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Background: Although malnutrition is common in cancer patients, its molecular mechanisms has not been fully clarified. This study aims to identify significantly differential metabolites, match the corresponding metabolic pathways, and develop a predictive model of malnutrition in patients with gastric cancer. Methods: In this cross-sectional study, we applied non-targeted metabolomics using liquid chromatography-mass spectrometry to explore the serum fingerprinting of malnutrition in patients with gastric cancer. Malnutrition-specific differential metabolites were identified by orthogonal partial least-squares discriminant analysis and t-test and matched with the Human Metabolome Database and the LIPID Metabolites and Pathways Strategy. We matched the corresponding metabolic pathways of malnutrition using pathway analysis at the MetaboAnalyst 5.0. We used random forest analyses to establish the predictive model. Results: We recruited 220 malnourished and 198 non-malnourished patients with gastric cancer. The intensities of 25 annotated significantly differential metabolites were lower in patients with malnutrition than those without, while two others were higher in patients with malnutrition than those without, including newly identified significantly differential metabolites such as indoleacrylic acid and lysophosphatidylcholine(18:3/0:0). We matched eight metabolic pathways associated with malnutrition, including aminoacyl-tRNA biosynthesis, tryptophan metabolism, and glycerophospholipid metabolism. We established a predictive model with an area under the curve of 0.702 (95% CI: 0.651–0.768) based on four annotated significantly differential metabolites, namely indoleacrylic acid, lysophosphatidylcholine(18:3/0:0), L-tryptophan, and lysophosphatidylcholine(20:3/0:0). Conclusions: We identified 27 specific differential metabolites of malnutrition in malnourished compared to non-malnourished patients with gastric cancer. We also matched eight corresponding metabolic pathways and developed a predictive model. These findings provide supportive data to better understand molecular mechanisms of malnutrition in patients with gastric cancer and new strategies for the prediction, diagnosis, prevention, and treatment for those malnourished. [ABSTRACT FROM AUTHOR]

Background: Independent and valid prognostic predictors for locally advanced gastric cancer (LAGC) patients with non-elevated serum tumor markers (Triple-negative: CA199 < 37U/ml, CEA < 5 µg/ml and CA125 < 35U/ml) before and after neoadjuvant chemotherapy (NACT) remain unclear. Methods: A total of 352 LAGC patients treated with NACT(NLAGC) from two centers were included. Of the 156 were Triple-negative patients. CA72-4 trajectory groupings was defined as longitudinal changes in CA72-4 levels before and after NACT to identify different potential subgroups and to compare recurrence-free survival (RFS) and overall survival (OS) among subgroups. The predictive performance of the nomogram-trajectory was evaluated using the area under the receiver operating characteristic curve(AUC), decision curve analysis, and C-index. Results: In the Triple-negative patients, the Stable group had significantly worse 3-year OS than the Normal, Elevated, and Descend groups(3-year OS: 53.9% vs. 77.9% vs. 73.5% vs. 87.7%;P = 0.002). Cox multivariate analysis showed that CA72-4 trajectory groupings (Stable group: HR:3.442, 95%CI[1.574–7.528], P = 0.002) was an independent prognostic risk factor. In addition, the C-index and AUC values based on the nomogram-trajectory were significantly higher than those of ypTNM staging (C-index: 0.788 vs. 0.719,P < 0.001;AUC: 0.800 vs. 0.667,P < 0.001). Furthermore, The survival analysis revealed that the 3-year OS of the Low-Risk group of nomogram scores was significantly better than that of the High-Risk group(3-year OS:84.7% vs. 29.1%). And the Low-Risk group had the lower cumulative risk of recurrence (P < 0.001). Conclusion: The CA72-4 trajectory groupings were an independent prognostic factor for NLAGC Triple-negative patients. The predictive efficacy of the Nomogram-trajectory was significantly better than the ypTNM. [ABSTRACT FROM AUTHOR]

Background: This multi-center cohort study aimed to investigate whether sex and prediagnosis lifestyle affect the prognosis of gastric cancer. Methods: Patients with gastric cancer were from four gastric cancer cohorts of the National Cancer Center of China, The First Hospital of Lanzhou University, Lanzhou University Second Hospital, and Gansu Provincial Cancer Hospital. Prediagnosis lifestyle factors in our study included body mass index (BMI) at diagnosis, usual BMI, weight loss, the history of Helicobacter pylori (Hp) infection, and the status of smoking and drinking. Results: Four gastric cancer cohorts with 29,779 gastric cancer patients were included. In total patients, female patients had a better prognosis than male patients (HR = 0.938, 95%CI: 0.881–0.999, P = 0.046). For prediagnosis lifestyle factors, BMI at diagnosis, usual BMI and the amount of smoking were statistically associated with the prognosis of gastric cancer patients. Female patients with smoking history had a poorer survival than non-smoking females (HR = 0.782, 95%CI: 0.616–0.993, P = 0.044). Tobacco consumption > 40 cigarettes per day (HR = 1.182, 95%CI: 1.035–1.350, P = 0.013) was independent adverse prognostic factors in male patients. Obesity paradox was observed only in male patients (BMI < 18.5, HR = 1.145, 95%CI: 1.019–1.286, P = 0.023; BMI: 23–27.4, HR = 0.875, 95%CI: 0.824–0.930, P < 0.001; BMI ≥ 27.5, HR = 0.807, 95%CI: 0.735–0.886, P < 0.001). Conclusions: Sex and some prediagnosis lifestyle factors, including BMI at diagnosis, usual BMI and the amount of smoking, were associated with the prognosis of gastric cancer. [ABSTRACT FROM AUTHOR]

Gastric cancer is one of the most malignant digestive tract tumors worldwide and its progression is associated with gene expression and metabolic alteration. We revealed that the gastric cancer patients with lower expression level of TOB1 exhibited poorer overall survivals according to the data in Kaplan–Meier Plotter. The unphosphorylated TOB1 protein which is effective expressed lower in gastric cancer cells. The gastric cancer cells with TOB1 gene depletion performed higher abilities of proliferation, migration and invasion and lower ability of apoptosis in vitro. The TOB1 gene depletion also promoted the tumorigenesis of gastric cancer cells in vivo. The gastric cancer cells with TOB1 gene overexpression had the converse behaviors. The transcriptional and metabolic sequencing was performed. The analyzation results showed that genes correlate-expressed with TOB1 gene were enriched in the pathways related to ERK pathway, including focal adhesion pathway, which was verified using real-time quantitative PCR. After inhibiting ERK pathway, the proliferation, colony formation and migration abilities were reduced in gastric cancer cells with low phosphorylated TOB1 protein expression level. Moreover, Pearson correlation analysis was adopted to further analyze the correlation of enriched metabolic products and differentially expressed genes. The expression of Choline, UDP-N-acetylglucosamine, Adenosine and GMP were related to the function of TOB1. This study demonstrates the genes and metabolites related to focal adhesion pathway and ERK pathway are the potential diagnosis and therapeutic targets to gastric cancer with TOB1 depletion. [ABSTRACT FROM AUTHOR]

Background/Aims: Gastric cancer (GC) ranks among the prevalent types of cancer, and its progression is influenced by the tumor microenvironment (TME). A comprehensive comprehension of the TME associated with GC has the potential to unveil therapeutic targets of significance. Methods: The complexity and heterogeneity of TME interactions were revealed through our investigation using an integrated analysis of single-cell and bulk-tissue sequencing data. Results: We constructed a single-cell transcriptomic atlas of 150,913 cells isolated from GC patients. Our analysis revealed the intricate nature and heterogeneity of the GC TME and the metabolic properties of major cell types. Furthermore, two cell subtypes, LOX+ Fibroblasts and M2 Macrophages, were enriched in tumor tissue and related to the outcome of GC patients. In addition, LOX+ Fibroblasts were significantly associated with M2 macrophages. immunofluorescence double labeling indicated LOX+ Fibroblasts and M2 Macrophages were tightly localized in GC tissue. The two cell subpopulations strongly interacted in a hypoxic microenvironment, yielding an immunosuppressive phenotype. Our findings further suggest that LOX+ Fibroblasts may act as a trigger for inducing the differentiation of monocytes into M2 Macrophages via the IL6-IL6R signaling pathway. Conclusions: Our study revealed the intricate and interdependent communication network between the fibroblast and macrophage subpopulations, which could offer valuable insights for targeted manipulation of the tumor microenvironment. [ABSTRACT FROM AUTHOR]

