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Laboratory Investigation; a Journal of... Sep 2023Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric...
Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric cancer (GC) to identify signature genes that accurately predict prognosis and the efficacy of immunotherapy. Least absolute shrinkage and selection operator and multivariate Cox regression analysis were conducted to develop an epigenetic modification-associated molecular classification. We investigated the significance of PIP4P2, an independent prognostic factor of the classification system, in predicting the prognosis and immunotherapy efficacy of patients with GC. The epigenetic modification-associated molecular classification was highly associated with the clinicopathological characteristics of patients and the existing classification of GC. PIP4P2 was highly expressed in GC tissue and tumor-associated macrophages. High PIP4P2 expression in GC tissue-induced tumor progression by activating PI3K/AKT signal transduction had a negative impact on immunotherapy efficacy. High expression of PIP4P2 in macrophages was correlated with poor prognosis in patients with GC. PIP4P2 is an independent unfavorable prognostic factor of epigenetic modification-associated molecular classification, is involved in tumorigenic progression, and is essential for assessing the prognosis and immunotherapy efficacy of GC.
Topics: Humans; Stomach Neoplasms; Phosphatidylinositol 3-Kinases; Carcinogenesis; Epigenesis, Genetic; Immunotherapy; Prognosis
PubMed: 37150296
DOI: 10.1016/j.labinv.2023.100170 -
Autoimmunity Dec 2023Breast cancer (BC) is highly malignant and its mortality rate remains high. The development of immunotherapy has gradually improved the prognosis and survival rate of...
Breast cancer (BC) is highly malignant and its mortality rate remains high. The development of immunotherapy has gradually improved the prognosis and survival rate of patients. Therefore, identifying molecular markers concerned with BC immunity is of great importance for the treatment of this disease. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) was utilized as the training set while the BC expression dataset from the gene expression omnibus database was taken as the validation set here. Weighted gene co-expression network analysis combined with Pearson analysis and Tumor immune estimation resource (TIMER) was used to obtain immune cell-related hub gene module. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on this module. Then, receiver operating characteristic curves combining Kaplan-Meier was used to evaluate the effectiveness of the model. Feature genes were screened and the independence of risk score was evaluated by univariate and multivariate Cox analyses. Differences in immune characteristics were analyzed via single-sample gene set enrichment analysis and CIBERSORT, and differences in gene mutation frequency were assessed via GenVisR analysis. Finally, the expression levels of prognostic feature genes in BC cells were validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). In this study, cell immune-related gene modules in TCGA-BRCA were successfully excavated, and a five-gene (TNFRSF14, NFKBIA, DLG3, IRF2, and CYP27A1) prognostic model was established. The prognostic model could effectively forecast the prognosis and survival rate of BC patients. The result showed that human leukocyte antigen-related proteins and macrophage M2 scores were remarkably highly expressed in the high-risk group, whereas CD8+ T cells, natural killer cells, M1, and other anti-tumor cells were lowly expressed. The model could be used as an independent prognostic factor to predict the prognosis of BC patients. The results of qRT-PCR validation were consistent with the results in the database, that is, except DLG3, the other four feature genes were lowly expressed in BC. The five-gene model established in this study can predict the prognostic and immune mode of BC patients effectively, which is anticipated to become a feasible molecular target for BC therapy.
Topics: Humans; Female; Breast Neoplasms; Gene Regulatory Networks; Prognosis; CD8-Positive T-Lymphocytes; Carcinoma
PubMed: 37584152
DOI: 10.1080/08916934.2023.2244695 -
Journal of Translational Medicine Feb 2024Lactylation, a novel contributor to post-translational protein modifications, exhibits dysregulation across various tumors. Nevertheless, its intricate involvement in...
BACKGROUND
Lactylation, a novel contributor to post-translational protein modifications, exhibits dysregulation across various tumors. Nevertheless, its intricate involvement in colorectal carcinoma, particularly for non-histone lactylation and its intersection with metabolism and immune evasion, remains enigmatic.
