BACKGROUND Biliary neuroendocrine neoplasm (NEN) arising from the extrahepatic bile duct is rare, with an incidence of 0.2% among gastroentero-hepatopancreatobiliary NEN cases. Biliary neuroendocrine carcinoma (NEC) is an extremely rare high-grade malignancy that requires multidisciplinary treatment, including surgery, chemotherapy, and radiation. However, there have been only a few reports on the combined therapy for biliary NEC. CASE REPORT A 74-year-old man was referred to our hospital with a chief concern of obstructive jaundice. He was diagnosed with perihilar biliary NEC. The tumor primarily involved the confluence of the hepatic and left hepatic ducts. After 4 courses of systemic chemotherapy with cisplatin and etoposide (EP regimen), the tumor showed partial shrinkage. The patient underwent left and caudate hepatectomy with combined resection and reconstruction of the extrahepatic bile duct. Intraoperatively, strong adhesion between the right hepatic artery and the dorsal surface of the tumor was observed, requiring combined resection and reconstruction of the right hepatic artery. Postoperatively, the patient was treated with adjuvant chemotherapy (EP regimen) for 6 months. Ten months after surgery, he was diagnosed with multiple aggressive recurrences that were refractory to multimodal therapies. Eighteen months after the initial diagnosis and 12 months after surgery, he died of liver failure due to cholangitis. CONCLUSIONS This report presents the first case of perihilar biliary NEC that underwent perioperative chemotherapy and radical liver surgery. We believe that the introduction of perioperative chemotherapy is essential to achieve a better prognosis for perihilar biliary NEC, given its oncological malignancy and surgical invasiveness.

Rare cancers collectively account for a proportion of cancer-related morbidity and mortality, and patients face significant challenges, including delayed diagnosis, lack of targeted therapies, and poor clinical outcomes. Exosome-based therapies have emerged as promising tools to address these unmet needs. Exosomes, naturally secreted extracellular vesicles, are increasingly engineered as nanocarriers for the targeted delivery of chemotherapeutics, nucleic acids, and immune modulators. Their ability to modulate the tumor microenvironment, influence immune responses, and overcome drug resistance makes them especially attractive. In rare cancers, preliminary studies have demonstrated the utility of exosomes in improving tumor specificity, enhancing payload stability, and reducing systemic toxicity. Moreover, exosomes derived from tumor or immune cells can influence immune evasion, angiogenesis, and stromal remodeling, key processes in cancer progression. Despite this potential, the clinical application of exosome-based therapies in rare cancers remains underexplored. This review critically evaluates the limited but emerging body of evidence supporting exosome-based interventions in rare malignancies. By highlighting their therapeutic promise, we aim to understand exosome-driven strategies as personalized, effective, and accessible solutions for patients with rare cancers.

Accurate assessment of T-cell clonality is key for diagnosing mature T-cell neoplasms. TRBC1-based flow cytometry provides a rapid, robust, and cost-efficient approach. This systematic review and meta-analysis assessed the diagnostic accuracy of TRBC1 flow cytometry (TRBC1-FC) for detecting T-cell clonality in mature T-cell neoplasms.

We systematically searched Scopus, PubMed (MEDLINE), and Google Scholar for articles on TRBC1-FC diagnostic accuracy published up to July 1, 2025. Pooled sensitivity and specificity were estimated, between-study heterogeneity was evaluated and small-study effects were examined.

This meta-analysis included 10 studies. The pooled sensitivity was 97.6 % (95 % CI, 95.1-99.4 %) and specificity 90.7 % (95 % CI, 76.0-99.3 %). The pooled LR+ was 10.9 (95 % CI, 4.1-28.9), LR-was 0.053 (95 % CI, 0.025-0.12), and DOR 339 (95 % CI, 64-1,788). The HSROC curve demonstrated an AUC of 0.974 (partial AUC=0.970), confirming excellent global discriminatory capacity. Between-study heterogeneity was substantial (I²=83.3 %), mainly affecting specificity and DOR, while sensitivity remained highly consistent. No evidence of a threshold effect was found. Deeks' test showed significant small-study effects (p<0.001), and sensitivity analyses identified one influential study whose exclusion markedly reduced heterogeneity. These results confirm the high diagnostic performance and robustness of TRBC1-FC for T-cell clonality assessment.

TRBC1-FC demonstrates high sensitivity and low LR-, supporting its role as a rule-out test. Variability in specificity, LR+ and DOR, mainly due to small-study effects, advises caution for rule-in use. Standardized protocols and cost-effectiveness analyses are needed before broad clinical adoption.

