Genetic prediction of the relationship between metabolic syndrome and colorectal cancer risk: a Mendelian randomization study.

BACKGROUND: Despite a growing body of observational studies indicating a potential link between metabolic syndrome and colorectal cancer, a definitive causal relationship has yet to be established. This study aimed to elucidate the causal relationship between metabolic syndrome and colorectal cancer through Mendelian randomization. METHODS: We screened for instrumental variables associated with metabolic syndrome and its diagnostic components and with colorectal cancer through the use of a genome-wide association study database, and conducted a preliminary Mendelian randomization analysis. To corroborate the dependability of our conclusions, an additional dataset was used for replication analysis in a Mendelian randomization method, which was further integrated with a meta-analysis. RESULTS: Preliminary analysis using the inverse variance weighted method revealed positive correlations between metabolic syndrome (OR [95% CI] = 1.37[1.15-1.63], P = 5.02 × 10-4) and waist circumference (OR [95% CI] = 1.39[1.21-1.61], P = 7.38 × 10-6) and the risk of colorectal cancer. Replication analysis also revealed the same results: metabolic syndrome (OR [95% CI] = 1.24[1.02-1.51], P = 0.030) and waist circumference (OR [95% CI] = 1.23[1.05-1.45], P = 0.013). The meta-analysis results further confirmed the associations between metabolic syndrome (OR [95% CI] = 1.31[1.15-1.49], P < 0.001) and waist circumference (OR [95% CI] = 1.32[1.18-1.47], P < 0.001) and colorectal cancer. CONCLUSION: Our study indicated that metabolic syndrome increases the risk of CRC, particularly in patients with abdominal obesity.

Global trends in indocyanine green fluorescence navigation in the field of gastric cancer: bibliometrics and knowledge atlas analysis.

Background: Indocyanine green (ICG) fluorescence navigation can enhance the visualization of gastric cancer (GC) lesions, increase the lymph node detection rate, and reduce the incidence of anastomotic leakage in the treatment of GC. It thus holds considerable potential for application in GC clinical surgery and has attracted widespread research interest. The purpose of this study was to visualize the current topics and emerging trends in research regarding ICG in GC. Methods: We searched the Web of Science Core Collection (WoSCC) for articles relevant to the use of ICG in GC. The resulting information was then analyzed from a bibliometric and knowledge graph analysis perspective using CiteSpace, Scimago Graphica, and R Studio so that the key trends and hot spots in research within this field could be identified and visualized. Results: Ultimately, 1,385 papers from 58 countries or regions published from 1991 to 2022 were included in this study. The largest number of publications were from China, followed by Japan and the United States. High-yield institutions were concentrated in Asian countries, especially China. The top publication contributors were Shanghai Jiao Tong University. Li Y and Bang YJ ranked first among the top 10 most productive authors and top 10 most cocited authors, respectively. World Journal of Gastroenterology was the most productive academic journal on ICG in GC, while Cancer Research was the most commonly cocited journal. The keyword "indocyanine green" was among the top 5 keywords, and will likely remain a popular topic in future research. Furthermore, the emerging themes including surgery, biopsy, lymphadenectomy, dissection, and gastrectomy have attracted increasing attention. Conclusions: Current research hotspots in this area focus on the clinical implementation of ICG in precision surgery for GC. Given the imaging tracer characteristics of ICG and its utility in GC surgery, the optimization and application of ICG-guided precision surgery techniques for GC will be a research hot spot going forward.

Development and validation of a CT radiomics and clinical feature model to predict omental metastases for locally advanced gastric cancer.

