Search Results (580)

Background: Growth Differentiation Factor 15 (GDF15) has emerged as a key biomarker and therapeutic target in oncology, with roles extending beyond cancer cachexia. Elevated GDF15 levels correlate with poor prognosis across several solid tumors, including colorectal, gastric, pancreatic, breast, lung, prostate, and head and neck cancers. GDF15 modulates tumor progression through PI3K/AKT, MAPK/ERK, and SMAD2/3 signaling, thereby promoting epithelial-to-mesenchymal transition, metastasis, immune evasion, and chemoresistance via Nrf2 stabilization and oxidative stress regulation. Methods: We performed a narrative review of the literature focusing on the role of GDF15 in solid tumors, with a particular emphasis on head and neck cancers. Results: In head and neck squamous cell carcinoma (HNSCC), GDF15 overexpression is linked to aggressive phenotypes, radioresistance, poor response to induction chemotherapy, and failure of immune checkpoint inhibitors (ICIs). Similar associations are observed in colorectal, pancreatic, and prostate cancer, where GDF15 contributes to metastasis and therapy resistance. Targeting the GDF15-GFRAL axis appears therapeutically promising: the monoclonal antibody ponsegromab improved cachexia-related outcomes in the PROACC-1 trial, while visugromab combined with nivolumab enhanced immune response in ICI-refractory tumors. Conclusions: Further investigation is warranted to delineate the role of GDF15 across malignancies, refine patient selection, and evaluate combinatorial approaches with existing treatments. Full article

Hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC) are aggressive malignancies characterized by a poor prognosis and resistance to conventional therapies. Mounting evidence suggests the pivotal role of epithelial–mesenchymal transition (EMT) in tumor progression, metastasis, and therapeutic resistance in these cancers. Protein induced by vitamin K absence II (PIVKA-II)—a valuable HCC detector—has ultimately emerged as a potentially relevant biomarker in PDAC, serving as both a serum biomarker and a prognostic indicator. This study investigates the putative link between PIVKA-II expression and the EMT process in HCC and PDAC. Using a Western blot analysis and electrochemiluminescence immunoassay (ECLIA), we quantified PIVKA-II serum levels alongside two canonical EMT markers—Vimentin and E-cadherin—in selected cohorts. Emerging data suggest a dual, context-dependent role for PIVKA-II. Beyond its diagnostic value in both malignancies, its co-expression with EMT markers points to a potential mechanistic involvement in tumor invasiveness and phenotypic plasticity. Notably, the selective detection of E-cadherin in HCC implies limited EMT activation and a preservation of the epithelial phenotype, whereas the higher expression of Vimentin in PDAC reflects a more substantial shift toward EMT. We provide a comprehensive analysis of key molecular markers, their involvement in EMT-driven pathophysiological mechanisms, and their potential as novel diagnostic tools. 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

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

Since carbohydrate antigen 19-9 (CA 19-9) is a significant biomarker for the clinical diagnosis and treatment of pancreatic cancer, a sensitive sandwich-type immunosensor was proposed with an epoxy functionalized covalent organic framework (EP-COF_TTA-DHTA) as the antibody carrier and an electroactive COF_{TTA-2,6-NA(OH)2} as the signal amplification probe for the sensitive detection of CA 19-9. The flexible covalent linkage between the epoxy-functionalized EP-COF_TTA-DHTA and the antibodies was employed to improve the dynamics of the antigen–antibody interaction significantly. Meanwhile, AuNPs@COF_{TTA-2,6-NA(OH)2} with abundant electroactive sites enhanced the current response of the immunoreaction significantly. After optimizing the incubation time and concentration of the antibody, CA 19-9 was quantitatively detected by differential pulse voltammetry (DPV) based on the sensitive sandwich-type immunosensor with a low detection limit of 0.0003 U/mL and a wide linear range of 0.0009–100 U/mL. The electrochemical immunosensor exhibits high specificity, stability and repeatability, and it provides a feasible and efficient method for the pathologic analysis and treatment of tumor markers. 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: The identification and clinical implementation of robust biomarkers are essential for improving diagnosis, prognosis, and treatment across a wide range of diseases. Pancreatic stone protein (PSP) has recently emerged as a promising candidate biomarker. Objective: This narrative review aims to provide an updated and comprehensive overview of the clinical applications of PSP in infectious, oncological, metabolic, and surgical contexts. Methods: We conducted a structured literature search using PubMed^®, applying the SANRA framework for narrative reviews. Boolean operators were used to retrieve relevant studies on PSP in a wide range of clinical conditions, including sepsis, gastrointestinal cancers, diabetes, and ventilator-associated pneumonia. Results: PSP has shown strong diagnostic and prognostic potential in sepsis, where it may outperform traditional markers such as CRP and PCT. It has also demonstrated relevance in gastrointestinal cancers, type 1 and type 2 diabetes, and perioperative infections. PSP levels appear to rise earlier than other inflammatory markers and may be less affected by sterile inflammation. Conclusion: PSP represents a versatile and clinically valuable biomarker. Its integration into diagnostic protocols could enhance early detection and risk stratification in critical care and oncology settings. However, widespread adoption is currently limited by the availability of point-of-care assay platforms. Full article

