Search Results (2,496)

Background/Objectives: The TOPAZ-1 phase III trial reported a survival benefit of using durvalumab, an anti-programmed death ligand 1 (anti-PD-L1) antibody, in combination with gemcitabine and cisplatin (GCD) treatment in patients with advanced biliary tract cancer. This retrospective study investigated the efficacy and safety of GCD treatment for advanced biliary tract cancer in real-world conditions. Methods: The study subjects were 52 patients with biliary tract cancer who received GCD therapy between January 2023 and May 2024. The observation parameters included the modified Glasgow Prognostic Score (mGPS), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), tumor markers (CEA, CA19-9), overall response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and adverse events. Results: The cohort included 36 men and 16 women, with a median age of 73.0 years. There were 36 cases of cholangiocarcinoma (distal: 10, perihilar: 19, intrahepatic: 7), 13 cases of gallbladder cancer, and 3 cases of ampullary carcinoma. The stages were locally advanced in 30 cases and metastatic in 22 cases. Biliary drainage was performed in 30 cases. There were 38 cases receiving first-line therapy and 14 cases receiving second-line or later treatments. The median values at the start of GCD therapy were ALB 3.7 g/dL, CRP 0.39 mg/dL, NLR 2.4, PLR 162.5, CEA 4.8 ng/mL, and CA19-9 255.9 U/mL. The mGPS distribution was 0:23 cases, 1:18 cases, and 2:11 cases. The treatment outcomes were ORR 25.0% (CR 2 cases, PR 11 cases), DCR 78.8% (SD 28 cases, PD 10 cases, NE 1 case), median PFS 8.6 months, and median OS 13.9 months. The PLR was suggested to be useful for predicting PFS. A decrease in CEA at six weeks after the start of treatment was a significant predictor of PFS and OS. Gallbladder cancer had a significantly poorer prognosis compared to other cancers. The immune-related adverse events included hypothyroidism in two cases, cholangitis in one case, and colitis in one case. Conclusions: The ORR, DCR, and PFS were comparable to those in the TOPAZ-1 trial. Although limited by its retrospective design and small sample size, this study suggests that GCD therapy is an effective treatment regimen for unresectable biliary tract cancer in real-world clinical practice. Full article

Background/Objectives: Pancreatic cancer (PC) is the seventh leading cause of cancer-related deaths worldwide, with its incidence rising each year. Despite its relatively low incidence, the aggressiveness of pancreatic cancer results in high mortality, with only 12% of patients surviving five years post-diagnosis. Surgical resection remains the only potentially curative treatment, but the tumor is often diagnosed at an advanced stage. The goal of this work is to identify vulnerabilities that can affect the efficacy of treatments and improve the efficacy of therapy. Methods: MAP17 overexpression in pancreatic cancer cell lines, RT-qPCR analysis, xenografts, in vitro and in vivo treatments, analysis of data from pancreatic tumors in transcriptomic patient databases. Results: We studied the prognostic and predictive value of MAP17 (PDZK1IP1) expression in pancreatic cancer, and we found that high MAP17 mRNA expression was associated with poor prognosis. In addition, single-cell analysis revealed that high MAP17 expression was present only in tumor cells. We investigated whether the response to various antitumor agents depended on MAP17 expression. In 2D culture, MAP17-expressing pancreatic cancer cells responded better to gemcitabine and 5-fluorouracil. However, in vivo xenograft tumors with MAP17 expression showed resistance to all treatments. Additionally, MAP17-expressing cells had a high NAD pool, which seems to be effectively depleted in vivo by NAMPT inhibitors, the primary enzyme for NAD biosynthesis. Conclusions: Our findings suggest that MAP17 expression could enhance the prognostic stratification of pancreatic cancer patients. Moreover, the coadministration of NAMPT inhibitors with current treatments may sensitize tumors with high MAP17 expression to chemotherapy and improve the efficacy of chemotherapy. Full article

Cancer is a systemic disease rather than a localized pathology and is characterized by widespread effects, including whole-body exhaustion and chronic inflammation. A thorough understanding of cancer pathophysiology requires a systemic approach that accounts for the complex interactions between cancer cells and host tissues. To explore these dynamics, we employed a comprehensive metabolomic analysis of plasma samples from patients with either esophageal or head and neck squamous cell carcinoma (SCC). Plasma samples from 149 patients were metabolically profiled and correlated with clinical data. Among the metabolites identified, lysophosphatidylcholine (LPC) emerged as the sole biomarker strongly correlated with prognosis. A significant reduction in plasma LPC levels was linked to poorer overall survival. Plasma LPC levels demonstrated minimal correlation with patient-specific factors, such as tumor size and general condition, but showed significant association with the response to immune checkpoint inhibitor therapy. Proteomic and cytokine analyses revealed that low plasma LPC levels reflected systemic chronic inflammation, characterized by high levels of inflammatory proteins, the cytokines interleukin-6 and tumor necrosis factor-α, and coagulation-related proteins. These findings indicate that plasma LPC levels may be used as reliable biomarkers for predicting prognosis and evaluating the efficacy of immunotherapy in patients with SCC. Full article