Introduction: Mutated human epidermal growth factor receptor 2 (HER2) is an oncogene with critical pathogenic roles in breast cancer. HER2-low-positive breast cancer is a recently described subtype. We aimed to explore the clinical and molecular characteristics of gastric cancer with low HER2 expression, drawing on recent developments in breast cancer subtypes. Materials and methods: This retrospective study involved 129 patients with HER2-non-amplified gastric cancer treated in Iwate prefectural Iwai Hospital from 2013 to 2019. Tumors were classified as HER2-null or low-positive based on immunohistochemistry score 0 or 1 + or 2 + with HER2 negativity in situ hybridization, respectively. Statistical analyses, including Kaplan–Meier analyses and Cox proportional hazards model were conducted. Results: Low HER2 expression was present in 26% (33/129) of the patients. Clinicopathological characteristics were not significantly different between the HER2-low and null groups. Kaplan–Meier analysis of overall survival was significantly longer in the HER2-low group than in the HER2-null group (P = 0.01). In multivariate Cox regression analysis, HER2-null status was associated with worse survival (hazard ratio 3.01; 95% confidence interval 1.18–7.65; and P = 0.02). Conclusion: This study highlights the prognostic importance of low HER2 expression in gastric cancer, similar to that observed in HER2-low-positive breast cancer, and suggests reclassification of gastric cancer to improve personalized treatment. Future studies should elucidate the molecular underpinnings of low HER2 expression in gastric cancer to guide novel therapeutic strategies and improve outcomes. [ABSTRACT FROM AUTHOR]

Background: Intestinal obstruction represents a severe intestinal disease associated with higher mortality rates. However, the determinants of mortality in patients with intestinal obstruction remain inadequately understood. This study sought to elucidate the potential risk factors associated with mortality in the context of intestinal obstruction during the COVID-19 pandemic. Methods: A retrospective analysis was performed on a cohort of 227 patients diagnosed with intestinal obstruction at the First Hospital of Hebei Medical University, spanning the period from September 7, 2022, to January 7, 2023. The primary endpoint of the study was mortality within four weeks following discharge. Univariate and multivariable logistic regression models were utilized to evaluate the risk factors associated with mortality outcomes. Results: A cohort of 227 patients diagnosed with intestinal obstruction (median age, 59.02 years [IQR, 48.95–70.85 years]) was included in our study. Malignant bowel obstruction (MBO) and COVID-19 were identified as independent risk factors for mortality among these patients. Notably, the mortality rate increased significantly to 38.46% when MBO was concomitant with COVID-19. Furthermore, postoperative pulmonary complications (PPC) (OR, 54.21 [death]; 95% CI, 3.17-926.31), gastric cancer (OR, 9.71 [death]; 95% CI, 1.38–68.18), VTE (Caprini Score ≥ 5) (OR, 7.64 [death]; 95% CI, 1.37–42.51), and COVID-19 (OR, 5.72 [death]; 95% CI, 1.01–32.29) were all determined to be independent risk factors for postoperative mortality. Additionally, gastric cancer could have emerged as one of the most severe risk factors for mortality in individuals with intestinal obstruction within the cohort of cancer patients, of which gastric cancer exhibited higher mortality rates compared to individuals with other forms of cancer. Conclusion: The study identifies MBO, gastric cancer, COVID-19, PPC, and VTE as potential risk factors for mortality in cases of intestinal obstruction. These findings highlight the necessity for continuous monitoring of indicators related to these mortality risk factors and their associated complications, thereby offering valuable insights for the management and treatment of intestinal obstruction. [ABSTRACT FROM AUTHOR]

Background: Vascular invasion (VI) is closely related to the metastasis, recurrence, prognosis, and treatment of gastric cancer. Currently, predicting VI preoperatively using traditional clinical examinations alone remains challenging. This study aims to explore the value of radiomics analysis based on preoperative enhanced CT images in predicting VI in gastric cancer. Methods: We retrospectively analyzed 194 patients with gastric adenocarcinoma who underwent enhanced CT examination. Based on pathology analysis, patients were divided into the VI group (n = 43) and the non-VI group (n = 151). Radiomics features were extracted from arterial phase (AP) and portal venous phase (PP) CT images. The radiomics score (Rad-score) was then calculated. Prediction models based on image features, clinical factors, and a combination of both were constructed. The diagnostic efficiency and clinical usefulness of the models were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Results: The combined prediction model included the Rad-score of AP, the Rad-score of PP, Ki-67, and Lauren classification. In the training group, the area under the curve (AUC) of the combined prediction model was 0.83 (95% CI 0.76–0.89), with a sensitivity of 64.52% and a specificity of 92.45%. In the validation group, the AUC was 0.80 (95% CI 0.67–0.89), with a sensitivity of 66.67% and a specificity of 88.89%. DCA indicated that the combined prediction model might have a greater net clinical benefit than the clinical model alone. Conclusion: The integrated models, incorporating enhanced CT radiomics features, Ki-67, and clinical factors, demonstrate significant predictive capability for VI. Moreover, the radiomics model has the potential to optimize personalized clinical treatment selection and patient prognosis assessment. [ABSTRACT FROM AUTHOR]

Purpose: Exosomal microRNAs have been identified as important mediators of communication between tumor cells and macrophages in the microenvironment. miR-541-5p was reported to be involved in hepatocellular carcinoma progression, but its role in gastric cancer (GC) and in GC cell-macrophage crosstalk is unknown. Methods: Cell proliferation, migration and invasion were respectively assessed by CCK-8 assay, scratch and Transwell assays. RT-qPCR was used to detect the level of miR-541-5p, macrophage markers and DUSP3. The percentage of CD11b+CD206+ cell population was analyzed by flow cytometry. Western blotting was employed to evaluate DUSP3-JAK2/STAT3 pathway proteins and exosome markers. The interaction between miR-541-5p and DUSP3 was verified by luciferase assay. Results: The results showed that miR-541-5p was upregulated in GC tissues and cells, and stimulated GC cell growth, migration and invasion in vitro. GC cells induce M2 macrophage polarization by secreting the exosomal miR-541-5p. Exosomal miR-541-5p maintained JAK2/STAT3 pathway activation in macrophages by targeting negative regulation of DUSP3. Inhibiting miR-541-5p significantly limited tumor growth in vivo. Conclusion: In conclusion, miR-541-5p promotes GC cell progression. GC cells may induce macrophage M2 polarization through the exosomal miR-541-5p-mediated DUSP3/JAK2/STAT3 pathway. miR-541-5p may be a potential therapeutic target for GC. [ABSTRACT FROM AUTHOR]

Abstract Background This multi-center cohort study aimed to investigate whether sex and prediagnosis lifestyle affect the prognosis of gastric cancer. Methods Patients with gastric cancer were from four gastric cancer cohorts of the National Cancer Center of China, The First Hospital of Lanzhou University, Lanzhou University Second Hospital, and Gansu Provincial Cancer Hospital. Prediagnosis lifestyle factors in our study included body mass index (BMI) at diagnosis, usual BMI, weight loss, the history of Helicobacter pylori (Hp) infection, and the status of smoking and drinking. Results Four gastric cancer cohorts with 29,779 gastric cancer patients were included. In total patients, female patients had a better prognosis than male patients (HR = 0.938, 95%CI: 0.881–0.999, P = 0.046). For prediagnosis lifestyle factors, BMI at diagnosis, usual BMI and the amount of smoking were statistically associated with the prognosis of gastric cancer patients. Female patients with smoking history had a poorer survival than non-smoking females (HR = 0.782, 95%CI: 0.616–0.993, P = 0.044). Tobacco consumption > 40 cigarettes per day (HR = 1.182, 95%CI: 1.035–1.350, P = 0.013) was independent adverse prognostic factors in male patients. Obesity paradox was observed only in male patients (BMI

Abstract Background Gastric cancer (GC), a molecularly heterogeneous disease, is the third leading cause of cancer death worldwide. The majority of GC cases worldwide occur in East Asia, predominantly China. Mutational Signature Framework offers an elegant approach to identify mutational processes present in tumors. Methods To identify mutational signature patterns, we conducted whole exome sequencing (WES) analysis in Chinese patients with GC. Mutect2 and MutsigCV were used to identify significantly mutated genes in 175 Chinese GC cases using paired tumor-normal tissues. We investigated mutational signatures using Catalogue of Somatic Mutations in Cancer (COSMIC) Version 2 (V2) and Version 3 (V3). Results We identified 104 mutated genes with P

Abstract Background Although malnutrition is common in cancer patients, its molecular mechanisms has not been fully clarified. This study aims to identify significantly differential metabolites, match the corresponding metabolic pathways, and develop a predictive model of malnutrition in patients with gastric cancer. Methods In this cross-sectional study, we applied non-targeted metabolomics using liquid chromatography-mass spectrometry to explore the serum fingerprinting of malnutrition in patients with gastric cancer. Malnutrition-specific differential metabolites were identified by orthogonal partial least-squares discriminant analysis and t-test and matched with the Human Metabolome Database and the LIPID Metabolites and Pathways Strategy. We matched the corresponding metabolic pathways of malnutrition using pathway analysis at the MetaboAnalyst 5.0. We used random forest analyses to establish the predictive model. Results We recruited 220 malnourished and 198 non-malnourished patients with gastric cancer. The intensities of 25 annotated significantly differential metabolites were lower in patients with malnutrition than those without, while two others were higher in patients with malnutrition than those without, including newly identified significantly differential metabolites such as indoleacrylic acid and lysophosphatidylcholine(18:3/0:0). We matched eight metabolic pathways associated with malnutrition, including aminoacyl-tRNA biosynthesis, tryptophan metabolism, and glycerophospholipid metabolism. We established a predictive model with an area under the curve of 0.702 (95% CI: 0.651–0.768) based on four annotated significantly differential metabolites, namely indoleacrylic acid, lysophosphatidylcholine(18:3/0:0), L-tryptophan, and lysophosphatidylcholine(20:3/0:0). Conclusions We identified 27 specific differential metabolites of malnutrition in malnourished compared to non-malnourished patients with gastric cancer. We also matched eight corresponding metabolic pathways and developed a predictive model. These findings provide supportive data to better understand molecular mechanisms of malnutrition in patients with gastric cancer and new strategies for the prediction, diagnosis, prevention, and treatment for those malnourished.

