Utilizing machine learning to integrate single-cell and bulk RNA sequencing data for constructing and validating a novel cell adhesion molecules related prognostic model in gastric cancer.

BACKGROUND: Cell adhesion molecules (CAMs) play a vital role in cell-cell interactions, immune response modulation, and tumor cell migration. However, the unique role of CAMs in gastric cancer (GC) remains largely unexplored. METHODS: This study characterized the genetic alterations and mRNA expression of CAMs. The role of CD34, a representative molecule, was validated in 375 GC tissues. The activity of the CAM pathway was further tested using single-cell and bulk characterization. Next, data from 839 patients with GC from three cohorts was analyzed using univariate Cox and random survival forest methods to develop and validate a CAM-related prognostic model. RESULTS: Most CAM-related genes exhibited multi-omics alterations and were associated with clinical outcomes. There was a strong correlation between increased CD34 expression and advanced clinical staging (P = 0.026), extensive vascular infiltration (P = 0.003), and unfavorable prognosis (Log-rank P = 0.022). CD34 expression was also found to be associated with postoperative chemotherapy and tumor immunotherapy response. Furthermore, the CAM pathway was significantly activated and mediated poor prognosis. Additionally, eight prognostic signature genes (PSGs) were identified in the training cohort. There was a substantial upregulation of the expression of immune checkpoints and a pronounced infiltration of immune cells in GC tissues with high PSG score, which is consistent with the prediction of increased sensitivity to immunotherapy. Moreover, 9 compounds from the CTRPv2 database and 13 from the Profiling Relative Inhibition Simultaneously in Mixture (PRISM) database were identified as potential therapeutic drugs for patients with GC with high PSG score. CONCLUSION: Thorough understanding of CAM pathways regulation and the innovative PSG score model hold significant implications for medical diagnosis, potentially enhancing personalized treatment strategies and improving patient outcomes in GC management.

Development and validation of a machine learning-based 18F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival.

BACKGROUND: Survival prognosis of patients with gastric cancer (GC) often influences physicians' choice of their follow-up treatment. This study aimed to develop a positron emission tomography (PET)-based radiomics model combined with clinical tumor-node-metastasis (TNM) staging to predict overall survival (OS) in patients with GC. METHODS: We reviewed the clinical information of a total of 327 patients with pathological confirmation of GC undergoing 18 F-fluorodeoxyglucose (18 F-FDG) PET scans. The patients were randomly classified into training (n = 229) and validation (n = 98) cohorts. We extracted 171 PET radiomics features from the PET images and determined the PET radiomics scores (RS) using the least absolute shrinkage and selection operator (LASSO) and random survival forest (RSF). A radiomics model, including PET RS and clinical TNM staging, was constructed to predict the OS of patients with GC. This model was evaluated for discrimination, calibration, and clinical usefulness. RESULTS: On multivariate COX regression analysis, the difference between age, carcinoembryonic antigen (CEA), clinical TNM, and PET RS in GC patients was statistically significant (p < 0.05). A radiomics model was developed based on the results of COX regression. The model had the Harrell's concordance index (C-index) of 0.817 in the training cohort and 0.707 in the validation cohort and performed better than a single clinical model and a model with clinical features combined with clinical TNM staging. Further analyses showed higher PET RS in patients who were older (p < 0.001) and those who had elevated CEA (p < 0.001) and higher clinical TNM (p < 0.001). At different clinical TNM stages, a higher PET RS was associated with a worse survival prognosis. CONCLUSIONS: Radiomics models based on PET RS, clinical TNM, and clinical features may provide new tools for predicting OS in patients with GC.

Comprehensive analysis of the prognosis, tumor microenvironment, and immunotherapy response of SDHs in colon adenocarcinoma.