Carboxypeptidase A4 (CPA4) is an exopeptidase that cleaves peptide bonds at the C-terminal domain within peptides and proteins. It preferentially cleaves peptides with terminal aromatic or branched chain amino acid residues such as phenylalanine, tryptophan, or leucine. CPA4 was first discovered in prostate cancer cells, but it is now known to be expressed in various tissues throughout the body. Its physiologic expression is governed by latexin, a noncompetitive endogenous inhibitor of CPA4. Nevertheless, the overexpression of CPA4 has been associated with the progression and aggressiveness of many malignancies, including prostate, pancreatic, breast and lung cancer, to name a few. CPA4’s role in cancer has been attributed to its disruption of many cellular signaling pathways, e.g., PI3K-AKT-mTOR, STAT3-ERK, AKT-cMyc, GPCR, and estrogen signaling. The dysregulation of these pathways by CPA4 could be responsible for inducing epithelial--mesenchymal transition (EMT), tumor invasion and drug resistance. Although CPA4 has been found to regulate cancer aggressiveness and poor prognosis, no comprehensive review summarizing the role of CPA4 in cancer is available so far. In this review, we provide a brief description of peptidases, their classification, history of CPA4, mechanism of action of CPA4 as a peptidase, its expression in various tissues, including cancers, its role in various tumor types, the associated molecular pathways and cellular processes. We further discuss the limitations of current literature linking CPA4 to cancers and challenges that prevent using CPA4 as a biomarker for cancer aggressiveness and predicting drug response and highlight a number of future strategies that can help to overcome the limitations. Full article

Background/Objectives. This manuscript presents an overview of advances in oncological radiotherapy as an effective treatment method for cancerous tumors, focusing on mechanisms of action within metabolite–antimetabolite systems. The urgency of this topic is underscored by the fact that cancer remains one of the leading causes of death worldwide: as of 2022, approximately 20 million new cases were diagnosed globally, accounting for about 0.25% of the total population. Given prognostic models predicting a steady increase in cancer incidence to 35 million cases by 2050, there is an urgent need for the latest developments in physics, chemistry, molecular biology, pharmacy, and strict adherence to oncological vigilance. The purpose of this work is to demonstrate the relationship between the nature and mechanisms of past diagnostic and therapeutic oncology approaches, their current improvements, and future prospects. Particular emphasis is placed on isotope technologies in the production of therapeutic nuclides, focusing on the mechanisms of formation of simple and complex theranostic compounds and their classification according to target specificity. Methods. The methodology involved searching, selecting, and analyzing information from PubMed, Scopus, and Web of Science databases, as well as from available official online sources over the past 20 years. The search was structured around the structure–mechanism–effect relationship of active pharmaceutical ingredients (APIs). The manuscript, including graphic materials, was prepared using a narrative synthesis method. Results. The results present a sequential analysis of materials related to isotope technology, particularly nucleus stability and instability. An explanation of theranostic principles enabled a detailed description of the action mechanisms of radiopharmaceuticals on various receptors within the metabolite–antimetabolite system using specific drug models. Attention is also given to radioactive nanotheranostics, exemplified by the mechanisms of action of radioactive nanoparticles such as Tc-99m, AuNPs, wwAgNPs, FeNPs, and others. Conclusions. Radiotheranostics, which combines the diagnostic properties of unstable nuclei with therapeutic effects, serves as an effective adjunctive and/or independent method for treating cancer patients. Despite the emergence of resistance to both chemotherapy and radiotherapy, existing nuclide resources provide protection against subsequent tumor metastasis. However, given the unfavorable cancer incidence prognosis over the next 25 years, the development of “preventive” drugs is recommended. Progress in this area will be facilitated by modern medical knowledge and a deeper understanding of ligand–receptor interactions to trigger apoptosis in rapidly proliferating cells. Full article

