Fibroblast activation protein (FAP) has emerged as a promising molecular target for theranostic strategies. Here is a case of a 37-year-old woman with poorly differentiated pancreatic adenocarcinoma with lymph node metastasis who received 1 cycle of gemcitabine plus nab-paclitaxel, but relapsed a year ago. She then received 3 cycles of 177Lu-FAP-2286 treatment, in combination with 6 cycles of gemcitabine plus nab-paclitaxel therapy. After that, the patient received an additional 2 cycles of 225Ac-FAP-2286 treatment. A follow-up 68Ga-FAP-2286 PET/CT scan revealed complete metabolic response of the lesions, and no severe adverse reactions were reported.

Primary splenic angiosarcoma is a rare, aggressive malignancy carrying a poor prognosis. A 65-year-old woman with a pathologically confirmed well-differentiated splenic angiosarcoma developed liver metastases 5 months into follow-up. Subsequent 18F-FDG and 68Ga-FAPI PET/CT imaging revealed a "dual-negative" pattern, demonstrating no significant radiotracer uptake in the metastatic liver lesions. Despite well-differentiated histology, the tumor showed rapid progression, confirming aggressive behavior in well-differentiated angiosarcoma. The high-grade splenic angiosarcoma demonstrated negative findings on dual-tracer PET/CT, underscoring that vigilance and comprehensive multimodal evaluation are crucial for such occult malignancies.

Cancer-associated fibroblasts (CAFs) represent a predominant cell population in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC). How the spatial distribution of CAF subtypes relates to immune modulation within the TME remains incompletely understood. This study aimed to characterize the spatial organization of CAF subtypes in HCC and to explore their potential associations with immune contexture.

Mucosal melanoma (MM), an aggressive melanoma subtype arising in mucosal tissues, displays resistance to therapies effective in cutaneous melanoma. To understand how mucosal microenvironment contributes to treatment nonresponsiveness, we performed integrative analysis of single-cell and bulk messenger RNA sequencing data derived from oral mucosa-originated melanoma and revealed that mucosa-specific inflammation induces enrichment of low-pigmented neural crest-like cancer cell, mediated by COX2+ macrophages and their secretome. Maintenance of this inflammation-induced neural crest-like state in cancer cells depends on HER2 and HER3 activation. Inhibition of HER2/3 by pan-HER inhibitors blocks cell state plasticity and overcomes chemoresistance in primary MM cell lines and patient-derived xenograft (PDX) models. These findings provide insights into how the tissue of origin determines cancer aggressiveness, highlight the role of mucosal inflammation in driving melanoma stemness and chemoresistance, and advance the identification of effective treatment options currently lacking for patients with MM.

Altered cell-surface glycans are established cancer biomarkers, yet no oncogenes have been identified within glycan biosynthesis machinery. This represents a critical gap, as defining a gene as a true oncogene, rather than merely a component of an oncogenic pathway, reveals targetable dependencies that can improve clinical decisions. To date, no gain-of-function mutations have been detected in glycogenes, and the search for such mutations is largely saturated. To address this gap, we developed a bioinformatic-experimental pipeline to identify copy number alteration (CNA)-based driver genes, overcoming noise from passenger genes. The approach recovered known oncogenes and tumor suppressors, while revealing novel candidates, including glyco-oncogenes. Focusing on the glycosphingolipid (GSL) biosynthetic pathway, we validated B4GALT5 as a bona fide glyco-oncogene whose genomic amplification drives proliferation, oncogene addiction, and poor prognosis, effects that can be reversed by targeted pathway inhibition. Mechanistic studies show that B4GALT5 promotes cancer cell survival via integrin-Src signaling under anchorage-independent conditions. Collectively, these findings establish glycosylation enzymes as a druggable oncogene class and provide a resource of high-confidence CNA-based cancer regulatory genes.

