PeerJ:Gastroenterology and Hepatologyhttps://peerj.com/articles/index.atom?journal=peerj&subject=4600Gastroenterology and Hepatology articles published in PeerJIntegrating single-cell and bulk sequencing data to identify glycosylation-based genes in non-alcoholic fatty liver disease-associated hepatocellular carcinomahttps://peerj.com/articles/170022024-03-182024-03-18Zhijia ZhouYanan GaoLongxin DengXiaole LuYancheng LaiJieke WuShaodong ChenChengzhong LiHuiqing Liang
Background
The incidence of non-alcoholic fatty liver disease (NAFLD) associated hepatocellular carcinoma (HCC) has been increasing. However, the role of glycosylation, an important modification that alters cellular differentiation and immune regulation, in the progression of NAFLD to HCC is rare.
Methods
We used the NAFLD-HCC single-cell dataset to identify variation in the expression of glycosylation patterns between different cells and used the HCC bulk dataset to establish a link between these variations and the prognosis of HCC patients. Then, machine learning algorithms were used to identify those glycosylation-related signatures with prognostic significance and to construct a model for predicting the prognosis of HCC patients. Moreover, it was validated in high-fat diet-induced mice and clinical cohorts.
Results
The NAFLD-HCC Glycogene Risk Model (NHGRM) signature included the following genes: SPP1, SOCS2, SAPCD2, S100A9, RAMP3, and CSAD. The higher NHGRM scores were associated with a poorer prognosis, stronger immune-related features, immune cell infiltration and immunity scores. Animal experiments, external and clinical cohorts confirmed the expression of these genes.
Conclusion
The genetic signature we identified may serve as a potential indicator of survival in patients with NAFLD-HCC and provide new perspectives for elucidating the role of glycosylation-related signatures in this pathologic process.
Background
The incidence of non-alcoholic fatty liver disease (NAFLD) associated hepatocellular carcinoma (HCC) has been increasing. However, the role of glycosylation, an important modification that alters cellular differentiation and immune regulation, in the progression of NAFLD to HCC is rare.
Methods
We used the NAFLD-HCC single-cell dataset to identify variation in the expression of glycosylation patterns between different cells and used the HCC bulk dataset to establish a link between these variations and the prognosis of HCC patients. Then, machine learning algorithms were used to identify those glycosylation-related signatures with prognostic significance and to construct a model for predicting the prognosis of HCC patients. Moreover, it was validated in high-fat diet-induced mice and clinical cohorts.
Results
The NAFLD-HCC Glycogene Risk Model (NHGRM) signature included the following genes: SPP1, SOCS2, SAPCD2, S100A9, RAMP3, and CSAD. The higher NHGRM scores were associated with a poorer prognosis, stronger immune-related features, immune cell infiltration and immunity scores. Animal experiments, external and clinical cohorts confirmed the expression of these genes.
Conclusion
The genetic signature we identified may serve as a potential indicator of survival in patients with NAFLD-HCC and provide new perspectives for elucidating the role of glycosylation-related signatures in this pathologic process.Validation of CDC45 as a novel biomarker for diagnosis and prognosis of gastric cancerhttps://peerj.com/articles/171302024-03-182024-03-18Lihua WuGan GaoHui MiZhou LuoZheng WangYongdong LiuLiangyan WuHaihua LongYongqi Shen
Background
Cell division cycle protein 45 (CDC45) has been demonstrated to play vital roles in the progression of various malignancies. However, the clinical significance of CDC45 in gastric cancer (GC) remains unreported.
Method
In this study, we employed the TCGA database and the TCGA & GTEx dataset to compare the mRNA expression levels of CDC45 between gastric cancer tissues and adjacent or normal tissues (p < 0.05 was considered statistically significant), which was further validated in multiple datasets including GSE13911, GSE29272, GSE118916, GSE66229, as well as RT-qPCR. Furthermore, we harnessed the Human Protein Atlas (HPA) to evaluate the protein expression of CDC45, which was subsequently verified through immunohistochemistry (IHC). To ascertain the diagnostic utility of CDC45, receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were calculated in TCGA database, and further validated it in TCGA & GTEx and GSE66229 datasets. The Kaplan–Meier method was used to reveal the prognostic importance of CDC45 in The Cancer Genome Atlas (TCGA) database and authenticated through the GSE66229, GSE84433, and GSE84437 datasets. Through cBioPortal, we identified co-expressed genes of CDC45, and pursued enrichment analysis. Additionally, we availed gene set enrichment analysis (GSEA) to annotate the biological functions of CDC45.