""We employed radiomics and clinical features to develop and validate a preoperative prediction model to estimate the omental metastases status of locally advanced gastric cancer (LAGC). A total of 460 patients (training cohort, n = 250; test cohort, n = 106; validation cohort, n = 104) with LAGC who were confirmed T3/T4 stage by postoperative pathology were continuously collected retrospectively, including clinical data and preoperative arterial phase computed tomography images (APCT). Dedicated radiomics prototype software was used to segment the lesions and extract features from the preoperative APCT images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the extracted radiomics features, and a radiomics score model was constructed. Finally, a prediction model of omental metastases status and a nomogram were constructed combining the radiomics scores and selected clinical features. An area under the curve (AUC) of the receiver operating characteristic curve (ROC) was used to validate the capability of the prediction model and nomogram in the training cohort. Calibration curves and decision curve analysis (DCA) were used to evaluate the prediction model and nomogram. The prediction model was internally validated by the test cohort. In addition, 104 patients from another hospital's clinical and imaging data were gathered for external validation. In the training cohort, the combined prediction (CP) model (AUC 0.871, 95% CI 0.798-0.945) of the radiomics scores combined with the clinical features, compared with clinical features prediction (CFP) model (AUC 0.795, 95% CI 0.710-0.879) and radiomics scores prediction (RSP) model (AUC 0.805, 95% CI 0.730-0.879), had the better predictive ability. The Hosmer-Lemeshow test of the CP model showed that the prediction model did not deviate from the perfect fitting (p = 0.893). In the DCA, the clinical net benefit of the CP model was higher than that of the CFP model and RSP model. In the test and validation cohorts, the AUC values of the CP model were 0.836 (95% CI 0.726-0.945) and 0.779 (95% CI 0.634-0.923), respectively. The preoperative APCT-based clinical-radiomics nomogram showed good performance in predicting omental metastases status in LAGC, which may contribute to clinical decision-making.

Immune-related adverse events associated with immune checkpoint inhibitors for advanced gastric and gastroesophageal junction cancer: A meta-analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have shown promising efficacy in treatment and clinical management of advanced gastric and gastroesophageal junction cancer. However, the inhibitors also cause immune-related adverse events (irAEs). The current systematic review and meta-analysis study aimed to investigate the incidence and nature of irAEs caused by ICIs. AIM: To investigate the incidence and nature of irAEs in advanced gastric and gastroesophageal junction cancer. METHODS: This systematic review was registered with PROSPERO (Reg. number: CRD42020152291). Data included in this study were collected from patients diagnosed with advanced gastric cancer or gastroesophageal junction cancer and treated with ICIs. A systematic literature search was conducted using the PubMed, EMBASE, and Cochrane Library databases. Meta-analysis was carried out using the single sample rate method. Synthesis and analysis of the data was conducted using Stata/SE and Review Manager Software. RESULTS: The patients enrolled in the present study included 14 patients from 14 case reports, 326 patients from 6 case series, and 1249 patients from 8 clinical trials. It was found that the overall incidence of irAEs was 16% [95% confidence interval (CI): 11-20] for all grades and 3% (95%CI: 2-4) for the severe grade. It was evident that the incidence of irAEs varied with the type of inhibitor and organs. A comparative study of the anti-programmed cell death receptor-1 (PD-1) and anti-programmed death receptor-ligand 1 (PD-L1) treatments showed that the anti-PD-1 group had a higher overall incidence of irAEs (20%) as compared with that of the anti-PD-L1 group (13%). Results of this study showed that the endocrine system experienced the highest incidence of organ-specific irAEs (7.4%), including hypothyroidism, hyperthyroidism, thyroiditis, diabetes, and adrenal insufficiency, followed by gastroenterology (2.2%), pulmonology (1.8%), neurology (1.4%), dermatology (1.4%), hematology (0.8%), and hepatology (0.7%). In clinical trials, it was found that the incidence of death related to irAEs was 1% (95%CI: 0-2.0), whereby colitis and interstitial lung diseases were the leading causes of death. CONCLUSION: It was evident that the incidence and nature of irAEs are both organ- and inhibitor-specific. The anti-PD-1 group had the highest incidence of all irAEs grades including the severe grades of irAEs. Early identification and management of irAEs allows clinical oncologists to effectively consider the pros and cons and hence enables them to strike a balance.

Overexpression of SATB1 correlates with epithelial-mesenchymal transition and lymphatic metastasis in gastric cancer.

BACKGROUND: Gastric cancer (GC) is a malignant tumor with a high mortality rate, and lymphatic metastasis is the main mode of GC metastasis. The nuclear transcriptional regulatory protein SATB1 has been confirmed to be closely related to GC metastasis, but the mechanism has not been elucidated. METHODS: Epithelial-mesenchymal transition (EMT) is known as the pivotal process of GC metastasis. To evaluate the relationship between SATB1 and EMT in GC metastasis, the immunohistochemical method was used to detect the expression of SATB1, E-cadherin, N-cadherin, Vimentin protein in 52 paraffin-embedded specimens of gastric cancer, and analyze the relationship between their expression and pathological parameters. RESULTS: Abnormal positive expression of SATB1 protein in paraffin-embedded tumor tissues was positively correlated with local invasion, lymph node metastasis, and TNM staging in gastric cancer. There was a statistically significant difference in the expression of SATB1 between the early stage of gastric cancer (stage I) and the advanced stage (stageII, III, IV). Moreover, SATB1 expression was positively correlated to N-cadherin and Vimentin but negatively to E-cadherin from Stages I to IV. CONCLUSION: The GC patients with overexpression of SATB1 tended to have advanced stage and lymph node metastasis. SATB1 was positively correlated with EMT in Gastric Cancer.