Pediatric high-grade glioma (pHGG) is a devastating group of childhood cancers associated with poor outcomes. Traditionally, diagnosis was based on histologic and immunohistochemical characteristics, including high mitotic activity, presence of necrosis, and presence of glial cell markers (e.g., GFAP). With advances in molecular tumor profiling, these tumors have been recategorized based on specific molecular findings that better lend themselves to prediction of treatment response and prognosis. pHGG is now categorized into four subtypes: H3K27-altered, H3G34-mutant, H3/IDH-WT, and infant-type high-grade glioma (iHGG). Molecular profiling has not only increased the specificity of diagnosis but also improved prognostication. Additionally, these molecular findings provide novel targets for individual tumor-directed therapy. While these therapies are largely still under investigation, continued investigation of distinct molecular markers in these tumors is imperative to extending event-free survival (EFS) and overall survival (OS) for patients with pHGG. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

Background: Colorectal liver metastasis (CRLM) represents a major clinical challenge in oncology, affecting 25–50% of colorectal cancer patients and significantly impacting survival. While multimodal therapies—including surgical resection, systemic chemotherapy, and local ablative techniques—have improved outcomes, prognosis remains heterogeneous due to variations in tumor biology, patient factors, and institutional practices. Methods: This review synthesizes current evidence on prognostic factors influencing CRLM management, encompassing clinical (e.g., tumor burden, anatomic distribution, timing of metastases), biological (e.g., CEA levels, inflammatory markers), and molecular (e.g., RAS/BRAF mutations, MSI status, HER2 alterations) determinants. Results: Key findings highlight the critical role of molecular profiling in guiding therapeutic decisions, with RAS/BRAF mutations predicting resistance to anti-EGFR therapies and MSI-H status indicating potential responsiveness to immunotherapy. Emerging tools like circulating tumor DNA (ctDNA) and radiomics offer promise for dynamic risk stratification and early recurrence detection, while the gut microbiome is increasingly recognized as a modulator of treatment response. Conclusions: Despite advancements, challenges persist in standardizing resectability criteria and integrating multidisciplinary approaches. Current guidelines (NCCN, ESMO, ASCO) emphasize personalized strategies but lack granularity in terms of incorporating novel biomarkers. This exhaustive review underscores the imperative for the development of a unified, biomarker-integrated framework to refine CRLM management and improve long-term outcomes. Full article

Endometrial cancer is one of the most prevalent gynecologic malignancies in developed countries, with its incidence steadily increasing each year. Early diagnosis is crucial for a favorable prognosis; however, certain patients experience recurrence and distant metastasis after surgery, similar to advanced cancer patients, with limited treatment options. Therefore, effective strategies for early screening, diagnosis, predicting local recurrence, and guiding rapid treatment interventions are essential for improving survival rates and prognosis. Liquid biopsy, a method known for being non-invasive, safe, and effective, has attracted widespread attention for cancer diagnosis and treatment. Although its clinical application in endometrial cancer is less established than in other cancers, research on biomarkers using liquid biopsy in endometrial cancer patients is currently in progress. This review examines the latest advancements in non-invasive biomarkers identified through liquid biopsy and provides a comprehensive overview of their clinical applications in endometrial cancer. Additionally, it discusses the challenges and future prospects of liquid biopsy, offering valuable insights into the diagnosis and personalized treatment of endometrial cancer. Full article

Background/Objectives: Alterations in DNA damage repair mechanisms can impair the therapeutic effectiveness of cisplatin. MicroRNAs (miRNAs), key regulators of DNA damage repair processes, have been proposed as promising biomarkers for predicting the response to platinum-based chemotherapy (CT) in non-small cell lung cancer (NSCLC). In this study, by using a bioinformatics approach, we identified six miRNAs, which were differentially expressed (DE) between NSCLC patients characterized as responders and non-responders to platinum-based CT. We further validated the differential expression of the selected miRNAs on tumor and matched normal tissues from patients with resected NSCLC. Methods: Two miRNA microarray expression datasets were retrieved from the Gene Expression Omnibus (GEO) repository, comprising a total of 69 NSCLC patients (N = 69) treated with CT and annotated data from their response to treatment. Differential expression analysis was performed using the Linear Models for Microarray Analysis (Limma) package in R to identify DE miRNAs between responders (N = 33) and non-responders (N = 36). Quantitative real-time PCR (qRT-PCR) was used to assess miRNA expression levels in clinical tissue samples (N = 20). Results: Analysis with the Limma package revealed 112 DE miRNAs between responders and non-responders. A random-effects meta-analysis further identified 24 miRNAs that were consistently up- or downregulated in at least two studies. Survival analysis using the Kaplan–Meier plotter (KM plotter) indicated that 22 of these miRNAs showed significant associations with prognosis in NSCLC. Functional and pathway enrichment analysis revealed that several of the identified miRNAs were linked to key pathways implicated in DNA damage repair, including the p53, Hippo, PI3K and TGF-β signaling pathways. We finally distinguished a six-miRNA signature consisting of miR-26a, miR-29c, miR-34a, miR-30e-5p, miR-30e-3p and miR-497, which were downregulated in non-responders and are involved in at least three DNA damage repair pathways. Comparative expression analysis on tumor and matched normal tissues from surgically treated NSCLC patients confirmed their differential expression in clinical samples. Conclusions: In summary, we identified a signature of six miRNAs that are suppressed in NSCLC and may serve as a predictor of cisplatin response in NSCLC. Full article