Background: Succinate dehydrogenase (SDH), one of the key enzymes in the tricarboxylic acid cycle, is mainly found in the mitochondria. SDH consists of four subunits encoding SDHA, SDHB, SDHC, and SDHD. The biological function of SDH is significantly related to cancer progression. Colorectal cancer (CRC) is one of the most common malignant tumors globally, whose most common histological subtype is colon adenocarcinoma (COAD). However, the correlation between SDH factors and COAD remains unclear. Methods: The data on pan-cancer was obtained from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier survival analysis showed the prognostic ability of SDHs. The cBioPortal database reflected genetic variations of SDHs. The correlation analysis was conducted between SDHs and mitochondrial energy metabolism genes (MMGs) and the protein-protein interaction (PPI) network was built. Consequently, Univariate and Multivariate Cox Regression Analysis on SDHs and other clinical characteristics were conducted. A nomogram was established. The ssGSEA analysis visualized the association between SDHs and immune infiltration. Immunophenoscore (IPS) explored the correlation between SDHs and immunotherapy, and the correlation between SDHs and targeted therapy was investigated through Genomics of Drug Sensitivity in Cancer. Finally, qPCR and immunohistochemistry detected SDHs' expression. Results: After assessing SDHs differential expression in pan-cancer, we found that SDHB, SDHC, and SDHD benefit COAD patients. The cBioPortal database demonstrated that SDHA was the top gene in mutation frequency rank. Correlation analysis mirrored a strong link between SDHs and MMGs. We formulated a nomogram and found that SDHB, SDHC, SDHD, and clinical characteristics correlated with COAD patients' survival. For T helper cells, Th2 cells, and Tem, SDHA, SDHB, SDHC, and SDHD were significantly enriched in the high expression group. Moreover, COAD patients with high SDHA expression were more suitable for immunotherapy. And COAD patients with different SDHs' expression have different sensitivity to targeted drugs. Further verifying the gene and protein expression levels of SDHs, we found that the tissues were consistent with the bioinformatics analysis. Conclusions: Our study analyzed the expression and prognostic value of SDHs in COAD, explored the pathway mechanisms involved, and the immune cell correlations, indicating that SDHs might be biomarkers for COAD patients.

HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution.

the automatic segmentation of lung infections in CT slices provides a rapid and effective strategy for diagnosing, treating, and assessing COVID-19 cases. However, the segmentation of the infected areas presents several difficulties, including high intraclass variability and interclass similarity among infected areas, as well as blurred edges and low contrast. Therefore, we propose HADCNet, a deep learning framework that segments lung infections based on a dual hybrid attention strategy. HADCNet uses an encoder hybrid attention module to integrate feature information at different scales across the peer hierarchy to refine the feature map. Furthermore, a decoder hybrid attention module uses an improved skip connection to embed the semantic information of higher-level features into lower-level features by integrating multi-scale contextual structures and assigning the spatial information of lower-level features to higher-level features, thereby capturing the contextual dependencies of lesion features across levels and refining the semantic structure, which reduces the semantic gap between feature maps at different levels and improves the model segmentation performance. We conducted fivefold cross-validations of our model on four publicly available datasets, with final mean Dice scores of 0.792, 0.796, 0.785, and 0.723. These results show that the proposed model outperforms popular state-of-the-art semantic segmentation methods and indicate its potential use in the diagnosis and treatment of COVID-19.

Serum creatinine/cystatin C ratio as a surrogate marker for sarcopenia in patients with gastric cancer.

BACKGROUND: Sarcopenia is an age-related syndrome that may have negative impact on surgical outcomes and long-term survival of patients with gastric cancer. Serum creatinine/cystatin C (Cr/CysC) ratio has attracted attention as a surrogate marker for sarcopenia but has not been adequately studied in patients with gastric cancer. The purpose of this study was to investigate the validity of serum Cr/CysC ratio as a predictor of sarcopenia, evaluate a statistical cut-off value, and assess the relationship between Cr/CysC ratio and prognosis of patients with gastric cancer. METHODS: We retrospectively studied 327 patients who underwent surgery for gastric cancer from June 2009 to October 2021. The skeletal muscle mass index was calculated using computed tomography (CT). We determined the relevance of serum Cr/CysC ratio as a surrogate maker for sarcopenia by comparing it with various biomarkers. The Concordance index (C-index) was calculted to measure whether the Cr/CysC ratio can prognosis of patients with gastric cancer. RESULTS: Serum Cr/CysC was significantly correlated with with Skeletal Muscle Index (SMI) (r = 0.221, p < 0.001) and Skeletal Muscle Area (SMA) (r = 0.258, p < 0.001). The area under the curve for sarcopenia was significantly larger for serum Cr/CysC ratio than for other biomarkers (Cr/CysC: 0.644, CysC: 0.535, Cr: 0.556). Patients in the high-Cr/CysC group have longer survival time than that in low-Cr/CysC group, defined by the cutoff value 0.67. The C-index of both Cr/CysC ratio and SMI with OS was 0.63. CONCLUSIONS: Serum Cr/CysC ratio can be used accurately, inexpensively, and easily to evaluate sarcopenia in male patients with gastric cancer. Our study shows that patients with Cr/CysC below 0.67 had possibility of sarcopenia and would be poor prognosis.