BACKGROUND Lymphangioma circumscriptum (LC) is a rare condition characterized by a lymphatic malformation primarily affecting the cutaneous region. Although surgical excision has historically been the first-line treatment, it may be associated with substantial complications and recurrence. This case report presents the first documented use of a simultaneous combination of erbium glass (1540 nm) and CO₂ (10 600 nm) lasers as a targeted therapeutic strategy for LC in a patient with a dark phototype. CASE REPORT A previously untreated 13-year-old Asian girl presented with a 5-month history of multiple reddish and pigmented papules located in the right medial scapular region. After histopathological confirmation, the lesions were simultaneously treated with an erbium glass (4.0 W, 1 millisecond, 4 mJ) and CO₂ (15 W, 0.25 milliseconds, 3.8 mJ) laser system, followed by topical tacrolimus (0.03%). The protocol was well tolerated, with moderate procedural pain and transient effects that resolved within 2 months. Clinical observation suggested a notable reduction in vesicles, reaching near-total clearance at the 2-month follow-up. CONCLUSIONS These results suggest that the simultaneous combination of erbium glass and CO₂ lasers represents a feasible therapeutic option for LC in patients with pigmented skin. Further investigation in larger studies with extended follow-up is required to establish long-term efficacy and safety compared with conventional surgical or laser-based standards.

Current aromatase inhibitors (AIs) are limited by poor bioavailability and high toxicity, underscoring the need for the development of new therapeutics. In the present study, a series of 12 benzimidazole-pyrazole hybrids was designed, synthesized, and structurally characterized using infrared spectroscopy, mass spectrometry, nuclear magnetic resonance spectroscopy, and elemental analysis. Their anti-breast cancer potential was evaluated against the MCF-7 cell line using the MTT assay. Notably, compounds 5g and 5i exhibited the highest cytotoxicity, reflected by the lowest IC50 values, while showing minimal toxicity toward the normal cell line, NIH3T3. Aromatase inhibitory activity, assessed using the fluorometric assay, further identified compound 5g as the most potent inhibitor. Complementary molecular docking studies demonstrated that compounds 5g and 5i form favorable interactions with the aromatase enzyme, showing higher binding affinity compared to letrozole, providing mechanistic insight into their inhibitory activity. ADMET analysis further confirmed the drug-likeness and pharmacokinetic suitability of the synthesized derivatives. Collectively, these results establish compound 5g as a promising lead for aromatase inhibition, necessitating further in vivo evaluation.

This review is designed to highlight recent research efforts to optimize treatment strategies in men with advanced prostate cancer.

Oligometastatic prostate cancer (oligoPCa) represents a clinical state of limited metastatic spread in which metastasis-directed therapy (MDT) may offer meaningful disease control either alone or with systemic therapy. As imaging, systemic therapy, and biologic characterization evolve, management strategies for both synchronous and metachronous presentations continue to undergo significant refinement.

Body-composition indices beyond body mass index (BMI) are increasingly being investigated as prognostic cancer markers. In pancreatic cancer, the prognostic relevance of skeletal muscle and adipose tissue compartments remains uncertain, with studies yielding inconsistent findings. We examined whether early on-treatment changes in subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle index (SMI) are associated with unresectable pancreatic cancer prognosis.

Globally, breast cancer (BC) continues to be the primary cause of cancer-related death for women, underscoring the need for reliable biomarkers for early detection and improved patient outcomes. Because of their stability in biological fluids and their functions in controlling gene expression, microRNAs (miRNAs) have become attractive diagnostic tools.

Head and neck cancers (HNC) significantly impact patients' quality of life (QOL), with oral health often being significantly compromised, especially in advanced stages. Green tea, with its known anti-inflammatory and antioxidant properties, may help to improve oral health in these patients. Therefore, this study aims to investigate the effect of green tea-based mouth rinse on oral health status, pain, and QOL of advanced HNC patients.