Results
Differential expression analysis revealed that CDC45 was significantly upregulated at both the mRNA and protein levels in GC (all p < 0.05). Remarkably, CDC45 emerged as a promising prognostic indicator and a novel diagnostic biomarker for GC. In a comprehensive the drug susceptibility analysis, we found that patients with high expression of CDC45 had high sensitivity to various chemotherapeutic agents, among which 5-fluorouracil, docetaxel, cisplatin, and elesclomol were most evident. Furthermore, our findings suggested a plausible association between CDC45 and immune cell infiltration. Enrichment analysis revealed that CDC45 and its associated genes may play crucial roles in muscle biofunction, whereas GSEA demonstrated significant enrichment of gene sets pertaining to G protein-coupled receptor ligand binding and G alpha (i) signaling events.
Conclusion
Our study elucidates that upregulation of CDC45 is intricately associated with immune cell infiltration and holds promising potential as a favorable prognostic marker and a novel diagnostic biomarker for GC.
Background
Cell division cycle protein 45 (CDC45) has been demonstrated to play vital roles in the progression of various malignancies. However, the clinical significance of CDC45 in gastric cancer (GC) remains unreported.
Method
In this study, we employed the TCGA database and the TCGA & GTEx dataset to compare the mRNA expression levels of CDC45 between gastric cancer tissues and adjacent or normal tissues (p < 0.05 was considered statistically significant), which was further validated in multiple datasets including GSE13911, GSE29272, GSE118916, GSE66229, as well as RT-qPCR. Furthermore, we harnessed the Human Protein Atlas (HPA) to evaluate the protein expression of CDC45, which was subsequently verified through immunohistochemistry (IHC). To ascertain the diagnostic utility of CDC45, receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were calculated in TCGA database, and further validated it in TCGA & GTEx and GSE66229 datasets. The Kaplan–Meier method was used to reveal the prognostic importance of CDC45 in The Cancer Genome Atlas (TCGA) database and authenticated through the GSE66229, GSE84433, and GSE84437 datasets. Through cBioPortal, we identified co-expressed genes of CDC45, and pursued enrichment analysis. Additionally, we availed gene set enrichment analysis (GSEA) to annotate the biological functions of CDC45.
Results
Differential expression analysis revealed that CDC45 was significantly upregulated at both the mRNA and protein levels in GC (all p < 0.05). Remarkably, CDC45 emerged as a promising prognostic indicator and a novel diagnostic biomarker for GC. In a comprehensive the drug susceptibility analysis, we found that patients with high expression of CDC45 had high sensitivity to various chemotherapeutic agents, among which 5-fluorouracil, docetaxel, cisplatin, and elesclomol were most evident. Furthermore, our findings suggested a plausible association between CDC45 and immune cell infiltration. Enrichment analysis revealed that CDC45 and its associated genes may play crucial roles in muscle biofunction, whereas GSEA demonstrated significant enrichment of gene sets pertaining to G protein-coupled receptor ligand binding and G alpha (i) signaling events.
Conclusion
Our study elucidates that upregulation of CDC45 is intricately associated with immune cell infiltration and holds promising potential as a favorable prognostic marker and a novel diagnostic biomarker for GC.Clinical significance of small nuclear ribonucleoprotein U1 subunit 70 in patients with hepatocellular carcinomahttps://peerj.com/articles/168762024-03-152024-03-15Dong JiangXia-Ling ZhuYan AnYi-ran Li
Background & Aims
Small nuclear ribonucleoprotein U1 subunit 70 (SNRNP70) as one of the components of the U1 small nuclear ribonucleoprotein (snRNP) is rarely reported in cancers. This study aims to estimate the application potential of SNRNP70 in hepatocellular carcinoma (HCC) clinical practice.
Methods
Based on the TCGA database and cohort of HCC patients, we investigated the expression patterns and prognostic value of SNRNP70 in HCC. Then, the combination of SNRNP70 and alpha-fetoprotein (AFP) in 278 HCC cases was analyzed. Next, western blotting and immunohistochemistry were used to detect the expression of SNRNP70 in nucleus and cytoplasm. Finally, Cell Counting Kit-8 (CCK-8) and scratch wound healing assays were used to detect the effect of SNRNP70 on the proliferation and migration of HCC cells.
