Bosnian Journal of Basic Medical Sciences
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Molecular and immune characteristics of neuroendocrine bladder carcinoma — Implications for diagnosis, prognosis, and therapy: A review
Full text linkNeuroendocrine bladder carcinoma (NEBC) is a rare but highly aggressive histologic subtype of bladder cancer with poor prognosis, often driven by delayed diagnosis and limited therapeutic options; despite widespread use of next-generation sequencing, its cellular origin remains unclear and controversial. We aimed to synthesize up-to-date molecular and immune features of NEBC and translate them into practical guidance for diagnosis and treatment. We performed a narrative review of English-language studies indexed in PubMed and Web of Science (January 2000–August 2025) using predefined keywords, integrating genomic, transcriptomic, immunohistochemical, and clinical outcome data. Key findings indicate frequent co-occurrence and probable common clonal origin with urothelial bladder carcinoma, with hallmark TP53 and RB1 alterations, prevalent APOBEC-driven mutagenesis, and recurrent TERT promoter mutations; tumor mutation burden is heterogeneous but can be high. Despite this, NEBC commonly exhibits an immune-cold or immune-excluded microenvironment characterized by low PD-L1 expression and T-cell dysfunction, which may blunt responses to immune checkpoint inhibitor monotherapy. Diagnostic practice still relies on morphology supported by immunohistochemistry (synaptophysin, chromogranin A, CD56, GATA3), with emerging tools such as INSM1 and a decision-tree model using synaptophysin, CD117, and GATA3 that improve accuracy. Therapeutically, neoadjuvant chemotherapy—most commonly EP or IA—followed by radical cystectomy improves outcomes compared with initial cystectomy alone, while metastatic disease is typically managed with EP chemotherapy and radiotherapy with limited durability. Early data support immunotherapy, particularly immune checkpoint inhibitors, and suggest potential benefit from chemoimmunotherapy; a prospective trial of neoadjuvant anti-PD-L1 plus EP is underway, and antibody-drug conjugates and bladder-sparing multimodality strategies are emerging. In conclusion, comprehensive molecular and immune characterization is critical to refine diagnosis, optimize patient selection, and accelerate prospective trials that evaluate neoadjuvant chemotherapy, chemoimmunotherapy, and targeted approaches in NEBC
Preoperative predictors of mortality in intestinal perforation
Full text linkBowel perforation represents a prevalent and life-threatening emergency within general surgical pathology. This study aims to evaluate clinical and biochemical parameters that predict mortality in cases of bowel perforation. A retrospective analysis was performed on 144 patients who underwent surgical intervention for bowel perforation between 2019 and 2024. Key variables assessed included the albumin/creatinine ratio, age, serum albumin levels, CRP, and history of COVID-19. Mortality-associated variables were analyzed using univariate and multivariate logistic regression, as well as receiver operating characteristic (ROC) analysis. The mean age of the patients was 60 years, with 84 patients (58.3%) being male. The overall mortality rate was 25%. Independent predictors of mortality identified in the study included an albumin/creatinine ratio <3.38 (odds ratio [OR]: 12.666, p<0.001), age >66 years (OR: 3.273, p=0.036), and serum albumin levels <3 g/dL (OR: 5.653, p=0.002). ROC analysis indicated that the area under the curve (AUC) for the albumin/creatinine ratio was 0.879, establishing it as the parameter with the highest predictive accuracy for mortality. Among patients with a history of COVID-19, ischemia was the predominant cause of perforation (87.5%), while malignancy was the leading cause (41.4%) in those without a COVID-19 history. This difference in etiology was statistically significant (p<0.001). In conclusion, the albumin/creatinine ratio, age, and serum albumin levels are robust parameters for predicting mortality in bowel perforation cases. Furthermore, a history of COVID-19 significantly increases the risk of bowel perforation due to ischemia
Tumor budding in preoperative breast biopsies predicts sentinel lymph node metastasis