Abstract Background Independent and valid prognostic predictors for locally advanced gastric cancer (LAGC) patients with non-elevated serum tumor markers (Triple-negative: CA199

Abstract Background/Aims Gastric cancer (GC) ranks among the prevalent types of cancer, and its progression is influenced by the tumor microenvironment (TME). A comprehensive comprehension of the TME associated with GC has the potential to unveil therapeutic targets of significance. Methods The complexity and heterogeneity of TME interactions were revealed through our investigation using an integrated analysis of single-cell and bulk-tissue sequencing data. Results We constructed a single-cell transcriptomic atlas of 150,913 cells isolated from GC patients. Our analysis revealed the intricate nature and heterogeneity of the GC TME and the metabolic properties of major cell types. Furthermore, two cell subtypes, LOX+ Fibroblasts and M2 Macrophages, were enriched in tumor tissue and related to the outcome of GC patients. In addition, LOX+ Fibroblasts were significantly associated with M2 macrophages. immunofluorescence double labeling indicated LOX+ Fibroblasts and M2 Macrophages were tightly localized in GC tissue. The two cell subpopulations strongly interacted in a hypoxic microenvironment, yielding an immunosuppressive phenotype. Our findings further suggest that LOX+ Fibroblasts may act as a trigger for inducing the differentiation of monocytes into M2 Macrophages via the IL6-IL6R signaling pathway. Conclusions Our study revealed the intricate and interdependent communication network between the fibroblast and macrophage subpopulations, which could offer valuable insights for targeted manipulation of the tumor microenvironment.

Abstract Gastric cancer is one of the most malignant digestive tract tumors worldwide and its progression is associated with gene expression and metabolic alteration. We revealed that the gastric cancer patients with lower expression level of TOB1 exhibited poorer overall survivals according to the data in Kaplan–Meier Plotter. The unphosphorylated TOB1 protein which is effective expressed lower in gastric cancer cells. The gastric cancer cells with TOB1 gene depletion performed higher abilities of proliferation, migration and invasion and lower ability of apoptosis in vitro. The TOB1 gene depletion also promoted the tumorigenesis of gastric cancer cells in vivo. The gastric cancer cells with TOB1 gene overexpression had the converse behaviors. The transcriptional and metabolic sequencing was performed. The analyzation results showed that genes correlate-expressed with TOB1 gene were enriched in the pathways related to ERK pathway, including focal adhesion pathway, which was verified using real-time quantitative PCR. After inhibiting ERK pathway, the proliferation, colony formation and migration abilities were reduced in gastric cancer cells with low phosphorylated TOB1 protein expression level. Moreover, Pearson correlation analysis was adopted to further analyze the correlation of enriched metabolic products and differentially expressed genes. The expression of Choline, UDP-N-acetylglucosamine, Adenosine and GMP were related to the function of TOB1. This study demonstrates the genes and metabolites related to focal adhesion pathway and ERK pathway are the potential diagnosis and therapeutic targets to gastric cancer with TOB1 depletion.

Abstract Introduction Mutated human epidermal growth factor receptor 2 (HER2) is an oncogene with critical pathogenic roles in breast cancer. HER2-low-positive breast cancer is a recently described subtype. We aimed to explore the clinical and molecular characteristics of gastric cancer with low HER2 expression, drawing on recent developments in breast cancer subtypes. Materials and methods This retrospective study involved 129 patients with HER2-non-amplified gastric cancer treated in Iwate prefectural Iwai Hospital from 2013 to 2019. Tumors were classified as HER2-null or low-positive based on immunohistochemistry score 0 or 1 + or 2 + with HER2 negativity in situ hybridization, respectively. Statistical analyses, including Kaplan–Meier analyses and Cox proportional hazards model were conducted. Results Low HER2 expression was present in 26% (33/129) of the patients. Clinicopathological characteristics were not significantly different between the HER2-low and null groups. Kaplan–Meier analysis of overall survival was significantly longer in the HER2-low group than in the HER2-null group (P = 0.01). In multivariate Cox regression analysis, HER2-null status was associated with worse survival (hazard ratio 3.01; 95% confidence interval 1.18–7.65; and P = 0.02). Conclusion This study highlights the prognostic importance of low HER2 expression in gastric cancer, similar to that observed in HER2-low-positive breast cancer, and suggests reclassification of gastric cancer to improve personalized treatment. Future studies should elucidate the molecular underpinnings of low HER2 expression in gastric cancer to guide novel therapeutic strategies and improve outcomes.

Abstract Background Intestinal obstruction represents a severe intestinal disease associated with higher mortality rates. However, the determinants of mortality in patients with intestinal obstruction remain inadequately understood. This study sought to elucidate the potential risk factors associated with mortality in the context of intestinal obstruction during the COVID-19 pandemic. Methods A retrospective analysis was performed on a cohort of 227 patients diagnosed with intestinal obstruction at the First Hospital of Hebei Medical University, spanning the period from September 7, 2022, to January 7, 2023. The primary endpoint of the study was mortality within four weeks following discharge. Univariate and multivariable logistic regression models were utilized to evaluate the risk factors associated with mortality outcomes. Results A cohort of 227 patients diagnosed with intestinal obstruction (median age, 59.02 years [IQR, 48.95–70.85 years]) was included in our study. Malignant bowel obstruction (MBO) and COVID-19 were identified as independent risk factors for mortality among these patients. Notably, the mortality rate increased significantly to 38.46% when MBO was concomitant with COVID-19. Furthermore, postoperative pulmonary complications (PPC) (OR, 54.21 [death]; 95% CI, 3.17-926.31), gastric cancer (OR, 9.71 [death]; 95% CI, 1.38–68.18), VTE (Caprini Score ≥ 5) (OR, 7.64 [death]; 95% CI, 1.37–42.51), and COVID-19 (OR, 5.72 [death]; 95% CI, 1.01–32.29) were all determined to be independent risk factors for postoperative mortality. Additionally, gastric cancer could have emerged as one of the most severe risk factors for mortality in individuals with intestinal obstruction within the cohort of cancer patients, of which gastric cancer exhibited higher mortality rates compared to individuals with other forms of cancer. Conclusion The study identifies MBO, gastric cancer, COVID-19, PPC, and VTE as potential risk factors for mortality in cases of intestinal obstruction. These findings highlight the necessity for continuous monitoring of indicators related to these mortality risk factors and their associated complications, thereby offering valuable insights for the management and treatment of intestinal obstruction.

Abstract Background Vascular invasion (VI) is closely related to the metastasis, recurrence, prognosis, and treatment of gastric cancer. Currently, predicting VI preoperatively using traditional clinical examinations alone remains challenging. This study aims to explore the value of radiomics analysis based on preoperative enhanced CT images in predicting VI in gastric cancer. Methods We retrospectively analyzed 194 patients with gastric adenocarcinoma who underwent enhanced CT examination. Based on pathology analysis, patients were divided into the VI group (n = 43) and the non-VI group (n = 151). Radiomics features were extracted from arterial phase (AP) and portal venous phase (PP) CT images. The radiomics score (Rad-score) was then calculated. Prediction models based on image features, clinical factors, and a combination of both were constructed. The diagnostic efficiency and clinical usefulness of the models were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Results The combined prediction model included the Rad-score of AP, the Rad-score of PP, Ki-67, and Lauren classification. In the training group, the area under the curve (AUC) of the combined prediction model was 0.83 (95% CI 0.76–0.89), with a sensitivity of 64.52% and a specificity of 92.45%. In the validation group, the AUC was 0.80 (95% CI 0.67–0.89), with a sensitivity of 66.67% and a specificity of 88.89%. DCA indicated that the combined prediction model might have a greater net clinical benefit than the clinical model alone. Conclusion The integrated models, incorporating enhanced CT radiomics features, Ki-67, and clinical factors, demonstrate significant predictive capability for VI. Moreover, the radiomics model has the potential to optimize personalized clinical treatment selection and patient prognosis assessment.