Deep learning model for diagnosing early gastric cancer using preoperative computed tomography images.

Background: Early gastric cancer (EGC) is defined as a lesion restricted to the mucosa or submucosa, independent of size or evidence of regional lymph node metastases. Although computed tomography (CT) is the main technique for determining the stage of gastric cancer (GC), the accuracy of CT for determining tumor invasion of EGC was still unsatisfactory by radiologists. In this research, we attempted to construct an AI model to discriminate EGC in portal venous phase CT images. Methods: We retrospectively collected 658 GC patients from the first affiliated hospital of Nanchang university, and divided them into training and internal validation cohorts with a ratio of 8:2. As the external validation cohort, 93 GC patients were recruited from the second affiliated hospital of Soochow university. We developed several prediction models based on various convolutional neural networks, and compared their predictive performance. Results: The deep learning model based on the ResNet101 neural network represented sufficient discrimination of EGC. In two validation cohorts, the areas under the curves (AUCs) for the receiver operating characteristic (ROC) curves were 0.993 (95% CI: 0.984-1.000) and 0.968 (95% CI: 0.935-1.000), respectively, and the accuracy was 0.946 and 0.914. Additionally, the deep learning model can also differentiate between mucosa and submucosa tumors of EGC. Conclusions: These results suggested that deep learning classifiers have the potential to be used as a screening tool for EGC, which is crucial in the individualized treatment of EGC patients.

Hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta gene as a tumour suppressor in stomach adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) is the most common type of gastric cancer. In this study, the functions and potential mechanisms of hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta (HADHB) in STAD were explored. Methods: Different bioinformatics analyses were performed to confirm HADHB expression in STAD. HADHB expression in STAD tissues and cells was also evaluated using western blot, qRT-PCR, and immunohistochemistry. Further, the viability, proliferation, colony formation, cell cycle determination, migration, and wound healing capacity were assessed, and the effects of HADHB on tumour growth, cell apoptosis, and proliferation in nude mice were determined. The upstream effector of HADHB was examined using bioinformatics analysis and dual luciferase reporter assay. GSEA was also employed for pathway enrichment analysis and the expression of Hippo-YAP pathway-related proteins was detected. Results: The expression of HADHB was found to be low in STAD tissues and cells. The upregulation of HADHB distinctly repressed the viability, proliferation, colony formation, cell cycle progression, migration, invasion, and wound healing of HGC27 cells, while knockdown of HADHB led to opposite effects. HADHB upregulation impeded tumour growth and cell proliferation, and enhanced apoptosis in nude mice. KLF4, whose expression was low in STAD, was identified as an upstream regulator of HADHB. KLF4 upregulation abolished the HADHB knockdown-induced tumour promoting effects in AGS cells. Further, HADHB regulates the Hippo-YAP pathway, which was validated using a pathway rescue assay. Low expression of KLF4 led to HADHB downregulation in STAD. Conclusion: HADHB might function as a tumour suppressor gene in STAD by regulation the Hippo-YAP pathway.

The m7G-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumour Immune Infiltration in Colon Cancer.