Proton pencil beam scanning (PBS) enables highly conformal dose distributions; however, its lateral dose fall-off (penumbra) can be compromised by the use of range shifters (RSs) and increased air gaps. In PBS for head and neck regions, where critical organs at risk (OARs) are frequently adjacent to the target, penumbra degradation may lead to increased OAR doses or suboptimal target coverage. The integration of a dynamic multi-leaf collimator (dMLC), which adjusts leaf positions at each energy layer, has been shown to improve dose conformity in single-field uniform dose (SFUD) delivery. In parallel, intensity-modulated proton therapy (IMPT) offers enhanced dose shaping over SFUD by modulating beam intensity across multiple fields and does not require a single beam to encompass the entire target volume, providing greater flexibility in utilizing dMLC capabilities.

This study integrates dMLC into IMPT for head and neck cancer and proposes a novel leaf positioning strategy. We evaluate the dosimetric impact of this approach and assess its potential clinical benefits in terms of target coverage and OAR sparing.

Treatment plans were retrospectively created for five patients with head and neck cancer. For each patient, IMPT plans with three beam angles were generated using three techniques: (1) uncollimated PBS, (2) dMLC_cover, in which the MLC encloses the target cross-section at each energy layer, and (3) dMLC_block, in which the MLC actively blocks OARs and their distal regions. Dose-volume histogram (DVH) metrics for the clinical target volume (CTV) and OARs were evaluated, including a total of 21 perturbed scenarios that combined ± 2 mm setup uncertainties (7 scenarios) and ± 3.5% range uncertainties (3 scenarios). The accuracy of dose calculations was validated by comparing calculated and measured lateral dose distributions at the isocenter plane in water using two-dimensional gamma analysis with a 2%/2 mm criterion.

The integration of dMLC with IMPT significantly reduced the dose to surrounding OARs while maintaining comparable target coverage and robustness relative to uncollimated PBS. Notably, dMLC_block demonstrated an enhanced dose-sparing effect than dMLC_cover, particularly for OARs surrounded by the target. While maintaining comparable CTV D98% across three techniques, dMLC_cover achieved the greatest reduction in the mean doses to the eyeballs and optic nerves, as well as in the D2% to the optic chiasm, brain, and brainstem in most cases. The gamma passing rate between calculated and measured doses for dMLC_block exceeded 95% for all beams, confirming the accuracy of dose calculations involving complex leaf positions.

The combination of IMPT and dMLC provides notable dosimetric advantages, supporting its potential for clinical applications. Further validation across a broader range of cases is necessary to comprehensively assess its efficacy and safety, particularly with respect to leaf positioning accuracy and potential variations in biological effectiveness.

Accurate structure contouring on computed tomography (CT) is critical for prostate cancer radiotherapy, but it remains labour intensive and prone to interobserver variability, particularly for small, low-contrast organs such as the prostate, seminal vesicles (SV) and penile bulb (PB). Deep-learning models can automate this task. However, they typically require large, fully labelled datasets that are often unavailable in clinical settings.

This study evaluated whether self-supervised (label-free) slice-prediction pretraining could enhance segmentation performance, especially in scenarios with limited annotated data.

We used 322 pelvic CT volumes (215 from UMMC, 107 from TCIA), split 80:20 into training and testing sets (258 training, 64 testing patients). A novel lightweight 2D U-Net encoder was first pretrained on unlabelled data using a slice-prediction task across axial, sagittal, and coronal planes. The pretrained model was then fine-tuned for multi-class segmentation using either the full dataset or a reduced subset of 60 labelled patients. Baselines trained from scratch with 1-channel or 3-channel input were included for comparison. Segmentation accuracy was assessed using mean distance agreement (MDA) and Dice similarity coefficient (DSC). Paired t-tests with Bonferroni correction were applied to assess statistical significance.

Models with self-supervised pretraining achieved consistently lower MDA across all major pelvic structures. Notable improvements included reductions in bladder MDA from 0.600 mm to 0.547 mm, femoral heads from 1.370 mm to 0.994 mm, PB from 1.470 mm to 1.283 mm, rectum from 0.792 mm to 0.669 mm, prostate from 1.281 mm to 1.183 mm, and SV from 1.175 mm to 0.893 mm.

Self-supervised pretraining via slice prediction enables anatomically informed feature learning and improves segmentation robustness under limited data conditions. This strategy enhances accuracy without reliance on manual labels during pretraining and is compatible with computationally lightweight architectures, making it well-suited in resource-constrained clinical environments.

Regulation of enhancer activity plays a pivotal role in governing gene expression and cellular behaviors. However, the precise mechanisms underlying dynamic control of active enhancers remain incompletely defined. Here, we demonstrate that the nuclear receptor estrogen-related receptor α (ERRα) forms a functional complex with the H3K4me3-specific demethylase KDM5C to co-occupy a large set of active enhancers, including the locus of STING. In breast cancer cells, ERRα depletion induces STING enhancer hyperactivation, evidenced by H3K4me3 deposition, decreased H3K4me1, and increased enhancer RNA (eRNA) transcription. Accordingly, depletion of ERRα leads to further activation of STING gene transcription and TBK1-IRF3 pathway, accompanied by increased type I interferon (IFN) and IFN-stimulated gene (ISG) expression, as confirmed by transcriptomic analysis. Notably, depleting ERRα markedly attenuates breast tumor cell growth in vitro and in vivo, and our in vitro evidence indicates this occurs in part through activating STING signaling. These findings establish that the ERRα-KDM5C serves as a critical checkpoint for STING enhancer activity, revealing a regulatory mechanism of STING enhancer activity in breast tumor progression.

