Multicenter International Study of the Consensus Immunoscore for the Prediction of Relapse and Survival in Early-Stage Colon Cancer.

Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4−82.6), 88.1% (95%-CI, 85.7−90.4), 93.4% (95%-CI, 91.1−95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18−0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17−0.50); p < 0.0001) of the patient's gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01−0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.

BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.

Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women. Advances in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer patients. However, the manual inspection of tissue slides by pathologists is cumbersome, time-consuming and is subject to significant inter- and intra-observer variability. Recently, the advent of whole-slide scanning systems has empowered the rapid digitization of pathology slides and enabled the development of Artificial Intelligence (AI)-assisted digital workflows. However, AI techniques, especially Deep Learning, require a large amount of high-quality annotated data to learn from. Constructing such task-specific datasets poses several challenges, such as data-acquisition level constraints, time-consuming and expensive annotations and anonymization of patient information. In this paper, we introduce the BReAst Carcinoma Subtyping (BRACS) dataset, a large cohort of annotated Hematoxylin and Eosin (H&E)-stained images to advance AI development in the automatic characterization of breast lesions. BRACS contains 547 Whole-Slide Images (WSIs) and 4539 Regions Of Interest (ROIs) extracted from the WSIs. Each WSI and respective ROIs are annotated by the consensus of three board-certified pathologists into different lesion categories. Specifically, BRACS includes three lesion types, i.e., benign, malignant and atypical, which are further subtyped into seven categories. It is, to the best of our knowledge, the largest annotated dataset for breast cancer subtyping both at WSI and ROI levels. Furthermore, by including the understudied atypical lesions, BRACS offers a unique opportunity for leveraging AI to better understand their characteristics. We encourage AI practitioners to develop and evaluate novel algorithms on the BRACS dataset to further breast cancer diagnosis and patient care. Database URL: https://www.bracs.icar.cnr.it/.

Multi-gene panel testing increases germline predisposing mutations' detection in a cohort of breast/ovarian cancer patients from Southern Italy.

Breast cancer is the most common neoplasia in females worldwide, about 10% being hereditary/familial and due to DNA variants in cancer-predisposing genes, such as the highly penetrant BRCA1/BRCA2 genes. However, their variants explain up to 25% of the suspected hereditary/familial cases. The availability of NGS methodologies has prompted research in this field. With the aim to improve the diagnostic sensitivity of molecular testing, a custom designed panel of 44 genes, including also non-coding regions and 5' and 3' UTR regions, was set up. Here, are reported the results obtained in a cohort of 64 patients, including also few males, from Southern Italy. All patients had a positive personal and/or familial history for breast and other cancers, but tested negative to routine BRCA analysis. After obtaining their written informed consent, a genomic DNA sample/patient was used to obtain an enriched DNA library, then analyzed by NGS. Sequencing data analysis allowed the identification of pathogenic variants in 12 of tested patients (19%). Interestingly, MUTYH was the most frequently altered gene, followed by RNASEL, ATM, MSH6, MRE11A, and PALB2 genes. The reported resultsreinforce the need for enlarged molecular testing beyond BRCA genes, at least in patients with a personal and familial history, strongly suggestive for a hereditary/familial form. This gives also a hint to pursue more specific precision oncology therapy.

Glyoxalase 1 knockdown induces age-related ß-cell dysfunction and glucose intolerance in mice.

Tight control of glycemia is a major treatment goal for type 2 diabetes mellitus (T2DM). Clinical studies indicated that factors other than poor glycemic control may be important in fostering T2DM progression. Increased levels of methylglyoxal (MGO) associate with complications development, but its role in the early steps of T2DM pathogenesis has not been defined. Here, we show that MGO accumulation induces an age-dependent impairment of glucose tolerance and glucose-stimulated insulin secretion in mice knockdown for glyoxalase 1 (Glo1KD). This metabolic alteration associates with the presence of insular inflammatory infiltration (F4/80-positive staining), the islet expression of senescence markers, and higher levels of cytokines (MCP-1 and TNF-α), part of the senescence-activated secretory profile, in the pancreas from 10-month-old Glo1KD mice, compared with their WT littermates. In vitro exposure of INS832/13 ß-cells to MGO confirms its casual role on ß-cell dysfunction, which can be reverted by senolytic treatment. These data indicate that MGO is capable to induce early phenotypes typical of T2D progression, paving the way for novel prevention approaches to T2DM.