NSUN2 modified by SUMO-2/3 promotes gastric cancer progression and regulates mRNA m5C methylation.

The 5-methylcytosine (m5C) RNA methyltransferase NSUN2 is involved in the regulation of cell proliferation and metastasis formation and is upregulated in multiple cancers. However, the biological significance of NSUN2 in gastric cancer (GC) and the modification of NSUN2 itself have not been fully investigated. Here, we analyzed the expression level of NSUN2 in tissue microarrays containing 403 GC tissues by immunohistochemistry. NSUN2 was upregulated in GC, and that it was a predictor of poor prognosis. NSUN2 promotes the proliferation, migration, and invasion of GC cells in vitro. We also demonstrated that small ubiquitin-like modifier (SUMO)-2/3 interacts directly with NSUN2 by stabilizing it and mediating its nuclear transport. This facilitates the carcinogenic activity of NSUN2. Furthermore, m5C bisulfite sequencing (Bis-seq) in NSUN2-deficient GC cells showed that m5C-methylated genes are involved in multiple cancer-related signaling pathways. PIK3R1 and PCYT1A may be the target genes that participate in GC progression. Our findings revealed a novel mechanism by which NSUN2 functions in GC progression. This may provide new treatment options for GC patients.

Establishment of the Radiologic Tumor Invasion Index Based on Radiomics Splenic Features and Clinical Factors to Predict Serous Invasion of Gastric Cancer.

BACKGROUND: Currently, there are shortcomings in diagnosing gastric cancer with or without serous invasion, making it difficult for patients to receive appropriate treatment. Therefore, we aimed to develop a radiomic nomogram for preoperative identification of serosal invasion. METHODS: We selected 315 patients with gastric cancer, confirmed by pathology, and randomly divided them into two groups: the training group (189 patients) and the verification group (126 patients). We obtained patient splenic imaging data for the training group. A p-value of <0.05 was considered significant for features that were selected for lasso regression. Eight features were chosen to construct a serous invasion prediction model. Patients were divided into high- and low-risk groups according to the radiologic tumor invasion risk score. Subsequently, univariate and multivariate regression analyses were performed with other invasion-related factors to establish a visual combined prediction model. RESULTS: The diagnostic accuracy of the radiologic tumor invasion score was consistent in the training and verification groups (p<0.001 and p=0.009, respectively). Univariate and multivariate analyses of invasion risk factors revealed that the radiologic tumor invasion index (p=0.002), preoperative hemoglobin <100 (p=0.042), and the platelet and lymphocyte ratio <92.8 (p=0.031) were independent risk factors for serosal invasion in the training cohort. The prediction model based on the three indexes accurately predicted the serosal invasion risk with an area under the curve of 0.884 in the training cohort and 0.837 in the testing cohort. CONCLUSIONS: Radiological tumor invasion index based on splenic imaging combined with other factors accurately predicts serosal invasion of gastric cancer, increases diagnostic precision for the most effective treatment, and is time-efficient.

Preoperative Albumin-Bilirubin Grade as a Prognostic Predictor in Colorectal Cancer Patients Who Undergo Radical Resection.

