Search Results (288)

Background: Mucinous adenocarcinoma (MAC) of the colorectum is a biologically distinct histological subtype whose prognostic significance may vary substantially according to primary tumor location. The impact of anatomical site on clinicopathological characteristics and long-term survival in MAC remains incompletely characterized. This study aimed to evaluate the influence of tumor location on oncological outcomes in patients with mucinous colorectal cancer using a large population-based dataset. Methods: Patients diagnosed with mucinous colorectal adenocarcinoma between 2000 and 2023 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Operated patients were stratified by anatomical location into three groups: right colon (cecum, ascending colon, hepatic flexure, transverse colon), left colon (splenic flexure, descending colon, sigmoid colon, rectosigmoid junction), and rectum. The primary endpoints were overall survival (OS) and cancer-specific survival (CSS). Survival analyses were performed using the Kaplan–Meier method with log-rank testing. Multivariable Cox proportional hazards regression was used to assess the independent association of tumor location with survival outcomes, adjusting for age at diagnosis, year of diagnosis, sex, AJCC (American Joint Committee on Cancer) stage, tumor grade, receipt of radiotherapy and chemotherapy. Temporal trends in survival were evaluated across four consecutive diagnostic periods: 2000–2005, 2006–2011, 2012–2017, and 2018–2023. Results: A total of 40,698 patients with mucinous colorectal cancer were identified, of whom 40,174 underwent cancer-directed surgery (right colon n = 25,317; left colon n = 10,408; rectum n = 4449). The right colon was the predominant site of disease (62.9%). Median age was highest in the right colon group (74.0 years) and lowest in the rectum (65.0 years), while female sex predominated in right-sided tumors (55.7%) and male sex in rectal tumors (61.1%). Chemotherapy and radiotherapy utilization were markedly higher in the rectal group (68.6% and 64.5%, respectively) compared with the right colon (28.8% and 1.1%). Median OS was equivalent in the right and left colon groups (87.0 months each) but declined to 80.0 months in the rectal group. All pairwise CSS comparisons were statistically significant (all p < 0.001). On multivariable analysis, using the right colon as reference, the adjusted hazard ratios for CSS were 1.33 (95% CI: 1.28–1.39) for the left colon and 1.45 (95% CI: 1.34–1.57) for the rectum (both p < 0.001). Despite receiving the highest rates of multimodal therapy, rectal MAC demonstrated the worst long-term CSS across all anatomical groups. Temporal analyses revealed consistent CSS improvements in right-sided and left-sided MAC over the study period, whereas rectal MAC showed a non-linear trajectory with a plateau in the most recent diagnostic cohort (2018–2023). Conclusions: Mucinous colorectal adenocarcinoma demonstrates substantial biological and prognostic heterogeneity according to anatomical tumor location. Right-sided MAC was the most prevalent subtype and exhibited superior cancer-specific survival despite older patient age and lower treatment intensity. Rectal MAC demonstrated the worst long-term outcomes despite high utilization of multimodal neoadjuvant therapy, consistent with the established reduced responsiveness of mucinous tumors to conventional chemoradiotherapy. These findings underscore the necessity of incorporating anatomical location and tumor biology into individualized risk stratification and therapeutic planning for patients with mucinous colorectal cancer. Full article

Azurin is a promising antitumor agent that selectively enters cancer cells and inhibits tumor progression. It is also known to participate in cellular processes involving single-electron transfer, including protection against oxidative stress, anaerobic respiration, and denitrification. However, the physiological role of azurin remains poorly understood. In this work, a multifaceted phenotypic characterization of an azurin-deficient mutant (Δazu) of the plant endophytic bacterium Pseudomonas sp. OHS18 was performed, using complementary approaches and technologies. Deletion of the azu gene did not affect resistance to antibiotics, copper, or hydrogen peroxide, while nuclear magnetic resonance-based metabolomic analysis revealed that the Δazu strain was moderately impaired in maintaining metabolic homeostasis from the exponential to the stationary growth phase. Phenotype microarray analyses showed that the two strains exhibited largely similar metabolic and resistance profiles, except for bromosuccinic acid utilization, under which the Δazu strain displayed reduced growth. This phenotype was further associated with a reduced ability of the mutant to colonize Arabidopsis thaliana, suggesting a role for azurin in maintaining the plant–bacterium association. Overall, these findings provide new insights into the physiological role of azurin in environmental bacteria and suggest its involvement in bacterium–eukaryote interactions, thereby opening new perspectives for biotechnological and biomedical applications. Full article