Breast cancer remains the most prevalent malignancy among women worldwide, driven by complex interactions between tumor-intrinsic factors and the immune microenvironment. Understanding immune-related molecular regulators is essential to improve diagnostic and therapeutic strategies. Transcriptomic data from the TCGA-BRCA dataset (1109 tumor and 113 normal samples) were analyzed to identify differentially expressed immune-related genes by cross-referencing ImmPort and InnateDB gene sets. Protein-protein interaction networks were constructed using STRING and Cytoscape to identify hub genes. Validation analyses were conducted using GSCA, cBioPortal, and GEO datasets. miRNA-mRNA regulatory interactions were explored using TargetScan, miRDB, miRWalk, and miRTarBase databases, followed by dual-luciferase reporter assays. Functional characterization of CCL5 and CD74 was performed through siRNA-mediated knockdown in breast cancer cell lines, proliferation, colony formation, and wound healing assays, as well as xenograft mouse models. Four key immune-related hub genes, including CXCL9, CXCL13, CCL5, and CD74 were identified as significantly upregulated in breast cancer. Epigenetic and prognostic analyses revealed that these genes were influenced by promoter methylation and correlated with poor survival outcomes. miRNA-mRNA network analysis identified hsa-miR-146a-5p and hsa-miR-200c-3p as central regulators, validated by luciferase assays. Functional studies showed that silencing CCL5 and CD74 significantly reduced cell proliferation, migration, and tumor growth in vivo, confirming their oncogenic roles. This integrative multi-omics and experimental study identified CCL5 and CD74 as key immune-oncogenic drivers of breast cancer progression. Their modulation of the MIF-CD74 signaling axis highlights potential therapeutic targets for immunomodulatory interventions and combination therapy in breast cancer.

Pancreatic ductal adenocarcinoma (PDAC) is among the most devastating malignancies worldwide, characterized by late diagnosis, rapid progression, and dismal survival rates. The discovery of reliable biomarkers for early detection and disease monitoring remains an urgent clinical need. Owing to its proximity to tumor cells and protein-rich composition, pancreatic juice represents a compelling reservoir for biomarker discovery.

Although endocrine therapies prevent recurrence and progression of estrogen receptor alpha (ER)-positive breast cancer, approximately one-third of patients experience recurrent disease that is rarely cured in the advanced/metastatic setting. A subpopulation of endocrine-tolerant breast cancer cells persists as residual disease that confers risk for the eventual emergence of drug resistance. An analysis of persisters that continue to proliferate despite endocrine therapy revealed the activation of pathways related to metabolism and E2F transcription factor signaling. E2F signaling is driven by cyclin-dependent kinases 4 and 6 (CDK4/6), and CDK4/6 inhibitors (CDK4/6i) are used clinically to prevent and manage endocrine resistance. CDK4/6i slowed the cycling of endocrine-tolerant persisters. Analyzing metabolic alterations induced by CDK4/6i, we found that CDK4/6i-tolerant persisters had upregulation of mitochondrial content, mitochondrial membrane potential, respiration, and reactive oxygen species (ROS). Inhibition of mitochondrial complex I further increased ROS levels and enhanced growth inhibition in both endocrine-sensitive and -resistant cell lines and patient-derived xenografts. These findings collectively offer mitochondrial respiration as a therapeutic target in CDK4/6-tolerant persister breast cancer cells to help eradicate residual disease.

Despite the remarkable success of immune checkpoint inhibitor (ICI) therapy in solid tumors, immune-related adverse events (irAEs) have posed great challenges in the whole-course management of ICI immunotherapy. Reliable biomarkers helping to predict irAEs are still limited and lacking.

Tumor dynamic models are vital for evaluating oncology treatments and guiding clinical drug development decisions. However, few studies rigorously assess their predictive capabilities, especially when forecasting tumor trajectories from clinical trials with short or inconsistent follow-up across treatment arms. Poor predictive performance or biases related to follow-up time could potentially limit the general utility of tumor growth inhibition (TGI) models. This study quantitatively evaluates prediction bias across several established tumor dynamic models, comparing five classical pharmacometric TGI models with the deep learning-based Tumor Dynamic Neural-ODE (TDNODE) framework. Using time-truncated clinical trial data from 3106 patients with non-small cell lung cancer (NSCLC) across four completed atezolizumab phase III studies, we consistently observed moderate-to-high positive bias in the predictions from pharmacometric models, particularly with more limited follow-up. By examining the structures of these models and comparing them to observed data, we highlight how the assumed kinetic patterns potentially lead to biased parameter estimation and systemic overestimation of tumor size when applied to immature datasets. In contrast, the TDNODE framework, using deep learning, demonstrated promising early results, exhibiting improved predictive performance in the same evaluations. These findings underscore the critical need to address prediction bias in tumor dynamic modeling with immature data and to consider alternative approaches to established paradigms for certain drug development applications. This study also generally demonstrates the potential of novel methods, such as deep learning, to potentially enhance the reliability of tumor dynamics modeling, especially in challenging early-phase clinical decision-making scenarios.

