Ovarian cancer remains the most lethal gynaecological malignancy, and it exhibits substantial histologic and molecular heterogeneity. Traditional systemic therapies have produced only modest survival gains. Integration of immunohistochemical (IHC) and molecular diagnostics has shifted care toward biomarker-driven personalised treatment. This review presents current IHC approaches for histotype classification and the most important actionable protein markers (FR, HER2, TROP2, MMR proteins, and PD-L1), together with molecular testing for BRCA1/2, homologous recombination deficiency (HRD) status, and circulating tumour DNA (ctDNA) monitoring. These diagnostics now direct poly(ADP-ribose) polymerase inhibitors maintenance in HRD-positive disease and antibody-drug conjugates such as mirvetuximab soravtansine in FR-high platinum-resistant tumours. However, important limitations remain: intratumoral heterogeneity, variable assay performance, lack of standardisation, and unequal access to testing worldwide. We also discuss how best to combine multiple biomarkers and outline future directions, such as AI-assisted digital pathology, composite predictive models, and ctDNA-guided adaptive strategies, to refine patient selection and improve long-term outcomes.

Uterine mesenchymal tumours represent a group of heterogeneous tumours, the classification of which is evolving, especially in the context of a broader use of molecular testing. Some entities can be diagnosed based on the combination of morphological and immunohistochemical features. In other entities, such as endometrial sarcomas with KAT6B/A::KANSL1 fusion, the correct diagnosis cannot currently be achieved without molecular testing. In this review, we focus on some of the new entities in which molecular testing plays an essential role for diagnosis, including tumours with KAT6B/A::KANSL1 fusion, tumours with MEIS1::NCOA2 fusion, and tumours with fusion involving the KDM2B gene. In addition, uterine tumours with whorling and GREB1:CTNNB1 fusion and endometrial stromal tumours with CTNNB1 mutation will be discussed. Other tumours with recurrent molecular alterations not specific to a single entity (such as tumours with PLAG1 fusion or RAD51B fusion) are also mentioned. In summary, molecular testing is a very important part of the classification of uterine mesenchymal tumours. The growing number of emerging entities helps to correctly classify tumours into clinically significant categories. However, these entities should be viewed with caution until their clinical significance is supported by robust data, and molecular findings should always be correlated with morphological features.

Immunohistochemistry (IHC) is essential in diagnostic pathology, but antibody reliability is often limited by insufficient validation and high variability between clones. Conventional validation approaches normally use only few tissues or cell lines which do not reflect tissue and cell type complexity. A high-throughput validation platform based on large-scale tissue microarrays (TMAs) was established to assess antibody specificity across 76 normal tissue types and to evaluate the diagnostic performance in > 15,000 tumours from > 130 entities. Comparative staining with independent antibodies on a full set of normal tissues enables robust detection of cross-reactivity. Comparative staining of critical tumour cohorts under different conditions enables protocol optimization to obtain the best possible sensitivity and specificity for the distinction of different tumour types. Large-scale tumour profiling studies on ≥ 15,000 cancers generated comprehensive datasets refining the diagnostic value of established markers (e.g., CK7/CK20, PLAP) and characterizing the impact of emerging diagnostic targets such as MTAP, CDH16, and CDH17. Furthermore, screening of over 6000 antibodies of previously unknown clinical significance identified various novel diagnostic markers, including CPA1, GAD2, and KDM6A, with high specificity for distinct tumour entities and/or neoplastic transformation. In conclusion, large-scale TMA-based validation improves antibody identification and characterization and provides a robust framework for integrating IHC into digital pathology solutions.

Postoperative venous thromboembolism (VTE) is a major source of morbidity and mortality. Real-time risk stratification for VTE is important to guide measures for thromboprophylaxis. We sought to compare the discrimination of three VTE predictive systems in classifying 90-day postoperative VTE among cancer patients undergoing pancreas and liver surgery using administrative data.

