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Background:Periodontal pathogens have been linked to oral and gastrointestinal (orodigestive) carcinogenesis. However, the exact mechanisms remain unknown. Treponema denticola (Td) is associated with severe periodontitis, a chronic inflammatory disease leading to tooth loss. The anaerobic spirochete Td is an invasive bacteria due to its major virulence factor chymotrypsin-like proteinase. Here we aimed to investigate the presence of Td chymotrypsin-like proteinase (Td-CTLP) in major orodigestive tumours and to elucidate potential mechanisms for Td to contribute to carcinogenesis.Methods:The presence of Td-CTLP within orodigestive tumour tissues was examined using immunohistochemistry. Oral, tonsillar, and oesophageal squamous cell carcinomas, alongside gastric, pancreatic, and colon adenocarcinomas were stained with a Td-CTLP-specific antibody. Gingival tissue from periodontitis patients served as positive controls. SDS-PAGE and immunoblot were used to analyse the immumodulatory activity of Td-CTLP in vitro.Results:Td-CTLP was present in majority of orodigestive tumour samples. Td-CTLP was found to convert pro MMP-8 and -9 into their active forms. In addition, Td-CTLP was able to degrade the proteinase inhibitors TIMP-1, TIMP-2, and α-1-antichymotrypsin, as well as complement C1q.Conclusions:Because of its presence within tumours and regulatory activity on proteins critical for the regulation of tumour microenvironment and inflammation, the Td-CTLP may contribute to orodigestive carcinogenesis.

Abstract Background Trophoblast cell-surface antigen 2 (Trop2), a transmembrane glycoprotein overexpressed in multiple cancers, plays crucial roles in tumor progression and therapy resistance, yet its expression patterns and clinical significance in digestive cancers remain incompletely characterized. Methods This retrospective study analyzed a consecutive cohort of 2370 patients with histologically confirmed digestive cancers (804 gastric [GC], 1,384 colorectal [CRC], and 182 pancreatic cancers [PC]). Comprehensive clinicopathological data were systematically collected. Trop2 expression was quantitatively evaluated by immunohistochemistry and classified into Trop2-negative, Trop2-low, and Trop2-high based on the product of staining intensity and the proportion of positive tumor cells. Statistical analyses included univariate and multivariate logistic regression were used to identify significant clinicopathological and molecular predictors of Trop2 expression patterns. Univariate and multivariate logistic regression analyses were used to explore the relationship between Trop2 expression status (positive [Trop2 intensity ≥ 2] vs. negative) and various clinicopathological features of different tumor types. Results Trop2 was widely expressed in digestive cancers, with highest prevalence in PC and GC. Multivariate analysis revealed distinct Trop2 expression patterns in gastrointestinal malignancies. At the pan-cancer level, Trop2 expression significantly correlated with tumor type, (signet ring cell carcinoma) SRCC, vascular invasion (VI) and perineural invasion. Notably, GC showed independent associations with SRCC and intestinal-type Lauren classification; CRC showed VI as the predominant factor associated with Trop2 expression; while PC demonstrated unique correlations with female sex and T1 stage. These findings highlight tumor-type specific regulation of Trop2, providing critical insights for prognostic assessment and targeted therapy. Conclusion Trop2 is a promising biomarker for tumor aggressiveness and a potential target for antibody-drug conjugates (ADCs) in digestive cancers, particularly in SRCC-rich, metastatic, and invasive subtypes. These findings provide strong rationale for stratifying patient populations in future clinical investigations of Trop2-directed ADC therapies.

