Search Results (6,738)

Background: Diffuse Large B-cell Lymphoma (DLBCL) is a biologically heterogeneous subtype of non-Hodgkin’s lymphoma (NHL), accounting for 30–40% of cases worldwide. Despite the incorporation of rituximab into standard chemo-immunotherapy regimen, approximately one-third of patients present with relapsed or refractory disease, implicating the need for improved prognostic markers and therapeutic targets. Gene expression profiling successfully classified DLBCL into Germinal Center B-cell-like (GCB) and non-GCB subtypes, which differ in genetic alterations, response to therapy, and clinical outcome. While intrinsic tumor biology has been extensively studied, the contribution of the tumor microenvironment (TME) to disease progression and therapeutic resistance still remains incompletely understood. Methods: In this study, we investigated the mutational landscape of stromal-related genes in DLBCL and evaluated their impact on gene expression, downstream signaling pathways, and tumor progression. Results: A total of 176 DLBCL patients were screened, of which 113 were enrolled based on availability of complete clinical data. The cohort demonstrated male predominance (male:female ratio: 2.1:1), advanced disease stage in 72.6% of patients, and elevated serum lactate dehydrogenase levels in 57.5%. Based on immunohistochemistry, 43.4% cases were classified as GCB-DLBCL and 56.6% as non-GCB DLBCL. Although the International Prognostic Index (IPI) retained prognostic significance for event-free survival (EFS) and overall survival (OS), considerable heterogeneity was observed within similar risk groups. Whole-exome sequencing (WES) uncovered recurrent somatic mutations in key oncogenic and epigenetic regulators, including TNFAIP3, NFIB, NOTCH1, TSC2, EZH2, EP300, KMT2D, and B2M, with subtype-specific distribution. Pathway enrichment analysis implicated role of Notch, Wnt, mTOR, JAK-STAT, TGF-β, and antigen-presentation pathways. Comprehensive WES analysis identified multiple novel mutations in genes associated with the stromal/extracellular matrix with distinct patterns in GCB and non-GCB DLBCL, accompanied by concordant alterations in gene expression profiles, suggesting functional relevance within the TME. Functional validation through primary cell culture demonstrated significantly elevated Th2 (IL-4, IL-6, IL-10) and Th17 (IL-17) cytokines in co-cultures containing both neoplastic cells and stromal components, underscoring the role of TME in DLBCL progression. Conclusions: Taken together, this study provides novel insights into stromal mutational signatures and cytokine-mediated tumor–stroma interactions, offering potential prognostic biomarkers and therapeutic targets for the improved management of DLBCL. Full article

Background: Soft-tissue sarcomas (STSs) are rare and heterogeneous malignancies with generally poor and unpredictable prognosis. Tertiary lymphoid structures (TLSs) have been identified as favorable prognostic indicators in several cancer types, yet their role in STS remains poorly defined. This study investigates the prognostic relevance of TLS presence, maturity, location and density in resected STSs. Methods: We retrospectively analyzed 219 cases of primary STS surgically resected at the Bergonié Institute (France) between 1990 and 2020. TLSs were assessed for presence, spatial distribution, semi-quantitative density and degree of maturity using CD20 and CD23 immunohistochemistry, categorizing tumors as fully mature TLS-positive (fmTLS⁺) or -negative (fmTLS⁻). RNA sequencing was performed on 126 formalin-fixed paraffin-embedded samples to characterize immune microenvironment profiles. Survival outcomes—including overall survival (OS), time to locoregional progression (TTLRP), and time to distant progression (TTDP)—were analyzed using Kaplan–Meier estimates and Cox proportional hazards models. Results: The presence of fmTLS was significantly associated with improved 5-year OS (p = 0.012) and cause-specific survival (p = 0.006). Unexpectedly, fmTLS⁺ tumors showed a higher rate of local recurrence (22.9% vs. 8.1%, p = 0.002). On multivariate analysis, high-density fmTLS⁺ tumors conferred a 2.68-fold increased risk of locoregional progression (95% CI: 1.28–5.59, p = 0.009). Transcriptomic profiling confirmed a significant correlation between fmTLS⁺ status and a high-immune phenotype (Φ = 0.30, p < 0.001). Conclusions: STSs with fmTLS are associated with improved OS but increased risk of local recurrence. These findings support fmTLS as a dual prognostic biomarker and highlight the need for tailored surveillance and adjuvant strategies in fmTLS⁺ patients. Full article