Pancreatic cancer is frequently accompanied by cancer-associated cachexia, a debilitating metabolic syndrome marked by progressive skeletal muscle wasting and systemic metabolic dysfunction. This study presents a systems biology framework to simultaneously identify therapeutic targets for both pancreatic ductal adenocarcinoma (PDAC) and its associated cachexia (PDAC-CX), using cell-specific genome-scale metabolic models (GSMMs). The human metabolic network Recon3D was extended to include protein synthesis, degradation, and recycling pathways for key inflammatory and structural proteins. These enhancements enabled the reconstruction of cell-specific GSMMs for PDAC and PDAC-CX, and their respective healthy counterparts, based on transcriptomic datasets. Medium-independent metabolic biomarkers were identified through Parsimonious Metabolite Flow Variability Analysis and differential expression analysis across five nutritional conditions. A fuzzy multi-objective optimization framework was employed within the anticancer target discovery platform to evaluate cell viability and metabolic deviation as dual criteria for assessing therapeutic efficacy and potential side effects. While single-enzyme targets were found to be context-specific and medium-dependent, eight combinatorial targets demonstrated robust, medium-independent effects in both PDAC and PDAC-CX cells. These include the knockout of SLC29A2, SGMS1, CRLS1, and the RNF20–RNF40 complex, alongside upregulation of CERK and PIKFYVE. The proposed integrative strategy offers novel therapeutic avenues that address both tumor progression and cancer-associated cachexia, with improved specificity and reduced off-target effects, thereby contributing to translational oncology. Full article

Background: Assessing pancreatic ductal adenocarcinoma (PDAC) resectability after neoadjuvant therapy (NAT) remains a diagnostic challenge. Traditional computed tomography (CT) criteria often fail to distinguish viable tumor from fibrosis, necessitating a reassessment of imaging-based standards. Methods: A comprehensive literature review was conducted using PubMed, focusing on prospective and retrospective studies over the past 25 years that evaluated the role of CT and complementary imaging modalities (MRI, PET-CT) in predicting resectability post-NAT in non-metastatic PDAC. Studies with small sample sizes or case reports were excluded. Results: Across studies, conventional CT parameters—particularly >180° vascular encasement—showed a limited correlation with histologic invasion or surgical outcomes after NAT. Persistent vessel contact on CT often reflected fibrosis, rather than active tumor. Dynamic changes, such as regression in the tumor–vessel interface and vessel lumen restoration, correlated more accurately with R0 resection. Adjunct markers like CA 19-9 response and patient performance status further improved resectability prediction. Conclusions: CT-based resectability assessment after NAT should transition from static morphologic criteria to response-based interpretation. Multidisciplinary evaluation integrating radiologic, biochemical, and clinical findings is essential to guide surgical decision-making and improve patient outcomes. Full article