Results
SNRNP70 was highly expressed in HCC. Its expression was increasingly high during the progression of HCC and was positively related to immune infiltration cells. Higher SNRNP70 expression indicated a poor outcome of HCC patients. In addition, nuclear SNRNP70/AFP combination could be a prognostic biomarker for overall survival and recurrence. Cell experiments confirmed that knockdown of SNRNP70 inhibited the proliferation and migration of HCC cells.
Conclusion
SNRNP70 may be a new biomarker for HCC progression and HCC diagnosis as well as prognosis. SNRNP70 combined with serum AFP may indicate the prognosis and recurrence status of HCC patients after operation.
Background & Aims
Small nuclear ribonucleoprotein U1 subunit 70 (SNRNP70) as one of the components of the U1 small nuclear ribonucleoprotein (snRNP) is rarely reported in cancers. This study aims to estimate the application potential of SNRNP70 in hepatocellular carcinoma (HCC) clinical practice.
Methods
Based on the TCGA database and cohort of HCC patients, we investigated the expression patterns and prognostic value of SNRNP70 in HCC. Then, the combination of SNRNP70 and alpha-fetoprotein (AFP) in 278 HCC cases was analyzed. Next, western blotting and immunohistochemistry were used to detect the expression of SNRNP70 in nucleus and cytoplasm. Finally, Cell Counting Kit-8 (CCK-8) and scratch wound healing assays were used to detect the effect of SNRNP70 on the proliferation and migration of HCC cells.
Results
SNRNP70 was highly expressed in HCC. Its expression was increasingly high during the progression of HCC and was positively related to immune infiltration cells. Higher SNRNP70 expression indicated a poor outcome of HCC patients. In addition, nuclear SNRNP70/AFP combination could be a prognostic biomarker for overall survival and recurrence. Cell experiments confirmed that knockdown of SNRNP70 inhibited the proliferation and migration of HCC cells.
Conclusion
SNRNP70 may be a new biomarker for HCC progression and HCC diagnosis as well as prognosis. SNRNP70 combined with serum AFP may indicate the prognosis and recurrence status of HCC patients after operation.Prognostic value of RNA methylation-related genes in gastric adenocarcinoma based on bioinformaticshttps://peerj.com/articles/169512024-02-292024-02-29Xionghui HeXiang ChenChangcheng YangWei WangHening SunJunjie WangJincheng FuHuaying Dong
Background
Gastric cancer (GC) is a malignant tumor that originates from the epithelium of the gastric mucosa and has a poor prognosis. Stomach adenocarcinoma (STAD) covers 95% of total gastric cancer. This study aimed to identify the prognostic value of RNA methylation-related genes in gastric cancer.
Methods
In this study, The Cancer Genome Atlas (TCGA)-STAD and GSE84426 cohorts were downloaded from public databases. Patients were classified by consistent cluster analysis based on prognosis-related differentially expressed RNA methylation genes Prognostic genes were obtained by differential expression, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. The prognostic model was established and validated in the training set, test set and validation set respectively. Independent prognostic analysis was implemented. Finally, the expression of prognostic genes was affirmed by reverse transcription quantitative PCR (RT-qPCR).
Results
In total, four prognostic genes (ACTA2, SAPCD2, PDK4 and APOD) related to RNA methylation were identified and enrolled into the risk signature. The STAD patients were divided into high- and low-risk groups based on the medium value of the risk score, and patients in the high-risk group had a poor prognosis. In addition, the RNA methylation-relevant risk signature was validated in the test and validation sets, and was authenticated as a reliable independent prognostic predictor. The nomogram was constructed based on the independent predictors to predict the 1/3/5-year survival probability of STAD patients. The gene set enrichment analysis (GSEA) result suggested that the poor prognosis in the high-risk subgroup may be related to immune-related pathways. Finally, the experimental results indicated that the expression trends of RNA methylation-relevant prognostic genes in gastric cancer cells were in agreement with the result of bioinformatics.
Conclusion
Our study established a novel RNA methylation-related risk signature for STAD, which was of considerable significance for improving prognosis of STAD patients and offering theoretical support for clinical therapy.
Background
Gastric cancer (GC) is a malignant tumor that originates from the epithelium of the gastric mucosa and has a poor prognosis. Stomach adenocarcinoma (STAD) covers 95% of total gastric cancer. This study aimed to identify the prognostic value of RNA methylation-related genes in gastric cancer.
