Bosnian Journal of Basic Medical Sciences (BJBMS)
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A novel deep learning framework for automatic scoring of PD-L1 expression in non-small cell lung cancer
Get PDFA critical predictive marker for anti-PD-1/PD-L1 therapy is programmed death-ligand 1 (PD-L1) expression, assessed by immunohistochemistry (IHC). This paper explores a novel automated framework using deep learning to accurately evaluate PD-L1 expression from whole slide images (WSIs) of non-small cell lung cancer (NSCLC), aiming to improve the precision and consistency of Tumor Proportion Score (TPS) evaluation, which is essential for determining patient eligibility for immunotherapy. Automating TPS evaluation can enhance accuracy and consistency while reducing pathologists\u27 workload. The proposed automated framework encompasses three stages: identifying tumor patches, segmenting tumor areas, and detecting cell nuclei within these areas, followed by estimating the TPS based on the ratio of positively stained to total viable tumor cells. This study utilized a Reference Medicine (Phoenix, Arizona) dataset containing 66 NSCLC tissue samples, adopting a hybrid human-machine approach for annotating extensive WSIs. Patches of size 1000x1000 pixels were generated to train classification models such as EfficientNet, Inception, and Vision Transformer models. Additionally, segmentation performance was evaluated across various UNet and DeepLabV3 architectures, and the pre-trained StarDist model was employed for nuclei detection, replacing traditional watershed techniques. PD-L1 expression was categorized into three levels based on TPS: negative expression (TPS < 1%), low expression (TPS 1-49%), and high expression (TPS ≥ 50%). The Vision Transformer-based model excelled in classification, achieving an F1-score of 97.54%, while the modified DeepLabV3+ model led in segmentation, attaining a Dice Similarity Coefficient of 83.47%. The TPS predicted by the framework closely correlated with the pathologist\u27s TPS at 0.9635, and the framework\u27s three-level classification F1-score was 93.89%. The proposed deep learning framework for automatically evaluating the TPS of PD-L1 expression in NSCLC demonstrated promising performance. This framework presents a potential tool that could produce clinically significant results more efficiently and cost-effectively
Hormonal predictors of the insulin sensitive phenotype in humans
Get PDFClinical obesity, a chronic condition marked by excessive fat accumulation, often leads to insulin resistance and a heightened risk of comorbidities. This study aimed to identify hormonal predictors of an insulin-sensitive phenotype (ISP) in patients undergoing body contouring surgeries, focusing on the relationship between gut hormones, adipokines, and fat mass. ISP was defined as the highest tertile of HOMA insulin sensitivity. We prospectively followed patients undergoing abdominoplasty, lower body lift, or thigh lift at Hamad General Hospital from January 2021 to December 2023. Body composition, glycemic indices, and hormonal levels were assessed, with data analyzed using descriptive statistics and regression models. The study included 34, 22, and 27 subjects at visits 1, 2, and 3, respectively. Fat percentage decreased slightly at visits 2 and 3 compared to baseline, though not significantly. Median levels of glucagon-like peptide-1 (GLP-1), gastric inhibitory polypeptide (GIP), pancreatic polypeptide (PP), liver-expressed antimicrobial peptide 2 (LEAP2), and amylin varied significantly across visits, initially rising at visit 2 before declining at visit 3. Logistic regression revealed that ISP was negatively associated with serum GIP. LEAP2, and leptin levels while positively associated with PP. History of bariatric surgery was only weakly associated with the ISP after hormonal associations were accounted for. Notably, total body fat percentage did not predict ISP after accounting for hormonal factors. This study highlights GIP, PP, leptin, and LEAP2 as key predictors of ISP, with GIP being the primary negative regulator. These findings underscore the importance of hormonal interplay in insulin sensitivity, emphasizing the role of gut hormones and adipokines in predicting ISP in humans
Influence of menopause status on T-helper cell profiles in acute myocardial infarction
