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Construction of risk assessment model by LASSO and Cox regression analysis in training group. (A) Selection of the optimal parameter (lambda) in the LASSO model for STAD. (B) LASSO coefficient profiles of genes in STAD. A coefficient profile plot was generated against the log (lambda) sequence. (C) After optimization by Cox analysis, 10 mRNAs were selected to construct the risk assessment model as shown in forest graph. LASSO -least absolute shrinkage and selection operator; STAD -stomach adenocarcinoma.
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Background
Increasing studies have shown the important clinical role of immune and stromal cells in gastric cancer microenvironment. Based on information of immune and stromal cells in The Cancer Genome Atlas, this study aimed to construct a prognostic risk assessment model for gastric cancer.
Material/Methods
Based on the immune/structural scores...
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Citations
... It has been reported that the overexpression of PRSS23 is associated with poor prognosis and macrophage infiltration in GC patients, promoting tumorigenesis and progression [41,42]. Decreased RNASE1, a member of novel gene signatures with prognostic implications in the GC microenvironment, has been reported [43,44]. Consistent with previous studies, reduced RNASE1 was observed in GAC. ...
Background:
Gastric adenocarcinoma (GAC) is a malignant tumor with the highest incidence in the digestive system. Macrophages have been proven to play important roles in tumor microenvironment.
Methods:
Herein, single-cell RNA sequencing (scRNA-seq) profiles from the Gene Expression Omnibus (GEO) and bulk RNA-seq data from the Cancer Genome Atlas (TCGA) database were utilized to construct a macrophage marker gene signature (MMGS) to predict the prognosis of GAC patients. Subsequently, a risk score model based on the MMGS was built to predict the prognosis of GAC patients; further, this was validated in the GEO cohort. The risk score categorized patients into the high- and low-risk groups. A nomogram model based on the risk score and clinic-pathological characteristics was developed.
Results:
Seven genes, ABCA1, CTHRC1, GADD45B, NPC2, PLTP, PRSS23, and RNASE1, were included in the risk score model. Patients with a low-risk score showed a better prognosis. The MMGS had good sensitivity and specificity for predicting the prognosis inGAC patients. The risk score was an independent prognostic factor. The constructed nomogram exhibited favorable predictability and reliability for predicting GAC prognosis.
Conclusion:
In conclusion, the risk score model based on the seven MMGSs performed well in the predicting prognosis of GAC patients. Our study may provide new insights into clinical decision-making for the personalized treatment of patients with gastric cancer (GC).
... Microsomal human lanosterol-14-alpha-demethylase (CYP51A1) has been considered as a therapeutic target for the development of new anticholesterolemic drugs [26][27][28]. It was shown that anticancer steroidal drugs interact with human CYP51A1 [29] and CYP51A1 gene expression level correlated with the survival rate of patients with gastric adenocarcinoma [30]. We have shown previously that CYP51A1 is inhibited by the luteolin 7,3′-disulphate (LDS) [31]. ...
Cytochromes P450 (CYP) are a family of membrane proteins involved in the production of endogenous molecules and the metabolism of xenobiotics. It is well-known that the composition of the membrane can influence the activity and orientation of CYP proteins. However, little is known about how membrane composition affects the ligand binding properties of CYP. In this study, we utilized surface plasmon resonance and fluorescence lifetime analysis to examine the impact of membrane micro-environment composition on the interaction between human microsomal CYP51 (CYP51A1) and its inhibitor, luteolin 7,3’′-disulphate (LDS). We observed that membranes containing cholesterol or sphingomyelin exhibited the lowest apparent equilibrium dissociation constant for the CYP51A1-LDS complex. Additionally, the tendency for relation between kinetic parameters of the CYP51A1-LDS complex and membrane viscosity and overall charge was observed. These findings suggest that the specific composition of the membrane, particularly the presence of cholesterol and sphingomyelin, plays a vital role in regulating the interaction between CYP enzymes and their ligands.