Microbiome composition indicate dysbiosis and lower richness in tumor breast tissues compared to healthy adjacent paired tissue, within the same women.

BACKGROUND: Breast cancer (BC) is the most common malignancy in women, in whom it reaches 20% of the total neoplasia incidence. Most BCs are considered sporadic and a number of factors, including familiarity, age, hormonal cycles and diet, have been reported to be BC risk factors. Also the gut microbiota plays a role in breast cancer development. In fact, its imbalance has been associated to various human diseases including cancer although a consequential cause-effect phenomenon has never been proven. METHODS: The aim of this work was to characterize the breast tissue microbiome in 34 women affected by BC using an NGS-based method, and analyzing the tumoral and the adjacent non-tumoral tissue of each patient. RESULTS: The healthy and tumor tissues differed in bacterial composition and richness: the number of Amplicon Sequence Variants (ASVs) was higher in healthy tissues than in tumor tissues (p = 0.001). Moreover, our analyses, able to investigate from phylum down to species taxa for each sample, revealed major differences in the two richest phyla, namely, Proteobacteria and Actinobacteria. Notably, the levels of Actinobacteria and Proteobacteria were, respectively, higher and lower in healthy with respect to tumor tissues. CONCLUSIONS: Our study provides information about the breast tissue microbial composition, as compared with very closely adjacent healthy tissue (paired samples within the same woman); the differences found are such to have possible diagnostic and therapeutic implications; further studies are necessary to clarify if the differences found in the breast tissue microbiome are simply an association or a concausative pathogenetic effect in BC. A comparison of different results on similar studies seems not to assess a universal microbiome signature, but single ones depending on the environmental cohorts' locations.

Hierarchical graph representations in digital pathology.

Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on the phenotype and topological distribution of constituting histological entities. Thus, adequate tissue representations for encoding histological entities is imperative for computer aided cancer patient care. To this end, several approaches have leveraged cell-graphs, capturing the cell-microenvironment, to depict the tissue. These allow for utilizing graph theory and machine learning to map the tissue representation to tissue functionality, and quantify their relationship. Though cellular information is crucial, it is incomplete alone to comprehensively characterize complex tissue structure. We herein treat the tissue as a hierarchical composition of multiple types of histological entities from fine to coarse level, capturing multivariate tissue information at multiple levels. We propose a novel multi-level hierarchical entity-graph representation of tissue specimens to model the hierarchical compositions that encode histological entities as well as their intra- and inter-entity level interactions. Subsequently, a hierarchical graph neural network is proposed to operate on the hierarchical entity-graph and map the tissue structure to tissue functionality. Specifically, for input histology images, we utilize well-defined cells and tissue regions to build HierArchical Cell-to-Tissue (HACT) graph representations, and devise HACT-Net, a message passing graph neural network, to classify the HACT representations. As part of this work, we introduce the BReAst Carcinoma Subtyping (BRACS) dataset, a large cohort of Haematoxylin & Eosin stained breast tumor regions-of-interest, to evaluate and benchmark our proposed methodology against pathologists and state-of-the-art computer-aided diagnostic approaches. Through comparative assessment and ablation studies, our proposed method is demonstrated to yield superior classification results compared to alternative methods as well as individual pathologists. The code, data, and models can be accessed at https://github.com/histocartography/hact-net.

Role and evaluation of pathologic response in early breast cancer specimens after neoadjuvant therapy: consensus statement.

Pathologic evaluation of early breast cancer after neoadjuvant therapy is essential to provide prognostic information based on tumor response to treatment (pathologic complete response [pCR] or non-pCR) and to inform therapy decisions after surgery. To harmonize the pathologist's handling of surgical specimens after neoadjuvant therapy, a panel of experts in breast cancer convened to developed a consensus on six main topics: (1) definition of pCR, (2) required clinical information, (3) gross examination and sampling, (4) microscopic examination, (5) evaluation of lymph node status, and (6) staging of residual breast tumor. The resulting consensus statements reported in this document highlight the role of an accurate evaluation of tumor response and define the minimum requirements to standardize the assessment of breast cancer specimens after neoadjuvant therapy.

Strategies to evaluate outcomes in long-COVID-19 and post-COVID survivors.