Background: Transcription factor pancreatic and duodenal homeobox 1 (PDX1) plays a central role in pancreatic development and insulin regulation. However, its role in breast cancer remains largely unexplored. Objective: This study investigated the effects of PDX1 knockdown and overexpression on MCF7 breast cancer cell proliferation and responsiveness to paclitaxel and doxorubicin. Methods: PDX1 knockdown and overexpression models were established in MCF7 cells. Cell viability was assessed using the XTT assay following exposure to paclitaxel (5–100 nM) or doxorubicin (125–10 µM). Gene and protein expression levels were analyzed by qRT-PCR and western blotting. Results: PDX1 knockdown in MCF7 cells led to a significant increase in proliferation compared to the scrambled control, with approximately 3.22-fold at 72 h, whereas PDX1 overexpression markedly reduced proliferation by about 2.4-fold at 72 h when compared with the control. Upon treatment with paclitaxel or doxorubicin, knockdown cells showed higher viability, indicating reduced drug sensitivity. In contrast, PDX1-overexpressing cells exhibited a significant decrease in viability after treatment with both drugs, demonstrating enhanced sensitivity. Conclusions: PDX1 exhibits tumor-suppressive properties in MCF7 cells and modulates drug response, suggesting that it may serve as a biomarker or therapeutic target in hormone receptor-positive breast cancer. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains among the most lethal malignancies, with a five-year survival rate below 12%, largely attributable to its asymptomatic onset, late-stage diagnosis, and limited curative treatment options. Although PDAC accounts for approximately 3% of all cancers, it is projected to become the second leading cause of cancer-related mortality in the United States by 2030. A major contributor to its dismal prognosis is the lack of validated early detection strategies for asymptomatic individuals. In this review, we present a comprehensive synthesis of current advances in the early detection of PDAC, with a focus on the identification of high-risk populations, novel biomarker platforms, advanced imaging modalities, and artificial intelligence (AI)-driven tools. We highlight high-risk groups—such as those with new-onset diabetes after age 50, pancreatic steatosis, chronic pancreatitis, cystic precursor lesions, and hereditary cancer syndromes—as priority populations for targeted surveillance. Novel biomarker panels, including circulating tumor DNA (ctDNA), miRNAs, and exosomes, have demonstrated improved diagnostic accuracy in early-stage disease. Recent developments in imaging, such as multiparametric MRI, contrast-enhanced endoscopic ultrasound, and molecular imaging, offer improved sensitivity in detecting small or precursor lesions. AI-enhanced radiomics and machine learning models applied to prediagnostic CT scans and electronic health records are emerging as valuable tools for risk prediction prior to clinical presentation. We further refine the Define–Enrich–Find (DEF) framework to propose a clinically actionable strategy that integrates these innovations. Collectively, these advances pave the way for personalized, multimodal surveillance strategies with the potential to improve outcomes in this historically challenging malignancy. Full article

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high recurrence rates even after curative resection and adjuvant chemotherapy. Although immunotherapeutic approaches, such as immune checkpoint blockade (ICB), have revolutionized the treatment of some solid tumor malignancies, this has not been the case for PDAC. Several characteristics of PDAC, including its distinctive desmoplastic tumor microenvironment (TME), intratumor heterogeneity, and poor antigenicity and immune cell infiltration, contribute to its dismal immunotherapeutic landscape. Cancer vaccines offer one approach to overcoming these barriers, particularly in the resectable or borderline resectable settings, where tumor burden is low and immunosuppression is less pronounced. Various vaccination platforms have been tested in the clinical setting, from off-the-shelf peptide-based vaccines (e.g., AMPLFIFY-201 study, where over 80% of participants exhibited T-cell and biomarker responses) to personalized neoantigen mRNA vaccine approaches (e.g., autogene cevumeran, with significant responders experiencing longer median recurrence-free survival (RFS)). The key considerations for enhancing the efficacy of vaccination include combinations with chemotherapy, radiotherapy, and/or ICBs, as well as selecting appropriate immunomodulators or adjuvants. Recent results suggest that with continued mechanistic advancement and novel therapeutic development, cancer vaccines may finally be poised for clinical success in PDAC. Full article