Mesothelin (MSLN) is a cell surface glycoprotein with limited expression in normal tissues but frequent overexpression in solid tumors, including gynecological malignancies. This review summarizes the state of the art on the biological role, diagnostic value, prognostic significance, and therapeutic potential of MSLN in ovarian, endometrial, and cervical cancers. Evidence from clinical and experimental studies indicates that MSLN contributes to tumor progression through interactions with CA125, promotion of cell adhesion and peritoneal metastasis, activation of oncogenic signaling pathways, modulation of immune responses, and development of chemoresistance. Elevated MSLN expression has been associated with advanced clinical stage of the disease, platinum resistance, and poorer survival outcomes, particularly in ovarian cancer patients, although prognostic findings remain inconsistent. Circulating soluble MSLN may serve as a minimally invasive biomarker and may improve diagnostic accuracy when combined with established markers. Therapeutic MSLN strategies—antibody-drug conjugates, CAR-T and NK cell therapies, monoclonal antibodies, immunotoxins, vaccines, and checkpoint blockade—provide promising pre-clinical and early clinical results, particularly in resistant or recurrent forms of the disease. Overall, MSLN constitutes a promising target for precision oncology in gynecological cancers, although further clinical studies are required to validate its diagnostic utility and optimize targeted therapeutic approaches. Full article

Retinal detachment (RD) is a potentially sight-threatening condition that requires timely diagnosis and appropriate surgical management. In macula-off rhegmatogenous retinal detachment (RRD), visual recovery after successful reattachment remains highly variable, highlighting the need for reliable preoperative prognostic markers. This study focuses on the contribution of advanced retinal imaging to the preoperative assessment of macula-off RRD, summarizing current evidence on imaging-derived biomarkers associated with disease severity and postoperative functional outcome. In this narrative review, we analyze studies employing spectral-domain and swept-source optical coherence tomography (SD-OCT and SS-OCT), OCT angiography (OCT-A), and adaptive optics OCT (AO-OCT) to characterize microstructural and microvascular retinal alterations. Emerging approaches, including ultra-widefield OCT (UWF-OCT) and artificial intelligence-based image analysis, are also discussed for their potential role in refining diagnosis, supporting surgical planning, and improving prognostic stratification. While several imaging parameters appear promising, their prognostic value is not yet fully realized. Further prospective studies are required to validate clinically meaningful imaging biomarkers and to integrate advanced imaging into routine preoperative decision-making for macula-off RRD. Full article

Ovarian cancer (OC) remains one of the most lethal gynaecological malignancies, which is mainly due to late diagnosis, high frequency of metastasis, and the risk of developing resistance to systemic therapy. In recent years, exosomes—small extracellular vesicles (EVs) secreted by cancer cells and components of the tumour microenvironment (TME)—have been identified as potential mediators of OC progression. Exosomes participate in intercellular communication and enable the transfer of RNA, proteins, and lipids. These vesicles may modulate the immune response, promote angiogenesis, remodel the extracellular matrix, and drive epithelial–mesenchymal transitions. Exosomes also appear to play a role in the development of drug resistance via direct transfer of resistance factors or indirect modification of TME. In this review article, we summarise current knowledge on the biological role of exosomes in OC pathogenesis. We also discuss their possible diagnostic, prognostic, and therapeutic relevance. The properties and composition of exosomes make them promising noninvasive liquid biomarkers and convenient carriers for anticancer drugs. However, to fully exploit their potential, further large-scale preclinical and clinical studies are required, which should focus primarily on standardising research methods and assessing the safety and efficacy of exosome-based diagnostic and therapeutic methods. Full article

Background and Objectives: Metastatic renal cell carcinoma (mRCC) remains a lethal disease despite advances with immune checkpoint inhibitors such as nivolumab. However, a substantial proportion of patients exhibit primary resistance or early progression, highlighting the need for reliable and easily accessible prognostic biomarkers. The C-reactive protein–albumin–lymphocyte (CALLY) index is a novel immunonutritional biomarker integrating systemic inflammation, nutritional status, and immune competence. Materials and Methods: In this retrospective single-center study, 91 patients with mRCC treated with nivolumab were analyzed. Patients were stratified into low and high CALLY index groups based on a receiver operating characteristic-derived cut-off (0.322). Survival outcomes were assessed using Kaplan–Meier analysis and Cox regression models. Results: Patients with a low CALLY index demonstrated significantly shorter progression-free survival (4.5 vs. 13.5 months, p < 0.001) and overall survival (9.1 vs. 25.5 months, p = 0.003). Multivariate analysis confirmed the CALLY index as an independent prognostic factor for both progression-free survival (HR: 2.63, p = 0.002) and overall survival (HR: 1.88, p = 0.035). Conclusions: The CALLY index is a simple, cost-effective, and reproducible biomarker that independently predicts survival in nivolumab-treated mRCC. It may serve as a practical tool for risk stratification and personalized treatment planning in the immunotherapy era. Full article