SARS-CoV-2 infection can impact the physical, cognitive, mental health of patients, especially in those recovered in intensive care units. Moreover, it was proved that the effects of the virus may persist for weeks or months. The term long-COVID or post-COVID syndrome is commonly used for indicating a variety of physical and psychological symptoms that continue after the resolution of the acute phase. This narrative review is aimed at providing an updated overview of the impact of physical, cognitive, and psychological health disorders in COVID-19 survivors, by summarizing the data already published in literature in the last year. Studies cited were found through PubMed searches. We also presented an overview of the post-COVID-19 health consequences on three important aspects: nutritional status, neurological disorders, and physical health. Moreover, to activate a correct health planning policy, a multidisciplinary approach for addressing the post- COVID-19 issue, has been proposed. Finally, the involvement of health professionals is necessary even after the pandemic, to reduce expected post-pandemic psychosocial responses and mental health disorders.

The Role of lncRNAs in Rare Tumors with a Focus on HOX Transcript Antisense RNA (HOTAIR).

Rare cancers are identified as those with an annual incidence of fewer than 6 per 100,000 persons and includes both epithelial and stromal tumors from different anatomical areas. The advancement of analytical methods has produced an accurate molecular characterization of most human cancers, suggesting a "molecular classification" that has allowed the establishment of increasingly personalized therapeutic strategies. However, the limited availability of rare cancer samples has resulted in very few therapeutic options for these tumors, often leading to poor prognosis. Long non coding RNAs (lncRNAs) are a class of non-coding RNAs mostly involved in tumor progression and drug response. In particular, the lncRNA HOX transcript antisense RNA (HOTAIR) represents an emergent diagnostic, prognostic and predictive biomarker in many human cancers. The aim of this review is to highlight the role of HOTAIR in rare cancers, proposing it as a new biomarker usable in the management of these tumors.

Correction: Mediterranean diet and quality of life in women treated for breast cancer: A baseline analysis of DEDiCa multicentre trial.

[This corrects the article DOI: 10.1371/journal.pone.0239803.].

Prospective Evaluation of Radiotherapy-Induced Immunologic and Genetic Effects in Colorectal Cancer Oligo-Metastatic Patients with Lung-Limited Disease: The PRELUDE-1 Study.

BACKGROUND: in recent years, the management of advanced colorectal cancer (CRC) has been greatly improved with integrated strategies including stereotactic radiation therapy (SRT). The administration of SRT has been demonstrated, particularly in oligo-metastatic (om) CRC, to be a safe and effective option. Interestingly, it has been demonstrated that SRT can induce regression of tumors in non-irradiated regions ("abscopal effect") through stimulation of anti-tumor immune effects ("radiation-induced immunity"). We have recently shown that lung-limited omCRC is characterized by regression of tumor clones bearing specific key driver gene mutations. AIMS: to assess the genetic evolution on tumor cancer cells induced by SRT in lung-limited omCRC. Secondary objectives included descriptions of the abscopal effect, responses' duration, toxicity, and progression-free survival. A translational research will be performed to evaluate tumor genetic evolution (through liquid biopsies and Next Generation Sequencing), HLA class I repertoire, peripheral immune cells, and cytokine dynamics. METHODS: PRELUDE-1 is a prospective translational study. SRT will be administered only to the largest nodule (with a maximum diameter ≤ 25 mm) in omCRC with two or three radiologically evident lesions. The sample size is based on the innovative hypothesis that radiation-induced immunity could induce regression of tumor clones bearing KRAS oncogene mutations. According to the binomial test, considering the frequency of KRAS mutations and assuming a probability of mutant KRAS→wild type KRAS of p0 = 0.0077, with α = 0.05 and 1-ß = 0.60, the final sample size is 25 patients.

HLA Does Not Impact on Short-Medium-Term Antibody Response to Preventive Anti-SARS-Cov-2 Vaccine.

The response to anti-SARS-Cov-2 preventive vaccine shows high interpersonal variability at short and medium term. One of the explanations might be the individual HLA allelic variants. Indeed, B cell response is stimulated and sustained by CD4+ T helper cells activated by antigens presented by HLA-class II alleles on antigen-presenting cells (APCs). The impact of the number of antigens binding to HLA class-II alleles on the antibody response to the COVID vaccine has been assessed in a cohort of 56 healthcare workers who received the full schedule of the Pfizer-BioNTech BNT162b2 vaccine. Such vaccine is based on the entire spike protein of the SARS-CoV-2. Ab titers have been evaluated 2 weeks after the first dose as well as 2 weeks and 4 months after the boosting dose. HLA-DRB1 and DBQ1 for each of the vaccinees have been assessed, and strong binders have been predicted. The analysis showed no significant correlation between the short-medium-term Ab titers and the number of strong binders (SB) for each individual. These results indicate that levels of Ab response to the spike glycoprotein is not dependent on HLA class II allele, suggesting an equivalent efficacy at global level of the currently used vaccines. Furthermore, the pattern of persistence in Ab titer does not correlate with specific alleles or with the number of SBs.

Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes' iTNF-α Expression.

In December 2019, a novel coronavirus, "SARS-CoV-2", was recognized as the cause of coronavirus disease 2019 (COVID-19). Several studies have explored the changes and the role of inflammatory cells and cytokines in the immunopathogenesis of the disease, but until today, the results have been controversial. Based on these premises, we conducted a retrospective assessment of monocyte intracellular TNF-α expression (iTNF-α) and on the frequencies of lymphocyte sub-populations in twenty-five patients with moderate/severe COVID-19. We found lymphopenia in all COVID-19 infected subjects compared to healthy subjects. On initial observation, in patients with favorable outcomes, we detected a high absolute eosinophil count and a high CD4+/CD8+ T lymphocytes ratio, while in the Exitus Group, we observed high neutrophil and CD8+ T lymphocyte counts. During infection, in patients with favorable outcomes, we observed a rise in the lymphocyte count, in the monocyte and in Treg lymphocyte counts, and in the CD4+ and in CD8+ T lymphocytes count but a reduction in the CD4+/CD8+ T lymphocyte ratio. Instead, in the Exitus Group, we observed a reduction in the Treg lymphocyte counts and a decrease in iTNF-α expression. Our preliminary findings point to a modulation of the different cellular mediators of the immune system, which probably play a key role in the outcomes of COVID-19.

Organ Sparing for Locally Advanced Rectal Cancer after Neoadjuvant Treatment Followed by Electrochemotherapy.

BACKGROUND: Currently, 45-55% of rectal cancer patients receive preoperative chemo- radio-therapy for Locally Advanced Rectal Cancer (LARC). The idea of our study is to use Electrochemotherapy (ECT) before surgery, in patients with major clinical response after neoadjuvant therapy, to allow for a more conservative surgical approach. OBJECTIVE: To evaluate the increase of the complete response rate after neoadjuvant treatment in LARC and to spare organ function due to total mesorectal excision (TME). PATIENTS AND METHODS: This is a Phase II randomized controlled trial enrolling 70 patients that will be developed in two stages. In the first step, 28 patients will be enrolled: 14 of these will receive ECT for four weeks after neo-adjuvant treatment and then local excision (treatment group) and 14 patients will receive neo-adjuvant treatment and then local excision (control group). If an increase of response rate is observed in the first stage, and/or feasibility/safety is demonstrated, the second stage of the trial will be performed, enrolling an additional 42 patients. The treatment response. in both the control arm and the treatment arm, will be assessed using the histopathological tumor regression grade on tissue specimens after local excision.

The SGLT-2 inhibitor empagliflozin improves myocardial strain, reduces cardiac fibrosis and pro-inflammatory cytokines in non-diabetic mice treated with doxorubicin.

