Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with pronounced resistance to conventional therapies. Irreversible electroporation (IRE) is a promising therapy for PDAC; however, its clinical efficacy is limited by a high recurrence rate. Here, using a preclinical PDAC model, we characterized the tumor immune microenvironment following insufficient IRE (iIRE) through single-cell RNA sequencing. We found that iIRE induces a CCR2⁺ tumor-associated macrophage (CCR2⁺ TAM)-mediated immunosuppressive microenvironment in residual tumors. Consequently, we developed a macrophage-based proteolipid vesicle (mPLV) coencapsulating the CCR2 antagonist PF-4136309 (PF) and gemcitabine (GEM), named PF/GEM@mPLV. Our findings suggest that PF/GEM@mPLV achieves high drug accumulation within tumors through iIRE-induced inflammation. Reduction of CCR2⁺ TAMs enhances antitumor immunity and improves chemotherapeutic response. PF/GEM@mPLV markedly inhibits tumor recurrence following iIRE, diminishes hepatic metastases, and prolongs survival in preclinical PDAC models. These findings uncover the role of CCR2⁺ TAMs in iIRE-induced immunosuppression, offering a promising strategy to enhance the clinical potential of IRE in PDAC.

Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detecting high-risk IPMN, they lack specificity, resulting in surgical overtreatment. Artificial Intelligence (AI)-based medical image analysis has the potential to augment the clinical management of IPMNs by improving diagnostic accuracy. Based on a systematic review of the academic literature on AI in IPMN imaging, 1041 publications were identified of which 25 published studies were included in the analysis. The studies were stratified based on prediction target, underlying data type and imaging modality, patient cohort size, and stage of clinical translation and were subsequently analyzed to identify trends and gaps in the field. Research on AI in IPMN imaging has been increasing in recent years. The majority of studies utilized CT imaging to train computational models. Most studies presented computational models developed on single-center datasets (n = 11,44%) and included less than 250 patients (n = 18,72%). Methodologically, convolutional neural network (CNN)-based algorithms were most commonly used. Thematically, most studies reported models augmenting differential diagnosis (n = 9,36%) or risk stratification (n = 10,40%) rather than IPMN detection (n = 5,20%) or IPMN segmentation (n = 2,8%). This systematic review provides a comprehensive overview of the research landscape of AI in IPMN imaging. Computational models have potential to enhance the accurate and precise stratification of patients with IPMN. Multicenter collaboration and datasets comprising various modalities are necessary to fully utilize this potential, alongside concerted efforts towards clinical translation.

Background and Clinical Significance: Neurofibromatosis type 1 (NF1) predisposes individuals to various peripheral nerve sheath tumors (PNSTs), including benign neurofibromas, malignant peripheral nerve sheath tumors (MPNSTs), and intermediate lesions known as atypical neurofibromatous neoplasms of uncertain biologic potential (ANNUBP), previously often termed atypical neurofibroma. These atypical lesions are considered premalignant precursors to MPNST. Case Presentation: We present the case of a 33-year-old male with NF1 who developed a rapidly growing, painful mass in his right calf. Clinical examination revealed signs consistent with NF1. Magnetic resonance imaging showed a large, heterogeneous mass in the lateral compartment. Biopsy revealed a neurofibroma with hypercellularity, moderate atypia, scarce S100 positivity, focal CD34 positivity, and an elevated Ki-67 proliferation index of 10-12%, consistent with ANNUBP. The patient underwent wide surgical resection, including the fibula and peroneal muscles. At the 30-month follow-up, there was no local recurrence, though the patient had a mild residual limp. Discussion: This case highlights the clinical presentation, diagnostic features, and management considerations for ANNUBP in NF1, emphasizing the importance of recognizing warning signs and the role of pathology in guiding treatment for these high-risk precursor lesions.

