Head and neck cancer (HNC) is the seventh most common cancer worldwide with its highest incidence in Asia. Tobacco, alcohol, and HPV contribute to this phenomenon. CD44 has been found to have a mechanistic role in tumorigenicity and metastasis, however current literature shows conflicting evidence regarding its role in HNC. This review attempts to synthesize available studies to clarify its clinicopathological significance.

A PRISMA-compliant systematic search was performed using PubMed, Cochrane, and the Directory of Open Access Journals for studies comparing clinicopathological features between immunohistochemically assessed CD44 expression levels. Meta-analysis was conducted utilizing Review Manager 5.4. Further subgroup analysis was conducted based on the CD44 expression quantification method.

Nine studies, representing 484 patients, were included in the final analysis. An association between CD44 expression and histopathological grading (OR = 0.46, 95% CI: 0.25-0.84) was found. Gender, survival, lymph node involvement, and perineural invasion were not found to be predicted by CD44.

This meta-analysis demonstrates that CD44 expression is associated with histopathological grading in HNC. However, survival, lymph node involvement, and perineural invasion are found to be independent of CD44 expression.

Chronic growth hormone and insulin-like growth factor 1 excess may promote tumorigenesis, but the magnitude of malignancy risk in acromegaly remains uncertain and regional data from the Gulf are limited.

To describe the frequency, spectrum, detection, outcomes, and clinical correlates of malignancy among patients with acromegaly treated across Gulf tertiary centers.

Multicenter retrospective observational study.

Five tertiary centers across Saudi Arabia, Qatar, and the United Arab Emirates.

Medical records of patients aged >16 years with acromegaly who were evaluated from 2010 through 2024 were reviewed. Demographic, disease, treatment, cancer-testing, and malignancy data were collected. Group comparisons were descriptive and exploratory because only 10 malignancies occurred.

Documented malignancy frequency, cancer type, method of detection, stage, treatment, outcome, and clinical correlates.

157 patients.

The mean age was 47.1 years, 101 patients (64.3%) were male, and the mean disease duration was 9.4 years. Malignancy was documented in 10 patients (6.4%), most commonly papillary thyroid carcinoma (8/10). Two of the eight papillary thyroid carcinomas were classified as T1a (≤10 mm); exact pathology measurements were not consistently available. One patient had colorectal cancer, and one had prostate cancer. Exploratory comparisons showed that patients with malignancy were older than those without malignancy (mean age, 56.6 vs 46.5 years; P=.039). The remaining comparisons were inconclusive. All patients with malignancy were in remission or had an excellent response at the last documented follow-up.

Malignancy was documented in 6.4% (10 out of 157) in this multi-center Gulf acromegaly cohort, predominantly papillary thyroid carcinoma. The findings support individualized surveillance based on population guidance, symptoms, family history, and clinical findings rather than an acromegaly-specific screening program.

Retrospective design, small number of malignancy events, missing data, lack of a population comparator, and nonstandardized cancer testing may introduce selection and detection biases.

Two-field esophagectomy for esophageal cancer and tumors of the esophagogastric junction is associated with substantial postoperative morbidity and mortality. Enhanced Recovery After Surgery (ERAS^®) protocols aim to improve perioperative outcomes through standardized multimodal care pathways. At our institution, a modified perioperative regimen has been implemented that deviates from current ERAS^® recommendations, incorporating selective oral decontamination, an enforced near-zero fluid balance, colloid administration using hydroxyethyl starch (HES), and routine nasogastric decompression.

We performed a retrospective analysis of 325 consecutive patients who underwent two-field esophagectomy. Of these, 279 were treated under the modified perioperative regimen, while 46 received standard care. To adjust for baseline differences, we conducted 1:1 propensity-score matching. Postoperative outcomes, including complication rates, anastomotic leakage, Comprehensive Complication Index (CCI) and textbook outcome rates were compared between groups. This trial was prospectively registered (DRKS00024369) and approved by the Medical Ethics Committee of the University of Freiburg (Reg.-Nr. 21-1093 and 21-1713).