Background/Objectives: Eph receptor A5 (EphA5) is a receptor tyrosine kinase that is implicated in multiple malignancies, although its role in endometrial cancer (EC) remains unclear. The aim of this study was to investigate the clinicopathological significance of EphA5 expression in EC and explore its association with proliferative and metabolic markers. Methods: We retrospectively analyzed 75 EC tissue samples from treatment-naïve patients by using immunohistochemistry and H-score quantification. Associations between EphA5 expression and clinicopathological parameters were assessed through logistic regression analysis. Kaplan–Meier analysis was used to evaluate survival outcomes. Correlation analysis, stratified according to cancer stage, was used to explore biomarker interactions. Results: High EphA5 expression levels were significantly associated with elevated Ki-67 expression (adjusted odds ratio (aOR): 1.08 per 1-point H-score increase, p = 0.024) and decreased pAMPK expression (aOR: 0.89 per 1-point H-score increase, p = 0.024), indicating its involvement in proliferative and metabolic pathways. Paradoxically, patients with high EphA5 levels had significantly better overall survival probabilities (H-score > 105, log-rank p = 0.007). Stage-specific analyses suggested that EphA5 levels correlated with proliferation in early-stage disease and epithelial–mesenchymal transition in advanced stages. Conclusions: EphA5 may act as a context-dependent biomarker in EC. Despite its positive correlation with proliferation and negative association with metabolic stress signaling, high EphA5 expression levels were predictive of a favorable prognosis. Full article

The biggest challenge in cancer therapy is tumor resistance to the classical approach. Thus, research interest has shifted toward the cancer stem cell population (CSC). CSCs are a small subpopulation of cancer cells within tumors with self-renewal, differentiation, and metastasis/malignant potential. They are involved in tumor initiation and development, metastasis, and recurrence. Method. A narrative review of significant scientific publications related to the topic and its applicability in endometrial cancer (EC) was performed with the aim of identifying current knowledge about the identification of CSC populations in endometrial cancer, their biological significance, prognostic impact, and therapeutic targeting. Results: Therapy against the tumor population alone has no or negligible effect on CSCs. CSCs, due to their stemness and therapeutic resistance, cause tumor relapse. They target CSCs that may lead to noticeable persistent tumoral regression. Also, they can be used as a predictive marker for poor prognosis. Reverse transcription–polymerase chain reaction (RT-PCR) demonstrated that the cultured cells strongly expressed stemness-related genes, such as SOX-2 (sex-determining region Y-box 2), NANOG (Nanog homeobox), and Oct 4 (octamer-binding protein 4). The expression of surface markers CD133+ and CD44+ was found on CSC as stemness markers. Along with surface markers, transcription factors such as NF-kB, HIF-1a, and b-catenin were also considered therapeutic targets. Hypoxia is another vital feature of the tumor environment and aids in the maintenance of the stemness of CSCs. This involves the hypoxic activation of the WNT/b-catenin pathway, which promotes tumor survival and metastasis. Specific antibodies have been investigated against CSC markers; for example, anti-CD44 antibodies have been demonstrated to have potential against different CSCs in preclinical investigations. Anti-CD-133 antibodies have also been developed. Targeting the CSC microenvironment is a possible drug target for CSCs. Focusing on stemness-related genes, such as the transcription pluripotency factors SOX2, NANOG, and OCT4, is another therapeutic option. Conclusions: Stemness surface and gene markers can be potential prognostic biomarkers and management approaches for cases with drug-resistant endometrial cancers. Full article