Abstract Background Gastric cancer (GC) is a major contributor to cancer-related mortality. Glycolysis plays a pivotal role in tumor microenvironment (TME) reprogramming. In this research, the functions of glycolysis-associated genes (GRGs) were evaluated to predict the outcome and reveal the characteristics of the immune microenvironment in individuals with stomach cancer. Methods The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) cohort provided gene expression and clinical data for gastric cancer (GC) patients, which were further authenticated using datasets sourced from the Gene Expression Omnibus (GEO). By referencing the Molecular Signatures Database (MSigDB), a total of 326 GRGs were pinpointed. The various subtypes of GC were outlined through consensus clustering, derived from the expression patterns of these GRGs. Utilizing multivariate Cox regression analysis, a multigene risk score model was formulated. Both the CIBERSORT and ESTIMATE algorithms played a pivotal role in assessing the immune microenvironment. To delve into the biological functions of the key genes, wound healing, transwell invasion, and MTT assays were conducted. Results Based on the expression patterns of GRGs, patients were categorized into two distinct groups: the metabolic subtype, designated as cluster A, and the immune subtype, labeled as cluster B. Patients belonging to cluster B exhibited a poorer prognosis. A prognostic risk score model, formulated upon the expression levels of six key GRGs — ME1, PLOD2, NUP50, CXCR4, SLC35A3, and SRD35A3 — emerged as a viable tool for predicting patient outcomes. The downregulation of CXCR4 notably diminished the glycolytic capacity of gastric cancer (GC) cells, alongside their migratory, invasive, and proliferative capabilities. Intriguingly, despite the adverse prognostic implications associated with both the immune subtype (cluster B) and the high-risk cohort, these groups exhibited a favorable immune microenvironment coupled with elevated expression of immune checkpoint genes. Our investigations revealed a positive correlation between high CXCR4 expression and low ME1 expression with the infiltration of CD8+ T cells, as well as an enhanced responsiveness to treatment with an anti-PD-1 immune checkpoint inhibitor. Conclusions In this study, we discovered that the expression profiles of GRGs hold the potential to forecast the prognosis of gastric cancer (GC) patients, thereby possibly aiding in clinical treatment decision-making.

Abstract Purpose Exosomal microRNAs have been identified as important mediators of communication between tumor cells and macrophages in the microenvironment. miR-541-5p was reported to be involved in hepatocellular carcinoma progression, but its role in gastric cancer (GC) and in GC cell-macrophage crosstalk is unknown. Methods Cell proliferation, migration and invasion were respectively assessed by CCK-8 assay, scratch and Transwell assays. RT-qPCR was used to detect the level of miR-541-5p, macrophage markers and DUSP3. The percentage of CD11b+CD206+ cell population was analyzed by flow cytometry. Western blotting was employed to evaluate DUSP3-JAK2/STAT3 pathway proteins and exosome markers. The interaction between miR-541-5p and DUSP3 was verified by luciferase assay. Results The results showed that miR-541-5p was upregulated in GC tissues and cells, and stimulated GC cell growth, migration and invasion in vitro. GC cells induce M2 macrophage polarization by secreting the exosomal miR-541-5p. Exosomal miR-541-5p maintained JAK2/STAT3 pathway activation in macrophages by targeting negative regulation of DUSP3. Inhibiting miR-541-5p significantly limited tumor growth in vivo. Conclusion In conclusion, miR-541-5p promotes GC cell progression. GC cells may induce macrophage M2 polarization through the exosomal miR-541-5p-mediated DUSP3/JAK2/STAT3 pathway. miR-541-5p may be a potential therapeutic target for GC.

Abstract Objective Ubiquitin-specific peptidase 10 (USP10), a typical de-ubiquitinase, has been found to play a double-edged role in human cancers. Previously, we reported that the expression of USP10 was negatively correlated with the depth of gastric wall invasion, lymph node metastasis, and prognosis in gastric cancer (GC) patients. However, it remains unclear whether USP10 can regulate the metastasis of GC cells through its de-ubiquitination function. Methods In this study, proteome, ubiquitinome, and transcriptome analyses were conducted to comprehensively identify novel de-ubiquitination targets for USP10 in GC cells. Subsequently, a series of validation experiments, including in vitro cell culture studies, in vivo metastatic tumor models, and clinical sample analyses, were performed to elucidate the regulatory mechanism of USP10 and its de-ubiquitination targets in GC metastasis. Results After overexpression of USP10 in GC cells, 146 proteins, 489 ubiquitin sites, and 61 mRNAs exhibited differential expression. By integrating the results of multi-omics, we ultimately screened 9 potential substrates of USP10, including TNFRSF10B, SLC2A3, CD44, CSTF2, RPS27, TPD52, GPS1, RNF185, and MED16. Among them, TNFRSF10B was further verified as a direct de-ubiquitination target for USP10 by Co-IP and protein stabilization assays. The dysregulation of USP10 or TNFRSF10B affected the migration and invasion of GC cells in vitro and in vivo models. Molecular mechanism studies showed that USP10 inhibited the epithelial-mesenchymal transition (EMT) process by increasing the stability of TNFRSF10B protein, thereby regulating the migration and invasion of GC cells. Finally, the retrospective clinical sample studies demonstrated that the downregulation of TNFRSF10B expression was associated with poor survival among 4 of 7 GC cohorts, and the expression of TNFRSF10B protein was significantly negatively correlated with the incidence of distant metastasis, diffuse type, and poorly cohesive carcinoma. Conclusions Our study established a high-throughput strategy for screening de-ubiquitination targets for USP10 and further confirmed that inhibiting the ubiquitination of TNFRSF10B might be a promising therapeutic strategy for GC metastasis.

Abstract Background Inflammatory factors have increasingly become a more cost-effective prognostic indicator for gastric cancer (GC). The goal of this study was to develop a prognostic score system for gastric cancer patients based on inflammatory indicators. Methods Patients’ baseline characteristics and anthropometric measures were used as predictors, and independently screened by multiple machine learning(ML) algorithms. We constructed risk scores to predict overall survival in the training cohort and tested risk scores in the validation. The predictors selected by the model were used in multivariate Cox regression analysis and developed a nomogram to predict the individual survival of GC patients. Results A 13-variable adaptive boost machine (ADA) model mainly comprising tumor stage and inflammation indices was selected in a wide variety of machine learning models. The ADA model performed well in predicting survival in the validation set (AUC = 0.751; 95% CI: 0.698, 0.803). Patients in the study were split into two sets – “high-risk” and “low-risk” based on 0.42, the cut-off value of the risk score. We plotted the survival curves using Kaplan-Meier analysis. Conclusion The proposed model performed well in predicting the prognosis of GC patients and could help clinicians apply management strategies for better prognostic outcomes for patients.

Abstract Background Evaluation of human epidermal growth factor receptor 2 (HER2) overexpression caused by erb-b2 receptor tyrosine kinase 2 (ERBB2) amplification (AMP) by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) is essential for treating unresectable metastatic gastric cancer (GC). A targeted tumour sequencing test enables comprehensive assessment of alterations in cancer-related genes, including ERBB2. This study aimed to evaluate the concordance between the targeted tumour sequencing test and IHC/FISH for detecting HER2-positive GC and to clarify the significance of ERBB2 AMP and concomitant genetic alterations in HER2 downstream pathways (DPs) in anti-HER2 therapy for unresectable metastatic GC patients. Methods ERBB2 copy number alteration (CNA) was examined via a targeted tumour sequencing test in 152 formalin-fixed paraffin-embedded (FFPE) GC tissues. ERBB2 CNA was compared to HER2 status evaluated by IHC/FISH in FFPE block sections, which were identical to those subjected to the targeted tumour sequencing test. Treatment outcomes of anti-HER2 therapy in 11 patients with unresectable metastatic GC was evaluated. Results ERBB2 AMP (≥ 2.5-fold change) was detected by the targeted tumour sequencing test in 15 patients (9.9%), and HER2 positivity (IHC 3 + or IHC 2+/FISH positive) was detected in 21 patients (13.8%). The overall percent agreement, positive percent agreement, negative percent agreement and Cohen’s kappa between ERBB2 CNA and HER2 status were 94.7%, 66.7%, 99.2% and 0.75, respectively. Progression-free survival for trastuzumab therapy in patients with ERBB2 AMP was significantly longer than that in patients with no ERBB2 AMP detected by the targeted tumour sequencing test (median 14 months vs. 4 months, P = 0.007). Treatment response to trastuzumab therapy was reduced in patients with ERBB2 AMP and concomitant CNAs of genes in HER2 DPs. One patient with ERBB2 AMP and concomitant CNAs of genes in HER2 DPs achieved a durable response to trastuzumab deruxtecan as fourth-line therapy. Conclusions A targeted tumour sequencing test is a reliable modality for identifying HER2-positive GC. ERBB2 AMP and concomitant genetic alterations detected through the targeted tumour sequencing test are potential indicators of treatment response to trastuzumab therapy. The targeted tumour sequencing test has emerged as a plausible candidate for companion diagnostics to determine indications for anti-HER2 therapy in the era of precision medicine for GC.