Prior to PSM, modified care group demonstrated a higher frequency of textbook outcomes and a significantly lower incidence of anastomotic leakage compared with standard care. Overall rates of major complications did not differ significantly between groups, though a trend toward reduced complication severity as measured by CCI was observed. After PSM, baseline characteristics were balanced. Rates of textbook outcome (Clavien-Dindo 0: 15.2% vs 28.3%, p=0.14) and severe complications (Clavien-Dindo ≥III: 39.1% vs 58.7%, p=0.095) were reduced but did not reach statistical significance. The CCI remained numerically lower in modified care (32.01 vs 35.70, p=0.061). Odds ratios for major complications (OR 0.45, 95% CI 0.20-1.04), anastomotic leakage (OR 0.30, 95% CI 0.06-1.59) and IMC readmission (OR 0.33, 95% CI 0.08-1.34) favored modified care but were not statistically significant. Fluid balance on POD4 and early parenteral nutrition were similar after matching. Acute kidney injury did not occur more frequently after HES-application. Overall and disease-free survival did not differ between groups.

The modified perioperative regimen applied in this study appears to be a safe alternative to conventional ERAS®-based pathways. While definitive superiority could not be demonstrated after propensity matching, the observed trends - particularly regarding anastomotic integrity and overall complication burden - support further prospective evaluation of this approach.

Tumor response to radiotherapy is strongly influenced by oxygen availability and phenotypic heterogeneity, yet their combined impact on the relative performance of fractionation schedules remains unclear. Here, we develop a mathematical model that integrates spatial oxygen dynamics with continuous phenotypic adaptation to hypoxia and radiation, and use it to systematically compare radiotherapy protocols under a common normal-tissue toxicity constraint. Under spatially uniform oxygenation, we find that alternative fractionation schedules provide little improvement over standard-of-care protocols in normoxic conditions. Under moderate hypoxia, however, a distinct class of protracted schedules with longer inter-fraction intervals substantially increases time-to-progression, in some cases by up to twofold. This regime-dependent benefit is consistent with a shift in the balance between reoxygenation and selection for resistant phenotypes. When oxygen delivery is spatially heterogeneous, treatment outcomes depend strongly on the geometric organization of oxygen sources. Even with identical total oxygen supply, different spatial configurations lead to large variability in time-to-progression and can alter the relative ranking of radiotherapy protocols. These results show that radiotherapy effectiveness is not an intrinsic property of a treatment schedule alone, but emerges from its interaction with tumor microenvironmental structure and evolutionary dynamics. Incorporating both spatial heterogeneity and phenotypic adaptation may therefore be important for the consistent evaluation and design of fractionation strategies in heterogeneous tumors.

The potential relationship between fungal biology and cervical cancer remains poorly understood. This study aimed to assess the ability of ChatGPT-4o to generate research hypotheses concerning possible links between fungal factors, HPV persistence, and cervical carcinogenesis. ChatGPT-4o generated hypotheses in three prespecified domains: microbial dysbiosis, inflammation, and immune modulation. Three author-evaluators with expertise in pathology, oncology, and microbiology independently assigned overall evaluation scores and assessed the scientific reasonableness of experimental-plan components. Targeted literature searches identified publications directly addressing each proposed mechanism. Inter-rater reliability was quantified using a two-way random-effects, absolute-agreement intraclass correlation coefficient (ICC) and pairwise quadratic-weighted Cohen's kappa. No human-generated hypothesis set, alternative language model, or repeated independent AI session was included. ChatGPT-4o generated 55 hypotheses. No directly matching publication was identified for 48 hypotheses under the prespecified search framework; this finding was interpreted as indicating an underexplored direction, not proof of novelty. Based on the predefined composite evaluation rubric, 35 hypotheses (63.6%) received high mean evaluation scores and 20 (36.4%) received moderate mean evaluation scores. Agreement for hypothesis scores was high (ICC (2,1) = 0.975; pairwise weighted kappa = 0.963-1.000). Among 18 experimental-plan components, 12 received high mean scores and 6 received moderate mean scores; agreement was lower but still strong (ICC (2,1) = 0.821; weighted kappa = 0.727-0.914). Representative hypotheses concerned fungal metabolites and oxidative stress, fungal-associated inflammation and oxidative damage, and fungal modulation of immune-checkpoint pathways. This pilot study suggests that ChatGPT-4o can generate diverse and potentially testable hypotheses concerning fungal biology and cervical cancer. However, the generated hypotheses should be regarded as exploratory research directions rather than validated mechanisms and require independent literature verification and experimental validation.