Background/Objectives: Prostate cancer (PCa) remains a major global health issue, associated with significant mortality and morbidity. Despite advances in diagnosis and treatment, predicting biochemical recurrence (BCR) after radical prostatectomy remains challenging, highlighting the need for reliable biomarkers to guide prognosis and therapy. The study aimed to evaluate the prognostic significance of the PTEN and ERG biomarkers in predicting BCR and tumor progression in PCa patients who underwent radical prostatectomy. Methods: This study consisted of a cohort of 91 patients with localized PCa who underwent radical prostatectomy between 2016 and 2022. From this cohort, 77 patients were selected for final analysis. Tissue microarrays (TMAs) were constructed from paraffin blocks, and immunohistochemical (IHC) staining for PTEN and ERG was performed using specific antibodies on the Ventana BenchMark ULTRA system (Roche Diagnostics, Indianapolis, IN, USA). Stained sections were evaluated and correlated with clinical and pathological data. Results: PTEN expression showed a significant negative correlation with BCR (r = −0.301, p = 0.014), indicating that reduced PTEN expression is associated with increased recurrence risk. PTEN was not significantly linked to PSA levels, tumor stage, or lymph node involvement. ERG expression correlated positively with advanced pathological tumor stage (r = 0.315, p = 0.005) but was not associated with BCR or other clinical parameters. Conclusions: PTEN appears to be a valuable prognostic marker for recurrence in PCa, while ERG may indicate tumor progression. These findings support the potential integration of PTEN and ERG into clinical practice to enhance risk stratification and personalized treatment, warranting further validation in larger patient cohorts. Full article

Background/Objectives: In non-muscle-invasive bladder cancer (NMIBC), the decision for immediate postoperative single-dose intravesical chemotherapy (SI) is based on clinical and presumed pathological features, as a definitive pathology is unknown at the time of surgery. This study aims to assess how accurately urologists can predict the pathological features of bladder tumors based solely on cystoscopic appearance and evaluate their ability to identify patients eligible for SI. Methods: A total of 104 patients with bladder masses were included. Seven senior urologists and four residents participated. Before transurethral resection, both groups predicted tumor stage, grade, and the presence of carcinoma in situ (CIS). Resident predictions were collected for all 104 patients, while senior predictions were collected for 72 patients. Based on these predictions, patient eligibility for SI was determined according to the EAU NMIBC guidelines. After final pathology reports, risk scores were recalculated and compared with the surgeons’ predictions. Cohen’s Kappa (κ) coefficient was used to assess agreement between predictions and pathology. Positive and negative predictive values were also calculated for both groups. Results: Strong agreement with final pathology could not be demonstrated for stage, grade, or CIS for either group. Urology residents’ predictions were slightly more accurate than those of senior urologists. Overall, 19.4% (14/72) (based on senior urologists’ predictions) and 18.2% (19/104) (based on resident predictions) of patients were misclassified and either overtreated or undertreated. Conclusions: Cystoscopic visual prediction alone is insufficient for determining eligibility for immediate postoperative intravesical chemotherapy, regardless of the urologist’s experience. More objective criteria are needed to improve the selection of appropriate patients for SI. Full article

Background: The prognosis management of thyroid cancer remains a significant challenge. This study highlights the critical role of T cells in the tumor microenvironment and aims to improve prognostic precision by integrating bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data, providing a more comprehensive view of tumor biology at the single-cell level. Method: 15 thyroid cancer scRNA-seq samples were analyzed from GEO and 489 patients from TCGA. A multi-level attention graph neural network (MLA-GNN) model was applied to integrate T-cell-related differentially expressed genes (DEGs) for predicting disease-free survival (DFS). Patients were divided into training and validation cohorts in an 8:2 ratio. Result: We systematically characterized the immune microenvironment of metastatic thyroid cancer by using single-cell transcriptomics and identified the important role of T-cell subtypes in the development of thyroid cancer. T-cell-based DEGS between tumor tissues and normal tissues were also identified. Subsequently, T-cell-based risk signatures were selected for establishing a risk model using MLA-GNN. Finally, our MLA-GNN-based model demonstrated an excellent ability to predict the DFS of thyroid cancer patients (1-year AUC: 0.965, 3-years AUC: 0.979, and 5-years AUC: 0.949 in training groups, and 1-year AUC: 0.879, 3-years AUC: 0.804, and 5-years AUC: 0.804 in validation groups). Conclusions: Risk features based on T-cell genes have demonstrated the effectiveness in predicting the prognosis of thyroid cancer. By conducting a comprehensive characterization of T-cell features, we aim to enhance our understanding of the tumor’s response to immunotherapy and uncover new strategies for the treatment of cancer. Full article