BACKGROUND: Empagliflozin (EMPA), a selective inhibitor of the sodium glucose co-transporter 2, reduced the risk of hospitalization for heart failure and cardiovascular death in type 2 diabetic patients in the EMPA-REG OUTCOME trial. Recent trials evidenced several cardio-renal benefits of EMPA in non-diabetic patients through the involvement of biochemical pathways that are still to be deeply analysed. We aimed to evaluate the effects of EMPA on myocardial strain of non-diabetic mice treated with doxorubicin (DOXO) through the analysis of NLRP3 inflammasome and MyD88-related pathways resulting in anti-apoptotic and anti-fibrotic effects. METHODS: Preliminary cellular studies were performed on mouse cardiomyocytes (HL-1 cell line) exposed to doxorubicin alone or combined to EMPA. The following analysis were performed: determination of cell viability (through a modified MTT assay), study of intracellular ROS production, lipid peroxidation (quantifying intracellular malondialdehyde and 4-hydroxynonenal), intracellular Ca2+ homeostasis. Moreover, pro-inflammatory studies were also performed: expression of NLRP3 inflammasome, MyD88 myddosome and p65/NF-κB associated to secretion of cytokines involved in cardiotoxicity (Interleukins 1ß, 8, 6). C57Bl/6 mice were untreated (Sham, n = 6) or treated for 10 days with doxorubicin (DOXO, n = 6), EMPA (EMPA, n = 6) or doxorubicin combined to EMPA (DOXO-EMPA, n = 6). DOXO was injected intraperitoneally. Ferroptosis and xanthine oxidase were studied before and after treatments. Cardiac function studies, including EF, FS and radial/longitudinal strain were analysed through transthoracic echocardiography (Vevo 2100). Cardiac fibrosis and apoptosis were histologically studied through Picrosirius red and TUNEL assay, respectively and quantified through pro-collagen-1α1, MMP-9 and Caspase-3 expression. Tissue NLRP3, MyD88 and cytokines were also quantified before and after treatments through ELISA methods. RESULTS: Cardiomyocytes exposed to doxorubicin increased the intracellular Ca2+ content and expression of several pro-inflammatory markers associated to cell death; co-incubation with EMPA reduced significantly the magnitude of the effects. In preclinical study, EMPA increased EF and FS compared to DOXO groups (p < 0.05), prevented the reduction of radial and longitudinal strain after 10 days of treatment with doxorubicin (RS) 30.3% in EMPA-DOXO vs 15.7% in DOXO mice; LS - 17% in EMPA-DOXO vs - 11.7% in DOXO mice (p < 0.001 for both). Significant reductions in ferroptosis, xanthine oxidase expression, cardiac fibrosis and apoptosis in EMPA associated to DOXO were also seen. A reduced expression of pro-inflammatory cytokines, NLRP3, MyD88 and NF-kB in heart, liver and kidneys was also seen in DOXO-EMPA group compared to DOXO (p < 0.001). CONCLUSION: EMPA reduced ferroptosis, fibrosis, apoptosis and inflammation in doxorubicin-treated mice through the involvement of NLRP3 and MyD88-related pathways, resulting in significant improvements in cardiac functions. These findings provides the proof of concept for translational studies designed to reduce adverse cardiovascular outcomes in non-diabetic cancer patients treated with doxorubicin.

Aberrant Expression of Long Non Coding RNA HOTAIR and De-Regulation of the Paralogous 13 HOX Genes Are Strongly Associated with Aggressive Behavior of Gastro-Entero-Pancreatic Neuroendocrine Tumors.

Gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NENs) are rare diseases occurring in the gastrointestinal tract and pancreas. They are characterized by the loss of epithelial tubular gland elements, and by the increased expression of neuroendocrine markers. GEP-NENs are subdivided into two histo-pathological types, gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) and gastro-entero-pancreatic neuroendocrine carcinomas (GEP-NECs). According to WHO 2017 and 2019 classification criteria are graded and staged in four categories, NET-G1, NET-G2, NET-G3, and NEC-G3. The molecular characterization of these tumors can be fundamental for the identification of new diagnostic, prognostic and predictive biomarkers. The main purpose of this study was to analyze the expression of the paralogous 13 HOX genes, normally involved in embryogenic development and frequently deregulated in human cancers, and of the HOX regulating lncRNA HOTAIR in GEP-NENs. The expression of HOX genes is gradually lost in the transition from GEP NET G1 to NET/NEC G3 tumors, while HOTAIR expression, inversely correlated with HOX genes expression and weakly expressed in low-grade GEP NENs, becomes aberrant in NET G3 and NEC G3 categories. Our data highlights their potential role in the molecular stratification of GEP-NENs by suggesting new prognostic markers and potential therapeutic targets.

Risk Analysis in Healthcare Organizations: Methodological Framework and Critical Variables.

PURPOSE: A risk assessment matrix is a widely used tool for analyzing, assessing and setting priorities in risk management in many fields. This paper overviews critical variables, advantages, disadvantages, strengths and weaknesses of this tool, according to the ISO 31000 risk management framework. RESULTS: Risk assessment is one of the key stages in the Risk Management Process and involves specific steps: identifying hazards, analyzing and evaluating all possible risks. Several methods are developed to assess risks in the literature. A risk matrix method, also called "decision matrix risk assessment (DMRA) technique", is a systematic approach used to determine the risk level and to compare different risks and define which threats need to be controlled first. The actors involved in risk assessment are called on to manage different issues related to the choice of the most appropriate methodological approach, the assessment of the adequacy of the existing control measures, the articulation of risk consequence domains, the definition of the impact-consequences, the explanation of risk likelihood scales and the development of a risk matrix. CONCLUSION: We highlighted a number of recommendations in order to address these issues, especially useful when healthcare organizations provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms on their use.

Basic principles of biobanking: from biological samples to precision medicine for patients.

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.