With high morbidity and mortality, colon cancer (CC) is considered as one of the most often diagnosed cancers around the world. M7G-related lncRNA may provide a regulatory function in the formation of CC, but the principle of regulation is still unclear. The purpose of this research was to establish a novel signature that may be used to predict survival and tumour immunity in CC patients. Data about CC in TCGA was collected for analysis, coexpression analysis and univariate Cox analysis were used to screen prognostic m7G-related lncRNAs. A consensus clustering analysis based on prognostic m7G-related lncRNAs was applied, and a prognosis model based on least absolute shrinkage and selection operator (LASSO) regression analysis was established. Independent prognostic analysis, nomogram, PCA, clinicopathological correlation analysis, TMB, survival analysis, immune correlation analysis, qRT-PCR and clinical therapeutic compound prediction were also applied. 90 prognostic m7G-related lncRNAs were found, GO and KEGG analysis showed that prognostic m7G-related lncRNAs were mainly related to cell transcription and translation. The results of the consensus clustering analysis revealed substantial disparities in survival prognosis and tumour immune infiltration between two clusters. We built a risk model with 21 signature m7G-related lncRNAs, patients in the high-risk group had a considerably poorer prognosis than those in the low-risk group. Independent prognostic analysis confirmed that patients' prognosis was linked to their tumour stage and risk score. PCA, subgroups with distinct clinicopathological characteristics were studied for survival, multi-index ROC curve, c-index curve, the survival analysis of TMB, and model comparison tested the reliability of risk model. A tumour immunoassay revealed a substantial difference in immune infiltration between high-risk and low-risk individuals. Five chemicals were eliminated, and qRT-PCR indicated that the four lncRNAs were expressed differently. Overall, m7G-related lncRNA is closely related to colon cancer and the 21 signature lncRNAs risk model can efficiently evaluate the prognosis of CC patients, which has a possible positive consequence for the future diagnosis and therapy of CC.

NOL12 as an Oncogenic Biomarker Promotes Hepatocellular Carcinoma Growth and Metastasis.

Hepatocellular carcinoma (HCC) is a common malignancy with a poor prognosis worldwide. However, the pathogenesis of HCC remains poorly understood. In this study, we found that NOL12 was significantly overexpressed in independent HCC datasets from TCGA database. We confirmed that the expression level of NOL12 was upregulated in human HCC tissues and cell lines by RT-qPCR. High expression of NOL12 is associated with worse reduced overall survival (OS), high pathological grade, node metastasis, and advanced clinical stage in patients with HCC. Moreover, knockdown of NOL12 dramatically inhibits the proliferation and metastasis of HCC cells in vitro and in vivo. CIBERSORTx analysis revealed that twelve types of tumor-infiltrating immune cells (TICs) are correlated with NOL12 expression. The risk signature based on 8 NOL12-related genes is an independent prognostic factor for patients with HCC. The OS rate of patients in the low-risk score group was better than that in the high-risk score group. In addition, the total tumor mutation burden (TMB) in the high-risk score group increased significantly, and the risk scores could be used as an alternative indicator of immune checkpoint inhibitor (ICI) response. In conclusion, our findings indicated that NOL12 might be involved in the progression of HCC and can be used as a potential therapeutic target. Moreover, the NOL12-related risk signature may have predictive relevance with regard to ICI therapy.

Retraction Notice to: Long Noncoding RNA UCA1 Regulates PRL-3 Expression by Sponging MicroRNA-495 to Promote the Progression of Gastric Cancer.

[This retracts the article DOI: 10.1016/j.omtn.2019.10.020.].

microRNA-15b-5p encapsulated by M2 macrophage-derived extracellular vesicles promotes gastric cancer metastasis by targeting BRMS1 and suppressing DAPK1 transcription.

BACKGROUND: Extracellular vesicles (EVs) derived from tumor-associated macrophages are implicated in the progression and metastasis of gastric cancer (GC) via the transfer of molecular cargo RNAs. We aimed to decipher the impact of microRNA (miR)-15b-5p transferred by M2 macrophage-derived EVs in the metastasis of GC. METHODS: Expression of miR-15b-5p was assessed and the downstream genes of miR-15b-5p were analyzed. GC cells were subjected to gain- and loss-of function experiments for miR-15b-5p, BRMS1, and DAPK1. M2 macrophage-derived EVs were extracted, identified, and subjected to co-culture with GC cells and their biological behaviors were analyzed. A lung metastasis model in nude mice was established to determine the effects of miR-15b-5p on tumor metastasis in vivo. RESULTS: miR-15b-5p was upregulated in GC tissues and cells as well as in M2 macrophage-derived EVs. miR-15b-5p promoted the proliferative and invasive potentials, and epithelial-mesenchymal transition (EMT) of GC cells. M2 macrophage-derived EVs could transfer miR-15b-5p into GC cells where it targeted BRMS1 by binding to its 3'UTR. BRMS1 was enriched in the DAPK1 promoter region and promoted its transcription, thereby arresting the proliferative and invasive potentials, and EMT of GC cells. In vivo experiments demonstrated that orthotopic implantation of miR-15b-5p overexpressing GC cells in nude mice displayed led to enhanced tumor metastasis by inhibiting the BRMS1/DAPK1 axis. CONCLUSIONS: Overall, miR-15b-5p delivered by M2 macrophage-derived EVs constitutes a molecular mechanism implicated in the metastasis of GC, and may thus be considered as a novel therapeutic target for its treatment.