METHODS
Employing immunohistochemistry on tissue microarray with clinical information and immunofluorescence on colorectal cell lines, we investigated the presence of global lactylation and its association with development and progression in colorectal cancer as well as its functional location. Leveraging the AUCell algorithm alongside correlation analysis in single-cell RNA sequencing data, as well as cox-regression and lasso-regression analysis in TCGA dataset and confirmed in GEO dataset, we identified a 23-gene signature predicting colorectal cancer prognosis. Subsequently, we analyzed the associations between the lactylation related gene risk and clinical characteristics, mutation landscapes, biological functions, immune cell infiltration, immunotherapy responses, and drug sensitivity. Core genes were further explored for deep biological insights through bioinformatics and in vitro experiments.
RESULTS
Our study innovatively reveals a significant elevation of global lactylation in colorectal cancer, particularly in malignant tumors, confirming it as an independent prognostic factor for CRC. Through a comprehensive analysis integrating tumor tissue arrays, TCGA dataset, GEO dataset, combining in silico investigations and in vitro experiments, we identified a 23-gene Lactylation-Related Gene risk model capable of predicting the prognosis of colorectal cancer patients. Noteworthy variations were observed in clinical characteristics, biological functions, immune cell infiltration, immune checkpoint expression, immunotherapy responses and drug sensitivity among distinct risk groups.
CONCLUSIONS
The Lactylation-Related Gene risk model exhibits significant potential for improving the management of colorectal cancer patients and enhancing therapeutic outcomes, particularly at the intersection of metabolism and immune evasion. This finding underscores the clinical relevance of global lactylation in CRC and lays the groundwork for mechanism investigation and targeted therapeutic strategies given the high lactate concentration in CRC.
Topics: Humans; Prognosis; Immunotherapy; Algorithms; Cell Line; Colorectal Neoplasms; Tumor Microenvironment
PubMed: 38419085
DOI: 10.1186/s12967-024-04955-9 -
International Journal of Surgery... Nov 2023The tumor area may be a potential prognostic indicator. The present study aimed to determine and validate the prognostic value of tumor area in curable colon cancer.
Identification and initial validation of maximal tumor area as a novel prognostic factor for overall and disease-free survival in patients with resectable colon cancer: a retrospective study.
BACKGROUND
The tumor area may be a potential prognostic indicator. The present study aimed to determine and validate the prognostic value of tumor area in curable colon cancer.
METHODS
This retrospective study included a training and validation cohorts of patients who underwent radical surgery for colon cancer. Independent prognostic factors for overall survival (OS) and disease-free survival (DFS) were identified using Cox proportional hazards regression models. The prognostic discrimination was evaluated using the integrated area under the receiver operating characteristic curves (iAUCs) for prognostic factors and models. The prognostic discrimination between tumor area and other individual factors was compared, along with the prognostic discrimination between the tumor-node-metastasis (TNM) staging system and other prognostic models. Two-sample Wilcoxon tests were carried out to identify significant differences between the two iAUCs. A two-sided P <0.05 was considered statistically significant.
RESULTS
A total of 3051 colon cancer patients were included in the training cohort and 872 patients in the validation cohort. Tumor area, age, differentiation, T stage, and N stage were independent prognostic factors for both OS and DFS in the training cohort. Tumor area had a better OS and DFS prognostic discrimination characteristics than T stage, maximal tumor diameter, differentiation, tumor location, and number of retrieved lymph nodes. The novel prognostic model of T stage + N stage + tumor area (iAUC for OS, 0.714, P <0.001; iAUC for DFS, 0.694, P <0.001) showed a better prognostic discrimination than the TNM staging system (T stage + N stage; iAUC for OS, 0.664; iAUC for DFS, 0.658). Similar results were observed in an independent validation cohort.
CONCLUSIONS
Tumor area was identified as an independent prognostic factor for both OS and DFS in curable colon cancer patients, and in cases with an adequate number of retrieved lymph nodes. The novel prognostic model of combining T stage, N stage, and tumor area may be an alternative to the current TNM staging system.
Topics: Humans; Prognosis; Disease-Free Survival; Retrospective Studies; Neoplasm Staging; Colonic Neoplasms; Neoplasms, Second Primary
PubMed: 37526113
DOI: 10.1097/JS9.0000000000000623 -
Scientific Reports Nov 2023Intrahepatic cholangiocarcinoma (ICC) accounts for 20% of liver malignancies with a 5-year survival rate of 35% at best with limited prognostic predictors. Lung Immune...