Methods
In this study, The Cancer Genome Atlas (TCGA)-STAD and GSE84426 cohorts were downloaded from public databases. Patients were classified by consistent cluster analysis based on prognosis-related differentially expressed RNA methylation genes Prognostic genes were obtained by differential expression, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. The prognostic model was established and validated in the training set, test set and validation set respectively. Independent prognostic analysis was implemented. Finally, the expression of prognostic genes was affirmed by reverse transcription quantitative PCR (RT-qPCR).
Results
In total, four prognostic genes (ACTA2, SAPCD2, PDK4 and APOD) related to RNA methylation were identified and enrolled into the risk signature. The STAD patients were divided into high- and low-risk groups based on the medium value of the risk score, and patients in the high-risk group had a poor prognosis. In addition, the RNA methylation-relevant risk signature was validated in the test and validation sets, and was authenticated as a reliable independent prognostic predictor. The nomogram was constructed based on the independent predictors to predict the 1/3/5-year survival probability of STAD patients. The gene set enrichment analysis (GSEA) result suggested that the poor prognosis in the high-risk subgroup may be related to immune-related pathways. Finally, the experimental results indicated that the expression trends of RNA methylation-relevant prognostic genes in gastric cancer cells were in agreement with the result of bioinformatics.
Conclusion
Our study established a novel RNA methylation-related risk signature for STAD, which was of considerable significance for improving prognosis of STAD patients and offering theoretical support for clinical therapy.Identification of m6A-associated autophagy genes in non-alcoholic fatty liverhttps://peerj.com/articles/170112024-02-292024-02-29Ziqing HuangLinfei LuoZhengqiang WuZhihua XiaoZhili Wen
Background
Studies had shown that autophagy was closely related to nonalcoholic fat liver disease (NAFLD), while N6-methyladenosine (m6A) was involved in the regulation of autophagy. However, the mechanism of m6A related autophagy in NAFLD was unclear.
Methods
The NAFLD related datasets were gained via the Gene Expression Omnibus (GEO) database, and we also extracted 232 autophagy-related genes (ARGs) and 37 m6A. First, differentially expressed ARGs (DE-ARGs) and differentially expressed m6A (DE-m6A) were screened out by differential expression analysis. DE-ARGs associated with m6A were sifted out by Pearson correlation analysis, and the m6A-ARGs relationship pairs were acquired. Then, autophagic genes in m6A-ARGs pairs were analyzed for machine learning algorithms to obtain feature genes. Further, we validated the relationship between feature genes and NAFLD through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot (WB). Finally, the immuno-infiltration analysis was implement, and we also constructed the TF-mRNA and drug-gene networks.
Results
There were 19 DE-ARGs and four DE-m6A between NAFLD and normal samples. The three m6A genes and five AGRs formed the m6A-ARGs relationship pairs. Afterwards, genes obtained from machine learning algorithms were intersected to yield three feature genes (TBK1, RAB1A, and GOPC), which showed significant positive correlation with astrocytes, macrophages, smooth muscle, and showed significant negative correlation with epithelial cells, and endothelial cells. Besides, qRT-PCR and WB indicate that TBK1, RAB1A and GOPC significantly upregulated in NAFLD. Ultimately, we found that the TF-mRNA network included FOXP1-GOPC, ATF1-RAB1A and other relationship pairs, and eight therapeutic agents such as R-406 and adavosertib were predicted based on the TBK1.
Conclusion
The study investigated the potential molecular mechanisms of m6A related autophagy feature genes (TBK1, RAB1A, and GOPC) in NAFLD through bioinformatic analyses and animal model validation. However, it is critical to note that these findings, although consequential, demonstrate correlations rather than cause-and-effect relationships. As such, more research is required to fully elucidate the underlying mechanisms and validate the clinical relevance of these feature genes.
Background
Studies had shown that autophagy was closely related to nonalcoholic fat liver disease (NAFLD), while N6-methyladenosine (m6A) was involved in the regulation of autophagy. However, the mechanism of m6A related autophagy in NAFLD was unclear.
Methods
The NAFLD related datasets were gained via the Gene Expression Omnibus (GEO) database, and we also extracted 232 autophagy-related genes (ARGs) and 37 m6A. First, differentially expressed ARGs (DE-ARGs) and differentially expressed m6A (DE-m6A) were screened out by differential expression analysis. DE-ARGs associated with m6A were sifted out by Pearson correlation analysis, and the m6A-ARGs relationship pairs were acquired. Then, autophagic genes in m6A-ARGs pairs were analyzed for machine learning algorithms to obtain feature genes. Further, we validated the relationship between feature genes and NAFLD through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot (WB). Finally, the immuno-infiltration analysis was implement, and we also constructed the TF-mRNA and drug-gene networks.