Background/Objectives: Accurate determination of malignancy in pancreatic masses through endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is crucial for appropriate clinical management and prognostic assessment. However, the diagnostic sensitivity of conventional cytology using Papanicolaou (Pap) staining remains limited, often leading to inconclusive results. In this study, we investigated the diagnostic utility of methionyl-tRNA synthetase 1 (MARS1) through immunohistochemical (IHC) and immunofluorescence (IF) staining as a potential biomarker for pancreatic cancer. IHC analysis was conducted on resected tissue samples from 10 patients, including both pancreatic ductal adenocarcinoma and corresponding non-neoplastic pancreatic tissue. Additionally, cytologic samples were obtained from 198 patients with pancreatic masses who underwent EUS-FNA for diagnostic evaluation. Pap staining and MARS1 IF staining were performed on liquid-based cytology slides derived from EUS-FNA specimens. Results: MARS1 was detected by IHC staining in the 10 surgical specimens diagnosed with pancreatic adenocarcinomas. After Pap staining, 37 patients were excluded because of unsuitable specimens, leaving 161 patients who underwent both Pap and MARS1 IF staining. EUS-FNA specimens from the 151 patients with pancreatic ductal adenocarcinoma were classified by Pap staining as atypia (n = 36), suspicious for malignancy (n = 55), or malignancy (n = 60). MARS1 IF staining was positive in 147 of these patients and negative in 4. MARS1 IF staining distinguished pancreatic cancer in specimens with atypia on Pap staining. The sensitivity for detecting pancreatic cancer was significantly higher for MARS1 IF staining than for conventional Pap staining (97.4% vs. 79.1%, p < 0.0001). Conclusions: The high sensitivity of MARS1 IF staining improved malignancy detection in pancreatic masses. Further prospective studies are required to validate our findings. Full article

Background: Obesity is a growing global health concern and a modifiable risk factor for multiple pancreatic diseases, including acute pancreatitis (AP), chronic pancreatitis (CP), and pancreatic cancer (PC). While these conditions have distinct clinical courses, obesity contributes to their pathogenesis through shared mechanisms, such as visceral adiposity, systemic inflammation, insulin resistance, and ectopic pancreatic fat deposition. Methods: This narrative review synthesizes current evidence from clinical, epidemiological, and mechanistic studies exploring the relationship between obesity and pancreatic diseases. We also critically evaluate the effects of weight loss interventions—including lifestyle modifications, pharmacologic therapies, endoscopic approaches, and bariatric surgery—on the risk and progression of disease. Results: Obesity increases the risk and severity of AP via mechanisms such as gallstone formation, hypertriglyceridemia, and lipotoxicity. In CP, obesity-related intrapancreatic fat and metabolic dysfunction may influence disease progression, although some data suggest a paradoxical protective effect. In PC, obesity accelerates tumorigenesis through chronic inflammation, adipokine imbalance, and activation of oncogenic signaling pathways. Weight loss interventions, particularly bariatric surgery and incretin-based therapies (e.g., GLP-1 receptor agonists and dual agonists such as tirzepatide), show promising effects in reducing disease burden and improving metabolic and inflammatory profiles relevant to pancreatic pathology. Conclusions: Obesity plays a multifaceted role in the pathophysiology of pancreatic diseases. Therapeutic strategies targeting weight loss may alter disease trajectories, improve outcomes, and reduce cancer risk. Further research is needed to define optimal intervention strategies and to identify and validate biomarkers for personalized risk assessment and prevention. Full article

Immunotherapy has emerged as a transformative approach in gastrointestinal (GI) cancers, addressing historically poor survival rates in advanced-stage disease. Immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis demonstrate remarkable efficacy in colorectal cancer with deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H), exemplified by trials like NICHE-2 achieving exceptional pathological response rates. However, significant limitations persist, including resistance in some dMMR/MSI-H tumors, minimal efficacy in proficient mismatch repair (pMMR) tumors, and low overall response rates across most GI malignancies due to tumor heterogeneity and immune evasion mechanisms. Predictive biomarkers such as tumor mutational burden (TMB) and PD-L1 expression are crucial for optimizing patient selection, while hypermutated pMMR tumors with POLE mutations represent emerging therapeutic opportunities. In pancreatic adenocarcinoma, where survival remains dismal, combination strategies with chemotherapy and novel approaches like cancer vaccines show promise but lack transformative breakthroughs. Esophagogastric cancers benefit from ICIs combined with chemotherapy, particularly in MSI-H and HER2-positive tumors, while hepatocellular carcinoma has achieved significant progress with combinations like atezolizumab–bevacizumab and durvalumab–tremelimumab surpassing traditional therapies. Biliary tract cancers show modest improvements with durvalumab–chemotherapy combinations. Despite these advances, immunotherapy faces substantial challenges including immune-related adverse events, acquired resistance through cancer immunoediting, and the need for biomarker-driven approaches to overcome tumor microenvironment barriers. This review discusses key clinical trials, therapeutic progress, and emerging modalities including CAR T-cell therapies and combination strategies, emphasizing the critical need to address resistance mechanisms and refine precision medicine approaches to fully realize immunotherapy’s potential in GI malignancies. Full article