Intrahepatic cholangiocarcinoma (ICC) accounts for 20% of liver malignancies with a 5-year survival rate of 35% at best with limited prognostic predictors. Lung Immune Prognostic Index (LIPI) is a novel prognostic factor in pulmonary cancers. In this study, we developed a modified prognostic model from LIPI called intrahepatic immune prognostic index (IIPI) for ICC. A retrospectively study was conducted at Liver Transplant Center of West China Hospital between January 2015 and January 2023. Hematological factors and clinical features of ICC patients were collected and analyzed. The area under curve (AUC) and optimal cuff-off of each single hematological factor was calculated. In this study, derived neurtrophil to lymphocyte ratio (dNLR), arbohydrate antigen199 (CA199) and carcinoembryonic antigen (CEA) have higher AUC values. LIPI was composed of dNLR and was further modified by combing CA199 and CEA, forming the IIPI. The IIPI consists of four grades which are None, Light, Moderate and Severe. Compared to other prognostic factors, IIPI exhibited better ability to predict overall survival. The multivariate analysis indicated that cirrhosis, differentiation, hilar invasion and IIPI were independent prognostic factors for ICC patients. An IIPI-based nomogram was also established and could predict the overall survival. In addition, the subgroup analyses based on clinical prognostic factors showed that the IIPI exhibited excellent prognostic influence. IIPI model is suitable for predicting the prognosis of postoperative ICC patients. Further research is needed to explore the relationship between postoperative recurrence and metastasis of ICC patients and IIPI.
Topics: Humans; Carcinoembryonic Antigen; Retrospective Studies; Prognosis; Cholangiocarcinoma; Bile Ducts, Intrahepatic; Bile Duct Neoplasms
PubMed: 37935735
DOI: 10.1038/s41598-023-45056-9 -
World Journal of Surgical Oncology Jun 2023Although several studies have confirmed the prognostic value of the consolidation to tumor ratio (CTR) in non-small cell lung cancer (NSCLC), there still remains... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Although several studies have confirmed the prognostic value of the consolidation to tumor ratio (CTR) in non-small cell lung cancer (NSCLC), there still remains controversial about it.
METHODS
We systematically searched the PubMed, Embase, and Web of Science databases from inception to April, 2022 for eligible studies that reported the correlation between CTR and prognosis in NSCLC. Hazard ratios (HRs) with 95% confidence intervals (95% CIs) were extracted and pooled to assess the overall effects. Heterogeneity was estimated by I statistics. Subgroup analysis based on the cut-off value of CTR, country, source of HR and histology type was conducted to detect the sources of heterogeneity. Statistical analyses were performed using STATA version 12.0.
RESULTS
A total of 29 studies published between 2001 and 2022 with 10,347 patients were enrolled. The pooled results demonstrated that elevated CTR was associated with poorer overall survival (HR = 1.88, 95% CI 1.42-2.50, P < 0.01) and disease-free survival (DFS)/recurrence-free survival (RFS)/progression-free survival (PFS) (HR = 1.42, 95% CI 1.27-1.59, P < 0.01) in NSCLC. According to subgroup analysis by the cut-off value of CTR and histology type, both lung adenocarcinoma and NSCLC patients who had a higher CTR showed worse survival. Subgroup analysis stratified by country revealed that CTR was a prognostic factor for OS and DFS/RFS/PFS in Chinese, Japanese, and Turkish patients.
CONCLUSIONS
In NSCLC patients with high CTR, the prognosis was worse than that with low CTR, indicating that CTR may be a prognostic factor.
Topics: Humans; Carcinoma, Non-Small-Cell Lung; Prognosis; Lung Neoplasms; Proportional Hazards Models; Tomography
PubMed: 37349739
DOI: 10.1186/s12957-023-03081-y -
Annals of Medicine Dec 2023Anesthetic drugs had been reported may impact the bio-behavior of the tumor. Propofol and sevoflurane are common anesthetics in the operation for glioblastoma (GBM)....
OBJECTIVES
Anesthetic drugs had been reported may impact the bio-behavior of the tumor. Propofol and sevoflurane are common anesthetics in the operation for glioblastoma (GBM). This study aims to establish a co-expression prognostic-related genes signature base on propofol and sevoflurane anesthesia to predict prognosis and immunotherapy response in GBM.