Abstract Objective Tumor immune infiltration leads to poor prognosis of gastric cancer patients and seriously affects the life quality of gastric cancer patients. This study was based on bioinformatics to screen prognostic biomarkers in patients with high degree of immune invasion of gastric cancer. Meanwhile, the action of biomarker CCDC80 was explored in gastric cancer by cell and tumorigenesis experiments, to provide reference for the cure of gastric cancer patients. Methods Data sets and clinical massage on gastric cancer were collected from TCGA database and GEO database. ConsensusClusterPlus was used to cluster gastric cancer patients based on the 28 immune cells infiltration in ssGSEA. R “Limma” package was applied to analyze differential mRNAs between Cluster 1 and Cluster 2. Differential expression genes were screened by single factor analysis. Stemness markers (SERPINF1, DCN, CCDC80, FBLN5, SPARCL1, CCL14, DPYSL3) were identified for differential expression genes. Prognostic value of CCDC80 was evaluated in gastric cancer. Differences in genomic mutation and tumor microenvironment immune infiltration were assessed between high or low CCDC80. Finally, gastric cancer cells (HGC-27 and MKN-45) were selected to evaluate the action of silencing CCDC80 on malignant characterization, macrophage polarization, and tumor formation. Results Bioinformatics analysis showed that CCDC80, as a stemness marker, was significantly overexpressed in gastric cancer. CCDC80 was also related to the degree of gastric cancer immune invasion. CCDC80 was up-expressed in cells of gastric cancer. Silencing CCDC80 inhibited malignant characterization and subcutaneous tumor formation of gastric cancer cells. High expression of CCDC80 was positive correspondence with immune invasion. Silencing CCDC80 inhibited M2 polarization and promoted M1 polarization in tumor tissues. In addition, gastric cancer patients were likely to have mutations in CDH1, ACTRT1, GANAB, and CDH10 genes in the High-CCDC80 group. Conclusion Silencing CCDC80, a prognostic biomarker in patients with immune invasion of gastric cancer, could effectively inhibit the malignant characterization, M2 polarization, and tumor formation of gastric cancer.

Abstract Background Gastric cancer is one of the most common tumors worldwide, and most patients are deprived of treatment options when diagnosed at advanced stages. PRDM14 has carcinogenic potential in breast and non-small cell lung cancer. however, its role in gastric cancer has not been elucidated. Methods We aimed to elucidate the expression of PRDM14 using pan-cancer analysis. We monitored the expression of PRDM14 in cells and patients using quantitative polymerase chain reaction, western blotting, and immunohistochemistry. We observed that cell phenotypes and regulatory genes were influenced by PRDM14 by silencing PRDM14. We evaluated and validated the value of the PRDM14-derived prognostic model. Finally, we predicted the relationship between PRDM14 and small-molecule drug responses using the Connectivity Map and The Genomics of Drug Sensitivity in Cancer databases. Results PRDM14 was significantly overexpressed in gastric cancer, which identified in cell lines and patients’ tissues. Silencing the expression of PRDM14 resulted in apoptosis promotion, cell cycle arrest, and inhibition of the growth and migration of GC cells. Functional analysis revealed that PRDM14 acts in epigenetic regulation and modulates multiple DNA methyltransferases or transcription factors. The PRDM14-derived differentially expressed gene prognostic model was validated to reliably predict the patient prognosis. Nomograms (age, sex, and PRDM14-risk score) were used to quantify the probability of survival. PRDM14 was positively correlated with sensitivity to small-molecule drugs such as TPCA-1, PF-56,227, mirin, and linsitinib. Conclusions Collectively, our findings suggest that PRDM14 is a positive regulator of gastric cancer progression. Therefore, it may be a potential therapeutic target for gastric cancer.

Abstract Background Insufficient evidence existed about the prognostic role of the advanced lung cancer inflammation index (ALI) for gastric cancer patients who underwent curative resection. The aim of this study was to identify the predictive ability of ALI for survival after curative gastrectomy. Methods We retrospectively analyzed 328 gastric cancer patients who received curative gastrectomy from the database of Chongqing University Cancer Hospital, and investigated the prognostic role of the preoperative ALI compared with clinicopathological variables and other serum biomarkers, such as preoperative neutrophil-to-lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and Lymphocyte-monocyte ratio (LMR). To minimize intergroup differences, propensity score matching (PSM) analysis was employed. Additionally, we performed a meta-analysis of four cohort studies published up to October 2023 following the PRISMA guidelines. Results In the overall cohort, patients in the low ALI group had a significantly worse overall survival compared to those in the high ALI group (P

Abstract Background Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide and is associated with high morbidity and mortality rates. However, the specific biomarkers used to predict the postoperative prognosis of patients with gastric cancer remain unknown. Recent research has shown that the tumor microenvironment (TME) has an increasingly positive effect on anti-tumor activity. This study aims to build signatures to study the effect of certain genes on gastric cancer. Methods Expression profiles of 37 T cell-related genes and their TME characteristics were comprehensively analyzed. A risk signature was constructed and validated based on the screened T cell-related genes, and the roles of hub genes in GC were experimentally validated. Results A novel T cell-related gene signature was constructed based on CD5, ABCA8, SERPINE2, ESM1, SERPINA5, and NMU. The high-risk group indicated lower overall survival (OS), poorer immune efficacy, and higher drug resistance, with SERPINE2 promoting GC cell proliferation, according to experiments. SERPINE2 and CXCL12 were significantly correlated, indicating poor OS via the Youjiang cohort. Conclusions This study identified T cell-related genes in patients with stomach adenocarcinoma (STAD) for prognosis estimation and proposed potential immunotherapeutic targets for STAD.

Objective: Ubiquitin-specific peptidase 10 (USP10), a typical de-ubiquitinase, has been found to play a double-edged role in human cancers. Previously, we reported that the expression of USP10 was negatively correlated with the depth of gastric wall invasion, lymph node metastasis, and prognosis in gastric cancer (GC) patients. However, it remains unclear whether USP10 can regulate the metastasis of GC cells through its de-ubiquitination function. Methods: In this study, proteome, ubiquitinome, and transcriptome analyses were conducted to comprehensively identify novel de-ubiquitination targets for USP10 in GC cells. Subsequently, a series of validation experiments, including in vitro cell culture studies, in vivo metastatic tumor models, and clinical sample analyses, were performed to elucidate the regulatory mechanism of USP10 and its de-ubiquitination targets in GC metastasis. Results: After overexpression of USP10 in GC cells, 146 proteins, 489 ubiquitin sites, and 61 mRNAs exhibited differential expression. By integrating the results of multi-omics, we ultimately screened 9 potential substrates of USP10, including TNFRSF10B, SLC2A3, CD44, CSTF2, RPS27, TPD52, GPS1, RNF185, and MED16. Among them, TNFRSF10B was further verified as a direct de-ubiquitination target for USP10 by Co-IP and protein stabilization assays. The dysregulation of USP10 or TNFRSF10B affected the migration and invasion of GC cells in vitro and in vivo models. Molecular mechanism studies showed that USP10 inhibited the epithelial-mesenchymal transition (EMT) process by increasing the stability of TNFRSF10B protein, thereby regulating the migration and invasion of GC cells. Finally, the retrospective clinical sample studies demonstrated that the downregulation of TNFRSF10B expression was associated with poor survival among 4 of 7 GC cohorts, and the expression of TNFRSF10B protein was significantly negatively correlated with the incidence of distant metastasis, diffuse type, and poorly cohesive carcinoma. Conclusions: Our study established a high-throughput strategy for screening de-ubiquitination targets for USP10 and further confirmed that inhibiting the ubiquitination of TNFRSF10B might be a promising therapeutic strategy for GC metastasis. [ABSTRACT FROM AUTHOR]