... A few studies have investigated the role of TRIBs in GC, mostly focusing on the TRIB3 gene. Its expression was associated with either worse or more favorable prognosis, depending on the study [13,14], and was suggested to have predictive value in the prognostic stratification of GC patients [15]. So far, there is one only study on TRIB2 in GC, reporting that its level is downregulated in MGC-803 GC cells following treatment with the anti-cancer agent dioscin [16]. ...
... No association between TRIB1 mRNA expression and a CIN phenotype was found (Figure 3a). Studies assessing the prognostic value of TRIB3 overexpression, albeit controv have been reported [13][14][15], as well as work on its anti-apoptotic role in doxoru treated GC cell lines [17]. In contrast, the TRIB2 gene had not already been invest for its role in GC. ...
... Therefore, we focused on TRIB2 for further analyses. We corr TRIB2 gene expression ( Studies assessing the prognostic value of TRIB3 overexpression, albeit controversial, have been reported [13][14][15], as well as work on its anti-apoptotic role in doxorubicin-treated GC cell lines [17]. In contrast, the TRIB2 gene had not already been investigated for its role in GC. ...
Tribbles pseudokinases (TRIB1-3) are important signaling modulators involved in several cancers. However, their function in gastric cancer (GC) remains undefined. GC is still a deadly disease since the lack of sensitive and specific biomarkers for early diagnosis and therapy response prediction negatively affects patients’ outcome. The identification of novel molecular players may lead to more effective diagnostic and therapeutic avenues. Therefore, we investigated the role of TRIB genes in gastric tumorigenesis. Data mining of the TCGA dataset revealed that chromosomal instability (CIN) tumors have lower TRIB2 and higher TRIB3 expression versus microsatellite instability (MSI)-high tumors, while TRIB1 levels are similar in both tumor types. Moreover, in CIN tumors, low TRIB2 expression is significantly associated with aggressive stage IV disease. As no studies on TRIB2 in GC are available, we focused on this gene for further in vitro analyses. We checked the effect of TRIB2 overexpression (OE) on MKN45 and NCI-N87 CIN GC cell lines. In MKN45 cells, TRIB2 OE reduced proliferation and colony formation ability and induced G2/M arrest, while it decreased the proliferation and cell motility of NCI-N87 cells. These effects were not mediated by the MAPK pathway. Our results suggest a tumor-suppressive function of TRIB2 in GC with a CIN phenotype.
... In addition, the overall survival (OS) and disease-free survival of patients with colorectal cancer expressing high SLC17A9 levels in tumor tissues were poor (3). Studies have demonstrated that the survival of patients with gastric cancer expressing high SLC17A9 levels was poor (4,5). SLC17A9 affects liver hepatocellular carcinoma (LIHC) progression. ...
Previous studies have demonstrated the involvement of the solute carrier family 17 member 9 (SLC17A9) in certain types of cancer; however, the precise role of SLC17A9 is not well defined. In the present study, a comprehensive analysis was performed to determine the involvement of SLC17A9 in a pan-cancer panel. First, data on SLC17A9 expression levels from publicly available databases were obtained to determine SLC17A9 expression profiles in various types of cancer. Next, the involvement of SLC17A9 in the prognosis of patients, stemness indices and the immune microenvironment was examined in 34 types of cancer. Furthermore, CCK-8 and colony-formation assays were performed to determine the effect of SLC17A9 on osteosarcoma (OSS) cells. In a pan-cancer panel, a difference in SLC17A9 expression levels was observed in the tumor tissues as compared with healthy tissues. Furthermore, survival analysis revealed a significant association between SLC17A9 expression levels and the prognosis of patients with various cancer types, including adrenocortical carcinoma, kidney renal clear cell carcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, liver hepatocellular carcinoma, mesothelioma, lung adenocarcinoma, skin cutaneous melanoma, uveal melanoma, stomach adenocarcinoma and OSS. The results of the present study revealed correlations between stemness indices, tumor immunity and SLC17A9 expression levels. Furthermore, univariate and multivariate Cox regression analyses indicated that SLC17A9 may be utilized as an independent risk factor for overall survival of patients with OSS. In vitro experiments demonstrated that SLC17A9 promotes the proliferation and viability of OSS cells. Taken together, the results of the present study suggest an association between SLC17A9 and the prognosis of patients as well as tumor immunity in various cancer types. SLC17A9 may serve as a novel prognostic biomarker and target for improving the prognosis of patients with OSS.