Stress MAPKp38γ (MAPK12) has established roles in promoting tumorigenesis; however, the mechanisms involved remain largely unclear. This paper will review recently published and unpublished studies of p38γ in programming immune evasion in breast cancer, pancreatic cancer, and colon cancer to promote tumorigenesis. First, we show that p38γ is an oncogene that transforms breast epithelial cells into triple-negative breast cancer (TNBC), is required for breast tumorigenesis in mice, and activates tumor-suppressive environments via a positive feedback signaling loop. Moreover, we show that epithelial p38γ is required for KRAS-oncogene-induced pancreatic cancer in two genetic murine models (KPC and KTC) by activating glycolytic pathways to provide metabolic support for cancer cells and by increasing chemokine CXCL5-dependent fibrosis and immune cell infiltrations. Lastly, we will delineate how p38γ is activated by the main risk factors for colon cancer and serves as a key integrator of oncogenic and inflammatory signaling to promote tumorigenesis by increasing Wnt proliferative signaling and programming immune evasion. These results indicate that p38γ MAPK can integrate common risk factors for colon cancer and amplify oncogenic signaling by phosphorylating its substrate, β-catenin, increasing transcription of Wnt and the chemokine CXCL13, and promoting PD-L1 expression. In each of these tumor models, we will present evidence supporting our hypothesis, followed by additional experiments for verification. Our studies suggest that targeting p38γ may be an innovative approach in cancer therapeutic intervention. Full article

Background: Minimally invasive surgery has become the standard of care in colorectal cancer management, with laparoscopic techniques widely adopted due to their established short-term benefits and comparable oncological outcomes to open surgery. More recently, robotic-assisted surgery has emerged as an advanced minimally invasive alternative, offering enhanced visualization, improved instrument dexterity, and superior ergonomics. However, the extent to which these technical advantages translate into clinically meaningful improvements remains a subject of ongoing debate. Methods: A systematic review of the literature was conducted using PubMed, Scopus, and Web of Science databases, including studies published between 2005 and 2025. Eligible studies comprised randomized controlled trials, observational studies, cohort studies, and meta-analyses comparing laparoscopic and robotic colectomy for colon cancer. Outcomes of interest included intraoperative parameters (operative time, blood loss, conversion rate), postoperative outcomes (length of hospital stay, complications, mortality), and oncological endpoints (lymph node yield, resection margins, survival). The review was performed in accordance with PRISMA 2020 guidelines. Results: A total of 150 studies met the inclusion criteria. Robotic colectomy was consistently associated with reduced intraoperative blood loss, lower conversion rates to open surgery, and shorter length of hospital stay, albeit at the expense of longer operative times, particularly during the learning phase. Oncological outcomes, including lymph node harvest and margin status, were comparable between approaches, with some studies reporting a modest increase in lymph node yield in robotic procedures. The adoption of intracorporeal anastomosis was significantly higher in robotic surgery, contributing to improved postoperative recovery and reduced wound-related complications. Composite quality metrics, such as textbook outcome (TO), were more frequently achieved in robotic cohorts, largely driven by shorter hospitalization and lower complication rates. However, evidence from randomized controlled trials remains limited, and heterogeneity among studies persists. Conclusions: Robotic colectomy and rectal resection represent a safe and effective alternative to laparoscopic surgery in the treatment of colon cancer, offering potential advantages in perioperative outcomes and surgical precision. Its benefits appear particularly relevant in technically demanding cases, such as deep pelvic dissection and obese patients. Nevertheless, higher costs, longer operative times during the initial learning curve, and limited high-quality randomized evidence warrant cautious adoption. Future large-scale randomized studies are needed to clarify long-term oncological outcomes, cost-effectiveness, and the optimal integration of robotic platforms into standard colorectal surgical practice. Full article

