Pre-operative prediction of histopathological growth patterns of colorectal cancer liver metastasis using MRI-based radiomic models.

PURPOSE: Histopathological growth patterns (HGPs) of colorectal liver metastases (CRLMs) have prognostic value. However, the differentiation of HGPs relies on postoperative pathology. This study aimed to develop a magnetic resonance imaging (MRI)-based radiomic model to predict HGP pre-operatively, following the latest guidelines. METHODS: This retrospective study included 93 chemotherapy-naïve patients with CRLMs who underwent contrast-enhanced liver MRI and a partial hepatectomy between 2014 and 2022. Radiomic features were extracted from the tumor zone (RTumor), a 2-mm outer ring (RT+2), a 2-mm inner ring (RT-2), and a combined ring (R2+2) on late arterial phase MRI images. Analysis of variance method (ANOVA) and least absolute shrinkage and selection operator (LASSO) algorithms were used for feature selection. Logistic regression with five-fold cross-validation was used for model construction. Receiver operating characteristic curves, calibrated curves, and decision curve analyses were used to assess model performance. DeLong tests were used to compare different models. RESULTS: Twenty-nine desmoplastic and sixty-four non-desmoplastic CRLMs were included. The radiomic models achieved area under the curve (AUC) values of 0.736, 0.906, 0.804, and 0.794 for RTumor, RT-2, RT+2, and R2+2, respectively, in the training cohorts. The AUC values were 0.713, 0.876, 0.785, and 0.777 for RTumor, RT-2, RT+2, and R2+2, respectively, in the validation cohort. RT-2 exhibited the best performance. CONCLUSION: The MRI-based radiomic models could predict HGPs in CRLMs pre-operatively.

Microbial-Related Metabolites May Be Involved in Eight Major Biological Processes and Represent Potential Diagnostic Markers in Gastric Cancer.

Metabolites associated with microbes regulate human immunity, inhibit bacterial colonization, and promote pathogenicity. Integrating microbe and metabolome research in GC provides a direction for understanding the microbe-associated pathophysiological process of metabolic changes and disease occurrence. The present study included 30 GC patients with 30 cancerous tissues and paired non-cancerous tissues (NCs) as controls. LC-MS/MS metabolomics and 16S rRNA sequencing were performed to obtain the metabolic and microbial characteristics. Integrated analysis of the microbes and metabolomes was conducted to explore the coexistence relationship between the microbial and metabolic characteristics of GC and to identify microbial-related metabolite diagnostic markers. The metabolic analysis showed that the overall metabolite distribution differed between the GC tissues and the NC tissues: 25 metabolites were enriched in the NC tissues and 42 metabolites were enriched in the GC tissues. The α and ß microbial diversities were higher in the GC tissues than in the NC tissues, with 11 differential phyla and 52 differential genera. In the correlation and coexistence integrated analysis, 66 differential metabolites were correlated and coexisted, with specific differential microbes. The microbes in the GC tissue likely regulated eight metabolic pathways. In the efficacy evaluation of the microbial-related differential metabolites in the diagnosis of GC, 12 differential metabolites (area under the curve [AUC] >0.9) exerted relatively high diagnostic efficiency, and the combined diagnostic efficacy of 5 to 6 microbial-related differential metabolites was higher than the diagnostic efficacy of a single feature. Therefore, microbial diversity and metabolite distribution differed between the GC tissues and the NC tissues. Microbial-related metabolites may be involved in eight major metabolism-based biological processes in GC and represent potential diagnostic markers.

Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis.

IMPORTANCE: Gastric cancer is a significant and growing health problem in China. Studies have revealed significant differences in gastric microbiota between patients with gastric cancer and non-cancerous patients, suggesting that microbiota may play a role in tumorigenesis. In this meta-analysis, existing 16S rRNA microbial data were analyzed to find combinations consisting of five genera, which had good efficacy in distinguishing gastric cancer from non-cancerous patients in multiple types of samples. These results lend support to the use of microbial markers in detecting gastric cancer. Moreover, these biomarkers are plausible candidates for further mechanistic research into the role of the microbiota in tumorigenesis.