Full text linkSentinel lymph node biopsy (SLNB) is a pivotal technique employed to assess the necessity for axillary lymph node dissection (ALND), evaluated during the preoperative phase through clinical and radiological findings. The preoperative identification of sentinel lymph node metastasis has gained paramount importance in the surgical management of breast cancer. Tumor budding (TB) has emerged as a significant prognostic marker across various cancers, including breast cancer, where it is instrumental in detecting lymph node metastasis. This study aims to investigate the role of tumor budding in predicting sentinel lymph node metastasis in preoperative breast biopsies. We included patients diagnosed with breast cancer, specifically those with invasive ductal carcinoma (IDC), who underwent preoperative needle biopsy and subsequent evaluation of postoperative surgical specimens, as well as SLNB at our medical center. The histological slides of these cases were reevaluated, and tumor cell clusters comprising up to four cells were classified as TB. Lymph nodes exhibiting tumor cell involvement, limited to macrometastasis, were classified as positive. A total of 65 patients were enrolled in the study. Among these, 36 patients exhibited TB in their preoperative biopsies, while 29 did not. The median tumor sizes were 20 mm (range: 6–50 mm) in the TB-positive group and 19 mm (range: 2–50 mm) in the TB-negative group (p=0.3). Sentinel lymph node metastasis was detected in 18 patients with TB, compared to only five patients without TB, a difference that was statistically significant (p=0.006). We conclude that evaluating tumor budding in breast tru-cut specimens, in conjunction with clinical and radiological findings, may enhance the preoperative assessment of breast cancer cases requiring SLNB
A preliminary study on the prognostic significance of cysteine-rich EGF ligand domain 2 protein (CRELD2) in patients with triple negative breast cancer
Full text linkThe cysteine-rich epidermal growth factor ligand domain 2 protein (CRELD2) is associated with pathways that regulate epithelial-to-mesenchymal transition, a critical process driving cancer metastasis. This study aimed to determine the prognostic value of CRELD2 status on survival outcomes in triple-negative breast cancer (TNBC). Seventy patients were included in the study. Thirty-four patients were metastatic, and 36 patients were non-metastatic. CRELD2 protein expression in tumor tissue was determined by immunohistochemical staining (IHC). The patients were divided into two groups: CRELD2 positive and negative groups. Clinicopathological features and survival outcomes were compared between the groups. In the survival analysis of the non-metastatic patient group, five-year overall survival (OS) rate was 91.7% in the CRELD2-positive patient group and 91% in the negative group (P = 0.91). Median progression free survival (PFS) was 9.4 (95% confidence interval [CI]: 6.4–12.4) months in the CRELD2-positive group and 11.9 (95% CI: 8.2–18.6) months in the CRELD2-negative group (P = 0.04). The median OS was 17.2 (95% CI: 13.7–22.3) months in the CRELD2-positive group and 24.7 (95% CI: 21.8–29.6) months in the CRELD2-negative group (P = 0.02). In multivariate analysis, CRELD2 status (negative vs positive) (hazard ratio [HR]: 0.50, 95% CI: 0.38–0.96, P = 0.02) was determined to be a risk factor for OS and CRELD2 status (negative vs positive) (HR: 0.82, 95% CI: 0.33–0.96, P = 0.01) was defined as a risk factor for PFS in patients with metastatic TNBC. This is the first clinical study to determine the effect of CRELD2 on survival and as a prognostic marker in patients with triple metastatic breast cancer. These results need to be validated prospectively with a large sample size
Integrative PANoptosis gene profiling reveals prognostic and therapeutic insights in prostate cancer
Full text linkProstate cancer (PCa) remains a significant global health challenge, representing the most common solid tumor in men and the fifth leading cause of cancer-related death. Despite therapeutic advances, achieving a definitive cure remains difficult. Early diagnosis and personalized treatment strategies are crucial for improving patient outcomes. Programmed cell death—particularly PANoptosis, an inflammatory pathway that integrates pyroptosis, apoptosis, and necroptosis—has emerged as a promising therapeutic target in oncology.In this study, individuals with PCa were categorized into PANoptosis-high and PANoptosis-low subgroups based on the expression levels of 45 PANoptosis-related genes. Differential gene expression analysis and subsequent enrichment analyses were conducted to explore the biological pathways associated with each subgroup. A four-gene risk signature (CASP7, ADAR, DNM1L, and NAIP) was identified, showing strong predictive value for overall survival (OS) in both training and validation cohorts. This signature was independently associated with OS and showed meaningful correlations with the tumor microenvironment, particularly immune cell infiltration and immunotherapy responsiveness. These findings suggest that the PANoptosis-related gene signature may serve as a valuable prognostic biomarker and inform immunotherapeutic strategies in PCa management