Background/Objectives: Breast cancer is the most commonly diagnosed malignancy among women, with hormone receptor-positive tumors representing the majority of cases. Increasing survival rates have shifted attention toward long-term complications, including the risk of secondary malignancies. Emerging evidence suggests a potential association between breast cancer and gastrointestinal (GI) neoplasia. This study aimed to evaluate the role of colonoscopic and upper gastrointestinal endoscopic monitoring in patients with ER/PR-positive breast cancer and to assess its potential value in the early detection of digestive lesions. Methods: We conducted a prospective observational study including 186 female patients with histologically confirmed ER/PR-positive breast cancer. A total of 95 patients underwent colonoscopy, and 91 patients underwent upper gastrointestinal endoscopy. Clinical, demographic, and risk factor data were collected. A structured questionnaire was used to assess gastrointestinal symptoms. Endoscopic findings, lesion characteristics, and histopathological results were recorded. Bowel preparation quality was assessed using the Boston Bowel Preparation Scale. Results: Colonoscopy identified polyps and other lesions, with the majority located in the rectum and descending colon. A total of 12 biopsies were performed, revealing 1 malignant lesion, 2 borderline lesions, and the remainder benign. Upper gastrointestinal endoscopy showed gastritis as the most frequent finding, followed by gastric ulcers and polyps, while most patients had normal endoscopic results. Overall, 72% of patients presented at least one risk factor for digestive malignancy. Following treatment, most patients reported improvement in gastrointestinal symptoms. Conclusions: Patients with ER/PR-positive breast cancer may present a higher prevalence of gastrointestinal lesions, potentially related to shared risk factors and the systemic effects of endocrine therapy. Targeted, symptom-oriented endoscopic evaluation may facilitate early detection of premalignant and malignant digestive conditions. A multidisciplinary, risk-adapted surveillance approach should be considered to improve patient outcomes. Further large-scale studies are required to establish evidence-based screening strategies in this population. Full article

Background/Objectives: Mucinous adenocarcinoma (MAC) is a rare and clinically problematic subtype of rectal cancer, tending to present at an advanced stage and to respond poorly to neoadjuvant therapy. The consistently worse prognosis than that of not-otherwise-specified adenocarcinoma (NOS-AC) is not fully understood, potentially owing to intrinsically more aggressive biology or specific immune evasion mechanisms. We used the IMMUNOREACT multicentre cohort, with external validation in TCGA, to investigate the clinical and immunological features of rectal MAC in detail. Methods: Two hundred patients with rectal adenocarcinoma (16 MAC, 184 NOS-AC) from the IMMUNOREACT 1 (NCT04915326) and IMMUNOREACT 2 (NCT04917263) prospective cohorts were included. To account for the imbalance in baseline characteristics, propensity score matching (PSM) was performed on age, sex, neoadjuvant treatment and TNM stage. The immune microenvironment was characterised using immunohistochemistry (CD3, CD4, CD8, CD8β, Tbet, FoxP3, PD-L1, MSH6, PMS2, CD80), flow cytometry and NanoString PanCancer IO 360™ transcriptomics of adjacent healthy mucosa. Findings were externally validated against TCGA rectal and colon adenocarcinoma datasets. Results: MAC presented at significantly more advanced stage than NOS-AC across all TNM parameters: higher T stage (p = 0.006), N stage (p < 0.001), M stage (p = 0.039) and overall TNM stage (p < 0.001). In the unmatched cohort, MAC was associated with worse overall survival (HR 2.53; 95% CI 1.03–6.23; p = 0.043) and disease-free survival (HR 2.86; 95% CI 1.25–6.55; p = 0.013), but both differences became non-significant after PSM. MAC patients had higher haemoglobin after adjusting for confounders (mean difference [MD] 1.26 g/dL, 95% CI 0.30–2.31, p = 0.012), consistent with a hypothesis of reduced chronic rectal bleeding as a possible mechanism for late presentation. Transcriptomically, MAC showed suppression of HLA class II antigen presentation genes (HLA-DQA1, HLA-DQB1, HLA-DRB1) and myeloid activation genes (S100A8/A9/A12) in adjacent healthy mucosa. Loss of MMR proteins MSH6 and PMS2 in histologically normal mucosa was significantly more frequent in MAC. These findings were replicated in the TCGA cohort, which also showed lower tumour mutational burden and a distinct mucin-associated transcriptomic profile in MAC. Conclusions: The worse outcomes of rectal MAC appear to be driven largely by late-stage presentation, possibly owing to later diagnosis. MAC nonetheless carries a distinct immune phenotype, detectable even in histologically normal surrounding mucosa, that likely contributes to its treatment resistance. These observations provide a basis for developing histotype-specific approaches to both early detection and treatment in this uncommon but clinically challenging tumour subtype. Full article