Get PDFEstrogens modulate immune responses, particularly the activation and polarization of CD4+ T cells, which play key roles in cardiovascular homeostasis. This proof-of-concept study investigated the effect of menopausal status on the polarization of T-helper (Th) cells in women with acute myocardial infarction (AMI). A total of 41 female AMI patients were enrolled—seven premenopausal and 34 postmenopausal—and compared with a group of 17 male AMI patients. Flow cytometry was used to evaluate CD4+ T-cell subsets, including Th1 (T-bet+), Th2 (GATA3+), and Th17 (RORγt+) phenotypes. Serum levels of representative cytokines were also measured. Women exhibited higher numbers of circulating CD4+ T cells compared to men, with a marked shift toward the Th1 phenotype. Postmenopausal women demonstrated increased cardiovascular risk, as indicated by higher QRISK3 and GRACE scores, as well as elevated levels of C-reactive protein and cardiac troponin T compared to premenopausal women. However, menopausal status had minimal impact on Th cell polarization, as no significant differences were observed in the proportions of Th1, Th2, or Th17 subsets between premenopausal and postmenopausal women. Similarly, levels of interleukin (IL)-6, IL-1β, IL-10, tumor necrosis factor, and monocyte chemoattractant protein-1 were comparable between the two groups. This proof-of-concept study highlights sex-specific differences in immune responses and inflammatory profiles during AMI. Women exhibited a stronger polarization toward the Th1 phenotype, along with elevated markers of inflammation and myocardial injury. Notably, menopausal status did not significantly affect lymphocyte subpopulations or circulating cytokine levels
The role of COPD in survival of NSCLC patients receiving immune checkpoint inhibitors: A meta-analysis
Get PDFThe impact of chronic obstructive pulmonary disease (COPD) on the survival of patients with non-small cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs) remains unclear. Given the growing use of ICIs in NSCLC treatment and the high prevalence of COPD among these patients, understanding this relationship is essential. This meta-analysis aims to evaluate the association between COPD and survival outcomes in NSCLC patients treated with ICIs. A systematic search was conducted in PubMed, Embase, and Web of Science from inception to February 10, 2025. Observational studies reporting survival outcomes in NSCLC patients with and without COPD undergoing ICI therapy were included. Hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled using a random-effects model to account for heterogeneity. Thirteen retrospective cohort studies involving 5,564 patients were included. COPD was associated with improved progression-free survival (PFS) (HR: 0.68, 95% CI: 0.54–0.85, p < 0.001) and overall survival (OS) (HR: 0.80, 95% CI: 0.68–0.95, p = 0.01) in NSCLC patients receiving ICIs. Heterogeneity was moderate (I² = 46% for PFS, I² = 43% for OS). Subgroup analyses indicated that the association between COPD and survival outcomes was consistent across study regions (Asian vs. Western countries), patient age, sex distribution, COPD diagnostic criteria (spirometry, clinical diagnosis, or CT-diagnosed emphysema), follow-up duration, analytic models (univariate vs. multivariate), and study quality scores (p for subgroup differences > 0.05). Furthermore, univariate meta-regression analysis showed no significant modification of results by sample size, mean age, sex distribution, follow-up duration, or study quality scores (all p > 0.05)
Molecular classification and fertility-sparing outcomes in endometrial cancer and atypical endometrial hyperplasia
Get PDFMolecular classification has emerged as a critical tool for guiding personalized treatment in endometrial cancer (EC) and atypical endometrial hyperplasia (AEH). This retrospective study aimed to assess the impact of molecular classification on fertility-sparing treatment outcomes in patients diagnosed with EC and AEH who underwent fertility preservation therapy between 2006 and 2021. Patients were categorized into four molecular subtypes using immunohistochemistry (IHC) and Sanger sequencing, based on the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE): POLE-ultramutated, mismatch repair (MMR) deficient (MMRd), p53 abnormal (p53abn), and p53 wild-type (p53wt). All patients were evaluated for oncological prognosis and fertility outcomes, with a total of 103 patients included in the analysis. Recurrence rates exhibited significant differences among the molecular classifications, with the lowest recurrence rate observed in the p53wt subtype (19.7%), followed by MMRd (30.4%), POLE-ultramutated (66.7%), and p53abn (71.4%) subtypes. Multivariate Cox regression analysis indicated that the p53abn subtype was a significant risk factor for recurrence following conservation therapy when compared to the p53wt subtype. Additionally, there was a notable disparity in standard surgical treatment due to treatment failure, with operation rates of 7.5%, 19.2%, 66.7%, and 57.1% for the p53wt, MMRd, POLE-ultramutated, and p53abn subtypes, respectively. Regarding fertility outcomes, the p53wt group demonstrated the highest pregnancy rate after achieving a complete response compared to the other subtypes; however, no significant differences were observed in overall pregnancy outcomes. The ProMisE molecular classification holds significant prognostic value for patients with EC and AEH undergoing fertility-sparing treatment. Among the molecular subtypes, p53wt appears to be the most favorable for fertility-preserving interventions. This study provides essential insights into reproductive outcomes for this patient population