Objective Owing to its rarity and heterogeneity, the biological behavior and optimal therapeutic management of mixed neuroendocrine‐non‐neuroendocrine neoplasm (MiNEN) have not been established. Herein, we aimed to evaluate the clinicopathological characteristics and metastatic patterns of MiNEN. Methods Continuous clinicopathological data of MiNEN patients treated at our hospital were retrospectively collected and analyzed. Results This study had enrolled 169 patients since January 2010 to January 2020. Pathological components were assessed in 129 patients with MiNEN (76.3%), and a focal (non‐)neuroendocrine component was observed in 40 patients (23.7%; <30% of the tumor). Among the enrolled patients, 80 underwent surgical removal of the primary tumor and lymph nodes (LNs), and 34 with distant metastasis underwent biopsy of both primary tumor and metastatic lesions. In patients with LN metastasis, 68.8% (55/80) exhibited a pure component of either neuroendocrine (NE) or adenocarcinoma/squamous carcinoma (AS) in metastatic LNs, while 20% (16/80) showed different components in different LNs, and only 11.2% (9/80) exhibited both NE and AS components in the same LN. In patients with distant metastases, 26.5% (9/34) possessed coexisting NE and AS components in the distant metastases, 70.6% (24/34) were regarded as a pure NE component, and 2.9% (1/34) were comprised of a pure AS component. Conclusion Lymph node and distant metastases exhibited distinct metastatic patterns in patients with MiNEN. The major pathological component in regional LNs may have influenced the proportion of the two components within the primary tumor, but distant metastases were dominated by the NE component. Regional lymph nodes and distant metastases of MiNEN exhibited distinct metastatic patterns. We recommend that patients with MiNEN undergo aggressive multidisciplinary oncologic management, and an optimal modality should be established based on the NEC component.

Background Malignant digestive tract tumors are highly prevalent and fatal tumor types globally, often diagnosed at advanced stages due to atypical early symptoms, causing patients to miss optimal treatment opportunities. Traditional endoscopic and pathological diagnostic processes are highly dependent on expert experience, facing problems such as high misdiagnosis rates and significant inter-observer variations. With the development of artificial intelligence (AI) technologies such as deep learning, real-time lesion detection with endoscopic assistance and automated pathological image analysis have shown potential in improving diagnostic accuracy and efficiency. However, relevant applications still face challenges including insufficient data standardization, inadequate interpretability, and weak clinical validation. Objective This study aims to systematically review the current applications of artificial intelligence in diagnosing malignant digestive tract tumors, focusing on the progress and bottlenecks in two key areas: endoscopic examination and pathological diagnosis, and to provide feasible ideas and suggestions for subsequent research and clinical translation. Methods A systematic literature search strategy was adopted to screen relevant studies published between 2017 and 2024 from databases including PubMed, Web of Science, Scopus, and IEEE Xplore, supplemented with searches of early classical literature. Inclusion criteria included studies on malignant digestive tract tumors such as esophageal cancer, gastric cancer, or colorectal cancer, involving the application of artificial intelligence technology in endoscopic diagnosis or pathological analysis. The effects and main limitations of AI diagnosis were summarized through comprehensive analysis of research design, algorithmic methods, and experimental results from relevant literature. Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. However, the scale and quality of data across different studies vary widely, and the generalizability of models to multi-center, multi-device environments remains to be verified. In pathological analysis, using convolutional neural networks, multimodal pre-training models, etc., automatic tissue segmentation, tumor grading, and assisted diagnosis can be achieved, showing good scalability in interactive question-answering. Nevertheless, clinical implementation still faces obstacles such as non-uniform data standards, lack of large-scale prospective validation, and insufficient model interpretability and continuous learning mechanisms. Conclusion Artificial intelligence provides new technological opportunities for endoscopic and pathological diagnosis of malignant digestive tract tumors, achieving positive results in early lesion identification and assisted decision-making. However, to achieve the transition from research to widespread clinical application, data standardization, model reliability, and interpretability still need to be improved through multi-center joint research, and a complete regulatory and ethical system needs to be established. In the future, artificial intelligence will play a more important role in the standardization and precision management of diagnosis and treatment of digestive tract tumors. Graphical Abstract Highlights Early symptoms of malignant digestive tract tumors are often atypical, resulting in high misdiagnosis rates, which urgently calls for more precise diagnostic methods; artificial intelligence has demonstrated significant application potential in the two core areas of endoscopy and pathology. Real-time endoscopic assisted detection systems driven by deep learning can significantly improve the detection rate of early lesions, reducing the risk of missed diagnoses due to physician inexperience or fatigue. Pathological AI technologies based on multimodal and vision-language pre-training models can achieve automatic segmentation, grading, and interactive diagnosis of digital slides, providing objective quantitative basis for individualized treatment decisions. The main obstacles to current AI applications in endoscopy and pathology include insufficient data standardization, poor model interpretability, and lack of large-scale prospective validation; multi-center collaboration and standardized regulation urgently need to be strengthened. With the continued advancement of multidisciplinary integration and technological breakthroughs, artificial intelligence is expected to further improve early diagnosis and precise management of digestive tract tumors, enhancing patient prognosis and promoting the standardized development of diagnostic and treatment processes.