... It has been reported that SLC17A9 could affect cell viability by influencing lysosome dysfunction. 7,8 Although the prognostic value of SLC17A9 has been evaluated in prostate cancer, hepatocellular carcinoma, gastric carcinoma, and colorectal cancer, [9][10][11][12] there is still a need to investigate whether SLC17A9 could act as a potential biomarker for ccRCC and elucidate the role of SLC17A9 in promoting tumor progression. As an important transport protein, several drugs targeting SLC17A9 have been investigated for the treatment of steatohepatitis, acute liver injury, type 2 diabetes, and depression. ...
... Although it was reported that SLC17A9 acted as an oncogene for prostate cancer, 9 hepatocellular carcinoma, 12 gastric carcinoma, 11 and colorectal cancer, 10 the role of SLC17A9 in ccRCC has not been studied. TCGA-KIRC data was used to evaluate the expression levels of SLC17A9 in renal cancer, and ICGC-RECA-EU data was used to validate its high expression. ...
SLC17A9 is a vesicular ATP transport protein that plays an important role in determining cell functions and the onset and progression of different diseases. In this study, SLC17A9 was initially identified as a potential diagnostic and prognostic risk biomarker for clear cell renal cell carcinoma (ccRCC). Then, the aberrant expression levels of SLC17A9 were confirmed in both the cell lines and clinical tissues. Mechanistically, SLC17A9 could upregulate the expression of PTHLH, thus promoting epithelial-mesenchymal transition (EMT) in ccRCC. Functionally, SLC17A9 knockdown inhibited the proliferation, migration, and invasion activity of renal cancer cells, while its overexpression led to stronger cell viability and more malignant phenotype in vitro. The overexpression of SLC17A9 in vivo could significantly contribute to the growth of tumors. Finally, we found that SLC17A9 might be related to the drug resistance of vorinostat. Cumulatively, this study demonstrated that the SLC17A9-PTHLH-EMT axis could promote the progression of ccRCC.
... Laszlo et al. (2015) made a point that MMRN1 could be used as a new marker to refine pediatric acute myeloid leukemia. Sun et al. (2020) found that MMRN1 is one of the characteristic genes associated with GC prognosis. CD59 is a glycosylphosphatidylinositol (GPI)-anchored membrane protein that regulates complement activation by inhibiting membrane attack complex (MAC) formation (Zhang et al., 2018). ...
Background: Gastric cancer (GC) is the most common malignant tumor. Due to the lack of practical molecular markers, the prognosis of patients with advanced gastric cancer is still poor. A number of studies have confirmed that the coagulation system is closely related to tumor progression. Therefore, the purpose of this study was to construct a coagulation-related gene signature and prognostic model for GC by bioinformatics methods.
Methods: We downloaded the gene expression and clinical data of GC patients from the TCGA and GEO databases. In total, 216 coagulation-related genes (CRGs) were obtained from AmiGO 2. Weighted gene co-expression network analysis (WGCNA) was used to identify coagulation-related genes associated with the clinical features of GC. Last absolute shrinkage and selection operator (LASSO) Cox regression was utilized to shrink the relevant predictors of the coagulation system, and a Coag-Score prognostic model was constructed based on the coefficients. According to this risk model, GC patients were divided into high-risk and low-risk groups, and overall survival (OS) curves and receiver operating characteristic (ROC) curves were drawn in the training and validation sets, respectively. We also constructed nomograms for predicting 1-, 2-, and 3-year survival in GC patients. Single-sample gene set enrichment analysis (ssGSEA) was exploited to explore immune cells’ underlying mechanisms and correlations. The expression levels of coagulation-related genes were verified by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).