Decitabine suppresses tumor growth by activating mouse mammary tumor virus and interferon-β pathways
Get PDFDecitabine (DAC), a DNA methyltransferase inhibitor (DNMTi), is clinically effective in hematological malignancies such as myelodysplastic syndrome and acute myeloid leukemia, but its precise antineoplastic mechanisms remain incompletely understood. Beyond promoter demethylation, DAC is known to activate endogenous retroviruses (ERVs) and trigger type I interferon (IFN-I) responses, a phenomenon known as viral mimicry. The aim of this study was to investigate the roles of the mouse mammary tumor virus (MMTV) and interferon-β (IFN-β) in DAC-mediated tumor suppression. We employed two murine tumor models—4T1 mammary carcinoma and MC38 colon adenocarcinoma—in syngeneic immunocompetent mice, immunodeficient nude mice, and in vitro cultures. RNA and protein expression were assessed by quantitative PCR and immunoblotting, while functional contributions of MMTV and IFN-β were tested using short hairpin RNA (shRNA) knockdowns. DAC treatment suppressed tumor growth and pulmonary metastasis in vivo and inhibited cancer cell proliferation in vitro. It induced transcription of MMTV and expression of IFN-β, with a strong negative correlation between MMTV Env protein levels and tumor mass. Knockdown of either MMTV or IFN-β conferred resistance to DAC, confirming their functional roles. Reciprocal regulation was observed: MMTV knockdown reduced IFN-β expression, while IFN-β knockdown increased MMTV Env accumulation. Furthermore, DAC upregulated interferon regulatory factor 7 (IRF7), but this effect declined during prolonged treatment, suggesting a temporally restricted therapeutic window. In conclusion, our findings provide in vivo support for the viral mimicry hypothesis and demonstrate that MMTV and IFN-β contribute to DAC-mediated tumor suppression. The observed IRF7 downregulation and potential induction of immune checkpoints highlight the importance of therapeutic strategies combining DNMTis with immune checkpoint blockade to sustain antineoplastic efficacy.
ICU admission delays: Impact on length of stay and long-term outcomes
Get PDFDelays in intensive care unit (ICU) admissions are prevalent in overcrowded hospitals and can adversely affect patient outcomes. However, the extent of this impact, particularly beyond short-term mortality, remains unclear. We hypothesized that ICU admission delays exceeding 6 hours after consultation would independently increase 90-day mortality and prolong ICU length of stay. We conducted a retrospective analysis of data from 273 adult patients admitted to the ICU of a tertiary university hospital between January and December 2019. Patients were stratified into two groups: early admission (≤6 hours) and delayed admission (>6 hours). Multivariate Cox regression was employed to identify independent predictors of mortality. Delayed ICU admission was observed in 72.8% of patients. Although delayed admission was not independently associated with increased mortality in the multivariate analysis (HR: 0.88; 95% CI: 0.61–1.27), it was significantly correlated with prolonged ICU length of stay and higher 90-day mortality in the univariate analysis (p = 0.039), with no significant difference in vasopressor-free days (p = 0.809). In our assessment of independent mortality predictors, we found that patients with higher APACHE-II and Charlson scores experienced longer delays in ICU transfer. Additionally, respiratory and circulatory failure at admission were independently associated with increased mortality (HR: 2.17; 95% CI: 1.51–3.12). While early ICU admission did not independently predict mortality, it was linked to extended ICU stays, an increased treatment burden, and adverse long-term outcomes. These findings underscore the necessity of refining triage processes and evaluating baseline patient severity when interpreting the impact of ICU admission timing on outcomes
Gut microbial metabolites and the brain–gut axis in Alzheimer’s disease: A review