We conducted a retrospective analysis of the 2001-2015 SEER-Medicare data for patients with newly diagnosed primary pancreatic or liver malignancies who underwent surgery. The primary outcome was 90-day postoperative VTE (including deep venous thrombosis and pulmonary embolism [PE]). We used the 2001-2010 dataset to create a new VTE predictive model using multivariable logistic regression. We then compared the discrimination of the Caprini score (adapted for claims data), the Elixhauser comorbidity score, and the new predictive model using the 2011-2015 dataset.

Our sample included 15 479 patients (12 005 pancreas and 3474 liver surgery). Median age was 74 years (interquartile range: 69-78) and 7619 were female (49%). The overall incidence of 90-day VTE was 10.0% (90-day PE: 4.5%). The new VTE model included age, race, history of VTE, cancer stage, preoperative chemotherapy, and Elixhauser score. The discrimination of all predictive models was modest for both VTE (c-statistic 63.0%, 59.4%, and 67.8%) and PE (61.5%, 59.7%, 65.6% for Caprini, Elixhauser, and new score respectively).

The existing tools for predicting postoperative VTE show poor performance using claims data. Future research should supplement administrative data with additional data sources to better predict patients at high risk for postoperative VTE.

Gastric cancer (GC) remains a major cause of cancer‑related mortality worldwide, and only a subset of patients achieves durable benefit from immune checkpoint blockade (ICB). This suggests that non‑genomic barriers within the tumor microenvironment (TME) substantially limit antitumor immunity. Increasing evidence indicates that tumor‑intrinsic glycolytic reprogramming and lactate accumulation contribute to this immune resistance. Oncogenic signaling, hypoxia‑inducible factor‑1α (HIF‑1α), phosphoinositide 3‑kinase/protein kinase B/mechanistic target of rapamycin (mTOR) pathways and noncoding RNA networks promote the expression of glycolytic enzymes and lactate transporters, including hexokinase 2, 6‑phosphofructo‑2‑kinase/fructose‑2,6‑biphosphatase 3 (PFKFB3), pyruvate kinase M2, lactate dehydrogenase A (LDHA) and monocarboxylate transporters, thereby establishing a glycolysis‑high, lactate‑rich TME. Within this metabolic niche, lactate functions as a bioactive mediator that impairs dendritic cell differentiation and cross‑priming, weakens cytotoxic T‑cell and natural killer‑cell activity, and promotes M2‑like macrophages and myeloid‑derived suppressor cells through hydroxycarboxylic acid receptor 1/G protein‑coupled receptor 81‑dependent signaling and histone lactylation. Cancer‑associated fibroblasts and mesenchymal stem/stromal cells further reinforce this state through glycolysis, lactate shuttling, cytokine secretion, extracellular matrix remodeling and exosome‑mediated transfer of glycolysis‑promoting noncoding RNAs. These interactions generate spatially organized immunometabolic niches characterized by lactate accumulation, stromal remodeling, abnormal angiogenesis and poor CD8⁺ T‑cell infiltration. The present review summarizes the molecular drivers of glycolytic reprogramming in GC, the mechanisms by which lactate‑centered crosstalk reshapes stromal and immune compartments, and emerging therapeutic strategies targeting LDHA/monocarboxylate transporter 4, PFKFB3, HIF‑1α/mTOR, epigenetic regulators and repurposed metabolic drugs in combination with programmed death‑1/programmed death‑ligand 1 blockade. It is also discussed how fluorine‑18 fluorodeoxyglucose positron emission tomography/computed tomography, radiomics, glycolysis‑ and lactylation‑related gene signatures, exosomal biomarkers and dynamic metabolic monitoring may support patient stratification and response prediction. Viewing selected GC subtypes through a glycolysis‑centered immunometabolic framework may help guide the rational integration of metabolic and immune interventions to overcome metabolically protected, ICB‑refractory disease.