Results
There were 19 DE-ARGs and four DE-m6A between NAFLD and normal samples. The three m6A genes and five AGRs formed the m6A-ARGs relationship pairs. Afterwards, genes obtained from machine learning algorithms were intersected to yield three feature genes (TBK1, RAB1A, and GOPC), which showed significant positive correlation with astrocytes, macrophages, smooth muscle, and showed significant negative correlation with epithelial cells, and endothelial cells. Besides, qRT-PCR and WB indicate that TBK1, RAB1A and GOPC significantly upregulated in NAFLD. Ultimately, we found that the TF-mRNA network included FOXP1-GOPC, ATF1-RAB1A and other relationship pairs, and eight therapeutic agents such as R-406 and adavosertib were predicted based on the TBK1.
Conclusion
The study investigated the potential molecular mechanisms of m6A related autophagy feature genes (TBK1, RAB1A, and GOPC) in NAFLD through bioinformatic analyses and animal model validation. However, it is critical to note that these findings, although consequential, demonstrate correlations rather than cause-and-effect relationships. As such, more research is required to fully elucidate the underlying mechanisms and validate the clinical relevance of these feature genes.Use of Callistemon citrinus as a gastroprotective and anti-inflammatory agent on indomethacin-induced gastric ulcers in obese ratshttps://peerj.com/articles/170622024-02-282024-02-28Jonathan Saúl Piñón-SimentalLuis Alberto Ayala-RuizLuis Gerardo Ortega-PérezOliver Rafid Magaña-RodríguezEsperanza Meléndez-HerreraAsdrubal Aguilera-MéndezPatricia Rios-Chavez
Background
Obesity leads to an elevated risk of developing gastrointestinal disease such as gastric ulcers. Callistemon citrinus leaf extract has shown antioxidant, antimicrobial, hepatoprotective, and chemoprotective effects against colon cancer. The aim of this study is to evaluate the gastroprotective effect of C. citrinus leaf extract on indomethacin-induced gastric ulcers in obese rats.
Methods
Gastric ulcers were induced in female obese Wistar rats using a single oral dose of indomethacin (IND). In the first stage, the rats were fed with a high fat sugar diet (HFSD) for 15 weeks to induce obesity and, at the same time, the diet of the other group of animals included daily administration of ethanolic C. citrinus leaf extract (250 mg/kg) in addition to HFSD. In the second stage, gastric ulcers were induced with IND (30 mg/kg). The gastroprotective activity of C. citrinus, the inflammatory enzyme activities, and cytokines in the stomach were determined.
Results
C. citrinus produced a reduction of gastric lesions caused by IND. Myeloperoxidase (MPO), cyclooxygenase-2 (COX-2), and 5-lipoxygenase (5-LOX) activities also decreased. Although inflammatory biomarkers such as TNFα, IL-6, AOPP, and leptin were significantly decreased by C. citrinus, adiponectin levels increased. Moreover, C. citrinus decreased weight gain and morphological and biochemical parameters.
Conclusion
The use of indomethacin in rats fed with a high fat-sugar diet increased gastric ulcers. Gastroprotective effect of C. citrinus in obese rats is attributed to the reduction of pro-inflammatory cytokines and the inflammatory enzymes.
Background
Obesity leads to an elevated risk of developing gastrointestinal disease such as gastric ulcers. Callistemon citrinus leaf extract has shown antioxidant, antimicrobial, hepatoprotective, and chemoprotective effects against colon cancer. The aim of this study is to evaluate the gastroprotective effect of C. citrinus leaf extract on indomethacin-induced gastric ulcers in obese rats.
Methods
Gastric ulcers were induced in female obese Wistar rats using a single oral dose of indomethacin (IND). In the first stage, the rats were fed with a high fat sugar diet (HFSD) for 15 weeks to induce obesity and, at the same time, the diet of the other group of animals included daily administration of ethanolic C. citrinus leaf extract (250 mg/kg) in addition to HFSD. In the second stage, gastric ulcers were induced with IND (30 mg/kg). The gastroprotective activity of C. citrinus, the inflammatory enzyme activities, and cytokines in the stomach were determined.