Colonoscopy polyp segmentation is important for colorectal cancer screening, yet it remains challenging because polyps exhibit large morphological variation, weak lesion–background contrast, blurred boundaries, and severe foreground–background imbalance. To address these issues, this paper presents MCM-UNet++, a hybrid U-Net++-based segmentation framework that combines three targeted enhancements. First, a Multi-Axis Transformer Block (MATransformerBlock) is incorporated into convolutional feature blocks to model long-range horizontal and vertical dependencies with lower complexity than dense global self-attention. Second, a Cross-Channel Mixing (CCM) module is used in nested skip fusion paths to recalibrate the channel and spatial responses and reduce redundant feature transmissions. Third, a Multi-Objective Adaptive Loss (MOALoss) combines focal, Dice, and boundary-aware terms with learnable weights to improve supervision for small regions and ambiguous boundaries. Experiments on four public polyp segmentation datasets (Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, and ETIS-Larib) show competitive performance against the selected baseline methods, with Dice/IoU scores of 0.9563/0.9278 on Kvasir-SEG and 0.8593/0.7896 on CVC-ColonDB. These results indicate that the proposed components can improve benchmark-level polyp segmentation performance, while broader validation is still required before clinical deployment. Full article

Colorectal cancer is the third most commonly diagnosed cancer worldwide, and early detection of polyps via colonoscopy is essential for improving patient survival. However, automatic polyp segmentation faces three key challenges: balancing global context with local detail, delineating ambiguous boundaries under low contrast, and handling large variations in polyp size and morphology. To address these challenges, we propose WMA-Net, a Wavelet-Guided Mamba-Attention Network that uses wavelet-domain semantic–boundary separation as the organizing design principle. Rather than introducing a new individual operator, the contribution lies in how existing components—wavelet decomposition, Mamba state space modeling, multi-directional pixel difference convolution, and uncertainty-aware reverse attention—are combined and coordinated within one boundary-aware framework. The architecture integrates pixel difference convolution for multi-directional edge detection, frequency-selective cross-scale fusion with dual-stream wavelet-domain processing, Mamba-based multi-scale aggregation with linear complexity, and uncertainty-aware progressive boundary refinement. Extensive experiments on five public polyp benchmarks demonstrate state-of-the-art performance on four out of five datasets. On the seen datasets, WMA-Net achieves mean Dice scores of 94.4% on CVC-ClinicDB and 93.6% on Kvasir-SEG. On the unseen datasets, WMA-Net attains 91.7% on CVC-300, 82.3% on CVC-ColonDB, and 83.8% on ETIS-LaribPolypDB, demonstrating robust cross-dataset generalization. Comprehensive ablation studies validate the effectiveness and synergy of each proposed module. Full article

Background/Objectives: Colorectal cancer (CRC) is one of the most commonly diagnosed malignancies worldwide and a leading cause of cancer-related mortality. Surgical resection remains the cornerstone of curative treatment. Over the past two decades, robotic-assisted surgery has emerged as an evolution of minimally invasive surgery, aiming to overcome several limitations of conventional laparoscopy. This narrative review summarizes the current state of the art of robotic surgery in CRC. Methods: A narrative review of the literature was conducted using PubMed/MEDLINE and Scopus databases, focusing on publications from 2015 to 2026. The review provides an overview of robotic platforms and summarizes the available clinical evidence. Priority was given to randomized controlled trials, meta-analyses, large observational studies, and clinical practice guidelines. The review focuses on major commercially available robotic systems, including the da Vinci^®, Hugo™ RAS, and Versius^® platforms, as well as emerging robotic technologies. Results: Robotic colorectal surgery showed potentially favorable perioperative and oncological outcomes compared with laparoscopy. In rectal cancer, robotic approaches were associated with improved total mesorectal excision quality, lower conversion rates, and improved postoperative functional outcomes. Emerging evidence also suggested potential improvements in disease-free survival and local disease control following robotic rectal surgery. In colon cancer, robotic colectomy were associated with lower conversion rates, reduced blood loss, and faster postoperative recovery, with comparable long-term oncological outcomes. However, robotic procedures showed longer operative times and higher procedural costs. Conclusions: Robotic colorectal surgery appears to be a safe and effective minimally invasive approach, particularly in rectal cancer surgery. The development of new robotic platforms and increasing market competition may improve cost sustainability and expand its future role in colorectal cancer management. Full article