Background/Objectives: Trastuzumab emtansine (T-DM1) is widely used in Human Epidermal Growth Factor Receptor2 (HER2)-positive metastatic breast cancer; however, outcomes vary, and reliable prognostic markers remain limited. We developed the CALA index as a composite biomarker integrating CA15-3, lactate dehydrogenase (LDH), and albumin. This study aimed to evaluate the prognostic value of the CALA index in metastatic breast cancer treated with T-DM1. Methods: This multicenter retrospective study included 168 patients treated with T-DM1 across four tertiary centers. The CALA index was calculated using pretreatment levels of CA15-3, LDH, and albumin. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value, and patients were stratified into groups accordingly. Survival outcomes and independent risk factors were assessed using Kaplan–Meier and Cox regression analyses. Results: The median overall survival (OS) was 26 months (95% CI: 21.3–30.7). ROC analysis identified an optimal CALA cutoff value of 118.3. Patients with CALA ≤ 118.3 demonstrated significantly longer OS compared with those with CALA > 118.3 (log-rank p = 0.006), with 1- and 3-year OS rates of 81.2% and 43.2% versus 69.8% and 22.7%, respectively. In univariate analysis, CALA > 118.3 was associated with worse OS (HR: 1.699; 95% CI: 1.151–2.506; p = 0.008), and this association remained significant in multivariate analysis (HR: 1.671; 95% CI: 1.088–2.565; p = 0.019). Conclusions: The CALA index was associated with overall survival in metastatic breast cancer treated with trastuzumab emtansine and may serve as a practical tool for risk stratification. Full article

Background/Objectives: Integrating multi-omics data for cancer prognosis remains a challenging problem in bioinformatics because molecular profiles are high-dimensional, heterogeneous, and structured by incomplete biological relationships. Pathway databases provide biologically meaningful prior knowledge for modeling gene-level associations, but the sparsity and local incompleteness of pathway-derived networks often limit the performance of graph-based survival models. This study aimed to develop a pathway-guided framework for improving multi-omics survival prediction and identifying biologically relevant prognostic signals. Methods: We proposed PANA-Surv, a pathway-guided adaptive neighborhood augmentation framework for multi-omics cancer survival analysis. In this framework, KEGG pathways were used to construct gene graphs, and gene-level multi-omics profiles were encoded as node features. A conditional variational autoencoder module (PANA-VAE) was designed to enhance local representations through neighborhood reconstruction and adaptive weighting. The augmented features were then integrated into a graph convolutional survival model optimized with the Cox partial likelihood. Results: PANA-Surv was evaluated on 10 cancer cohorts from The Cancer Genome Atlas (TCGA). The proposed method achieved the highest mean concordance index (C-index) among all compared models and significantly outperformed Cox-EN, DeepSurv, GraphSurv, and LAGProg (all p < 0.01). Ablation analyses showed that both neighborhood reconstruction and adaptive weighting contributed to the observed performance gains, and KEGG-guided graph construction was more effective than alternative graph construction strategies. In a breast cancer (BRCA) case study, PANA-Surv identified 18 prognostic genes, including 12 genes supported by previous studies and 6 potentially novel candidates. Conclusions: These findings indicate that the integration of pathway prior knowledge with adaptive local feature enhancement can improve multi-omics survival modeling and support the identification of biologically relevant prognostic signals associated with cancer outcomes. Full article

Background: Although immune checkpoint inhibitors (ICIs) have improved survival in advanced melanoma, predicting individual responses remains challenging; thus, practical and inexpensive biomarkers are needed. In this study, we investigated the prognostic value of the neutrophil percentage–albumin ratio (NPAR) in patients with advanced melanoma receiving ICI therapy. Methods: Fifty patients treated in our clinic were included, with a mean age of 53.3 years and 66% being male. Visceral metastases were present in 76% of the cohort. Through conducting Receiver Operating Characteristic (ROC) analysis, we determined an NPAR cut-off value of 1.81, with patients categorized into low (<1.81, n = 27)- and high (≥1.81, n = 23)-NPAR groups. The progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier and Cox regression analyses. Results: High NPAR (≥1.81) significantly shortened both PFS and OS. In the univariate analysis, high NPAR emerged as a strong risk factor for PFS (HR: 2.68, p = 0.002) and OS (HR: 3.70, p < 0.001), while multivariate analysis confirmed NPAR as an independent negative prognostic factor for PFS (HR: 2.45, p = 0.006) and OS (HR: 2.82, p = 0.003), regardless of clinical variables. Additionally, visceral metastasis was an independent negative predictor of survival. Conclusions: Pre-treatment NPAR levels may be an independent and potential predictor of survival in advanced melanoma patients receiving ICIs. This easily calculable ratio could provide a practical guide for risk stratification. Full article