Objective: Tumor immune infiltration leads to poor prognosis of gastric cancer patients and seriously affects the life quality of gastric cancer patients. This study was based on bioinformatics to screen prognostic biomarkers in patients with high degree of immune invasion of gastric cancer. Meanwhile, the action of biomarker CCDC80 was explored in gastric cancer by cell and tumorigenesis experiments, to provide reference for the cure of gastric cancer patients. Methods: Data sets and clinical massage on gastric cancer were collected from TCGA database and GEO database. ConsensusClusterPlus was used to cluster gastric cancer patients based on the 28 immune cells infiltration in ssGSEA. R "Limma" package was applied to analyze differential mRNAs between Cluster 1 and Cluster 2. Differential expression genes were screened by single factor analysis. Stemness markers (SERPINF1, DCN, CCDC80, FBLN5, SPARCL1, CCL14, DPYSL3) were identified for differential expression genes. Prognostic value of CCDC80 was evaluated in gastric cancer. Differences in genomic mutation and tumor microenvironment immune infiltration were assessed between high or low CCDC80. Finally, gastric cancer cells (HGC-27 and MKN-45) were selected to evaluate the action of silencing CCDC80 on malignant characterization, macrophage polarization, and tumor formation. Results: Bioinformatics analysis showed that CCDC80, as a stemness marker, was significantly overexpressed in gastric cancer. CCDC80 was also related to the degree of gastric cancer immune invasion. CCDC80 was up-expressed in cells of gastric cancer. Silencing CCDC80 inhibited malignant characterization and subcutaneous tumor formation of gastric cancer cells. High expression of CCDC80 was positive correspondence with immune invasion. Silencing CCDC80 inhibited M2 polarization and promoted M1 polarization in tumor tissues. In addition, gastric cancer patients were likely to have mutations in CDH1, ACTRT1, GANAB, and CDH10 genes in the High-CCDC80 group. Conclusion: Silencing CCDC80, a prognostic biomarker in patients with immune invasion of gastric cancer, could effectively inhibit the malignant characterization, M2 polarization, and tumor formation of gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer is one of the most common tumors worldwide, and most patients are deprived of treatment options when diagnosed at advanced stages. PRDM14 has carcinogenic potential in breast and non-small cell lung cancer. however, its role in gastric cancer has not been elucidated. Methods: We aimed to elucidate the expression of PRDM14 using pan-cancer analysis. We monitored the expression of PRDM14 in cells and patients using quantitative polymerase chain reaction, western blotting, and immunohistochemistry. We observed that cell phenotypes and regulatory genes were influenced by PRDM14 by silencing PRDM14. We evaluated and validated the value of the PRDM14-derived prognostic model. Finally, we predicted the relationship between PRDM14 and small-molecule drug responses using the Connectivity Map and The Genomics of Drug Sensitivity in Cancer databases. Results: PRDM14 was significantly overexpressed in gastric cancer, which identified in cell lines and patients' tissues. Silencing the expression of PRDM14 resulted in apoptosis promotion, cell cycle arrest, and inhibition of the growth and migration of GC cells. Functional analysis revealed that PRDM14 acts in epigenetic regulation and modulates multiple DNA methyltransferases or transcription factors. The PRDM14-derived differentially expressed gene prognostic model was validated to reliably predict the patient prognosis. Nomograms (age, sex, and PRDM14-risk score) were used to quantify the probability of survival. PRDM14 was positively correlated with sensitivity to small-molecule drugs such as TPCA-1, PF-56,227, mirin, and linsitinib. Conclusions: Collectively, our findings suggest that PRDM14 is a positive regulator of gastric cancer progression. Therefore, it may be a potential therapeutic target for gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Insufficient evidence existed about the prognostic role of the advanced lung cancer inflammation index (ALI) for gastric cancer patients who underwent curative resection. The aim of this study was to identify the predictive ability of ALI for survival after curative gastrectomy. Methods: We retrospectively analyzed 328 gastric cancer patients who received curative gastrectomy from the database of Chongqing University Cancer Hospital, and investigated the prognostic role of the preoperative ALI compared with clinicopathological variables and other serum biomarkers, such as preoperative neutrophil-to-lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and Lymphocyte-monocyte ratio (LMR). To minimize intergroup differences, propensity score matching (PSM) analysis was employed. Additionally, we performed a meta-analysis of four cohort studies published up to October 2023 following the PRISMA guidelines. Results: In the overall cohort, patients in the low ALI group had a significantly worse overall survival compared to those in the high ALI group (P < 0.0001). Subgroup analysis identified that ALI maintained its prognostic significance across different subgroups. In addition, ROC analysis showed that ALI had a higher AUC value for 3-year overall survival compared to NLR, PLR, and LMR (0.576 vs. 0.573 vs. 0.557 vs. 0.557). Multivariate analysis indicated that ALI, other than other serum biomarkers, was an independent risk factor for decreased overall survival in GC patients following curative surgery (HR = 1.449; 95%CI: 1.028–2.045; P = 0.034). Consistently, PSM analysis supported all of these findings. The meta-analysis including 4 studies evaluating 2542 patients, confirmed the association between the low ALI and poor survival outcomes. Conclusion: The preoperative ALI was an independent prognostic factor for survival in gastric cancer patients who underwent curative gastrectomy. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide and is associated with high morbidity and mortality rates. However, the specific biomarkers used to predict the postoperative prognosis of patients with gastric cancer remain unknown. Recent research has shown that the tumor microenvironment (TME) has an increasingly positive effect on anti-tumor activity. This study aims to build signatures to study the effect of certain genes on gastric cancer. Methods: Expression profiles of 37 T cell-related genes and their TME characteristics were comprehensively analyzed. A risk signature was constructed and validated based on the screened T cell-related genes, and the roles of hub genes in GC were experimentally validated. Results: A novel T cell-related gene signature was constructed based on CD5, ABCA8, SERPINE2, ESM1, SERPINA5, and NMU. The high-risk group indicated lower overall survival (OS), poorer immune efficacy, and higher drug resistance, with SERPINE2 promoting GC cell proliferation, according to experiments. SERPINE2 and CXCL12 were significantly correlated, indicating poor OS via the Youjiang cohort. Conclusions: This study identified T cell-related genes in patients with stomach adenocarcinoma (STAD) for prognosis estimation and proposed potential immunotherapeutic targets for STAD. [ABSTRACT FROM AUTHOR]

Abstract Background Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. Methods A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. Results Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629–0.950 in the TCGA dataset and 0.736–0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. Conclusions Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Abstract Background The aim of this study was to explore the correlation between biomarkers of lipid metabolism and gastric cancer. Methods 1120 gastric cancer patients and 1134 health examiners enrolled in this study. The clinic data and serum lipid level, including Total cholesterol (TC), Triglyceride (TG), Low-density lipoprotein cholesterol (LDL-C) and High-density lipoprotein cholesterol (HDL-C), were collected. Results Serum TG and LDL-C levels in patients with gastric cancer were higher than those in the control group. HDL-C levels were lower than the control group (P

Abstract Background Accurate microsatellite instability (MSI) testing is essential for identifying gastric cancer (GC) patients eligible for immunotherapy. We aimed to develop and validate a CT-based radiomics signature to predict MSI and immunotherapy outcomes in GC. Methods This retrospective multicohort study included a total of 457 GC patients from two independent medical centers in China and The Cancer Imaging Archive (TCIA) databases. The primary cohort (n = 201, center 1, 2017–2022), was used for signature development via Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis. Two independent immunotherapy cohorts, one from center 1 (n = 184, 2018–2021) and another from center 2 (n = 43, 2020–2021), were utilized to assess the signature’s association with immunotherapy response and survival. Diagnostic efficiency was evaluated using the area under the receiver operating characteristic curve (AUC), and survival outcomes were analyzed via the Kaplan-Meier method. The TCIA cohort (n = 29) was included to evaluate the immune infiltration landscape of the radiomics signature subgroups using both CT images and mRNA sequencing data. Results Nine radiomics features were identified for signature development, exhibiting excellent discriminative performance in both the training (AUC: 0.851, 95%CI: 0.782, 0.919) and validation cohorts (AUC: 0.816, 95%CI: 0.706, 0.926). The radscore, calculated using the signature, demonstrated strong predictive abilities for objective response in immunotherapy cohorts (AUC: 0.734, 95%CI: 0.662, 0.806; AUC: 0.724, 95%CI: 0.572, 0.877). Additionally, the radscore showed a significant association with PFS and OS, with GC patients with a low radscore experiencing a significant survival benefit from immunotherapy. Immune infiltration analysis revealed significantly higher levels of CD8 + T cells, activated CD4 + B cells, and TNFRSF18 expression in the low radscore group, while the high radscore group exhibited higher levels of T cells regulatory and HHLA2 expression. Conclusion This study developed a robust radiomics signature with the potential to serve as a non-invasive biomarker for GC’s MSI status and immunotherapy response, demonstrating notable links to post-immunotherapy PFS and OS. Additionally, distinct immune profiles were observed between low and high radscore groups, highlighting their potential clinical implications.

Abstract Background As comprehensive surgical management for gastric cancer becomes increasingly specialized and standardized, the precise differentiation between ≤T1 and ≥T2 gastric cancer before endoscopic intervention holds paramount clinical significance. Objective To evaluate the diagnostic efficacy of contrast-enhanced gastric ultrasonography in differentiating ≤T1 and ≥T2 gastric cancer. Methods PubMed, Web of Science, and Medline were searched to collect studies published from January 1, 2000 to March 16, 2023 on the efficacy of either double contrast-enhanced gastric ultrasonography (D-CEGUS) or oral contrast-enhanced gastric ultrasonography (O-CEGUS) in determining T-stage in gastric cancer. The articles were selected according to specified inclusion and exclusion criteria, and the quality of the included literature was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 scale. Meta-analysis was performed using Stata 12 software with data from the 2 × 2 crosslinked tables in the included literature. Results In total, 11 papers with 1124 patients were included in the O-CEGUS analysis, which revealed a combined sensitivity of 0.822 (95% confidence interval [CI] = 0.753–0.875), combined specificity of 0.964 (95% CI = 0.925–0.983), and area under the summary receiver operating characteristic (sROC) curve (AUC) of 0.92 (95% CI = 0.89–0.94). In addition, five studies involving 536 patients were included in the D-CEGUS analysis, which gave a combined sensitivity of 0.733 (95% CI = 0.550–0.860), combined specificity of 0.982 (95% CI = 0.936–0.995), and AUC of 0.93 (95% CI = 0.91–0.95). According to the I2 and P values ​​of the forest plot, there was obvious heterogeneity in the combined specificities of the included papers. Therefore, the two studies with the lowest specificities were excluded from the O-CEGUS and D-CEGUS analyses, which eliminated the heterogeneity among the remaining literature. Consequently, the combined sensitivity and specificity of the remaining studies were 0.794 (95% CI = 0.710–0.859) and 0.976 (95% CI = 0.962–0.985), respectively, for the O-CEDUS studies and 0.765 (95% CI = 0.543–0.899) and 0.986 (95% CI = 0.967–0.994), respectively, for the D-CEGUS studies. The AUCs were 0.98 and 0.99 for O-CEGUS and D-CEGUS studies, respectively. Conclusion Both O-CEGUS and D-CEGUS can differentiate ≤T1 gastric cancer from ≥T2 gastric cancer, thus assisting the formulation of clinical treatment strategies for patients with very early gastric cancer. Given its simplicity and cost-effectiveness, O-CEGUS is often favored as a staging method for gastric cancer prior to endoscopic intervention.