Oncogenic driver mutations in non-small cell lung cancer (NSCLC) activate defined signaling pathways that sustain tumor growth and influence the immune landscape. Yet, how coordinated interactions among diverse cell populations within the tumor immune microenvironment (TIME) contribute to this process remains largely unresolved. To address this, we profiled approximately 200,000 single cells from 45 treatment-naïve NSCLC patients representing seven major driver mutations. This analysis uncovered five multicellular modules (CM1–5) with distinct functional properties, each linked to specific malignant regulatory programs. Among them, CM2 and CM5 exhibited pronounced invasive features and were associated with unfavorable clinical outcomes. CM2 was predominantly observed in EGFR- and MET-driven brain metastases and was defined by strong crosstalk between astrocytes and myofibroblasts. Factors such as SPP1, PTN, and PSAP, together with metabolic alterations, contributed to a microenvironment supportive of metastatic colonization in the brain. By contrast, CM5 was enriched in ROS1-, KRAS-, and EGFR-mutant tumors and consisted of diverse myeloid and endothelial subsets characterized by immunosuppressive and pro-angiogenic signaling, including MIF, GALECTIN, and RETN, collectively facilitating immune escape and vascular remodeling. We further constructed and validated a driver mutation-specific prognostic signature (DMSP.sig) model integrating receptor–ligand interactions and core transcription factors, which effectively stratified patient survival. Leveraging this model, we also identified potential therapeutic candidates linked to these prognostic features, highlighting opportunities for clinical intervention. In summary, our study delineates how oncogenic drivers give rise to distinct TIME architectures, providing a framework for prognostic assessment and precision immunotherapy in high-risk NSCLC. Full article

Imaging-based multi-omics derived from digital histopathology provides a valuable approach for characterizing tumor heterogeneity from routine clinical specimens. However, robust multi-cancer histopathological analysis remains challenging due to pronounced intra-tumor variability, inter-organ morphological overlap, and sensitivity to staining and acquisition variations, which can limit the generalizability of deep learning models. These limitations are largely driven by insufficient representation learning, particularly in multi-organ and multi-class diagnostic settings. In this study, we propose a hierarchically regularized representation learning framework for multi-cancer histopathological image analysis that models imaging-based features across multiple organs and diagnostic categories. The framework integrates complementary mechanisms to capture fine-grained cellular morphology, long-range tissue architecture, and organ-aware diagnostic semantics within a unified computational model. A hierarchical supervision strategy guides the network to reduce entanglement between organ-level structural characteristics and disease-specific diagnostic patterns in the learned representations. The method operates without pixel-level annotations or handcrafted morphological priors, supporting scalable experimental evaluation. We demonstrate the approach on balanced lung and colon cancer histopathology cohorts, achieving 96.5% accuracy on lung cancer classification and 96.8% accuracy on colon cancer classification. Ablation and robustness analyses further validate the contributions of hierarchical regularization and consistency learning. Overall, this work provides a demonstrated proof-of-concept framework for representation-centric imaging-based analysis in multi-organ histopathology under the evaluated dataset conditions. Full article