Role of gut microbiota and immune response in breast cancer progression
Full text linkBreast cancer is one of the most prevalent cancers among women and is associated with high mortality rates. Emerging evidence suggests a link between gut microbiota and the development of various tumors, particularly those involving immune-mediated mechanisms. However, the potential relationship between gut microbiota and breast cancer—and whether this relationship is mediated by immune cells—remains unclear. This Mendelian randomization (MR) study utilized summary statistics from genome-wide association studies of 412 gut microbiota, 731 immune cell traits, and breast cancer (including its subtypes). Two-sample MR analyses were conducted to assess potential causal relationships between gut microbiota and breast cancer. To further validate the findings, Bayesian weighted MR was applied. Robustness was ensured through sensitivity, specificity, and pleiotropy analyses. A reverse MR analysis was also performed to assess the potential for reverse causality. Finally, mediation analysis was employed to investigate whether immune cells mediate the pathway from gut microbiota to breast cancer. The MR analysis identified 15 gut microbiota and related metabolic pathways significantly associated with breast cancer, with nine showing positive associations and six showing negative associations. The reverse MR analysis did not support a causal effect of breast cancer on gut microbiota. Mediation analysis revealed that DP (CD4⁺CD8⁺) % leukocyte mediated the pathway between gut microbiota (PWY-6263: superpathway of menaquinol-8 biosynthesis II) and breast cancer. These findings suggest a causal relationship between gut microbiota and breast cancer, with a small portion of this effect mediated by immune cells. This study underscores the potential role of gut microbiota and immune modulation in the pathogenesis of breast cancer
A deep learning model based on chest CT to predict benign and malignant breast masses and axillary lymph node metastasis
Full text linkDifferentiating early-stage breast cancer from benign breast masses is crucial for radiologists. Additionally, accurately assessing axillary lymph node metastasis (ALNM) plays a significant role in clinical management and prognosis for breast cancer patients. Chest computed tomography (CT) is a commonly used imaging modality in physical and preoperative evaluations. This study aims to develop a deep learning model based on chest CT imaging to improve the preliminary assessment of breast lesions, potentially reducing the need for costly follow-up procedures such as magnetic resonance imaging (MRI) or positron emission tomography-CT and alleviating the financial and emotional burden on patients. We retrospectively collected chest CT images from 482 patients with breast masses, classifying them as benign (n = 224) or malignant (n = 258) based on pathological findings. The malignant group was further categorized into ALNM-positive (n = 91) and ALNM-negative (n = 167) subgroups. Patients were randomly divided into training, validation, and test sets in an 8:1:1 ratio, with the test set excluded from model development. All patients underwent non-contrast chest CT before surgery. After preprocessing the images through cropping, scaling, and standardization, we applied ResNet-34, ResNet-50, and ResNet-101 architectures to differentiate between benign and malignant masses and to assess ALNM. Model performance was evaluated using sensitivity, specificity, accuracy, receiver operating characteristic (ROC) curves, and the area under the curve (AUC). The ResNet models effectively distinguished benign from malignant masses, with ResNet-101 achieving the highest performance (AUC: 0.964; 95% CI: 0.948–0.981). It also demonstrated excellent predictive capability for ALNM (AUC: 0.951; 95% CI: 0.926–0.975). In conclusion, these deep learning models show strong diagnostic potential for both breast mass classification and ALNM prediction, offering a valuable tool for improving clinical decision-making
Anti-Müllerian hormone in PCOS: Molecular regulation and emerging therapeutic strategies