Get PDFAlzheimer’s disease (AD) is increasingly recognised as a disorder that extends beyond the brain, with accumulating evidence implicating gut microbiota–derived metabolites in its onset and progression. This narrative review synthesises 92 peer-reviewed animal, human and meta-analytic studies published between 2010 and 2025 that investigated short-chain fatty acids (SCFAs), tryptophan-derived indoles and kynurenines, trimethylamine N-oxide (TMAO) and secondary bile acids in the context of AD. Collectively, the literature shows that SCFAs support blood–brain-barrier integrity, dampen microglial reactivity and enhance synaptic plasticity, yet can paradoxically amplify β-amyloid (Aβ) deposition under germ-free or supraphysiological conditions, highlighting the importance of host status and dosing. Beneficial indole metabolites such as indole-3-propionic acid counter oxidative stress, strengthen intestinal and cerebral barriers and suppress pro-inflammatory cascades, whereas a shift toward neurotoxic kynurenines correlates with cognitive decline. TMAO emerges as a consistently deleterious metabolite that aggravates endothelial dysfunction, neuroinflammation and Aβ aggregation; dietary precursor restriction and microbial enzyme inhibitors are therefore being explored as mitigation strategies. Secondary bile acids and polyphenol derivatives further modulate mitochondrial bioenergetics and NF-κB signalling, broadening the therapeutic landscape. Multi-omics profiling reveals that AD patients typically exhibit reduced SCFAs and indoles but elevated TMAO, changes that scale with Mini-Mental State Examination scores, brain atrophy and cerebrospinal Aβ₄₂ levels. Early probiotic and faecal-microbiota-transplant trials have begun to normalise these metabolite profiles and yield modest cognitive benefits, underscoring translational potential. Altogether, gut-derived metabolites are not passive by-products but active modulators of neural, immune and metabolic circuits along the microbiota–gut–brain axis; their targeted manipulation and standardised metabolomic assessment could enable earlier diagnosis and precision microbiome-based interventions for AD, a promise that now warrants validation in large, longitudinal and mechanistically informed clinical studies
TBRG4 as a prognostic biomarker and key regulator of cell cycle and EMT in lung cancer
Get PDFTransforming growth factor β regulator 4 (TBRG4) is upregulated in lung cancer, but its biological role and underlying mechanisms remain poorly understood. In this study, we analyzed pancancer gene expression profiles and clinical data from University of California, Santa Cruz Xena (UCSC Xena) to evaluate the prognostic significance of TBRG4 using univariate and multivariate Cox regression analyses. Genes with a Pearson correlation coefficient above 0.4 with TBRG4 in lung cancer were identified via UALCAN, followed by pathway enrichment analyses to explore their functional associations. To investigate TBRG4’s role in lung cancer progression, we assessed cell proliferation, colony formation, and cell cycle alterations in lung cancer cells following TBRG4 knockdown. Western blot analysis was performed to examine the effects of TBRG4 depletion on key cell cycle regulators and epithelial-mesenchymal transition (EMT) markers. Additionally, the biological significance of TBRG4 was evaluated in vivo using a mouse xenograft model. TBRG4 knockdown significantly inhibited cell proliferation and colony formation while inducing cell cycle arrest and apoptosis in lung cancer cells. Analysis of co-expressed genes in the The Cancer Genome Atlas - Lung Adenocarcinoma (TCGA-LUAD) cohort revealed enrichment in cell cycle-related pathways, aligning with our experimental findings. Furthermore, TBRG4 depletion reduced EMT marker expression and suppressed tumor growth in vivo. Collectively, these findings suggest that TBRG4 may serve as a promising prognostic biomarker and therapeutic target in lung cancer
Andrographolide suppresses cervical cancer progression by targeting angiogenesis and inducing apoptosis in a CAM-PDX model
Get PDFCervical cancer poses significant clinical challenges, particularly in advanced stages. This study explores the therapeutic potential of andrographolide (AND), a bioactive compound derived from Andrographis paniculata, in mitigating cervical cancer progression using the chick embryo chorioallantoic membrane patient-derived xenograft (CAM-PDX) model. The model was validated through hematoxylin–eosin (H&E) staining and immunohistochemistry, which confirmed its ability to accurately replicate the histological and molecular characteristics of patient-derived xenografts (PDXs), establishing its reliability for therapeutic screening. A dose of 20 mg/kg AND was selected for further evaluation based on preliminary chorioallantoic membrane (CAM) assay findings. In the CAM-PDX model, AND significantly inhibited tumor growth, primarily by reducing angiogenesis and vessel density. Immunohistochemical analysis revealed that AND downregulated key proteins associated with cancer cell proliferation and survival, including Ki67, B-cell lymphoma 2 (BCL-2), and Erythroblast transformation-specific-related gene (ERG). These results indicate that AND not only disrupts tumor angiogenesis but also induces cell cycle arrest and promotes apoptosis in cervical cancer cells. In summary, this study successfully established a reproducible CAM-PDX model for drug evaluation and highlighted the potential of AND as a promising therapeutic candidate for cervical cancer, warranting further clinical investigation