-CoV-2-negative subjects for the presence of IgM, IgG and IgA antibodies as well as soluble pro-inflammatory mediators in the sera. Non-hospitalized subjects showed lower antibody titers and blood pro-inflammatory cytokine profiles as compared to patients in Intensive Care Units (ICU), irrespective of the antibodies tested. Noteworthy, in non-severe COVID-19 infections, antibody titers against RBD and Spike, but not against the N protein, as well as pro-inflammatory cytokines decreased within a month after viral clearance. Thus, rapid decline in antibody titers and in pro-inflammatory cytokines may be a common feature of non-severe SARS-CoV-2 infection, suggesting that antibody-mediated protection against re-infection with SARS-CoV-2 is of short duration. These results suggest caution in using serological testing to estimate the prevalence of SARS-CoV-2 infection in the general population.

The natural history of ductal carcinoma in situ (DCIS) is highly variable and difficult to predict. Biomarkers are needed to stratify patients with DCIS for adjuvant therapy. We investigated the prognostic and predictive relevance of cell cycle progression (CCP) score in women with DCIS. We measured the expression of 23 genes involved in CCP with quantitative RT-PCR on RNA extracted from formalin-fixed paraffin-embedded tumor samples, and assessed the correlation of a predefined score with histopathologic features and recurrence. The signature was analyzed in a cohort of 909 consecutive DCIS with full histopathological features treated in a single institution. The main outcome measure was ipsilateral breast event (IBE) as first event observed, be it in situ or invasive. Median follow-up time was 8.7 years (IQR 6.5-10.5 years). There were 150 ipsilateral IBEs, 84 (56%) of which were invasive. In the first 5 years of follow-up, the score provided statistically different findings (p = 0.009), with IBE rates of 14.7% (95% CI, 10.4-19.7) for the highest quartile of CCP score (Q4) and 8.7% (95% CI, 6.7-11.0) for the lowest quartiles (Q1-3). The prognostic value for IBEs approached significance also in women treated with mastectomy (adjusted hazard ratio [HR] Q4 vs. Q1-3 = 2.60; 95% CI: 0.96-7.08; P = 0.06). Radiotherapy provided a greater benefit in women with higher CCP score. In addition, Q4 predicted a different risk after tamoxifen depending on menopausal status, with a beneficial trend on IBEs in postmenopausal women (HR 0.30; 95% CI, 0.07-1.39), and an opposite trend in premenopausal women (HR 1.68; 95% CI, 0.38-7.44) (P-interaction = 0.03). The results of this study provide for the first time the evidence that CCP score is a prognostic marker, which, after additional validation, could have an important role in personalizing the management of DCIS.

Background: In breast cancer (BC), axillary lymph node (ALN) involvement is one of the strongest adverse prognostic factors. However, it is unclear whether loco-regional lymph node deposits are effectively the root of secondary metastases or only an indicator of competence of the primary tumour to spread to distant organs., Methods: Here, we investigated the evolutionary trajectories of primary tumour, ALN and distant metastasis samples from 16 estrogen-receptor (ER)-positive lymph node-positive BC patients. Low-pass whole genome sequencing was performed to infer somatic copy number aberrations and the phylogenetic profiles for all patients were obtained., Findings: We show that lymph nodes and distant metastases shared a common origin in only 25% of the cases highlighting that the predominant route of metastatic dissemination is the direct seeding of tumour cells from the primary tumour to distant organs, independently of lymph node metastasis. Noticeably, patients sharing a common origin significantly have worse prognosis., Interpretation: Our results shed light on the routes on which tumour cells metastasize and their role in disease progression in ER-positive BC., Funding: This work has received financial support from Les Amis de l'Institut Bordet, MEDIC, the Breast Cancer Research Foundation (BCRF), the Belgian Fonds National de la Recherche Scientifique (F.R.S-FNRS) and from a grant of the Région Wallonne., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Prostate cancer (PCa) is the second most common cancer among men. New imaging-modalities have increased the diagnosed patients with limited number of metastasis after primary curative therapy, introducing so-called oligometastatic state. Stereotactic body radiotherapy (SBRT) is emerging as a low-toxicity treatment to erase PCa localizations and postpone androgen deprivation therapy (ADT). A deeper understanding of the predictive role of biomarkers is desirable for a targeted treatment selection and surveillance programs. The aims of the RADIOSA trial are: 1. Compare SBRT +/- ADT for oligorecurrent-castration-sensitive PCa (OCS-PCa) in terms of efficacy, toxicity and Quality of Life (QoL). 2. Develop biology/imaging based prognostic tool that allows identifying OCS-PCa subclasses., Methods: This is a randomized phase II clinical trial, recruiting 160 OCS-PCa in 3 years, with progression-free survival (PFS) as primary endpoint. Three tasks will be developed: 1. Randomized clinical study (3 years for accrual and 2 years for follow-up and data analysis); 2. Imaging study, including imaging registration and METastasis Reporting and Data System (MET-RADS) criteria; 3. Pre-clinical study, development of a biobank of blood samples for the analysis of neutrophil-to-lymphocyte ratio and preparatory for a subsequent miRNA profiling. We aim to determine which arm is justified for testing in a subsequent Phase III trial. A decision-tree algorithm, based on prognosis, biological phenotype and imaging profile, will be developed., Discussion: Recruiting will start in July 2019. SBRT will allow obtaining excellent PFS, local control, QoL and low toxicity. In SBRT arm, ADT deferral will allow for a drug-holiday, delaying the detrimental impact on QoL. A sufficient number of blood samples will be collected to perform biological patient profiling. A stratification tool will be established with an analysis of morphological and functional imaging, based on the use of MET-RADS criteria. So, in conclusion, RADIOSA aims to define the optimal management of bone/nodal PCa relapses in a SBRT regimen. This study will increase our knowledge on low-burden metastatic PCa in the era of high precision and high technology personalized medicine, offering highly effective therapy in terms of clinical outcome and cost-effectiveness., Trial Registration: The RADIOSA study was prospectively registered at clinicaltrials.gov ( NCT03940235 , May 2019).