Prostate cancer is one of the most commonly diagnosed malignancies among men worldwide, with higher reported incidence in many high-income countries. Environmental factors are receiving increasing attention as potential contributors to cancer development. Microplastics, which are found in air, water, food, and personal care items, are one possible risk factor.

Data from 22 nations were investigated to examine whether an association exists between exposure to microplastics and the rate of prostate cancer. Data on exposure were combined from several sources, such as stool particles, breathed air, drinking water, seafood intake, and personal care products. Statistical and machine learning methods, such as K-means clustering, principal component analysis, and random forest modeling, were applied to find the most important exposure variables linked to cancer risk.

Stool microplastic concentrations and heavy metal burden showed the strongest model-based associations with prostate cancer incidence. Countries with higher external exposure indicators did not consistently show higher reported prostate cancer incidence. This pattern suggests that external exposure metrics alone may be insufficient to explain country-level variation. Internal retention and tissue-response pathways remain plausible hypotheses, but they require direct validation using individual-level and tissue-based data.

The findings support the need to integrate exposure pathways, biomonitoring indicators, and biological-response markers when studying microplastic-related cancer risk. However, this study was limited by its ecological design, cross-sectional structure, and small sample size of 22 countries. Therefore, the results should be interpreted as exploratory and hypothesis-generating rather than causal. Further longitudinal and individual-level studies are required to validate these associations.

Oral and pharyngeal cancers affect 850,000 new cases annually with 440,000 deaths worldwide. This study explores the causal relationship between immune cell profiles and oral-pharyngeal cancer risk through Mendelian randomization analysis integrated with experimental validation.

A two-sample Mendelian randomization study was conducted using the MRC IEU OpenGWAS platform, analyzing data from 3757 European individuals for immune cell profiles and 4671 oral-pharyngeal cancer cases, with 80% statistical power to detect OR ≥ 1.2. Multiple Mendelian randomization methods were employed, including inverse-variance weighted, MR-Egger, and weighted median approaches. Findings were validated through coculture experiments examining immune cell-cancer cell interactions via flow cytometry.

Among 731 immune traits analyzed, Mendelian randomization revealed elevated cancer risk associated with CD127 on CD45RA+ CD4+ T cells (OR = 1.33, 95% CI: 1.04-1.70, p = 0.025, F - statistic = 53.08), CD4 on CD39+ CD4+ T cells (OR = 1.17, 95% CI: 1.01-1.35, p = 0.032, F = 34.88), and HLA-DR on CD8+ T cells (OR = 1.25, 95% CI: 1.04-1.50, p = 0.018, F = 50.99). Flow cytometry validation (n = 3 independent experiments, five replicates each) demonstrated that memory B cells enhanced cancer cell viability (92.95% ± 3.2% at 72 h, p < 0.001) while inhibiting apoptosis. Conversely, naive CD8+ T cells showed antitumor effects, reducing cancer cell viability to 67.99% ± 2.8% and inducing apoptosis (28.42% ± 1.9% vs. 12.35% ± 1.2% control, p < 0.001).

This integrated analysis not only reveals novel immune cell-cancer risk associations and their underlying mechanisms but also provides promising opportunities for personalized immunotherapy development in oral-pharyngeal cancer. These findings enable precise patient stratification based on immune cell profiles and suggest tailored therapeutic strategies that could significantly improve clinical outcomes.

While observational studies have indicated a potential link between cancer and coronary atherosclerosis, the relationship remains obscured by confounding factors. Elucidating a shared genetic basis may uncover common pathophysiological pathways.

We employed a two-sample Mendelian randomization (MR) approach to evaluate causal relationships between 23 cancer types and coronary atherosclerosis. Reverse MR analysis was also conducted to explore potential bidirectional effects. Given the exploratory nature of this pan-cancer analysis, we report nominal significance (p < 0.05) without multiple-testing correction.