PURPOSE: The relationship between liver function and colorectal cancer without liver metastases has not been explored. Therefore, we investigated whether the preoperative albumin-bilirubin grade could predict the prognosis of patients with colorectal cancer (CRC) undergoing radical resection, and we designed a quantifiable predictive model. PATIENTS AND METHODS: We retrospectively analyzed data from 284 patients with CRC who underwent radical resection in the Second Affiliated Hospital of the Wenzhou Medical University between January 2011 and January 2016. Patients were divided in two groups according to the calculated cut-off: the high albumin-bilirubin (>-2.48) grade and low albumin-bilirubin (≤-2.48) grade group. Kaplan-Meier curves were constructed to compare the overall survival (OS) between the two groups. Univariate and multivariate analyses were performed to identify the independent risk factors for postoperative complications and OS. RESULTS: Patients with a high albumin-bilirubin grade (n = 165, 58.1%) had a higher rate of postoperative complications (38.2% versus 17.6%, P < 0.001), especially medical (19.4% versus 6.7%, P = 0.002) and severe complications (1.7% versus 7.3%, P = 0.032). They also had a shorter OS (mean survival time, 47.6 versus 54.3 months, P = 0.005), especially patients with tumor-node-metastasis stage III (42.7 months versus 51.6 months, P = 0.036). Age ≥ 70 years (odds ratio [OR] = 2.22, P = 0.003) and high albumin-bilirubin grade (OR = 2.71, P = 0.001) were independent risk factors for postoperative complications, while age ≥ 70 years (hazard ratio [HR] = 2.65, P < 0.001), high albumin-bilirubin grade (HR = 1.81, P = 0.033), tumor-node-metastasis stage II (HR = 13.83, P = 0.010) and III (HR = 23.66, P = 0.002) were independent risk factors of OS. CONCLUSION: Preoperative albumin-bilirubin grade could predict postoperative complications (especially medical and severe complications) and OS in patients with CRC, especially in those with tumor-node-metastasis stage III.

Efficacy of the Preoperative Albumin-Bilirubin Grade for Predicting Survival and Outcomes of Postoperative Chemotherapy for Advanced Gastric Cancer.

PURPOSE: The liver function index can predict the prognosis of hepatocellular carcinoma and many other non-neoplastic diseases. We aimed to determine whether the preoperative albumin-bilirubin (ALBI) grade could predict the prognosis of patients with gastric cancer (GC). PATIENTS AND METHODS: Data of 243 patients with GC who underwent radical resection were collected retrospectively. Patients were divided into the high ALBI (>-2.34) and low ALBI (≤-2.34) grade groups. Overall survival was analyzed between the two groups using the Kaplan-Meier curves. Univariate and multivariate analyses identified the independent factors associated with postoperative complications and overall survival. RESULTS: The postoperative complication rates were higher in the high ALBI grade group than in the low ALBI grade group (P=0.005). The high ALBI grade group also had worse overall survival (P<0.001), especially TNM stage II-III patients (stage II, P=0.043; stage III, P<0.001). In the high ALBI grade group, patients with TNM stage III not undergoing chemotherapy had significantly worse survival times (P=0.001). High ALBI grade (P=0.032), Charlson score of 1-2 (P=0.007), and laparotomy surgery (P=0.045) were independent risk factors for postoperative complications. High ALBI grade (P=0.005), age ≥70 years (P=0.002), nutritional risk screening score 2002 score of 5-6 (P=0.019), tumor located in the cardia (P=0.020), diffuse tumor (P<0.001), and TNM stage III (P<0.001) were independent risk factors for overall survival. CONCLUSION: Preoperative ALBI grade could predict postoperative complications and overall survival of patients with GC, especially those with TNM stages II-III. This grading method has the advantages of preoperative availability, simplicity, and objectivity and aids in improving preoperative prognosis prediction and in achieving better outcomes of postoperative chemotherapy.

Use of radiomics to extract splenic features to predict prognosis of patients with gastric cancer.

INTRODUCTION: Radiomics allows for mining of imaging data to examine tissue characteristics non-invasively, which can be used to predict the prognosis of a patient. This study explored the use of imaging techniques to evaluate splenic tissue characteristics to predict the prognosis of patients with gastric cancer. MATERIALS AND METHODS: Computed tomography images from patients with gastric cancer were collected retrospectively. Splenic image characteristics, extracted with pyradiomics, of patients in the training group were randomly divided. Characteristics with a P value < 0.1 were selected for lasso regression to construct a survival risk model. Models for high-and low-risk groups were established. Patients were divided into the high- and low-risk groups for univariate and multivariate regression analysis of survival-related factors, and a visual prognostic prediction model was established. RESULTS: The splenic characteristic prognostic model was consistent in the training and verification groups (p < 0.001 and p = 0.016, respectively). The two groups that displayed different splenic characteristics showed no statistical difference in other basic data except the tumour-node-metastasis (pTNM) stage (p = 0.007). Univariate and multivariate analysis of survival risk factors showed that splenic characteristics (p = 0.042), age (p < 0.001), tumor location (p = 0.002), and pTNM stage (p < 0.001) were independent risk factors for survival. The prognostic prediction model combined with splenic characteristics significantly improved the accuracy of prognosis, predicting one-and three-year survival rates. CONCLUSION: Splenic features extracted from imaging technology can accurately predict the long-term survival of patients with gastric cancer. Splenic characteristic grouping can effectively improve the accuracy of survival prediction and gastric cancer prognosis.