Abstract Objective This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). Methods This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). Results A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. Conclusion The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

Abstract Background To establish a nomogram to predict the probability of survival of patients with stage II/III gastric cancer (GC) who received incomplete peri-operative adjuvant chemotherapy (PAC). Methods The medical records of stage II/III GC patients who received curative resection and 1 to 5 cycles of PAC from two tertiary hospitals were retrospectively reviewed. Patients were randomly classified into either a training group or validation group at a ratio of 7:3. The nomogram was constructed based on various prognostic factors using Cox regression analysis in the training cohort, and was validated by the validation group. Concordance index and calibration curves were used to evaluate the discrimination and calibration of the nomogram. Additionally, decision curve analysis (DCA) was used to compare the net clinical benefits of the nomogram and eighth version of TNM staging system. Results A total of 1,070 consecutive patients were included and 749 patients were enrolled into the training group. Lower body mass index (

Abstract Background Immune checkpoint inhibitor (ICI) or irinotecan-based chemotherapy is frequently used after failure of second-line paclitaxel plus ramucirumab treatment for patients with locally advanced unresectable or metastatic advanced gastric cancer (AGC). This study aimed to compare the efficacy between ICI and irinotecan-based chemotherapy as third-line treatment in patients with AGC. Methods We retrospectively reviewed patients with AGC, whose third-line treatment started between July 2019 and June 2021 at 17 institutions in Korea. The ICI group included patients who received nivolumab or pembrolizumab, and the irinotecan-based chemotherapy group included patients who received irinotecan or FOLFIRI (5-fluorouracil, leucovorin and irinotecan). Results A total of 363 patients [n = 129 (ICI) and n = 234 (irinotecan-based chemotherapy)] were analyzed. The median progression-free survival was 2.3 and 2.9 months in ICI and irinotecan-based chemotherapy groups, respectively (p = 0.802). The median overall survival (OS) was 5.5 and 6.0 months in ICI and irinotecan-based chemotherapy groups, respectively (p = 0.786). For all patients included in this study, multivariable analysis showed that weight loss, peritoneal metastasis, low serum sodium or albumin, and short duration of second-line treatment were associated with inferior OS (p

Abstract Background Cancer cachexia is associated with impaired functional and nutritional status and worse clinical outcomes. Global Leadership Initiative in Malnutrition (GLIM) consensus recommended the application of GLIM criteria to diagnose malnutrition in patients with cachexia. However, few previous study has applied the GLIM criteria in patients with cancer cachexia. Methods From July 2014 to May 2019, patients who were diagnosed with cancer cachexia and underwent radical gastrectomy for gastric cancer were included in this study. Malnutrition was diagnosed using the GLIM criteria. Skeletal muscle index was measured using abdominal computed tomography (CT) images at the third lumbar vertebra (L3) level. Hand-grip strength and 6-meters gait speed were measured before surgery. Results A total of 356 patients with cancer cachexia were included in the present study, in which 269 (75.56%) were identified as having malnutrition based on the GLIM criteria. GLIM-defined malnutrition alone did not show significant association with short-term postoperative outcomes, including complications, costs or length of postoperative hospital stays. The combination of low hand-grip strength or low gait speed with GLIM-defined malnutrition led to a significant predictive value for these outcomes. Moreover, low hand-grip strength plus GLIM-defined malnutrition was independently associated with postoperative complications (OR 1.912, 95% CI 1.151–3.178, P = 0.012). GLIM-defined malnutrition was an independent predictive factor for worse OS (HR 2.310, 95% CI 1.421–3.754, P = 0.001) and DFS (HR 1.815, 95% CI 1.186–2.779, P = 0.006) after surgery. The addition of low hand-grip strength or low gait speed to GLIM-defined malnutrition did not increase its predictive value for survival. Conclusion GLIM-defined malnutrition predicted worse long-term survival in gastric cancer patients with cachexia. Gait speed and hand-grip strength added prognostic value to GLIM-defined malnutrition for the prediction of short-term postoperative outcomes, which could be incorporated into preoperative assessment protocols in patients with cancer cachexia.

Abstract Background Systemic inflammatory factors can predict the survival prognosis of gastric cancer (GC) patients after neoadjuvant chemotherapy (NACT). However, whether longitudinal changes in systemic inflammatory factors are associated with short - and long-term outcomes has not been reported. Methods This study is a retrospective analysis of 216 patients with advanced gastric cancer who received NACT between January 2011 and June 2019, comparing receiver operating characteristic (ROC) curves for screening suitable inflammatory markers. Group-based trajectory modeling (GBTM) was used to analyze longitudinal changes in inflammatory markers during NACT to identify different potential subgroups and to compare postoperative complications, recurrence-free survival (RFS), and overall survival (OS) among subgroups. Results Ultimately, neutrophil-lymphocyte ratio (NLR) had the highest area under the curve (AUC) value in predicting prognosis was included in the GBTM analysis. Three trajectories of NLR were obtained: Stable group (SG) (n = 89), Ascent-descend group (ADG) (n = 80) and Continuous descend group (CDG) (n = 47). Compared with SG, ADG and CDG are associated with an increased risk of postoperative recurrence and death. The median time of RFS and OS of SG was longer than that of ADG and CDG (median RFS 81 vs. 44 and 22 months; median OS 69 vs. 41 and 30 months). In addition, CDG had significantly higher postoperative serious complications than SG and ADG (17 (36.2%) vs. 17 (19.1%) and 12 (15.0%); p = 0.005). Conclusion There were different trajectories of NLR during NACT, and these potential trajectories were significantly associated with severe postoperative complications, recurrence, and mortality in patients with GC.

Abstract Background Immune checkpoint inhibitors (ICIs) are commonly used in conjunction with chemotherapy to improve treatment outcomes for patients with gastric cancer. Since AFP could influence immunity by both inhibiting natural killer (NK) cells and regulating negatively the function of dendritic cells, we evaluated the influence of baseline serum alpha-fetoprotein (AFP) levels on the curative effect of ICIs in advanced gastric cancer (AGC) patients. Methods A retrospective analysis was conducted on 158 AGC patients who underwent ICI treatment. The patients were divided into high and low groups based on the AFP threshold of 20 ng/ml. The efficacy of ICI treatment was assessed using objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS). Results The higher levels of baseline AFP were found to be associated with a decrease in the effectiveness of ICIs, as evidenced by a DCR of 50.0% in the group with high AFP levels compared to 87.7% in the group with low AFP levels (P

BackgroundStudies from Asia indicate that normothermic intraperitoneal chemotherapy (NIPEC) may confer survival benefit in patients with gastric peritoneal carcinomatosis (PC). However, data regarding this approach is lacking in western population. The current STOPGAP trial is intended to assess 1-year progression-free survival benefit of sequential systemic chemotherapy and paclitaxel NIPEC in patients with gastric/ gastroesophageal junction (GEJ) adenocarcinoma PC.MethodsThis is a prospective, single center, single arm, phase II investigator-initiated clinical trial. Patients with histologically proven gastric/GEJ (Siewert 3) adenocarcinoma with positive peritoneal cytology or PC will be eligible to participate after three months of standard of care systemic chemotherapy and with no evidence of visceral metastasis on restaging scans. The primary treatment is iterative paclitaxel NIPEC with systemic paclitaxel and 5-fluorouracil, which will be administered on days1 and 8 and repeated every three weeks for 4 cycles. Patients will undergo diagnostic laparoscopy both before and after NIPEC to assess peritoneal cancer index (PCI). Patients with PCI less than or equal to 10 in whom complete cytoreduction (CRS) is feasible may opt to undergo CRS with heated intraperitoneal chemotherapy (HIPEC). The primary endpoint is 1-year progression free survival and secondary endpoints are overall survival and patient reported quality of life outcomes measured by EuroQol- 5 dimensions-5 level (EuroQol-5D-5L) questionnaire.DiscussionIf the sequential approach of systemic chemotherapy followed by paclitaxel NIPEC proves beneficial, then this approach could be used in larger, muti-institutional randomized clinical trial of gastric PC.Trial registrationThe trial was registered on 21/02/2021, under clinical trials.gov; Identifier: NCT04762953.