Background Digestive system cancers remain a leading cause of cancer-related mortality globally, underscoring the need for reliable prognostic tools. The C-reactive protein-Albumin-Lymphocyte (CALLY) index, which reflects inflammation, nutrition, and immunity, has shown potential in predicting survival. However, comprehensive evaluations of its role in digestive system cancers are still limited. Methods A meta-analysis of English-language studies from online databases was performed to assess the prognostic value of the CALLY index. Pooled hazard ratios (HRs) were calculated for overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS), and cancer-specific survival (CSS). Results A total of eighteen articles (19 studies, encompassing 7,951 patients) were included. A lower CALLY index was significantly associated with poorer outcomes across all survival endpoints. The pooled HR for OS was 1.973 (95% CI: 1.734–2.244), with HRs for DFS, RFS, and CSS being 2.093 (95% CI: 1.682–2.604), 1.462 (95% CI: 1.292–1.654), and 2.456 (95% CI: 1.887–3.221), respectively (all P  < 0.001). Subgroup analyses for OS demonstrated consistent prognostic significance across various treatment strategies, cancer types, cutoff values, sample sizes, and regions. Notably, the CALLY index was a strong predictor of OS in surgical patients (HR = 2.014, 95% CI: 1.794–2.260, P  < 0.001). Sensitivity analyses validated the robustness of these findings, with minimal publication bias (Egger’s test P  = 0.053). Conclusions The CALLY index serves as a cost-effective and reliable biomarker for predicting prognosis in digestive system cancers. Its utility as a pre-treatment risk stratification tool, which integrates key factors of inflammation, nutrition, and immunity, renders it valuable for guiding clinical decision-making.

Background Nutritional risk assessment indices impact disease prognosis, yet their prognostic roles in preoperative digestive system tumor (DST) patients remain unclear. Methods In this study, the Controlling Nutritional Status (CONUT) score, the Nutritional Risk Index (NRI) and the Prognostic Nutritional Index (PNI) before surgery were applied to 17, 338 patients with 10 kinds of newly diagnosed DSTs. The distribution of nutritional risk and its correlation with mortality were examined in this study through the utilization of three nutritional risk assessment indices. Results The study encompassed 17,338 cases of DSTs, comprising 7,644 cases of gastric cancer, 5,542 cases of esophageal cancer, 2,826 cases of pancreatic cancer, 570 cases of gastroesophageal junction cancer, 185 cases of liver cancer, and minimal instances of five other tumor types, each numbering approximately 100. According to the 3 nutritional risk assessment indices, CONUT, NRI and PNI, nutrition risk was common in patients with DSTs (79.24% with CONUT, 38.91% with NRI, 3.13% with PNI), and even in patients with normal or high BMI. In gastric cancer, in addition to age, stage, presence of metastasis, and tumor tissue type, three nutritional risk assessment indices could effectively stratify the prognosis based on nutritional status. CONUT was valuable for predicting the prognosis of intrahepatic cholangiocarcinoma, whereas NRI was significant in Esophageal Cancer and Pancreatic Cancer. Conclusions Nutritional risk was common among DSTs patients and was strongly associated with increased mortality in GC according to CONUT, NRI and PNI Stratification. More attention should be paid to nutritional risk assessment indices to improve prognosis, and prospective clinical trials were needed to evaluate the efficacy of nutritional interventions in GC patients. However, the utility of these three nutritional risk assessment indices in other DSTs was limited.