MiR-539 functions as a tumor suppressor in pancreatic cancer by targeting TWIST1.

The dysregulation of microRNA (miRNA) expression has been highlighted in a variety of human malignant conditions with reports implicating a critical role in the process of tumor growth. The role of miR-539 in pancreatic cancer (PC) is yet to be fully elucidated, hence the aim of the current study was to investigate the effect of miR-539 expression in relation to a cohort of 52 PC specimens. The application of a real-time quantitative polymerase chain reaction (qRT-PCR) revealed a significantly down-regulated miR-539 level, which was accompanied by an increased TWIST1 expression in PC when compared with the controls. The in vitro experiment results demonstrated that the endogenic mimic of miR-539 significantly suppressed the growth of the xenograft tumors in PANC-1 cells, when compared to the delivery of the control miRNA and blank control. Meanwhile, the key epithelial-mesenchymal transition (EMT) inducer, TWIST1 was verified as a direct target gene of miR-539 through the application of a luciferase reporter assay. In conclusion, the results of the current study present evidence emphasizing the significance of the interactions between miR-539 and TWIST1 in the development of and progression of PC, highlighting its potential as a therapeutic target in the treatment of PC patients.

Long noncoding RNA X-inactive specific transcript promotes malignant melanoma progression and oxaliplatin resistance.

Long noncoding RNA X-inactive specific transcript (XIST) was confirmed to participate in the development of many cancers. However, the function of XIST in malignant melanoma (MM) remained largely unknown. In the current study, we found that the XIST expression level was upregulated in MM tissues and cell lines. In addition, the growth rate of MM cells transfected with silencing XIST was significantly decreased compared with that with silencing normal control. XIST knockdown inhibited proliferation and migration in MM cells and increased the oxaliplatin sensitivity of oxaliplatin-resistant MM cells. Bioinformatics analysis showed that XIST acts as a molecular sponge for miR-21 and miR-21 directly targets with 3'-UTR of PI3KR1. Furthermore, XIST knockdown inhibited PI3KRI and AKT expression, and promoted Bcl-2 and Bax expression. In short, the current study showed that XIST was a crucial regulator in progression and oxaliplatin resistance of MM, providing a novel insight into the pathogenesis and underlying therapeutic target for MM.

The effects of novel chitosan-targeted gemcitabine nanomedicine mediating cisplatin on epithelial mesenchymal transition, invasion and metastasis of pancreatic cancer cells.