Background: Traumatic brain injury (TBI) remains a major cause of neurological morbidity and mortality. Mitochondria, being embedded as one of the key organelles disrupted after injury, play a central role in regulating neuronal metabolism, oxidative balance, and cell survival, hence the growing interest in their role after TBI. Methods: We present a narrative review of the literature on mitochondrial dysfunction after TBI to highlight the potential role in diagnosis, monitoring, prognostication and treatment strategies. Following SANRA guidelines we conducted a synthesis of 159 selected references published between 1997 and 2026, including 70 references published from 2020 onward. Results: Mitochondrial dysfunction underpins bioenergetic failure through the impairment of critical regulatory pathways, including oxidative phosphorylation, dysregulated reactive oxygen species production, and dysregulated calcium handling. These changes trigger downstream processes of oxidative damage, epigenetic and proteomic remodeling, and activation of regulated cell death pathways such as apoptosis, necroptosis, and ferroptosis in the context of an inflammatory milieu. As such, mitochondrial-derived molecules (such as mitochondrial DNA and microRNA) are emerging candidate biomarkers of TBI severity and prognosis. Additionally, therapeutic approaches under investigation include inhibition of the mitochondrial permeability transition pore, mitigation of mitochondrial oxidative stress using targeted antioxidants, restoration of NAD⁺-dependent metabolic pathways, and metabolic support through ketogenic interventions. Conclusions: Mitochondrial biology is advancing our understanding of TBI and offers a promising framework for improving its management. Full article

The role of zonulin as a biomarker of intestinal permeability in the allogeneic hematopoietic stem cell transplantation (allo-HSCT) setting remains poorly understood. In this study, we aimed to evaluate serum zonulin dynamics, identify its predictors, and assess its prognostic significance in patients undergoing allo-HSCT. This multicenter, prospective cohort study was conducted across four Brazilian hospitals. Eligible participants were patients aged ≥12 years who provided at least one blood sample during the allo-HSCT course. A control group of 15 healthy adult individuals was also included. Serum zonulin levels were quantified using enzyme-linked immunosorbent assay multiple times over the allo-HSCT course. Outcomes included acute graft-versus-host disease, overall survival, and bloodstream infections. A total of 477 blood samples were collected from 140 patients. Compared with the control group, zonulin levels were persistently elevated at all evaluated time points throughout the allo-HSCT course. However, no significant differences were observed among the different time points assessed during transplantation. No clinical or transplantation-related characteristics were identified as significant predictors of elevated zonulin levels. Finally, zonulin did not demonstrate prognostic value for allo-HSCT-related outcomes. Future studies should investigate whether other intestinal permeability biomarkers have prognostic relevance in the allo-HSCT setting. Full article

Blood-derived extracellular vesicle (EV) biomarkers have emerged as promising liquid-biopsy analytes for monitoring treatment response and prognosis in breast cancer. This scoping review mapped the clinical evidence on blood-derived EV in breast cancer and identified key barriers to clinical translation. Following the Joanna Briggs Institute framework and PRISMA-ScR guidelines, we searched PubMed, Embase, and Web of Science for eligible studies published through November 2025. After duplicate removal, title and abstract screening, and full-text assessment, 64 clinical studies were included. Research activity increased markedly from 2020 onward, accounting for 87.5% (56/64) of included studies. The literature was concentrated in East Asia, particularly China (51.6%, 33/64). RNA-based biomarkers predominated (60.9%, 39/64), especially microRNAs (39.1%, 25/64). Prognostic outcomes were evaluated in 89.1% (57/64) of studies, treatment response in 51.6% (33/64), and both endpoints in 40.6% (26/64). Triple-negative breast cancer was the most frequently studied subtype in isolation (15.6%, 10/64). Methodological heterogeneity was substantial, and kit-based precipitation was the most common EV isolation method (57.8%, 37/64). EV biomarkers show promise for non-invasive monitoring in breast cancer, but methodological standardization, compliance with Minimal Information for Studies of Extracellular Vesicles guidelines, and large prospective validation studies remain necessary before routine clinical implementation. Full article