Forward MR analysis identified nominally significant associations between coronary atherosclerosis and five cancer types; however, after rigorous sensitivity analyses, only the inverse associations with pancreatic cancer (OR = 0.90, 95%CI = 0.83-0.98 and hepatic cancer (OR = 0.87, 95%CI = 0.81-0.94 remained robust. Reverse MR analysis suggested that genetic predisposition to ovarian cancer was associated with lower odds of coronary atherosclerosis(OR = 0.97, 95%CI = 0.94-0.99 ), though the effect size was modest.

This comprehensive large-scale MR study provides hypothesis-generating evidence for a bidirectional genetic interplay between cardiovascular and oncological diseases. These findings point to a complex interplay between these conditions, paving the way for future investigations into shared mechanisms and integrated therapeutic strategies. However, all associations should be interpreted as suggestive rather than definitive causal evidence, and validation in independent cohorts is warranted.

Juxtaglomerular cell tumor (JGCT), also known as reninoma, is an exceptionally rare benign renal neoplasm arising from modified smooth muscle cells of the afferent arteriole of the juxtaglomerular apparatus. The tumor classically presents in young patients with secondary hypertension due to autonomous renin secretion, hypokalemia, and hyperaldosteronism.  A 56-year-old asymptomatic female with known hypothyroidism was incidentally detected to have a right renal mass on a routine health check-up. Contrast-enhanced computed tomography (CECT) confirmed a 2.7 × 2.5 cm homogeneously enhancing medullary lesion in the inter and lower polar region of the right kidney with mass effect and calyceal splaying. She underwent robot-assisted right partial nephrectomy. Histopathology confirmed a juxtaglomerular cell tumor, limited to the kidney, with uninvolved margins. Immunohistochemistry showed diffuse positivity for vimentin, smooth muscle actin (SMA), caldesmon, and CD34. This case is atypical in its presentation - an older, asymptomatic, post-menopausal female without the classic triad of hypertension, hypokalemia, and elevated renin levels. Nephron-sparing surgery is the treatment of choice whenever feasible. A high index of suspicion and a characteristic immunohistochemistry (IHC) profile are essential for definitive diagnosis.

The mediastinum contains a diverse array of tissues, giving rise to a wide spectrum of benign, inflammatory, and malignant lesions. Accurate diagnosis is essential for determining appropriate management strategies, ranging from observation to targeted therapy. Fine-needle aspiration (FNA) has become the cornerstone of mediastinal evaluation, particularly with the advent of endobronchial and endoscopic ultrasound-guided techniques [endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and endoscopic ultrasound-guided FNA (EUS-FNA)], which allow minimally invasive access to all mediastinal compartments. Cytologic evaluation of these specimens, however, presents diagnostic challenges due to overlapping morphologic features and limited material for ancillary testing. This comprehensive review outlines a systematic approach to mediastinal cytopathology, emphasizing specimen adequacy, cytomorphologic interpretation, and integration with ancillary studies. Key entities include reactive lymphoid hyperplasia, granulomatous inflammation, cystic lesions, and a range of neoplastic processes such as thymic epithelial tumors, lymphomas, germ cell tumors (GCTs), mesenchymal neoplasms, and metastatic malignancies. Ancillary techniques-immunocytochemistry (ICC), flow cytometry, and molecular testing-play pivotal roles in confirming lineage, assessing clonality, and enabling targeted therapeutic decisions. Advances in next-generation sequencing (NGS) have expanded the use of cytology specimens for molecular profiling, while digital cytology and artificial intelligence (AI) are emerging as promising tools to improve accuracy and reproducibility. The review also highlights common diagnostic pitfalls, including confusion between thymic lesions and metastatic carcinoma, lymphoma and thymoma, or GCTs and poorly differentiated carcinomas. An algorithmic diagnostic workflow that combines cytomorphology with clinical, radiologic, and molecular data enhances accuracy and efficiency.