The exact worldwide incidence of Burkitt’s lymphoma is not known. There are three distinct clinical variants of Burkitt’s lymphoma, each manifesting differences in epidemiology, clinical presentation, morphology, biology and genetic features: the endemic (African), the sporadic (non-endemic), and the immunodeficiency-associated form. In particular, we reported data regarding Burkitt’s lymphoma incidence in the world and across different European countries. Finally, we described clinic-pathological data of 48 Burkitt’s lymphomas occurred in Italy from 2003 to 2013, in 4 different hospitals, two of which located in east side, and the other ones located in the west-coast. Forty Burkitt’s lymphomas occurs in children (age range 3–12), and 8 were adulthood Burkitt’s lymphomas (age range 18–87). In the pediatric group the Male:Female ratio (M:F) was of 4:1, whereas the group of the adult patients has a M:F of 1:1.67. Immunohistochemical detection of Latent Membrane Protein 1 (LMP1) expression and Epstein-Barr virus Encoded RNA (EBER) In Situ Hybridization (ISH) procedures have been performed. Lymphocyte B monoclonal spread has been demonstrated using a Polymerase Chain Reaction (PCR) based method to amplify Fragment Restriction FR1, FR2 and FR3 immunoglobulin heavy chains DNA fragments. Only 38 cases out of 48 were analyzed for LMP-1 showing various percentage of stained cells in 47.4% of the patients. Considering ISH for EBER detection results: – 1 out 2 (50%) adult analyzed cases was positive, with 50% of stained tumor cells (this patient was a 22 years old female, coming from Napoli); – 15 out 24 (62.5%) children analyzed Burkitt’s lymphomas resulted as positive for EBER; – the overall positivity has been observed in 16/26 Burkitt’s lymphomas (61.53%). – Finally, EBV has been detected in children and adult patients, one of them with deregulation of the oncogene c-MYC by chromosomal translocation.

Background: A large number of renal cancer patients shows poor or partial response to chemotherapy and the mechanisms have not been still understood. Multi-drug resistance is the principal mechanism by which many cancers develop resistance to chemotherapic drugs. The role of the multi-drug resistant transporter (MDR-1/P-glycoprotein), the gene product of MDR-1, and that one of the so-called multi-drug resistance associated protein (MRP), two energy-dependent efflux pumps, are commonly known to confer drug resistance. We studied MDR-1 expression in selected cases of renal cell carcinoma (RCC), clear cell type, with long-term follow-up, in order to establish its prognostic role and its possible contribution in the choice of post-surgical therapy. Methods: MDR-1 has been studied by standard LSAB-HRP immunohistochemical technique, in paraffin embedded RCC samples. Protein expression has been compared to clinical and histopathological data and to disease specific survival of RCC patients, by Kaplan-Meier curve and Cox multivariate regression analyses. Results: Two groups of RCCs were obtained by esteeming MDR-1 expression and disease specific survival (obtained with Kaplan-Meier curve and Cox multivariate regression analyses): the first one presents low or absent MDR-1 expression and good survival; the second one is characterized by high MDR-1 expression and significant poor outcome (p < 0.05). Afterwards, we have found disease specific survival, adjusted for stages and independent of therapy: this difference of survival rates was statistically significant (p < 0.05). Stage adjusted disease specific survival rate, according to MDR-1 expression and therapy in patients affected by RCC in early stage (stage I), has revealed that the group of patients with high MDR-1 expression and without adjuvant therapy showed poor survival (p < 0.05). Cox multivariate regression analysis has confirmed that, in our cohort of RCC (clear cell type) patients, the strong association between MDR-1 and worse outcome is independent not only of the adjuvant therapy, but also of the other prognostic parameters (p < 0.05). Conclusion: In our opinion, the results of this study well prove the relationship between MDR-1 expression and worse clinical prognosis in RCC, because MDR-1 over-expressing RCCs can be considered a group of tumours with a more aggressive behavior. This finding outlines a possible role of MDR-1 as prognostic factor, dependent and independent of multidrug resistance. These results could be useful to predict cancer evolution and to choose the appropriate treatment: this is another step that can stimulate further promising and interesting investigations on broader study population.

Primary sarcoma tumours of the prostate are rare and are classified, according to their histology, as stromal tumours of uncertain malignant potential (STUMP) and stromal prostatic sarcoma (PS; low and high grade). We describe a case of a 71-year-old man that developed progressive urinary obstruction symptoms and was subjected to a transurethral prostatic resection (TURP). Histologically, there is a diffuse proliferation of epithelioid and spindle cells that showed rare atypical mitotic figures. Immunohistochemically, the neoplastic cells express diffusely CD34 and focally progesterone whereas no immunoreactivity was seen for cytocheratin, desmin, S-100, Bcl-2, chromogranin, CD117, and actin smooth muscle. A final diagnosis of low-grade prostatic stromal sarcoma (LG-PS) was made. This is a really rare neoplasm; in the literature, in fact, to our knowledge, only 6 cases are described and all of these were alive and free of disease at followup. Our patient too is free of disease at 15 months from the diagnosis.

Artificial intelligence (AI) is being investigated as a means to advance forensic histopathology from visual description to quantitative mapping, pattern recognition, and multimodal reconstruction of death. Recent developments in human postmortem analysis include validated whole-slide digitisation as foundational infrastructure and task-specific AI applications for diatom detection, glomerular quantification, coronary morphometry, myocardial classification, immunohistochemistry scoring, and virtual staining. AI-based postmortem interval (PMI) estimation remains experimental; the multi-organ study referenced in this commentary utilised an animal model, and human forensic validity has not yet been established. Foundation and vision-language models may ultimately extend these capabilities across organs and integrate microscopic findings with autopsy, toxicological, radiological, and circumstantial evidence. Postmortem tissue, however, is subject to autolysis, decomposition, agonal events, resuscitation, and non-standardised sampling, while the reference diagnosis is often a probabilistic whole-case opinion rather than an objective slide label. This work introduces FORENS-AI (FORensic Histopathology Evidence Network and Safeguards for AI), a conceptual architecture designed to convert computational outputs into traceable medicolegal evidence. FORENS-AI has not been empirically validated and is not presented as a standard, scoring system, clinical decision rule, or practice recommendation. The framework represents findings as an evidence graph, separates the Slide, Case, and Claim Gates, and proposes progressively stronger validation as outputs move from measurement to temporal, mechanistic, or causal inference. The primary aim is not to automate certification of death, but to identify safeguards to evaluate before AI-derived histological findings are permitted to inform expert opinion.