Objective: This study aimed to evaluate the prognostic value of inflammatory biomarkers and their interaction with nutritional status for risk stratification in patients with chronic limb-threatening ischemia (CTLI). Material and Methods: This was a prospective, single-center observational cohort study including adult patients admitted with CTLI. Clinical outcomes included major amputation, major vascular events (MACE), and all-cause mortality. Multivariate logistic regression analyses were performed using two separate models, one including IL-6 and another including hsCRP, to avoid potential collinearity between biomarkers. Model discrimination was assessed using ROC curves, and Kaplan–Meier survival analyses were performed. Results: A total of 170 patients were included (mean age 72 ± 12 years; 74% male), with high cardiovascular risk and frequent malnutrition and sarcopenia. At 6 months, major amputations occurred in 35.3% of patients, MACE in 35%, and all-cause mortality in 32%. In multivariable analyses, malnutrition was the strongest independent predictor of the composite endpoint. IL-6 (OR 2.90, 95% CI 1.45–5.81; p = 0.003) and hsCRP values above the median (OR 4.22, 95% CI 2.04–8.72; p < 0.001) remained independently associated with adverse outcomes, together with age > 72 years. The hsCRP-based model showed slightly higher discriminative performance than the IL-6 model (AUC = 0.77 VS AUC = 0.75). Kaplan–Meier analyses demonstrated significantly reduced event-free survival in patients with elevated inflammatory biomarkers. Conclusions: In CTLI, systemic inflammation and nutritional status jointly identify patients at extremely high risk of adverse outcomes. hsCRP, given its availability, may be a practical tool for clinical risk stratification. Full article

Background/Objectives: Heart failure (HF) remains a major cause of global mortality and morbidity; it is, therefore, of paramount importance that diagnosis and prognostication are made timely in order to better improve outcomes and reduce healthcare expenditure. This research presents a novel predictive model of heart failure that combines clinical criteria with demographic factors in order to maximize predictive performance and act as a reliable tool for individualized healthcare intervention. Methods: Complex machine learning techniques, including decision trees, random forest, and deep learning, are applied in analyzing a large dataset of subjects with heart failure. We collected a diverse dataset comprising clinical indicators such as echocardiographic data, biomarkers, electrocardiogram (ECG) features, and demographic information. Data preprocessing techniques, such as feature normalization and handling of missing values, were applied to ensure the integrity and reliability of the dataset. Results: The results indicate that integrating both clinical indicators and demographic characteristics significantly improves the predictive power of the model, compared to models based on clinical indicators alone. Specifically, the hybrid model demonstrated a superior ability to predict short- and long-term outcomes in heart failure patients, offering enhanced accuracy in risk stratification and prognosis prediction. Conclusions: This research highlights the potential of artificial intelligence (AI) and machine learning in revolutionizing heart failure care by providing healthcare professionals with more accurate, data-driven decision support tools. The proposed model not only holds promise for clinical applications but also offers insights for future research into personalized medicine. Full article

Background: Human epidermal growth factor receptor 2 (HER2) alterations have been implicated as mechanisms of resistance to anti-epidermal growth factor receptor (anti-EGFR) therapy in metastatic colorectal cancer (mCRC). We aimed to evaluate the predictive and prognostic significance of HER2 expression in patients with RAS wild-type mCRC in a real-world setting. Methods: We conducted a multicenter retrospective cohort study across ten oncology centers in Turkey, including patients with RAS wild-type mCRC treated between 2015 and 2022. Clinical outcomes, including progression-free survival (PFS) and overall survival (OS), were compared between HER2-positive and HER2-negative groups. Multivariable Cox proportional hazards models were used to identify independent predictors of survival outcomes. Results: Among 204 patients, 28 (13.7%) were HER2-positive. Baseline characteristics were generally comparable; however, HER2-positive patients showed a trend toward higher-grade tumors and were significantly less likely to receive anti-EGFR therapy. HER2-positive patients had significantly shorter PFS compared to HER2-negative patients (median 10 vs. 13 months; p = 0.006). In multivariable analysis, HER2 positivity remained an independent predictor of shorter PFS (HR 1.76, 95% CI 1.01–3.07; p = 0.045). In the subgroup of 144 patients receiving anti-EGFR therapy, HER2-positive patients also demonstrated significantly shorter PFS (median 9.0 vs. 14.0 months; p = 0.023). No significant differences in OS were observed between groups. Conclusions: HER2 positivity is associated with reduced response to anti-EGFR therapy and independently predicts shorter PFS in patients with RAS wild-type mCRC. These findings further support the role of HER2 as a clinically relevant biomarker in RAS wild-type mCRC, particularly in predicting response to anti-EGFR therapy, while highlighting the need for optimized patient selection strategies in the era of HER2-targeted treatments. Full article