Results
C. citrinus produced a reduction of gastric lesions caused by IND. Myeloperoxidase (MPO), cyclooxygenase-2 (COX-2), and 5-lipoxygenase (5-LOX) activities also decreased. Although inflammatory biomarkers such as TNFα, IL-6, AOPP, and leptin were significantly decreased by C. citrinus, adiponectin levels increased. Moreover, C. citrinus decreased weight gain and morphological and biochemical parameters.
Conclusion
The use of indomethacin in rats fed with a high fat-sugar diet increased gastric ulcers. Gastroprotective effect of C. citrinus in obese rats is attributed to the reduction of pro-inflammatory cytokines and the inflammatory enzymes.Identification and immunoinfiltration analysis of key genes in ulcerative colitis using WGCNAhttps://peerj.com/articles/169212024-02-262024-02-26Siyi NiYingchao LiuJihong ZhongYan Shen
Objective
Ulcerative colitis (UC) is a chronic non-specific inflammatory bowel disease characterized by an unclear pathogenesis. This study aims to screen out key genes related to UC pathogenesis.
Methods
Bioinformatics analysis was conducted for screening key genes linked to UC pathogenesis, and the expression of the screened key genes was verified by establishing a UC mouse model.
Results
Through bioinformatics analysis, five key genes were obtained. Subsequent infiltration analysis revealed seven significantly different immune cell types between the UC and general samples. Additionally, animal experiment results illustrated markedly decreased body weight, visible colonic shortening and damage, along with a significant increase in the DAI score of the DSS-induced mice in the UC group in comparison with the NC group. In addition, H&E staining results demonstrated histological changes including marked inflammatory cell infiltration, loss of crypts, and epithelial destruction in the colon mucosa epithelium. qRT-PCR analysis indicated a down-regulation of ABCG2 and an up-regulation of IL1RN, REG4, SERPINB5 and TRIM29 in the UC mouse model. Notably, this observed trend showed a significant dependence on the concentration of DSS, with the mouse model of UC induced by 7% DSS demonstrating a more severe disease state compared to that induced by 5% DSS.
Conclusion
ABCG2, IL1RN, REG4, SERPINB5 and TRIM29 were screened out as key genes related to UC by bioinformatics analysis. The expression of ABCG2 was down-regulated, and that of IL1RN, REG4, SERPINB5 and TRIM29 were up-regulated in UC mice as revealed by animal experiments.
Objective
Ulcerative colitis (UC) is a chronic non-specific inflammatory bowel disease characterized by an unclear pathogenesis. This study aims to screen out key genes related to UC pathogenesis.
Methods
Bioinformatics analysis was conducted for screening key genes linked to UC pathogenesis, and the expression of the screened key genes was verified by establishing a UC mouse model.
Results
Through bioinformatics analysis, five key genes were obtained. Subsequent infiltration analysis revealed seven significantly different immune cell types between the UC and general samples. Additionally, animal experiment results illustrated markedly decreased body weight, visible colonic shortening and damage, along with a significant increase in the DAI score of the DSS-induced mice in the UC group in comparison with the NC group. In addition, H&E staining results demonstrated histological changes including marked inflammatory cell infiltration, loss of crypts, and epithelial destruction in the colon mucosa epithelium. qRT-PCR analysis indicated a down-regulation of ABCG2 and an up-regulation of IL1RN, REG4, SERPINB5 and TRIM29 in the UC mouse model. Notably, this observed trend showed a significant dependence on the concentration of DSS, with the mouse model of UC induced by 7% DSS demonstrating a more severe disease state compared to that induced by 5% DSS.
Conclusion
ABCG2, IL1RN, REG4, SERPINB5 and TRIM29 were screened out as key genes related to UC by bioinformatics analysis. The expression of ABCG2 was down-regulated, and that of IL1RN, REG4, SERPINB5 and TRIM29 were up-regulated in UC mice as revealed by animal experiments.Expression patterns of E2Fs identify tumor microenvironment features in human gastric cancerhttps://peerj.com/articles/169112024-02-132024-02-13Fanni LiJun YanJing LengTianyu YuHuayou ZhouChang LiuWenbo HuangQi SunWei Zhao
Objective
E2F transcription factors are associated with tumor development, but their underlying mechanisms in gastric cancer (GC) remain unclear. This study explored whether E2Fs determine the prognosis or immune and therapy responses of GC patients.