Background: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. Methods: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. Results: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629–0.950 in the TCGA dataset and 0.736–0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. Conclusions: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). Methods: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). Results: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. Conclusion: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to explore the correlation between biomarkers of lipid metabolism and gastric cancer. Methods: 1120 gastric cancer patients and 1134 health examiners enrolled in this study. The clinic data and serum lipid level, including Total cholesterol (TC), Triglyceride (TG), Low-density lipoprotein cholesterol (LDL-C) and High-density lipoprotein cholesterol (HDL-C), were collected. Results: Serum TG and LDL-C levels in patients with gastric cancer were higher than those in the control group. HDL-C levels were lower than the control group (P < 0.05). HDL-C and LDL-C were significantly correlated with the risk of gastric cancer. Concentrating on clinicopathological features, increased TG was more frequently in male patients with distal gastric cancer, N0 stage and early TNM stage. Increased TC was more frequently in early T, N and TNM stage. Decreased HDL-C was more common in distal location and low-undifferentiated gastric cancer. LDL-C elevation was more common in distal gastric cancer and early T stage. Conclusions: The serum lipid level of gastric cancer patients was higher than healthy controls. HDL-C and LDL-C abnormal correlated with gastric cancer risk. However, as the progresses of gastric cancer, poor patient intake, increased tumor consumption, and continuous declining in nutritional status, the levels of TC and TG gradually decreased in advanced gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Accurate microsatellite instability (MSI) testing is essential for identifying gastric cancer (GC) patients eligible for immunotherapy. We aimed to develop and validate a CT-based radiomics signature to predict MSI and immunotherapy outcomes in GC. Methods: This retrospective multicohort study included a total of 457 GC patients from two independent medical centers in China and The Cancer Imaging Archive (TCIA) databases. The primary cohort (n = 201, center 1, 2017–2022), was used for signature development via Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis. Two independent immunotherapy cohorts, one from center 1 (n = 184, 2018–2021) and another from center 2 (n = 43, 2020–2021), were utilized to assess the signature's association with immunotherapy response and survival. Diagnostic efficiency was evaluated using the area under the receiver operating characteristic curve (AUC), and survival outcomes were analyzed via the Kaplan-Meier method. The TCIA cohort (n = 29) was included to evaluate the immune infiltration landscape of the radiomics signature subgroups using both CT images and mRNA sequencing data. Results: Nine radiomics features were identified for signature development, exhibiting excellent discriminative performance in both the training (AUC: 0.851, 95%CI: 0.782, 0.919) and validation cohorts (AUC: 0.816, 95%CI: 0.706, 0.926). The radscore, calculated using the signature, demonstrated strong predictive abilities for objective response in immunotherapy cohorts (AUC: 0.734, 95%CI: 0.662, 0.806; AUC: 0.724, 95%CI: 0.572, 0.877). Additionally, the radscore showed a significant association with PFS and OS, with GC patients with a low radscore experiencing a significant survival benefit from immunotherapy. Immune infiltration analysis revealed significantly higher levels of CD8 + T cells, activated CD4 + B cells, and TNFRSF18 expression in the low radscore group, while the high radscore group exhibited higher levels of T cells regulatory and HHLA2 expression. Conclusion: This study developed a robust radiomics signature with the potential to serve as a non-invasive biomarker for GC's MSI status and immunotherapy response, demonstrating notable links to post-immunotherapy PFS and OS. Additionally, distinct immune profiles were observed between low and high radscore groups, highlighting their potential clinical implications. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors (ICIs) are commonly used in conjunction with chemotherapy to improve treatment outcomes for patients with gastric cancer. Since AFP could influence immunity by both inhibiting natural killer (NK) cells and regulating negatively the function of dendritic cells, we evaluated the influence of baseline serum alpha-fetoprotein (AFP) levels on the curative effect of ICIs in advanced gastric cancer (AGC) patients. Methods: A retrospective analysis was conducted on 158 AGC patients who underwent ICI treatment. The patients were divided into high and low groups based on the AFP threshold of 20 ng/ml. The efficacy of ICI treatment was assessed using objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS). Results: The higher levels of baseline AFP were found to be associated with a decrease in the effectiveness of ICIs, as evidenced by a DCR of 50.0% in the group with high AFP levels compared to 87.7% in the group with low AFP levels (P < 0.001). Further analysis using Kaplan-Meier survival techniques indicated that a high AFP level was linked to shorter progression-free survival (PFS) (P < 0.001) and overall survival (OS) (P = 0.001) in AGC individuals receiving ICIs. After propensity score matching, a log rank test revealed that the high AFP group had a decrease in median PFS (P = 0.011) and median OS (P = 0.036) compared to the low AFP group. The high AFP levels also showed its association with shorter PFS and OS in the subgroup analysis of ICI plus chemotherapy patients. Conclusions: Baseline AFP levels may predict immune checkpoint inhibitor treatment efficacy in AGC patients. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitor (ICI) or irinotecan-based chemotherapy is frequently used after failure of second-line paclitaxel plus ramucirumab treatment for patients with locally advanced unresectable or metastatic advanced gastric cancer (AGC). This study aimed to compare the efficacy between ICI and irinotecan-based chemotherapy as third-line treatment in patients with AGC. Methods: We retrospectively reviewed patients with AGC, whose third-line treatment started between July 2019 and June 2021 at 17 institutions in Korea. The ICI group included patients who received nivolumab or pembrolizumab, and the irinotecan-based chemotherapy group included patients who received irinotecan or FOLFIRI (5-fluorouracil, leucovorin and irinotecan). Results: A total of 363 patients [n = 129 (ICI) and n = 234 (irinotecan-based chemotherapy)] were analyzed. The median progression-free survival was 2.3 and 2.9 months in ICI and irinotecan-based chemotherapy groups, respectively (p = 0.802). The median overall survival (OS) was 5.5 and 6.0 months in ICI and irinotecan-based chemotherapy groups, respectively (p = 0.786). For all patients included in this study, multivariable analysis showed that weight loss, peritoneal metastasis, low serum sodium or albumin, and short duration of second-line treatment were associated with inferior OS (p < 0.05). ICI showed significantly longer OS than irinotecan-based chemotherapy in patients without peritoneal metastasis. Whereas ICI showed significantly shorter OS in patients without PD-L1 expression than irinotecan-based chemotherapy. Conclusions: No significant difference in survival outcome was observed between ICI and irinotecan-based chemotherapy as third-line treatment for AGC patients. ICI might be preferred for patients without peritoneal metastasis and irinotecan-based chemotherapy for patients with tumors without PD-L1 expression. Trial registration: This study was registered in the Clinical Trial Registry of Korea (https://cris.nih.go.kr: KCT 0007732). [ABSTRACT FROM AUTHOR]

Background: Cancer cachexia is associated with impaired functional and nutritional status and worse clinical outcomes. Global Leadership Initiative in Malnutrition (GLIM) consensus recommended the application of GLIM criteria to diagnose malnutrition in patients with cachexia. However, few previous study has applied the GLIM criteria in patients with cancer cachexia. Methods: From July 2014 to May 2019, patients who were diagnosed with cancer cachexia and underwent radical gastrectomy for gastric cancer were included in this study. Malnutrition was diagnosed using the GLIM criteria. Skeletal muscle index was measured using abdominal computed tomography (CT) images at the third lumbar vertebra (L3) level. Hand-grip strength and 6-meters gait speed were measured before surgery. Results: A total of 356 patients with cancer cachexia were included in the present study, in which 269 (75.56%) were identified as having malnutrition based on the GLIM criteria. GLIM-defined malnutrition alone did not show significant association with short-term postoperative outcomes, including complications, costs or length of postoperative hospital stays. The combination of low hand-grip strength or low gait speed with GLIM-defined malnutrition led to a significant predictive value for these outcomes. Moreover, low hand-grip strength plus GLIM-defined malnutrition was independently associated with postoperative complications (OR 1.912, 95% CI 1.151–3.178, P = 0.012). GLIM-defined malnutrition was an independent predictive factor for worse OS (HR 2.310, 95% CI 1.421–3.754, P = 0.001) and DFS (HR 1.815, 95% CI 1.186–2.779, P = 0.006) after surgery. The addition of low hand-grip strength or low gait speed to GLIM-defined malnutrition did not increase its predictive value for survival. Conclusion: GLIM-defined malnutrition predicted worse long-term survival in gastric cancer patients with cachexia. Gait speed and hand-grip strength added prognostic value to GLIM-defined malnutrition for the prediction of short-term postoperative outcomes, which could be incorporated into preoperative assessment protocols in patients with cancer cachexia. [ABSTRACT FROM AUTHOR]