Erratum: RNF6 promotes the migration and invasion of breast cancer by promoting the ubiquitination and degradation of MST1.

[This corrects the article DOI: 10.3892/etm.2021.11041.].

Comprehensive Analysis of Immune Implications and Prognostic Value of SPI1 in Gastric Cancer.

BACKGROUND: The transcription factor Spi-1 proto-oncogene (SPI1, also known as PU.1) is a key regulator of signal communication in the immune system and is essential for the development of myeloid cells and lymphocytes. However, the potential role of SPI1 in gastric cancer (GC) and the correlations between SPI1 and immune infiltration remain unclear. METHODS: In the present study, multiple databases including ONCOMINE, TIMER, Kaplan-Meier Plotter, and The Cancer Genome Atlas were used to explore the expression levels and prognostic value of SPI1 in GC. cBioPortal was used to explore the possible reasons for the increased expression of SPI1 in GC. The correlations between SPI1 expression and tumor-infiltrating immune cells (TICs) were analyzed using CIBERSORT and TIMER. Gene set enrichment analysis was used to determine the biological function of SPI1 in the development of GC. In addition, a risk signature based on SPI1-related immunomodulators was constructed to accurately evaluate the prognosis of patients with GC. The upregulation of SPI1 expression in GC was further confirmed through immunohistochemistry, western blotting, and real-time quantitative PCR (RT-qPCR) assay. RESULTS: The expression of SPI1 was increased significantly in GC according to multiple databases, and high expression of SPI1 was related to poor prognosis and progression of GC. The main factor influencing the high expression of SPI1 mRNA in GC may be diploidy, not DNA methylation. Moreover, immunohistochemistry, western blotting, and RT-qPCR assays also confirmed the upregulated expression of SPI1 in GC. CIBERSORT analysis revealed that SPI1 expression was correlated with seven types of TICs (naive B cells, resting memory CD4 T cells, activated memory CD4 T cells, activated natural killer cells, resting natural killer cells, M2 macrophages, and resting dendritic cells). Gene set enrichment analysis indicated that SPI1 might be related to immune activation in GC and participate in cell cycle regulation. In addition, based on SPI1-related immunomodulators, we developed multiple-gene risk prediction signatures and constructed a nomogram that can independently predict the clinical outcome of GC. CONCLUSION: The results of the present study suggest that SPI1 has a critical role in determining the prognosis of GC patients and may be a potential immunotherapeutic target.

Comprehensive Analysis of Necroptosis-Related Long Noncoding RNA Immune Infiltration and Prediction of Prognosis in Patients With Colon Cancer.

Colon cancer (CC) is one of the most frequent malignancies in the world, with a high rate of morbidity and death. In CC, necroptosis and long noncoding RNA (lncRNAs) are crucial, but the mechanism is not completely clear. The goal of this study was to create a new signature that might predict patient survival and tumor immunity in patients with CC. Expression profiles of necroptosis-related lncRNAs in 473 patients with CC were retrieved from the TCGA database. A consensus clustering analysis based on differentially expressed (DE) genes and a prognostic model based on least absolute shrinkage and selection operator (LASSO) regression analysis were conducted. Clinicopathological correlation analysis, expression difference analysis, PCA, TMB, GO analysis, KEGG enrichment analysis, survival analysis, immune correlation analysis, prediction of clinical therapeutic compounds, and qRT-PCR were also conducted. Fifty-six necroptosis-related lncRNAs were found to be linked to the prognosis, and consensus clustering analysis was performed. There were substantial variations in survival, immune checkpoint expression, clinicopathological correlations, and tumor immunity among the different subgroups. Six lncRNAs were discovered, and patients were split into high-risk and low-risk groups based on a risk score generated using these six lncRNAs. The survival time of low-risk patients was considerably longer than that of high-risk patients, indicating that these lncRNAs are directly associated with survival. The risk score was associated with the tumor stage, infiltration depth, lymph node metastasis, and distant metastasis. After univariate and multivariate Cox regression analysis, the risk score and tumor stage remained significant. Cancer- and metabolism-related pathways were enriched by KEGG analyses. Immune infiltration was shown to differ significantly between high- and low-risk patients in a tumor immunoassay. Eight compounds were screened out, and qRT-PCR confirmed the differential expression of the six lncRNAs. Overall, in CC, necroptosis-related lncRNAs have an important function, and the prognosis of patients with CC can be predicted by these six necroptosis-related lncRNAs. They may be useful in the future for customized cancer therapy.