Methods
E2F regulation patterns from The Cancer Genome Atlas (TCGA) were systematically investigated and E2F patterns were correlated with the characteristics of cellular infiltration in the tumor microenvironment (TME). A principal component analysis was used to construct an E2F scoring model based on prognosis-related differential genes to quantify the E2F regulation of a single tumor. This scoring model was then tested in patient cohorts to predict effects of immunotherapy.
Results
Based on the expression profiles of E2F transcription factors in GC, two different regulatory patterns of E2F were identified. TME and survival differences emerged between the two clusters. Lower survival rates in the Cluster2 group were attributed to limited immune function due to stromal activation. The E2F scoring model was then constructed based on the E2F-related prognostic genes. Evidence supported the E2F score as an independent and effective prognostic factor and predictor of immunotherapy response. A gene-set analysis correlated E2F score with the characteristics of immune cell infiltration within the TME. The immunotherapy cohort database showed that patients with a higher E2F score demonstrated better survival and immune responses.
Conclusions
This study found that differences in GC prognosis might be related to the E2F patterns in the TME. The E2F scoring system developed in this study has practical value as a predictor of survival and treatment response in GC patients.
Objective
E2F transcription factors are associated with tumor development, but their underlying mechanisms in gastric cancer (GC) remain unclear. This study explored whether E2Fs determine the prognosis or immune and therapy responses of GC patients.
Methods
E2F regulation patterns from The Cancer Genome Atlas (TCGA) were systematically investigated and E2F patterns were correlated with the characteristics of cellular infiltration in the tumor microenvironment (TME). A principal component analysis was used to construct an E2F scoring model based on prognosis-related differential genes to quantify the E2F regulation of a single tumor. This scoring model was then tested in patient cohorts to predict effects of immunotherapy.
Results
Based on the expression profiles of E2F transcription factors in GC, two different regulatory patterns of E2F were identified. TME and survival differences emerged between the two clusters. Lower survival rates in the Cluster2 group were attributed to limited immune function due to stromal activation. The E2F scoring model was then constructed based on the E2F-related prognostic genes. Evidence supported the E2F score as an independent and effective prognostic factor and predictor of immunotherapy response. A gene-set analysis correlated E2F score with the characteristics of immune cell infiltration within the TME. The immunotherapy cohort database showed that patients with a higher E2F score demonstrated better survival and immune responses.
Conclusions
This study found that differences in GC prognosis might be related to the E2F patterns in the TME. The E2F scoring system developed in this study has practical value as a predictor of survival and treatment response in GC patients.Insulin signaling and pharmacology in humans and in coralshttps://peerj.com/articles/168042024-01-312024-01-31Meghana Hosahalli Shivananda MurthyPaniz JasbiWhitney LoweLokender KumarMonsurat OlaosebikanLiza RogerJinkyu YangNastassja LewinskiNoah DanielsLenore CowenJudith Klein-Seetharaman
Once thought to be a unique capability of the Langerhans islets in the pancreas of mammals, insulin (INS) signaling is now recognized as an evolutionarily ancient function going back to prokaryotes. INS is ubiquitously present not only in humans but also in unicellular eukaryotes, fungi, worms, and Drosophila. Remote homologue identification also supports the presence of INS and INS receptor in corals where the availability of glucose is largely dependent on the photosynthetic activity of the symbiotic algae. The cnidarian animal host of corals operates together with a 20,000-sized microbiome, in direct analogy to the human gut microbiome. In humans, aberrant INS signaling is the hallmark of metabolic disease, and is thought to play a major role in aging, and age-related diseases, such as Alzheimer’s disease. We here would like to argue that a broader view of INS beyond its human homeostasis function may help us understand other organisms, and in turn, studying those non-model organisms may enable a novel view of the human INS signaling system. To this end, we here review INS signaling from a new angle, by drawing analogies between humans and corals at the molecular level.