OBJECTIVE: The study aimed to evaluate the effects involved with the novel chitosan gemcitabine (Gem) nanoparticles mediating cisplatin (DDP) on epithelial mesenchymal transition (EMT), invasion and metastasis of pancreatic cancer (PC) cells. METHODS: A total of 62 healthy purebred BALB/C of specific-pathogen free (SPF) female nude mice were recruited and a SW1990 cell line was subsequently cultured. A heterotopic xenograft tumor model was constructed. After determining the optimal drug concentration, the nude mice were assigned into the control, glycol chitosan (GC)-Gem microsphere, antibody Complex (Abc)-GC-Gem and Abc-GC-Gem microsphere+DDP groups (n=8 in each group). The tumor morphology of the nude mice was observed and HE staining was used to observe the pathological changes of the respective tissues. TUNEL staining was performed to detect cell apoptosis, while immunohistochemistry was employed for analysis of the positive expression rate of EGFR and the number of microvessel density (MVD). Both RT-qPCR and Western blotting were utilized for mRNA and protein expressions of VEGF, EGFR, Bcl-2, Bax, Survivin, Bak, E-cadherin and Vimentin analysis. RESULTS: The optimal drug concentration of Gem was determined to be 120mg/m2. In comparison to the control group, tumor size, weight, positive expression rate of EGFR and tumor MVD, as well as mRNA and protein expressions of Bax and E-cadherin decreased, while the inhibition rate (IR) and apoptosis index (AI), expression of VEGF, EGFR, Bcl-2, Survivin, Bak and Vimentin increased in the GC-Gem microsphere, Abc-GC-Gem microsphere and Abc-GC-Gem microsphere+DDP groups. Compared with the GC-Gem microsphere group, Abc-GC-Gem and Abc-GC-Gem microsphere+DDP groups had decreases concerning tumor size and weight, positive rate of protein expression of EGFR and tumor MVD, as well as the expression of Bax and E-cadherin, and enhances on IR and AI, expression of VEGF, EGFR, Bcl-2, Survivin, Bak, and Vimentin, which were the most obvious in the Abc-GC-Gem+DDP group (P<0.05). CONCLUSION: Novel Gem nanoparticles aid in mediating DDP to inhibit PC cell invasion and migriation, promote PC cell apoptosis and enhance the efficacy of chemotherapy. Our findings demonstrated that Gem administered in combination with DDP was more effective than Gem alone.

Effects of microRNA-183 on epithelial-mesenchymal transition, proliferation, migration, invasion and apoptosis in human pancreatic cancer SW1900 cells by targeting MTA1.

OBJECTIVE: This study aims to explore effects of miR-183 on epithelial-mesenchymal transition (EMT) and invasion by targeting MTA1 in human pancreatic cancer (PC) cells. METHODS: Totally, 108 PC patients admitted in Wenzhou Central Hospital and Wenzhou People's Hospital, The Dingli Clinical Institute of Wenzhou Medical University from March 2010 to March 2014 were enrolled. qRT-PCR and immunohistochemistry were applied to examine expression of MTA1 mRNA and protein. Samples were divided into 6 groups: blank, NC, miR-183 mimics, miR-183 inhibitors, MTA1-siRNA and miR-183 inhibitors +MTA1-siRNA groups. CCK8 method was employed for determining cell proliferation rate, flow cytometry for cell apoptosis rate, scratch test for cell migration and Transwell assay for cell invasion. qRT-PCR and Western blotting were used to determine expression of MTA1, E-cadherin and Vimentin mRNA and protein. RESULTS: Positive expression rate of MTA1 was upregulated in PC tissues, and expression of miR-183 and MTA1 was associated with differentiation, migration, tumor size, TNM. The miR-183 mimics and MTA1-siRNA groups showed a decrease in proliferation, migration and invasion, whereas increased apoptosis, in comparison with blank and NC groups, as expression of MTA1 and Vimentin mRNA and protein were reduced, expression of E-cadherin mRNA and protein was elevated. Compared to blank and NC groups, the miR-183 inhibitors group exhibited enhanced proliferation, migration and invasion and inhibited apoptosis; increased expressions of MTA1 and Vimentin mRNA and protein and decreased expressions of E-cadherin mRNA and protein. CONCLUSION: Our study supported that miR-183 could repress EMT and invasion of human PC cells through inhibition of MTA1 expression.

Down-regulation of ribosomal protein S15A mRNA with a short hairpin RNA inhibits human hepatic cancer cell growth in vitro.

Ribosomal protein s15a (RPS15A) is a highly conserved protein that promotes mRNA/ribosome interactions early in translation. Recent evidence showed that RPS15A could stimulate growth in yeast, plant and human lung carcinoma. Here we report that RPS15A knockdown could inhibit hepatic cancer cell growth in vitro. When transduced with shRPS15A-containing lentivirus, we observed inhibited cell proliferation and impaired colony formation in both HepG2 and Bel7404 cells. Furthermore, cell cycle analysis showed that HepG2 cells were arrested at the G0/G1 phase when transduced with Lv-shRPS15A. In conclusion, our findings provide for the first time the biological effects of RPS15A in hepatic cancer cell growth. RPS15A may play a prominent role in heptocarcinogenesis and serve as a potential therapeutic target in hepatocellular carcinoma.