METHOD
GPM tissues with different anesthetics gene expression profiles (GSE179004) were obtained from the Gene Expression Omnibus (GEO) database. Core modules and central genes associated with propofol and sevoflurane anesthesia were identified by weighted gene coexpression network analysis (WGCNA) and establish a risk score prognostic model. Immune cell signature analysis in TCGA datasets was predicted via CIBERSORT. At last, serum methylation level of O6-methylguanine-DNA methyltransferase (MGMT) promoter was detected in GPM patient in different time during perioperative period.
RESULTS
The burlywood1 group screened was significantly associated with sevoflurane-treated GBM tissue. 22 independent prognostic differential genes were construct a prognostic-related genes risk score in GBM, and showed good predictive ability. The risk score was strongly correlated with the age of the patients, but not with the sex of the patients. In addition, the differential responses to immunotherapy in high and low risk groups were analyzed, indicating that sevoflurane signature genes were consistent in the classification of gliomas. High-risk patients have high T-cell damage score and are less sensitive to immunotherapy. At last, serum methylation level of MGMT promoter was decreased in GBM patients during propofol and sevoflurane anesthesia.
CONCLUSIONS
Propofol and sevoflurane anesthesia associated impact on the gene expression of GBM, included the methylation level of MGMT promoter. Propofol and sevoflurane anesthesia-based risk score prognostic model, which has good prognostic power and is an independent prognostic factor in GBM patients. Therefore, this model can be used as a new biomarker for judging the prognosis of GBM patients.KEY MESSAGESPropofol and sevoflurane anesthesia-based risk score prognostic model has good prognostic power and is an independent prognostic factor in GBM patients.High Propofol and sevoflurane anesthesia-based risk score GBM patients have high T-cell damage scores and are less sensitive to immunotherapy.Serum methylation level of MGMT promoter decrease during propofol and sevoflurane anesthesia in GBM patients.
Topics: Humans; Glioblastoma; Propofol; Sevoflurane; Prognosis; Anesthesia; Immunotherapy
PubMed: 36856519
DOI: 10.1080/07853890.2023.2171109 -
Medicine Aug 2023Cuproptosis, an unusual type of programmed cell death mechanism of cell death, involved the disruption of specific mitochondrial metabolic enzymes in the occurrence and...
Cuproptosis, an unusual type of programmed cell death mechanism of cell death, involved the disruption of specific mitochondrial metabolic enzymes in the occurrence and development of tumors. However, it was still unclear how the relationship between cuproptosis-related genes (CRGs) may contribute to hepatocellular carcinoma (HCC) potential the prognosis of HCC remained limited. Here, the landscape of 14 CRGs in HCC was evaluated using the Cancer Genome Atlas and International Cancer Genome Consortium datasets. And then, 4 CRGs (ATP7A, MTF1, GLS, and CDKN2A) were screened for the construction of risk signatures for prognosis and drug therapy. The HCC patients with CRGs high-risk showed poor prognosis than those with low risk. Moreover, the CRGs risk signature was shown to be an independent prognostic factor and associated with the immune microenvironment in HCC. Meanwhile, we constructed and verified a prognostic model based on cuproptosis-related lncRNAs (Cr-lncRNAs). We obtained 291 Cr-lncRNAs and constructed Cr-lncRNA prognosis signature based on 3 key Cr-lncRNAs (AC026356.1, NRAV, AL031985.3). The Cr-lncRNA prognosis signature was also an independent prognostic factor and associated with the immune microenvironment in HCC. Finally, the drug sensitivity database showed that 8 candidate drugs related to CRGs signature and Cr-lncRNAs signature. In summary, we evaluated and validated the CRGs and Cr-lncRNAs as potential predictive markers for prognosis, immunotherapy, and drug candidate with the personalized diagnosis and treatment of HCC.