Theragnostic biomarkers are still needed to select patients with digestive neuroendocrine neoplasms (NENs) for an optimal management. The PD-1/PD-L1 pathway plays a pivotal role in T cells activation and host immune response to cancer and PD-L1 expression in tumor and/or immune cells is used to identify patients who would benefit of treatment with immune checkpoint inhibitors. However, its role as a biomarker is still unclear in digestive NENs. We investigated PD-L1 expression in 68 well-characterized digestive NENs (32 NETs, 32 NECs and 4 MiNENs) and TPS and CPS scores were calculated. In addition, tumor infiltrating T-lymphocytes and mismatch repair protein expression (MMR) were evaluated. All results were correlated with clinicopathological features. PD-L1 expression was higher in NECs than in NETs: TPS > 1% and/or CPS > 1 were observed in 16% of NETs, 68.8% of NECs and 50% of MiNENs (p: 0.05). The mean TPS score in positive cases was 6.3% in NETs, 16.2% in NECs and 5% in MiNENs. The CPS score was 4.8 in NETs, 8.1 in NECs and 6 in MiNENs. MMR-deficient neoplasms were more frequently observed in NECs than in NETs (p: < 0.05) as well as intra-tumor immune infiltration (p: 0.00001). No correlation between PD-L1 expression and survival or other clinicopathological parameters was observed. Our results suggest that treatment with immune checkpoint inhibitors may have a potential role only in selected cases, mainly in NECs and MiNENs.

Cancer stem cells (CSCs) are a distinct subpopulation of cells within tumors, characterized by their ability to self-renew, differentiate and promote tumorigenesis. CSCs have critical roles in the initiation, progression and therapeutic resistance of digestive tract tumors, including in esophageal, gastric, colorectal and pancreatic cancer. The present review comprehensively explores the biology of CSCs, their interactions with the tumor microenvironment and their clinical relevance in predicting patient prognosis and guiding treatment strategies. The emerging therapeutic approaches that target CSCs, including pathway inhibitors, monoclonal antibodies and combination therapies, are also discussed, highlighting the potential of these strategies to improve patient outcomes in digestive tract cancer types. Additionally, future research directions and challenges in developing effective CSC-targeted therapies are addressed, emphasizing the need for innovative strategies to overcome treatment resistance and increase therapeutic efficacy.

The role of skeletal muscle and adipose tissue in the progression of cancer has been gradually discussed, but it needs further exploration. The objective of this study was to provide an in-depth analysis of skeletal muscle and fat in digestive malignancies and to construct novel predictors for clinical management. This is a retrospective study that includes data from Cancer Center, the First Hospital of Jilin University. Basic characteristic information was analyzed by T tests. Correlation matrices were drawn to explore the relationship between CT-related indicators and other indicators. Cox risk regression analyses were performed to analyze the association between the overall survivals (OS) and various types of indicators. A new indicator body composition score (BCS) was then created and a time-dependent receiver operating characteristic curve was plotted to analyze the efficacy of the BCS. Finally, a nomogram was produced to develop a scored-CT system based on BCS and other indicators. C-index and calibration curve analyses were performed to validate the predictive accuracy of the scored-CT system. A total of 575 participants were enrolled in the study. Cox risk regression model revealed that VFD, L3 SMI and VFA/SFA were associated with prognosis of cancer patients. After adjustment, BCS index based on CT was significantly associated with prognosis, both in all study population and in subgroup analysis according to tumor types (all study population: HR 2.036, P  < 0.001; colorectal cancer: HR 2.693, P  < 0.001; hepatocellular carcinoma: HR 4.863, P  < 0.001; esophageal cancer: HR 4.431, P  = 0.008; pancreatic cancer: HR 1.905, P  = 0.016; biliary system malignancies: HR 23.829, P  = 0.035). The scored-CT system was constructed according to tumor type, stage, KPS, PG-SGA and BCS index, and it was of great predictive validity. This study identified VFD, L3 SMI and VFA/SFA associated with digestive malignancies outcomes. BCS was created and the scored-CT system was established to predict the OS of cancer patients.

The prevalence of obesity has steadily increased over the past few decades. Previous studies suggest that obesity is an oncogenic factor and that over 20% of all cancers are obesity-related. Among such cancers, digestive system malignancies (including esophageal adenocarcinomas, colorectal cancers, and cancers of the gastric cardia, liver, and pancreas) are reported most frequently. While the 5-year survival rates of cancers of the breast and prostate are 90%, that rate is only 45% for digestive cancers. In this review, the mechanisms of obesity-associated digestive cancers are discussed, with an emphasis on obesity-related gene mutations, insulin and insulin-like growth factor signaling pathways, chronic inflammation, and altered adipokine levels. Evidence that these factors often function interdependently rather than independently in carcinogenesis is presented. Recommended interventions that may reduce the burden of obesity-associated digestive cancers, such as participation in physical activity, diet modulation, and calorie restriction, are also described.