Comprehensive Analysis of Immune Infiltrates of Ferroptosis-Related Long Noncoding RNA and Prediction of Colon Cancer Patient Prognoses.

Ferroptosis is a newly defined mode of programmed oxidative cell death. Knowledge of ferroptosis-related long noncoding (lnc) RNA in the tumor immune microenvironment of colon cancer is lacking. We systematically analyzed the correlations between ferroptosis-related lncRNAs and the tumor microenvironment, immune cell infiltration, and patient prognosis for 379 colon cancer samples in the Cancer Genome Atlas (TCGA). Using consensus clustering, we divided the 379 colon cancer patients into two subgroups (clusters 1 and 2) based on the differentially expressed ferroptosis-related lncRNAs. Cluster 1 was preferentially associated with longer overall survival, upregulated immune checkpoint inhibitor expressions, higher immunoscores, higher stromal scores, higher estimated scores, and distinct immune cell infiltration. Cancer- and metabolism-related pathways were enriched by gene set enrichment analyses. We constructed a prognostic signature of 15 ferroptosis-related lncRNAs (ZEB1-AS1, LINC01011, AC005261.3, LINC01063, LINC02381, ELFN1-AS1, AC009283.1, LINC02361, AC105219.1, AC002310.1, AL590483.1, MIR4435-2HG, NKILA, AC021054.1, and AL450326.1) and divided the patients into the high- and low-risk-score groups. The signature was validated using TCGA training and testing cohorts. The risk signature was an independent prognostic factor for predicting survival and excellently predicted the prognoses of patients with colon cancer. Moreover, the risk signature was related to immune characteristics. Chemosensitivity analyses showed that low-risk-score patients were more sensitive to sorafenib. In summary, our work revealed the important role of ferroptosis-related lncRNAs in the tumor microenvironment and immune cell infiltration and may help determine personalized prognoses and treatment for patients with colon cancer.

Comprehensive Analysis and Prognosis Prediction of N6-Methyladenosine-Related lncRNAs in Immune Microenvironment Infiltration of Gastric Cancer.

Purpose: N6-methyladenosine (m6A) RNA modification plays an important role in regulating tumor microenvironment (TME) infiltration. However, the relationship between the expression pattern of m6A-related long non-coding RNAs (lncRNAs) and the immune microenvironment of gastric cancer (GC) is unclear. Methods: In this study, 23 m6A-related lncRNAs were identified by Pearson's correlation analysis and univariate Cox regression analysis. According to the expression of these lncRNAs, we identified two distinct molecular clusters by consensus clustering and compared the differences of the TME and enriched pathways between the two clusters. We further constructed a prognostic risk signature and verified it using The Cancer Genome Atlas training and testing cohorts. Results: The results showed that cluster 1 was associated with tumor-related and immune activation-related pathways. In addition, cluster 1 was also associated with higher ImmuneScore, StromalScore, and ESTIMATEScore. The results of the stratified survival analysis and independent prognosis analysis indicated that the risk signature is an independent prognostic indicator for patients with GC. In addition, it can effectively predict survival status in patients with different clinical characteristics. Furthermore, we found that the risk signature was associated with a variety of tumor-infiltrating immune cells, and that low risk scores were significantly correlated with high expression of programmed death-1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA4), as well as sensitivity to chemotherapeutic drugs (eg, fluorouracil and oxaliplatin). Conclusion: This evidence contributes to our understanding of the regulation of TME infiltration by m6A-related lncRNAs and may lead to more effective immunotherapy and chemotherapy for patients with GC.

Comprehensive Analysis of Pyroptosis-Related Long Noncoding RNA Immune Infiltration and Prediction of Prognosis in Patients with Colon Cancer.