Comparison of clinicopathological parameters, prognosis, micro-ecological environment and metabolic function of Gastric Cancer with or without Fusobacterium sp. Infection.

Background: Fusobacterium sp. plays a crucial role in the tumorigenesis and development of gastrointestinal tumors. Our research group previously disclosed that Fusobacterium sp. was more abundant in gastric cancer (GC) tissues than adjacent non-cancerous (NC) tissues. However, Fusobacterium sp. did not exist in all GC tissues and the differentiated features of GC with or without Fusobacterium sp. infection is not clear. Methods: The expression data of 61 GC tissues came from 16S rRNA gene sequencing. Comparison groups were defined based on sOTU at the genus level of Fusobacterium sp., which was performed by the Qiime2 microbiome bioinformatics platform. We used Chi-square and Fisher's exact test to compare clinicopathological parameters, and used Kaplan-Meier analysis, Cox univariate and multivariate analysis to compare prognosis. Micro-ecological environment comparison was characterized by 16S rRNA gene sequencing, and the metabolic function prediction was applied by PICRUSt2. Results of microbial diversity, differential enrichment genus and metabolic function in GC with or without Fusobacterium sp. infection was validated with 229 GC tissues downloaded from an independent cohort in ENA database (PRJNA428883). Results: The infection rate of Fusobacterium sp. in 61 GC tissues was 52.46% and elderly GC patients were more prone to Fusobacterium sp. infection. GC patients infected with Fusobacterium sp. were more likely to have tumor-infiltrating lymphocytes and p53 expression. The microbial diversity and microbial structure showed significant differences between two GC tissue groups with 42 differential enrichment genera. The metabolic function of Fusobacterium sp.-positive GC tissues was related to the biosynthesis of lysine, peptidoglycan, and tRNA. The differences in microbial structure, the existence of some differential enrichment genera and the metabolic function of Fusobacterium sp.-positive GC tissues, were then validated by 229 GC tissues of an independent cohort. Conclusions: Fusobacterium sp. infection can affect the phenotypic characteristics, micro-ecological environment, and metabolic functions of GC, which may provide a basis for further exploring the relationship between Fusobacterium sp. infection and carcinogenesis of GC.

The Role of Gastric Mucosal Immunity in Gastric Diseases.

Gastric mucosa plays its immune function through innate and adaptive immunity by recruiting immune cells and releasing corresponding cytokines, which have an inseparable relationship with gastric diseases. Whether infective gastric diseases caused by Helicobacter pylori, Epstein-Barr virus or other microbe, noninfective gastric diseases, or gastric cancer, gastric mucosal immunity plays an important role in the occurrence and development of the disease. Understanding the unique immune-related tissue structure of the gastric mucosa and its role in immune responses can help prevent gastric diseases or treat them through immunotherapy. In this review, we summarize the basic feature of gastric mucosal immunity and its relationship with gastric diseases to track the latest progress of gastric mucosal immunity, update relevant knowledge and provide theoretical reference for the prevention and treatment of gastric diseases based on the gastric mucosal immunity.

Infiltration of Immunoinflammatory Cells and Related Chemokine/Interleukin Expression in Different Gastric Immune Microenvironments.

Gastric mucosal immune microenvironment plays an important role in the occurrence and development of diseases such as inflammation and cancer. In the present study, single-sample gene set enrichment analysis (ssGSEA) was used to evaluate the expression of cytokines and the degree of immune cell infiltration in four different gastric mucosa tissues from normal gastric mucosa, simple gastritis, and atrophic gastritis to gastric cancer. Here, we show the immune microenvironments of these four gastric mucosae were significantly different. From inflammation to gastric cancer, most immunoinflammatory cells showed a downward trend such as central memory CD4 T cell. Instead, several cells showed an upward trend such as macrophage. Additionally, we found some chemokines/interleukins were illustrated to be low expressed (or highly expressed) in precancerous stage and highly expressed (or low expressed) in postcancerous stage, which demonstrated an opposite expression characteristic in pre-/postcancerous stage.