Once thought to be a unique capability of the Langerhans islets in the pancreas of mammals, insulin (INS) signaling is now recognized as an evolutionarily ancient function going back to prokaryotes. INS is ubiquitously present not only in humans but also in unicellular eukaryotes, fungi, worms, and Drosophila. Remote homologue identification also supports the presence of INS and INS receptor in corals where the availability of glucose is largely dependent on the photosynthetic activity of the symbiotic algae. The cnidarian animal host of corals operates together with a 20,000-sized microbiome, in direct analogy to the human gut microbiome. In humans, aberrant INS signaling is the hallmark of metabolic disease, and is thought to play a major role in aging, and age-related diseases, such as Alzheimer’s disease. We here would like to argue that a broader view of INS beyond its human homeostasis function may help us understand other organisms, and in turn, studying those non-model organisms may enable a novel view of the human INS signaling system. To this end, we here review INS signaling from a new angle, by drawing analogies between humans and corals at the molecular level.A retrospective study investigating the clinical significance of body mass index in acute pancreatitishttps://peerj.com/articles/168542024-01-292024-01-29Yuanzhen BaiGuanwen GongReziya AierkenXingyu LiuWei ChengJunjie GuanZhiwei Jiang
Background
Acute pancreatitis is an unpredictable and potentially fatal condition for which no definitive cure is currently available. Our research focused on exploring the connection between body mass index, a frequently overlooked risk factor, and both the onset and progression of acute pancreatitis.
Material/Methods
A total of 247 patients with acute pancreatitis admitted to Jiangsu Provincial Hospital of Chinese Medicine from January 2021 to February 2023 were retrospectively reviewed. After screening, 117 patients with complete height and body weight data were selected for detailed assessment. Additionally, 85 individuals who underwent physical examinations at our hospital during this period were compiled to create a control group. The study received ethical approval from the ethics committee of Jiangsu Province Hospital of Chinese Medicine (Ref: No.2022NL-114-02) and was conducted in accordance with the China Good Clinical Practice in Research guidelines.
Results
A significant difference in body mass index (BMI) was observed between the healthy group and acute pancreatitis (AP) patients (p < 0.05), with a more pronounced disparity noted in cases of hyperlipidemic acute pancreatitis (p < 0.01). A potential risk for AP was identified at a BMI greater than 23.56 kg/m2 (AUC = 0.6086, p < 0.05). Being in the obese stage I (95%CI, [1.11–1.84]) or having a BMI below 25.4 kg/m2 (95%CI, [1.82–6.48]) are identified as risk factors for adverse AP progression. Moreover, BMI effectively predicts the onset of acute edematous pancreatitis and acute necrotizing pancreatitis (AUC = 0.7893, p < 0.001, cut-off value = 25.88 kg/m2). A higher BMI correlates with increased recurrence rates within a short timeframe (r = 0.7532, p < 0.01).
Conclusions
Elevated BMI is a risk factor for both the occurrence and progression of AP, and underweight status may similarly contribute to poor disease outcomes. BMI is crucial for risk prediction and stratification in AP and warrants ongoing monitoring and consideration.
Background
Acute pancreatitis is an unpredictable and potentially fatal condition for which no definitive cure is currently available. Our research focused on exploring the connection between body mass index, a frequently overlooked risk factor, and both the onset and progression of acute pancreatitis.
Material/Methods
A total of 247 patients with acute pancreatitis admitted to Jiangsu Provincial Hospital of Chinese Medicine from January 2021 to February 2023 were retrospectively reviewed. After screening, 117 patients with complete height and body weight data were selected for detailed assessment. Additionally, 85 individuals who underwent physical examinations at our hospital during this period were compiled to create a control group. The study received ethical approval from the ethics committee of Jiangsu Province Hospital of Chinese Medicine (Ref: No.2022NL-114-02) and was conducted in accordance with the China Good Clinical Practice in Research guidelines.
Results
A significant difference in body mass index (BMI) was observed between the healthy group and acute pancreatitis (AP) patients (p < 0.05), with a more pronounced disparity noted in cases of hyperlipidemic acute pancreatitis (p < 0.01). A potential risk for AP was identified at a BMI greater than 23.56 kg/m2 (AUC = 0.6086, p < 0.05). Being in the obese stage I (95%CI, [1.11–1.84]) or having a BMI below 25.4 kg/m2 (95%CI, [1.82–6.48]) are identified as risk factors for adverse AP progression. Moreover, BMI effectively predicts the onset of acute edematous pancreatitis and acute necrotizing pancreatitis (AUC = 0.7893, p < 0.001, cut-off value = 25.88 kg/m2). A higher BMI correlates with increased recurrence rates within a short timeframe (r = 0.7532, p < 0.01).
Conclusions
Elevated BMI is a risk factor for both the occurrence and progression of AP, and underweight status may similarly contribute to poor disease outcomes. BMI is crucial for risk prediction and stratification in AP and warrants ongoing monitoring and consideration.