Colon cancer (CC) is one of the most prevalent malignant tumours of the alimentary canal. It is unclear whether pyroptosis-related lncRNA expression is correlated with CC prognosis. We discovered 20 pyroptosis-related lncRNAs that were expressed differently in CC and normal colon tissues in our investigation. Based on differentially expressed genes (DEGs), we grouped all CC patients into two categories (Clusters 1 and 2). Cluster 1 was shown to be connected with a higher overall survival rate, upregulated expression of immune checkpoints, higher immunoscores, higher estimated scores, and immune cell infiltration. Using data from the Cancer Genome Atlas (TCGA), to create a multigene signature, the predictive significance of each lncRNA linked with pyroptosis for survival was assessed. A 9-lncRNA signature was established using the least absolute shrinkage and selection operator (LASSO) Cox regression method, and all CC patients in the TCGA cohort were classified into low-risk or high-risk groups. The low-risk CC patients had a much greater chance of survival than those in the high-risk group. The risk score is an independent prognostic indicator for predicting survival. In addition, risk characteristics are linked to immune characteristics. In summary, pyroptosis-related lncRNAs can be used to predict CC prognosis and participate in tumour immunity.

RNF6 promotes the migration and invasion of breast cancer by promoting the ubiquitination and degradation of MST1.

Ring finger protein 6 (RNF6), a member of E3 ubiquitin ligases, plays a potential role as a tumour promoter in numerous carcinomas. However, the role and expression of RNF6 in breast cancer (BC) remains to be elucidated. The present study showed that RNF6 upregulation was detected in BC tissues and was associated with short survival in patients with BC. Multivariate analysis also revealed that RNF6 overexpression is an independent predictor for poor outcome of patients with BC. Furthermore, migration and metastasis assay indicated that RNF6 silencing significantly inhibited the invasion and migration of BC cells in vivo and in vitro, and RNF6 suppression decreased YES-associated protein (YAP) expression. RNF6 promoted the metastatic ability of BC cells via YAP. Mechanistically, RNF6 interacts with mammalian STE20-like protein kinase 1 (MST1), a key factor that regulates YAP, and promoted its ubiquitination and degradation. Additionally, RNF6 regulated YAP signalling by promoting ubiquitination and degradation of MST1 in BC. Taken together, these data may highlight a role of RNF6 in BC, which could serve as a valuable prognostic indicator and potential therapeutic target for patients with BC.

Artificial intelligence applicated in gastric cancer: A bibliometric and visual analysis via CiteSpace.

Objective: This study aimed to analyze and visualize the current research focus, research frontiers, evolutionary processes, and trends of artificial intelligence (AI) in the field of gastric cancer using a bibliometric analysis. Methods: The Web of Science Core Collection database was selected as the data source for this study to retrieve and obtain articles and reviews related to AI in gastric cancer. All the information extracted from the articles was imported to CiteSpace to conduct the bibliometric and knowledge map analysis, allowing us to clearly visualize the research hotspots and trends in this field. Results: A total of 183 articles published between 2017 and 2022 were included, contributed by 201 authors from 33 countries/regions. Among them, China (47.54%), Japan (21.86%), and the USA (13.11%) have made outstanding contributions in this field, accounting fsor 82.51% of the total publications. The primary research institutions were Wuhan University, Tokyo University, and Tada Tomohiro Inst Gastroenterol and Proctol. Tada (n = 12) and Hirasawa (n = 90) were ranked first in the top 10 authors and co-cited authors, respectively. Gastrointestinal Endoscopy (21 publications; IF 2022, 9.189; Q1) was the most published journal, while Gastric Cancer (133 citations; IF 2022, 8.171; Q1) was the most co-cited journal. Nevertheless, the cooperation between different countries and institutions should be further strengthened. The most common keywords were AI, gastric cancer, and convolutional neural network. The "deep-learning algorithm" started to burst in 2020 and continues till now, which indicated that this research topic has attracted continuous attention in recent years and would be the trend of research on AI application in GC. Conclusions: Research related to AI in gastric cancer is increasing exponentially. Current research hotspots focus on the application of AI in gastric cancer, represented by convolutional neural networks and deep learning, in diagnosis and differential diagnosis and staging. Considering the great potential and clinical application prospects, the related area of AI applications in gastric cancer will remain a research hotspot in the future.