Background and Clinical Significance: Brenner tumors are rare epithelial tumors that can occur in both males and females. They consist of ovarian transition cells surrounded by dense fibrous tissue and can be classified as benign, borderline, or malignant. While most commonly found in the ovary, extraovarian Brenner tumors (EOBTs) have been reported in the uterus, vagina, broad ligament, and omentum. Case Presentation: A 71-year-old postmenopausal woman presented with a polypous formation on the upper third of the posterior vaginal wall, which was found at a routine health check. Macroscopically, the lesion appeared as a solid, polypoid mass with a yellowish-gray cut surface, measuring approximately 25 × 20 mm. Histological examination revealed a polypoid formation covered by stratified squamous epithelium, with a dense fibrous stroma (Van Gieson [VG]+) and tubular structures lined by clear epithelial cells. Parenchymal cells showed low proliferative activity, with Ki-67 expression in less than 5% of cells, also Cytokeratin (CK) 7/+/p63:/+/ CK AE1/AE3: /+/ Estrogen Receptor (ER): /+/ and Progesterone Receptor (PR)/-/; CK20/-/; p53/-/, Wilms' Tumor (WT)-1/-/; Prostate-Specific Acid Phosphatase (PSAP)/-/. The final diagnosis was an extraovarian Brenner tumor. The patient was monitored for two months post-excision, with no signs of recurrence. Conclusions: EOBTs are extremely rarely seen and vaginal involvement is far less common. Due to their rarity, these tumors may be confused with other benign or malignant vaginal lesions. In order to differentiate EOBTs from other neoplasms, histological analysis is crucial due to their characteristic transitional-type epithelium and large fibrous stroma. Further studies are required to understand the origin and clinical behavior of EOBTs. Long-term monitoring should be performed to look for any recurrence or malignant change, even though benign Brenner tumors usually have a good prognosis. Awareness of EOBTs and their possible locations is essential for accurate diagnosis and appropriate management.

Myelodysplastic neoplasms (MDS) represent a heterogeneous group of neoplastic bone marrow disorders. A crucial component in regulating bone marrow cell apoptosis is the B-cell CLL/lymphoma 2 (BCL-2) protein. This retrospective study aimed to assess BCL-2 expression by immunohistochemistry in trephine biopsy specimens from 76 patients diagnosed with MDS. The obtained retrospective results were correlated with clinical parameters, including age, sex, MDS subtype, IPSS, IPSS-R, bone marrow blast percentage, Ogata score, response to treatment, blood morphology parameters, and overall survival (OS). The median follow-up duration was 16 months. During the observation period, 58 patients died (median OS of this group: 14.6 months), and 25 patients experienced progression to acute myeloid leukemia. The median BCL-2 expression assessed using the Histoscore (H-score) was 10. Patients with BCL-2 expression below 10 had better survival outcomes than those with expression ≥ 10. Furthermore, patients without detectable BCL-2 expression had significantly better survival compared to those with detectable BCL-2 expression (p = 0.0084). Higher BCL-2 expression was significantly associated with high and very high cytogenetic risk, as defined by IPSS-R. BCL-2 immunohistochemistry should be viewed as a complementary biomarker that, when integrated with IPSS-R and mutational data, could refine therapeutic algorithms.

This study discusses the effect of photothermal therapy using PANI-conductive polymer composites with iron oxide and the amino acid cysteine ​​(Cys) on breast cancer cells. The study focused on the biological and toxicological effects associated with the treatment process and its impact on these cancer cells. The materials were prepared using a very simple chemical oxidation method to produce polymer nanoparticles to which iron and cysteine ​​molecules are attached. These composites were used as therapeutic agents in photothermal therapy, which relies primarily on the process of converting light into heat energy to kill cancer cells. The results showed that photothermal therapy using PANI-Fe₂O₃-Cys composites with near-infrared (NIR) light was significantly more effective in inhibiting breast cancer cells (MDA-MB-231) than using the composites without a laser. Significant changes in the morphology of the cancer cells were observed after treatment, demonstrating the treatment's effectiveness in destroying cancer cells. On the other hand, there was a slight and negligible effect on healthy cells, demonstrating the successful formulation and targeting of the treatment for cancerous tumors. Antibacterial evaluations also demonstrated effective activity against Staphylococcus aureus and Klebsiella bacteria. This study supports the use of composite nanomaterials in photothermal therapy as a targeted treatment for breast cancer, as well as enhancing the effectiveness of this treatment with lasers. It also explains how these materials could be used in future medical applications, particularly in cancer treatment, using methods that are considered less invasive and safer.