Initiation and sustainment of oncogenic signaling is a hallmark of cancer evolution and progression. In renal clear cell carcinoma, loss of von Hippel-Lindau protein causes stabilization of hypoxia-inducible transcription factors (HIF) evoking a pseudo-hypoxic response, perturbing epithelial homeostasis and leading to cancer development. Although genetic polymorphisms link the EPAS1 oncogene (coding for HIF-2α) to renal cancer and anti-HIF-2 compounds emerge as renal tumor therapies, little is known about transcriptional dysregulation of this factor in renal malignancies. We use genetic, epigenetic and transcriptomic data from large patient cohorts and cell models to dissect mechanisms of augmented EPAS1 transcription in clear cell renal cell carcinoma. We define an oncogenic enhancer of EPAS1 which operates depending on the presence of HIF and renal lineage-specific factors, thereby providing evidence for an auto-regulatory feed-forward circuit of HIF-2α regulation which promotes renal cancer growth.

Both solid and hematological malignancies are recognized as complex ecosystems in which the tumor microenvironment (TME) plays a pivotal role in mediating therapeutic resistance. TME-driven modulation of BCL2-family proteins has emerged as a key determinant of treatment response in B-cell malignancies. Here, we focused on the regulation of the pro-apoptotic BH3-only protein BIM, using mantle cell lymphoma (MCL), an aggressive and incurable B-cell neoplasm, as a cellular model. Comparative analysis of circulating and lymph node samples highlighted selective BIM downregulation in malignant cells within the nodal TME, contrasting with BIM upregulation observed with normal B cells. TME-mimicking ex vivo co-culture of primary samples recapitulated this tumor-specific and microenvironment-dependent mechanism. Mechanistically, we found that BIM downregulation is driven by a lymphoma-specific CD40L-mediated rewiring of the PI3K/AKT pathway, which in turn inhibits the transcriptional activity of FOXO1. Functionally, CRISPR/Cas9-mediated deletion of BIM in MCL primary cells was sufficient to bypass their dependence on microenvironmental survival cues, leading to long-term autonomous expansion ex vivo. Moreover, BIM loss conferred broad resistance to chemotherapy and clinically relevant targeted agents. In contrast, treatment with bispecific T-cell engagers elicited robust cytotoxic responses regardless of BIM expression, underscoring the potential of immunotherapies to overcome TME-induced apoptotic resistance.

Predicting metastasis in early stages of cancer plays a crucial role in effectively controlling cancer progression and thereby improving patient survival outcomes. Although several computational methods have been developed to predict cancer metastasis, most focus on lymph node metastasis. Distant metastasis is more difficult to detect or predict than lymph node metastasis. In this study, we developed a multilayer perceptron (MLP) model to predict distant cancer metastases. We constructed a weighted gene interaction network and computed sample-specific differential gene correlations for individual cancer samples. The MLP model was trained on sample-specific differential gene correlations and tested on independent datasets of differential gene correlations from samples that were not used in training the model. The MLP model is capable of predicting whether or not distant metastasis will occur and potential distant metastatic sites. In independent testing, it predicted distant metastasis with a high performance (AUC of 0.95) and predicted metastatic sites with an average AUC of 0.97. In comparison of our model with other state-of-the-art methods using the same data set, our model showed better performance than the others. The prediction model developed in this study may help clinicians determine site-specific testing and treatment options.

It is estimated that 70 million children and adolescents have latent tuberculosis infection (LTBI) worldwide, thus representing an important reservoir of the disease. Diagnosis and prophylaxis of LTBI in this population remain a challenge because of social factors and barriers in contact investigation. The objective of this study was to describe barriers in the follow-up of children and adolescents who are household contacts of adults with pulmonary tuberculosis (PTB). This was a prospective cohort study of children and adolescents, household contacts of PTB, followed for 2 years after contact detection, in the region of Itaboraí, Rio de Janeiro, Brazil. Out of 90 subjects included in the study, aged 0-15 years, 44 were lost to follow-up (48.9%), poverty being the main cause of being lost to follow-up. In the multivariate analysis, losses to follow-up were associated with male gender (P = .01) and with the caregiver's low level of education (P = .001). There was a lower chance of being lost to follow-up when the infection source was a sibling (P = .004). The absence of a guardian to accompany the child to medical consultations was linked to the loss of follow-up (P = .07). The main barriers to the diagnosis and treatment of LTBI in children and adolescents in our study population were socioeconomic and educational factors. Preventive treatment is still a challenge in tuberculosis endemic areas.