Topics: Humans; Carcinoma, Hepatocellular; Immunotherapy; Liver Neoplasms; Prognosis; RNA, Long Noncoding; Tumor Microenvironment; Copper; Apoptosis
PubMed: 37653738
DOI: 10.1097/MD.0000000000034741 -
Biochemia Medica Oct 2023Carbohydrate sulfotransferases (CHST) catalyse the biosynthesis of proteoglycans that enable physical interactions and signalling between different neighbouring cells in... (Review)
Review
Carbohydrate sulfotransferases (CHST) catalyse the biosynthesis of proteoglycans that enable physical interactions and signalling between different neighbouring cells in physiological and pathological states. The study aim was to provide an overview of emerging diagnostic and prognostic applications of CHST. PubMed database search was conducted using the keywords "carbohydrate sulfotransferase" together with appropriate inclusion and exclusion criteria, whereby 41 publications were selected. Additionally, 40 records on CHST genetic and biochemical properties were hand-picked from UniProt, GeneCards, InterPro, and neXtProt databases. Carbohydrate sulfotransferases have been applied mainly in diagnostics of connective tissue disorders, cancer and inflammations. The lack of CHST activity was found in congenital connective tissue disorders while CHST overexpression was detected in different malignancies. Mutations of gene cause skeletal dysplasia, chondrodysplasia, and autosomal recessive multiple joint dislocations while increased tissue expression of , and is an unfavourable prognostic factor in ovarian cancer, glioblastoma and pancreatic cancer, respectively. Recently, and overexpression in the vascular smooth muscle cells was linked to the severe lung pathology in COVID-19 patients. Promising CHST diagnostic and prognostic applications have been described but larger clinical studies and robust analytical procedures are required for the more reliable diagnostic performance estimations.
Topics: Humans; Prognosis; COVID-19; Sulfotransferases; Mutation; COVID-19 Testing
PubMed: 37545696
DOI: 10.11613/BM.2023.030503 -
Frontiers in Immunology 2023Colorectal cancer is one of the most common gastrointestinal cancers and the second leading cause of cancer-related death. Although colonoscopy screening has greatly...
INTRODUCTION
Colorectal cancer is one of the most common gastrointestinal cancers and the second leading cause of cancer-related death. Although colonoscopy screening has greatly improved the early diagnosis of colorectal cancer, its recurrence and metastasis are still significant problems. Tumour cells usually have the hallmark of metabolic reprogramming, while fatty acids play important roles in energy storage, cell membrane synthesis, and signal transduction. Many pathways of fatty acid metabolism (FAM) are involved in the occurrence and development of colon cancer, and the complex molecular interaction network contains a variety of genes encoding key enzymes and related products.
METHODS
Clinical information and RNA sequencing data were collected from TCGA and GEO databases. The prognosis model of colon cancer was constructed by LASSO-Cox regression analysis among the selected fatty acid metabolism genes with differential expression. Nomogram for the prognosis model was also constructed in order to analyze its value in evaluating the survival and clinical stage of the colon cancer patients. The differential expression of the selected genes was verified by qPCR and immunohistochemistry. GSEA and GSVA were used to analyze the enrichment pathways for high- and low-risk groups. CIBERSORT was used to analyze the immune microenvironment of colon cancer and to compare the infiltration of immune cells in the high- and low-risk groups. The "circlize" package was used to explore the correlation between the risk score signature and immunotherapy for colon cancer.
RESULTS
We analysed the differential expression of 704 FAM-related genes between colon tumour and normal tissue and screened 10 genes with prognostic value. Subsequently, we constructed a prognostic model for colon cancer based on eight optimal FAM genes through LASSO Cox regression analysis in the TCGA-COAD dataset, and its practicality was validated in the GSE39582 dataset. Moreover, the risk score calculated based on the prognostic model was validated as an independent prognostic factor for colon cancer patients. We further constructed a nomogram composed of the risk score signature, age and American Joint Committee on Cancer (AJCC) stage for clinical application. The colon cancer cohort was divided into high- and low-risk groups according to the optimal cut-off value, and different enrichment pathways and immune microenvironments were depicted in the groups.
DISCUSSION
Since the risk score signature was significantly correlated with the expression of immune checkpoint molecules, the prognostic model might be able to predict the immunotherapy response of colon cancer patients. In summary, our findings expand the prognostic value of FAM-related genes in colon cancer and provide evidence for their application in guiding immunotherapy.
Topics: Humans; Prognosis; Lipid Metabolism; Nomograms; Colonic Neoplasms; Fatty Acids; Tumor Microenvironment
PubMed: 38045683
DOI: 10.3389/fimmu.2023.1301452