Pregnancies complicated by BCR::ABL1-negative myeloproliferative neoplasms (MPNs) are associated with increased maternal and thrombotic risk; however, large real-world comparative data remain limited. We performed a multicenter retrospective propensity score-matched cohort study using the TriNetX database to evaluate maternal, obstetric, and thrombotic outcomes among pregnant patients with MPN compared with matched non-MPN controls. Baseline demographics, comorbidities, and antithrombotic medication use were balanced after matching (standardized mean difference < 0.1). Among 4,467,127 pregnancies, 4,563 patients had MPN, most commonly essential thrombocytosis (85%). Compared with matched controls, MPN pregnancies had significantly higher all-cause mortality (1.1% vs. 0.2%; hazard ratio [HR] 5.4, 95% CI 2.7-10.8), gestational hypertension (11.1% vs. 7.8%; HR 1.3, 95% CI 1.1-1.5), preeclampsia/eclampsia (10.4% vs. 5.3%; HR 1.8, 95% CI 1.6-2.1), preterm labor (6.1% vs. 3.7%; HR 1.5, 95% CI 1.2-1.8), intrauterine growth restriction (7.3% vs. 5.1%; HR 1.3, 95% CI 1.1-1.7), postpartum hemorrhage (5.5% vs. 3.8%; HR 1.3, 95% CI 1.1-1.6), and venous thromboembolism (2.7% vs. 0.7%; HR 3.2, 95% CI 2.2-4.6). Arterial thrombotic events were not significantly different between groups. Pregnancies in patients with MPN are associated with significantly increased maternal, obstetric, and venous thrombotic complications, highlighting the need for multidisciplinary management and individualized thromboprophylaxis strategies.

Targeted therapies significantly extend the survival of patients with myeloproliferative neoplasms (MPNs) and myelodysplastic syndromes (MDS). This prolonged lifespan introduces an unintended clinical hazard. These patients face an elevated risk of developing primary central nervous system (CNS) tumors. The internal relationship between them remains to be explored. We integrated the Global Burden of Disease (GBD) and the Cancer Incidence in Five Continents (CI5) datasets to conduct spatial clustering mapping using Moran's I. Vector autoregression and Granger causality analysis were employed to examine the longitudinal incidence of these diseases in Sweden from 1990 to 2021. Bibliometric profiling was utilized to identify research frontiers, and two-sample Mendelian randomization (MR) was used to determine genetic correlation. Geospatial mapping indicated a dually dominant burden of MPN + MDS (MPN and MDS, not MPN/MDS) and CNS tumors in developed regions. Longitudinal data from Sweden exposed a strictly unidirectional predictive trajectory exclusive to females. Myeloid malignancies reliably preceded CNS tumors. Bibliometric analysis demonstrated a remarkable interdecadal convergence on neuroinflammation and the tumor microenvironment. Significantly, MR confirmed that MPN (odds ratio [OR] = 1.84, 95% confidence interval [CI]: 1.22-2.76) and MDS (OR = 2.54, 95% CI: 1.62-3.96) have definite positive effects on GBM susceptibility. We established the possible comorbidity relationship between MPN + MDS and GBM, and raised the myeloid-neuro-immune crosstalk theory. It lays a reliable foundation on the interactions between MPN + MDS and GBM for future research, and offers insights for building multidisciplinary team collaboration.

Pilomatrix-like high-grade endometrial carcinoma (PiMHEC) is a recently recognized, clinically aggressive variant of endometrial carcinoma that is frequently misdiagnosed due to its morphological and immunophenotypic overlap with other high-grade endometrial malignancies. We report a 52-year-old woman who presented with widely metastatic high-grade carcinoma of endometrial origin, involving the vagina and distant sites including the brain, lung, and lymph nodes. Histologically, the tumor displayed a predominantly solid basaloid architecture with extensive geographic necrosis and abrupt keratinization with conspicuous shadow cells, supporting pilomatrix-like differentiation. Immunohistochemically, the tumor demonstrated strong, diffuse, aberrant nuclear β-catenin expression; patchy, heterogeneous expression of TTF1, GATA3 and CD10; and variable expression of CK7, CDX2, and p16. The tumor was negative for PAX8, ER, PR, and p40. p53 showed a wild-type pattern, and mismatch repair was retained (pMMR). Next-generation sequencing (NGS) identified a pathogenic exon 3 CTNNB1 p.S33Ymutation. The morphologic, immunophenotypic, and molecular findings supported a diagnosis of PiMHEC. Notably, expression of TTF-1, GATA3, and CD10, together with absence of ER and PR expression, creates substantial immunophenotypic overlap with mesonephric-like adenocarcinoma (MLA) and represents a potential diagnostic pitfall. Recognition of characteristic shadow cell keratinization and aberrant nuclear β-catenin expression, integrated with molecular findings, is critical for distinguishing PiMHEC from MLA. This case expands the clinicopathologic spectrum of this underrecognized aggressive neoplasm and highlights the importance of integrating morphology, immunohistochemistry, and molecular findings to avoid diagnostic misclassification.