Results: We identified seven CRGs employed to construct a Coag-Score risk model using WGCNA combined with LASSO regression. In both training and validation sets, GC patients in the high-risk group had worse OS than those in the low-risk group, and Coag-Score was identified as an independent predictor of OS, and the nomogram provided a quantitative method to predict the 1-, 2-, and 3-year survival rates of GC patients. Functional analysis showed that Coag-Score was mainly related to the MAPK signaling pathway, complement and coagulation cascades, angiogenesis, epithelial–mesenchymal transition (EMT), and KRAS signaling pathway. In addition, the high-risk group had a significantly higher infiltration enrichment score and was positively associated with immune checkpoint gene expression. Conclusion: Coagulation-related gene models provide new insights and targets for the diagnosis, prognosis prediction, and treatment management of GC patients.
... This finding led to the 17-gene leukaemia stem cell score (17LSC) which provides a prognostic measure of patient survival [102,136,137]. Similarly, MMRN1 expression levels alongside nine other mRNAs provide a prognostic risk score for gastric cancer patients [138], and Cai et al. [139] included MMRN1 expression in a risk score of papillary thyroid cancer. The observed correlation between MMRN1 expression and cancer risk scores highlights MMRN1 relevance in the disease process. ...
Multimerin-1 (MMRN1) is a platelet protein with a role in haemostasis and coagulation. It is also present in endothelial cells and the extracellular matrix, where it may be involved in cell adhesion, but its molecular functions and protein-protein interactions in these cellular locations have not been studied in detail yet. In recent years, MMRN1 has been identified as a differentially expressed gene in various cancers and it has been proposed as a possible cancer biomarker. Some evidence suggests that MMRN1 expression is regulated by methylation, protein interactions, and non-coding RNAs in different cancers. This raises the questions if a functional role of MMRN1 is being targeted during cancer development, and if MMRN1’s differential expression pattern correlates with cancer progression. As a result, it is timely to review the current state of what is known about MMRN1 to help inform future research into MMRN1’s molecular mechanisms in cancer.
... SLC17A9 can be used as a new molecular marker to predict the poor prognosis of patients with hepatocellular carcinoma 37 . It is also may play a role in the progression of colorectal cancer 38 and may potentially be used as an independent biomarker for gastric carcinoma prognostic evaluation as well 39,40 . KCNS1 was reported as a bone metastasis signature using a supervised classification approach in a large series of breast cancer patients 41 and variations in this potassium channel genes were associated with the occurrence of preoperative breast pain 42 . ...
Melanoma antigen gene (MAGE)-A6 and MAGE-A11 are two of the most cancer-testis antigens overexpressed in various types of cancers. However, the clinical and prognosis value of MAGE-A6 and MAGE-A11 co-expression in the pathophysiology of the bladder is unknown. Three studies were selected from GEO databases in order to introduce the common genes that are involved in bladder cancer. Then immunohistochemical analysis for staining pattern and clinicopathological significance of suggested markers, MAGE-A6 and MAGE-A11, were performed in 199 and 213 paraffin-embedded bladder cancer with long adjacent normal tissues, respectively. A significant and positive correlation was found between both nuclear and cytoplasmic expressions of MAGE-A6 as well as expression of cytoplasmic MAGE-A11 with histological grade, PT stage, lamina propria invasion, and LP/ muscularis (L/M) involvement (all of the p-values in terms of H-score were < 0.0001). Additionally, significant differences were found between both nuclear and cytoplasmic MAGE-A6/MAGE-A11 phenotypes with tumor size (P = 0.007, P = 0.043, respectively), different histological grades, PT stage, LP involvement, and L/M involvement (all of the p-values for both phenotypes were < 0.0001). The current study added the value of these novel markers to the bladder cancer clinical settlement that might be considered as an admirable target for immunotherapy.