The prognostic value of TP53 mutations in metastatic colorectal cancer remains unclear owing to inconsistent findings in the literature. Given its central role in tumor biology, clarifying the impact of TP53 status on survival outcomes is clinically relevant.

Solid tumors are organized pathophysiologic systems in which vascular dysfunction, stromal remodeling, and diffusion-consumption imbalance partition lesions into recurrent microenvironmental microdomains. These regions regulate not only whether agents enter tumors, but also where they localize and function within tissue. This review presents a microdomain-centered framework linking tumor biology and microenvironment heterogeneity to the behavior of microenvironment-responsive nanomaterials, with emphasis on clinically relevant tissue exposure rather than therapeutic outcome. We first distinguish trans-vascular entry from intratumoral transport, demonstrating why tumor-level accumulation does not ensure uniform cellular exposure. Vascular heterogeneity, including endothelial-mediated transport pathways and perfusion variability, is examined as a determinant of delivery efficiency across tumor types. We then analyze stromal and interstitial constraints-extracellular matrix organization, interstitial fluid pressure, solid stress, and cellular sequestration-that dominate postentry distribution and bias localization toward perivascular compartments. Hypoxic, acidic, protease-active, fibroblast-remodeled, and receptor-defined niches are interpreted as spatially structured metabolic and signaling environments whose clinical relevance depends on accessibility and residence time. We propose morphology-based evidence standards centered on compartment-resolved mapping of localization and in situ material state transitions, together with minimum reporting practices to improve reproducibility and cross-study translation. We identify recurring mismatches between tumor architecture and material design that contribute to heterogeneous distribution and variable response across lesions and patients. Standardized spatial metrics, including vessel-distance stratification and penetration-depth profiling, are recommended to support comparison across studies. Future work should prioritize 3D coregistration of microenvironmental markers, localization, and activation, and incorporate lesion-level heterogeneity as a measurable biological variable to improve clinical translation.

This review explores the role of bioinformatics in identifying novel biomarkers for immune cell exhaustion (ICE), a dysfunction state in T cells during chronic infections and cancer. ICE, marked by upregulation of inhibitory receptors such as PD-1 and CTLA-4, impairs immune responses, a critical barrier in chronic infection and cancer treatment. Understanding this state is crucial for developing therapies to reverse T cell exhaustion and improve immune function. The review highlights advanced bioinformatics tools that analyze high-throughput sequencing data, transcriptomics, proteomics, and metabolomics to identify biomarkers and therapeutic targets, enhancing diagnostics and treatments. Despite challenges like the complexity and heterogeneity of ICE, the integration of bioinformatics has advanced our molecular understanding and identification of key pathways. This facilitates the development of personalized immunotherapies, improving outcomes for patients with chronic infections and cancer. Additionally, this review emphasizes the tumor microenvironment's (TME) role in ICE, where factors such as the upregulation of immune checkpoint ligands, secretion of immunosuppressive cytokines like Transforming Growth Factor Beta (TGF-β) and Interleukin 10 (IL-10), and recruitment of regulatory immune cells create an immunosuppressive milieu fostering tumor growth. In conclusion, this review will also discuss the future directions for research in biomarker discovery and the integration of bioinformatics with clinical data to enhance the precision and effectiveness of therapies. By addressing these challenges, future research can lead to more targeted and efficient treatments for patients suffering from chronic infections and cancer.