Objective: To evaluate overall survival and to identify clinical, pathological, and demographic factors associated with survival in patients with stage III colon cancer. Methods: This retrospective cross-sectional study included 452 patients with stage III colon cancer who were followed at Ankara Bilkent City Hospital between 2005 and 2025. Patient data, including age, sex, ECOG performance status, comorbidities, tumor characteristics, treatment-related toxicities, and recurrence, were analyzed using PASW Statistics 18.0 (SPSS Inc., Chicago, IL, USA). Kaplan–Meier and log-rank tests were used for survival analysis. Prognostic factors, survival, mortality, and recurrence predictions were evaluated using machine learning algorithms, including coarse tree, bagged trees, support vector machines, and k-nearest neighbors. Furthermore, an explainable artificial intelligence framework was incorporated to improve model transparency and reveal clinically meaningful feature contributions. Model performance was assessed using accuracy, sensitivity, specificity, and F-score. Results: According to statistical analyses, older age, ECOG performance score ≥ 2, stage IIIC disease, N2-level lymph node metastasis, and the presence of comorbidities—particularly diabetes mellitus—were significantly associated with worse survival (p < 0.05). Machine learning analyses identified key prognostic factors, including positive surgical margins, rash, mucositis, thrombocytopenia, number of chemotherapy cycles, pathological tumor subtype, diarrhea, age at diagnosis, and anemia. SHAP analysis further demonstrated that treatment-related variables, particularly surgical margin positivity and chemotherapy-associated toxicities, were among the most influential predictors of survival. Several machine learning models outperformed traditional statistical methods in predicting mortality and recurrence, with the highest accuracy observed in ensemble methods such as coarse tree (87%) and bagged trees. Conclusions: This study identifies key prognostic factors influencing survival in stage III colon cancer and demonstrates that machine learning-based approaches can complement conventional statistical methods. The integration of clinical and treatment-related variables may improve individualized risk stratification and support clinical decision-making. These findings may also guide future large-scale, multicenter, and prospective studies. Full article

Cancer is an alarming health concern and economic burden in both developed and developing countries. Recently, there has been a growing demand for new alternative medications with more effectiveness and fewer harmful effects. During the past decades, a set of chemotherapeutic agents has been developed to fight against a large spectrum of cancer types. Unfortunately, their use is associated with a high level of toxicity; they are expensive, also, and their deployment is restricted by the emergence of cellular resistance. Plant-based components are garnering attention due to their low toxicity, selectivity, efficiency, and ease of accessibility. Alkaloids are one of these targeted compounds. Indeed, they are a highly diverse group with basic heterocyclic nitrogen-containing alkaloids that exhibit potent anticancer effects against a large panel of solid and liquid tumors, such as lung, breast, leukemia, liver, and colon cancer. The main molecular mechanisms involved in alkaloids’ anticancer effect are the induction of apoptosis via the extrinsic and intrinsic pathways, DNA damage, and the inhibition of cell cycle progression. Amazingly, these auspicious compounds exhibited strenuous inhibitory effects against a whole range of key enzymes involved in cancer progression and metastasis, such as Cytochrome P450 (CYP450), Cyclooxygenase-2 (Cox-2), Lysine-Specific Demethylase 1 (LSD1), Poly [ADP-ribose] polymerase (PARP), and topoisomerase, mainly through two action modes, namely irreversible and reversible inhibition. Furthermore, several conventional extraction methods have been developed to extract bioactive compounds from natural matrices, such as Soxhlet and hot water extraction. However, these techniques have many drawbacks, as they require a large amount of organic solvents, which not only affect human health but also generate severe environmental issues. To overcome these limitations, multiple eco-extraction techniques have emerged as potential alternatives to traditional extraction methods such as ultrasonic extraction, microwave-assisted extraction, and supercritical fluid extraction. In fact, they are considered eco-friendly and efficient technologies with less time and solvent consumption. Overall, this review aims to provide an updated overview of the most prominent anticancer alkaloids that have not been well reviewed already, as well as the main green extraction techniques relevant to the extraction of antineoplastic alkaloids. Full article