Full text linkAnti-Müllerian hormone (AMH), a glycoprotein belonging to the transforming growth factor-beta (TGF-β) superfamily, is a key regulator of ovarian folliculogenesis. Dysregulated AMH expression is a hallmark of polycystic ovary syndrome (PCOS), a common endocrine and metabolic disorder characterized by hyperandrogenism, anovulation, and polycystic ovarian morphology. Elevated AMH levels in PCOS impair follicle-stimulating hormone (FSH) sensitivity, disrupt follicular maturation, and contribute to androgen excess—creating a feedback loop that exacerbates ovarian dysfunction. This review explores the complex regulatory mechanisms governing AMH expression, including transcriptional, post-transcriptional, and post-translational processes. It highlights the interplay between AMH, FSH, and androgen signaling pathways, emphasizing their roles in the pathophysiology of PCOS. Particular attention is given to the downstream SMAD-dependent signaling cascade, which mediates many of AMH’s biological effects. Additionally, we summarize emerging therapeutic strategies targeting AMH signaling, such as AMHR2 (anti-Müllerian hormone receptor type 2) antagonists, GnRH (gonadotropin-releasing hormone) antagonists, and aromatase inhibitors. A deeper understanding of AMH regulation and signaling provides critical insights into its role in PCOS progression and supports the development of novel, targeted treatments aimed at alleviating both reproductive and metabolic symptoms
Predictive value of inflammatory markers in inguinal hernia surgery: General vs. spinal anesthesia
Full text linkInguinal hernia is a prevalent condition requiring surgical intervention, and accumulating evidence suggests that the type of anesthesia administered may influence systemic inflammatory responses. This study investigates the concentrations of inflammatory parameters in patients with inguinal hernia who underwent surgery utilizing either general or spinal anesthesia. The cohort comprised 87 male patients with inguinal hernia, classified as American Society of Anesthesiologists (ASA) physical status 1-2, who underwent elective surgical procedures. Participants were divided into two groups based on the anesthesia type: 44 received general anesthesia while 43 received spinal anesthesia. Plasma concentrations of leukocytes, C-reactive protein (CRP), interleukin-6 (IL-6), and lipopolysaccharide-binding protein (LBP) were quantified using automated immunoassays and a hematological analyzer. Standard parametric and non-parametric statistical tests were employed for data analysis, and the predictive capacity of select parameters, along with body mass index (BMI) and age, was assessed through Receiver Operating Characteristic (ROC) analysis with Area Under the Curve (AUC). Statistical analysis via the t-test identified significant differences in LBP concentrations (LBP 1, LBP 2, and LBP 3) between patients receiving general and spinal anesthesia. Correlation analysis of BMI and the measured parameters revealed statistically significant positive correlations for LBP 1 and LBP 2 in patients who underwent spinal anesthesia. Notably, the preoperative concentration of LBP, with a cutoff value exceeding 9.7 µg/mL, suggests a potentially superior approach with spinal anesthesia compared to general anesthesia, demonstrating 50% sensitivity and 81.4% specificity. Other parameters did not exhibit statistical significance in differentiating the type of anesthesia used for inguinal hernia surgery
Luteolin mitigates hippocampal damage in a rat model of streptozotocin-induced diabetes
Full text linkDiabetes mellitus (DM) is a chronic metabolic disorder that poses a serious threat to human health by causing long-term damage to various vital organs. It leads to insulin resistance and disrupts carbohydrate, fat, and protein metabolism. This study aimed to investigate the protective effects of luteolin (Lut) against diabetes-induced damage in the hippocampus of rats, using immunohistochemical, histopathological, biochemical, and molecular approaches. Lut [20 μg/kg, intraperitoneally (i.p.)] was administered to counteract hippocampal damage induced by diabetes, which was experimentally triggered using streptozotocin at a dose of 50 mg/kg (i.p.). The experiment lasted 28 days and included 48 rats divided into six groups of eight: Control, DM, citrate buffer (solvent), DM+Lut, Lut, and dimethyl sulfoxide (solvent). In the DM group, there was a decrease in Bcl-2 gene expression and an increase in the expression levels of Bax, caspase-3, cytochrome c, activating transcription factor-6, and inositol-requiring enzyme-1, compared to the DM+Lut group. Histological analysis revealed greater neuronal degeneration, neuroinflammation, and apoptosis in the DM group than in the DM+Lut group. Biochemical analysis also supported these findings, as indicated by increased oxidative stress index values. These results suggest that Lut mitigates the toxic effects of oxidative and endoplasmic reticulum stress, enhances antioxidant defenses, and supports hippocampal function. The findings demonstrate Lut’s potential to prevent diabetes-induced hippocampal damage. Consequently, further research is strongly recommended to explore Lut as a therapeutic agent for diabetic neurodegeneration