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.

Cutaneous metastasis from solid tumors is a rare event and usually represents a late occurrence in the natural history of an advanced visceral malignancy. Rarely, cutaneous metastasis has been described in colorectal cancer patients. The most frequent cutaneous site of colorectal metastasis is the surgical scar in the abdomen following the removal of the primary malignancy, followed by the extremities, perineum, head, neck, and penis. Metastases to the thigh and back of the trunk are anecdotical. Dermatological diagnosis of cutaneous metastasis can be quite complex, especially in unusual sites, such as in the facial skin or thorax and in cases of single cutaneous lesions since metastasis from colorectal cancer is not usually the first clinical hypothesis, leading to misdiagnosis. To date, due to the rarity of cutaneous metastasis from colorectal cancer, little evidence, most of which is based on case reports and very small case series, is currently available. Therefore, a better understanding of the clinic-pathological characteristics of this unusual metastatic site represents an unmet clinical need. We present a large series of 29 cutaneous metastases from colorectal cancer with particular concerns regarding anatomic localization and the time of onset with respect to primitive colorectal cancer and visceral metastases.

Nowadays, in the case of suspected prostate cancer (PCa), tissue needle biopsy remains the benchmark for diagnosis despite its invasiveness and poor tolerability, as serum prostate-specific antigen (PSA) is limited by low specificity. The aim of this proteomic study was to identify new diagnostic biomarkers in urine, an easily and non-invasively available sample, able to selectively discriminate cancer from benign prostatic hyperplasia (BPH), evaluating whether the presence of inflammation may be a confounding parameter. The analysis was performed by two-dimensional gel electrophoresis (2-DE), mass spectrometry (LC-MS/MS) and Enzyme-Linked Immunosorbent Assay (ELISA) on urine samples from PCa and BPH patients, divided into subgroups based on the presence or absence of inflammation. Significant quantitative and qualitative differences were found in the urinary proteomic profile of PCa and BPH groups. Of the nine differentially expressed proteins, only five can properly be considered potential biomarkers of PCa able to discriminate the two diseases, as they were not affected by the inflammatory process. Therefore, the proteomic research of novel and reliable urinary biomarkers of PCa should be conducted considering the presence of inflammation as a realistic interfering element, as it could hinder the detection of important protein targets.

Energy drinks (EDs) are non-alcoholic beverages containing high amounts of caffeine and other psychoactive substances. EDs also contain herbal extract whose concentration is usually unknown. EDs can have several adverse effects on different organs and systems, but their effects on the gastrointestinal (GI) tract have been poorly investigated. To determine the acute effects of EDs on the GI tract, we administered EDs, coffee, soda cola, or water to Sprague–Dawley rats (n = 7 per group, randomly assigned) for up to five days, and analyzed the histopathological changes in the GI tract. Data were compared among groups by Kruskal–Wallis or Mann–Whitney tests. We found that, while EDs did not cause any evident acute lesion to the GI tract, they triggered eosinophilic infiltration in the intestinal mucosa; treatment with caffeine alone at the same doses found in EDs leads to the same effects, suggesting that it is caffeine and not other substances present in the EDs that causes this infiltration. The interruption of caffeine administration leads to the complete resolution of eosinophilic infiltration. As no systemic changes in pro-inflammatory or immunomodulating molecules were observed, our data suggest that caffeine present in ED can cause a local, transient inflammatory status that recruits eosinophils.

Background: Although Ki-67 is not included among the grading criteria in the current WHO Classification of Tumours of the Central Nervous System (CNS), it provides valuable, albeit limited, prognostic information. Immunohistochemistry for Ki-67 can reveal uneven proliferation patterns and assist in the assessment of mitotic counts. Several studies indicate that meningiomas with a proliferation index > 4% show recurrence rates comparable to CNS WHO grade 2 (atypical) tumors, while tumors with an index > 20% are associated with mortality rates similar to CNS WHO grade 3 (anaplastic) meningiomas. Issues related to Ki-67 assessment include interobserver variability, the use of different cut-off values among pathologists, and the presence of a complex inflammatory tumour microenvironment, which may lead to an overestimation of the proliferative index (PI). Methods: In this study, we describe how Double Staining Immunohistochemistry (dIHC) with EMA/Ki-67 better highlights neoplastic meningothelial cells compared with single-stain evaluation. Furthermore, the application of Digital Pathology provides quantitative digital data that allow a more accurate assessment of proliferation. Results: Ki-67 expression varied by grade, with digital image analysis (dIHC) showing high agreement with manual assessments. dIHC improved accuracy in evaluating diagnostic and proliferative markers within tumor samples. Conclusions: dIHC combined with DP can support and standardize the evaluation of the proliferative index in meningiomas in routine diagnostic practice.

Little is known about the complex events driving host–pathogen and pathogen–pathogen interplay in polymicrobial infections. Using an in vitro model of a reconstituted vaginal epithelium (RVE) employing the A-431 cell line supplemented with synthetic vaginal fluid (SVF), we studied the consequences of single versus dual infections with Candida albicans and/or Herpes Simplex Virus-2 (HSV-2). Our data show (a) a relevant, SVF-enhanced expression of the differentiation marker cytokeratin 5/6 in the RVE; (b) the ability of Candida albicans to enhance HSV-2 in the dual infection model, with the virus titer almost doubling in the presence of SVF; (c) RVE damage (>20%), mostly attributable to Candida albicans and related to oxidative stress whether SVF is present; (d) the dysregulation of mucin-1, the production of which is enhanced (from 13 to 21 ng/mL) or impaired (from 21 to 10 ng/mL) in response to either SVF or infection, respectively; and (e) a partial-to-negligible cytokine response from the RVE, depending upon SVF presence. In conclusion, using an in vitro RVE model upgraded through the addition of synthetic vaginal fluid, we provide details on epithelial cell–pathogen–pathogen interaction, contributing to a better comprehension of the pathogenesis of polymicrobial infections at a mucosal level.