... According to the COSMIC (http://cancer.sanger.ac.uk/cosmic) resource, the CYP51A1 gene has a fairly low somatic mutation frequency (<0.1%) in various cancers. It has been shown that CYP51A1 gene expression correlates with the estrogen and progesterone receptor status of breast cancer [6] and could be one of the factors in assessing the survival rate of patients with gastric adenocarcinoma [7]. CYP51A1 catalyzes the production of 4,4-dimethyl-5α-cholesta-8,14,24-triene-3β-ol (follicular fluid meiosis-activating sterol, FF-MAS), one of the modulators of meiosis [8]. ...
Widespread pathologies such as atherosclerosis, metabolic syndrome and cancer are associated with dysregulation of sterol biosynthesis and metabolism. Cholesterol modulates the signaling pathways of neoplastic transformation and tumor progression. Lanosterol 14-alpha demethylase (cytochrome P450(51), CYP51A1) catalyzes one of the key steps in cholesterol biosynthesis. The fairly low somatic mutation frequency of CYP51A1, its druggability, as well as the possibility of interfering with cholesterol metabolism in cancer cells collectively suggest the clinical importance of CYP51A1.
Here, we show that the natural flavonoid, luteolin 7,3'-disulfate, inhibits CYP51A1 activity. We also screened baicalein and luteolin, known to have antitumor activities and low toxicity, for their ability to interact with CYP51A1. The Kd values were estimated using both a surface plasmon resonance optical biosensor and spectral titration assays. Unexpectedly, in the enzymatic activity assays, only the water-soluble form of luteolin—luteolin 7,3'-disulfate—showed the ability to potently inhibit CYP51A1. Based on molecular docking, luteolin 7,3'-disulfate binding suggests blocking of the substrate access channel. However, an alternative site on the proximal surface where the redox
partner binds cannot be excluded. Overall, flavonoids have the potential to inhibit the activity of human CYP51A1 and should be further explored for their cholesterol-lowering and anti-cancer activity.
... Among the identified 13 genes (ADAT3, TMEM171, DCBLD2, MARCKS, CLIP4, CTNNAL1, PIP4K2A, ZBTB10, NRP1, CST6, PLTP, CD109, and JAZF1) in our study, overexpression of MARCKS, CLIP4, NRP1, PLTP, CD109 has been previously associated with poor prognosis of GC [19][20][21][22][23]. MARCKS aggravates gastric cancer tumorigenesis and progression via EMT pathway [19]. ...
Gastric cancer represents a major public health problem. Owing to the great heterogeneity of GC, conventional clinical characteristics are limited in the accurate prediction of individual outcomes and survival. This study aimed to establish a robust gene signature to predict the prognosis of GC based on multiple datasets. Initially, we downloaded raw data from four independent datasets of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and performed univariate Cox proportional hazards regression analysis to identify prognostic genes associated with overall survival (OS) from each dataset. Thirteen common genes from four datasets were screened as candidate prognostic signatures. Then, a risk score model was developed based on this 13‑gene signature and validated by four independent datasets and the entire cohort. Patients with a high-risk score had poorer OS and recurrence-free survival (RFS). Multivariate regression and stratified analysis revealed that the 13-gene signature was not only an independent predictive factor but also associated with recurrence when adjusting for other clinical factors. Furthermore, in the high-risk group, gene set enrichment analysis (GSEA) showed that the mTOR signaling pathway and MAPK signaling pathway were significantly enriched. The present study provided a robust and reliable gene signature for prognostic prediction of both OS and RFS of patients with GC, which may be useful for delivering individualized management of patients.