Oral cancer is a common malignant tumor of the head and neck region, significantly impacting human health and quality of life. Radiotherapy has become an essential component of treatment, often used in combination with surgery and/or chemotherapy. Advances in radiotherapy techniques, such as intensity-modulated radiotherapy, image-guided radiotherapy, and proton beam therapy, have markedly improved clinical outcomes. Intensity-modulated radiotherapy, for example, has demonstrated 5-year overall survival rates ranging from 60 to 75%, with better local control and reduced toxicity compared to conventional radiotherapy. Proton therapy has shown promising results in sparing normal tissues and achieving high-dose conformity, leading to improved quality of life and comparable tumor control. This review highlights the recent technological developments, explores underlying molecular mechanisms and predictive biomarkers, and discusses future directions in the radiotherapeutic management of oral cancer, aiming to provide clinically valuable insights and evidence-based recommendations.

Neuroendocrine tumors (NETs) of the prostate gland represent a distinct entity within the spectrum of prostate cancer, characterized by neuroendocrine differentiation on morphology and unique clinical behavior. Despite their clinical significance, there remains a lack of consensus regarding their diagnosis, classification, immunohistochemical evaluation, and management. A comprehensive understanding of the molecular and clinical heterogeneity of prostate NETs is essential for developing tailored treatment strategies and improving patient outcomes. Over the years, there has been a continuous effort to refine the terminology and classification of neuroendocrine tumors of the prostate. The current WHO 2022 classification scheme for genitourinary neuroendocrine neoplasms provides a standardized framework. However, given the substantial clinical and molecular heterogeneity of prostate NETs, there is an emerging need for an organ-specific classification system that better captures the biological and clinical diversity of these tumors. In this review, we propose a novel classification system for neuroendocrine neoplasms (NENs) of the prostate that integrates both histomorphology and clinical context. With the growing role of liquid biopsy and molecular biomarkers, there is a shift towards more precise, real-time detection of disease progression and treatment resistance. This review highlights the importance of a more nuanced, biologically and clinically informed approach to the diagnosis and management of prostate NETs. A dedicated classification system, combined with advancements in precision genomics and targeted therapies, holds significant promise for improving outcomes in patients with these rare and challenging tumors.

RNA sequencing (RNA-Seq) is a next-generation sequencing method, routinely used in laboratories to detect abnormal transcripts with oncogenic activity after RNA extraction from formalin-fixed-paraffin-embedded (FFPE) samples of non-small-cell-lung cancers (NSCLC), then allowing targeting of the corresponding fusion kinase with adapted pharmacologic compounds in the clinical practice. Here, we provide a detailed protocol for total nucleic acid (i.e., RNA and DNA) extraction from FFPE samples and targeted RNA-Seq, by the FusionPlex^® method which allows the detection of the most current fusion transcripts found in NSCLC.

A global technological race is underway to develop increasingly powerful and precise quantum computers. As a transformative computing paradigm, quantum computing offers the potential for exponentially accelerating specific algorithms, thereby providing the necessary computational power to process vast amounts of data. In light of the challenges classical computing faces with the complexity and volume of oncology data, we introduce the concept of "quantum oncology" and explore its potential applications throughout the cancer care continuum. Additionally, we address several challenges and potential solutions for integrating quantum computing into oncology research. By illuminating these issues, we aim to deepen the understanding of quantum computing's potential in oncology and advocate for multidisciplinary collaboration to propel the advancement of precision oncology. CLINICAL TRIAL NUMBER: Not applicable.