Background: Liquid biopsy using circulating tumor DNA (ctDNA) is rapidly reshaping gastrointestinal (GI) oncology. The highest-impact applications are molecular residual disease (mRD) detection after curative-intent therapy and early recognition of progression or resistance during systemic treatment. Methods: We performed a structured, clinically oriented narrative synthesis by using explicit search, eligibility, evidence prioritization, and clinical interpretation rules, integrating landmark prospective cohorts, randomized ctDNA-guided strategy trials where available, meta-analyses, key methodological research (e.g., pre-analytics, assay design, and clonal hematopoiesis (CH)/clonal hematopoiesis of indeterminate potential (CHIP)), and selected trial registries. Results: In resected colorectal cancer (CRC), postoperative ctDNA positivity is among the strongest known biomarkers of recurrence risk; large prospective studies demonstrate clear separation of disease-free survival (DFS)/overall survival (OS) between mRD+ and mRD− patients. In stage II colon cancer, randomized data (DYNAMIC) show that a ctDNA-guided strategy reduces adjuvant chemotherapy exposure without compromising long-term outcomes. In metastatic CRC, ctDNA supports early response monitoring and resistance tracking; ctDNA-selected anti-EGFR rechallenge provides a model of biomarker-driven actionability (CHRONOS). In gastroesophageal cancers, longitudinal ctDNA dynamics correlate with relapse risk and treatment efficacy, and in esophageal squamous cell carcinoma, ctDNA after neoadjuvant chemoradiotherapy informs residual disease risk and adjuvant stratification. In pancreatic ductal adenocarcinoma and hepatobiliary malignancies, sensitivity is constrained by low shedding and background cell-free DNA (cfDNA), yet ctDNA positivity remains clinically meaningful, and emerging data in resected extrahepatic cholangiocarcinoma (STAMP-linked analyses) show that ctDNA dynamics during adjuvant therapy predict recurrence. Conclusions: ctDNA is a clinically validated biomarker for mRD in CRC, whereas in other GI cancers, it remains a promising but methodologically heterogeneous tool whose clinical utility is tumor- and context-dependent. The next phase requires interventional trials demonstrating outcome improvement, harmonized sampling and reporting standards, and rigorous control of confounders (notably CH/CHIP). Full article

Background: Colorectal cancer (CRC) is a major global health concern and a leading cause of cancer-related mortality. In Saudi Arabia, it is the most common cancer among men and the third most common among women. The disease affects predominantly older adults, with an increasing number of cases reported in younger populations. Emerging evidence suggests a potential association between Vitamin D deficiency and CRC risk and progression. Aim: This study aimed to investigate the relationship between serum Vitamin D levels and colorectal cancer, and to evaluate its association with clinicopathological characteristics. Methodology: A retrospective case–control study was conducted on newly diagnosed CRC patients between January 2021 and August 2024 at King Abdul-Aziz Specialist Hospital, Prince Muteb Hospital, and the Oncology Center in Al Jouf, Saudi Arabia. A total of 100 CRC cases and 50 healthy controls were included. Serum 25-hydroxyvitamin D levels were measured and categorized as deficient (<20 ng/mL), insufficient (21–29 ng/mL), and normal (≥30 ng/mL). Histopathological features and tumor characteristics were analyzed. Statistical analyses included independent t-test, one-way ANOVA, and chi-square tests. Results: During the four-year period, 5399 gastrointestinal specimens were analyzed, of which 2111 (39.1%) were colorectal specimens. CRC was diagnosed in 107 cases (5.1%), and 100 patients met the inclusion criteria. The mean age of patients was 53.07 ± 13.3 years, and 69% were older than 50 years. Males represented 58% of cases (male-to-female ratio 1.4:1). Invasive adenocarcinoma was the predominant histological subtype (81%), with the sigmoid colon being the most common tumor site (39%). Vitamin D deficiency was significantly more prevalent in CRC patients (59%) compared to controls (22%). The mean serum Vitamin D level was significantly lower in cases (18.7 ± 11.3 ng/mL) than in controls (34.9 ± 15.6 ng/mL) (p < 0.001). No significant difference in Vitamin D levels was observed between males and females. Lower Vitamin D levels were significantly associated with advanced tumor grade (p = 0.004), lymphovascular invasion (p < 0.001), lymph node involvement (p = 0.001), and distant metastasis (p < 0.001). Representative histopathological images confirmed invasive moderately differentiated adenocarcinoma with characteristic malignant glandular architecture. Conclusions: Vitamin D deficiency was highly prevalent among colorectal cancer patients and was significantly associated with advanced tumor characteristics, including higher grade and metastatic features. These findings suggest a strong inverse relationship between serum Vitamin D levels and CRC development and progression. Further large-scale prospective and interventional studies are warranted to clarify the causal role of Vitamin D and its potential therapeutic implications in colorectal cancer prevention and management. Full article