Glioblastoma (GBM) has a poor prognosis, and temozolomide (TMZ) therapy is limited by a short half-life and insufficient intratumoral availability. We developed a bevacizumab (BVZ)-functionalized, exosome-associated chitosan nanocomposite loaded with TMZ (BVZ-Exo@CS-TMZ) as a multifunctional biohybrid platform for experimental glioma therapy.

CS-TMZ nanoparticles were prepared by ionotropic gelation, non-covalently associated with adipose-derived stromal cell exosomes (Exo), and functionalized with BVZ via EDC/NHS conjugation to accessible surface carboxyl groups. The Exo preparation was characterized by Western blotting, while the final formulation was characterized by FTIR, XRD, FESEM, TEM, DLS, zeta potential, and VEGF-binding ELISA. Apparent TMZ retention, loading, and release were quantified by UV-visible spectrophotometry. Biological activity was evaluated in C6 glioma cells and in a proof-of-concept intracerebral C6 glioma-bearing rat model.

BVZ-Exo@CS-TMZ showed quasi-spherical morphology, a hydrodynamic diameter of 195.6 ± 6.7 nm, a PDI of 0.21 ± 0.03, and a zeta potential of -50.12 mV. Western blotting detected the EV-associated markers CD9, CD63, and CD81 in the Exo preparation, whereas calnexin was not detected. ELISA showed 74.9 ± 2.9% retained VEGF-binding activity after conjugation and washing. Apparent TMZ entrapment efficiency was 68.50 ± 2.15%, with a final trehalose-free loading of 15.96 ± 0.18 wt%. Apparent release over 96 h was acid-accelerated (Korsmeyer-Peppas n = 0.448-0.497). In C6 cells, the formulation reduced metabolic viability to 37.9% and lowered the TMZ-equivalent apparent IC_{5 0} from 99.4 to 55.6 µM. In vivo, it produced the smallest tumour area and fewest H&E-defined vascular-like regions, with increased Tp53, Bax, and Casp3 transcripts and reduced pri-/pre-miR-21 precursor RNA.

These findings support BVZ-Exo@CS-TMZ as a proof-of-concept EV-associated chitosan nanomedicine strategy for experimental glioma. Further pharmacokinetic, biodistribution, safety, and mechanistic validation in more clinically relevant glioblastoma models is required.

Although immune checkpoint inhibitors have reshaped the therapeutic landscape of gastric cancer, durable responses are achieved in only a minority of patients. The tumor microenvironment, particularly immune-cell composition and spatial organization, critically modulates cancer progression and the efficacy of immune checkpoint inhibitors. Nevertheless, the lack of clinically accessible approaches for spatially resolving the tumor immune contexture, whether by direct pathological quantification or indirect radiomic inference, has hindered a mechanistic understanding of how it dictates immunotherapy outcomes. Deep learning-based radiomics and pathomics extract high-dimensional phenotypic information from radiological and pathological images, thereby characterizing tumors at macroscopic and microscopic scales. Each modality, however, captures only a partial view of the tumor microenvironment. Multimodal models can integrate complementary imaging features associated with tumor heterogeneity and spatial immune organization, thus improving predictive performance and linking multimodal features to immune-related biological processes. In this review, we summarize recent advances in deep learning-based radiomics, pathomics, and multimodal frameworks for decoding the immune microenvironment and predicting immunotherapy outcomes in gastric cancer. We also discuss their potential to complement established biomarkers and support personalized treatment decisions. Finally, we highlight key challenges, including limited data availability, interinstitutional variability, insufficient external validation, poor interpretability, and barriers to clinical implementation. Addressing these limitations may accelerate the development of robust imaging biomarkers for guiding immunotherapy decisions in gastric cancer.