scholarly journals Identification of a Novel Five-Gene Signature as a Prognostic and Diagnostic Biomarker in Colorectal Cancers

2022 ◽  
Vol 23 (2) ◽  
pp. 793
Author(s):  
Souvik Ghatak ◽  
Syrina F. Mehrabi ◽  
Lubna M. Mehdawi ◽  
Shakti Ranjan Satapathy ◽  
Anita Sjölander
Keyword(s):  
In Silico ◽  
High Sensitivity ◽  
Gene Signature ◽  
Tnm Stage ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Systematic Exploration ◽  
Risk Stratification Model ◽  
Gender Status ◽  
And Gender

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality worldwide. The current TNM (Tumor, Node, and Metastasis) classification approach is suboptimal in determining the prognosis of CRC patients. The prognosis for CRC is affected by a variety of features that are present at the initial diagnosis. Herein, we performed a systematic exploration and established a novel five-panel gene signature as a prognostic and early diagnosis biomarker after performing differential gene expression analyses in five independent in silico CRCs cohort and independently validating it in one clinical cohort, using immunohistochemistry. Four genes (BDNF, PTGS2, GSK3B, and CTNNB1) were significantly upregulated and one gene (HPGD) was significantly downregulated in primary tumor tissues compared with adjacent normal tissues throughout all the five in silico datasets. The univariate CoxPH analysis yielded a five-gene signature that accurately predicted overall survival (OS) and recurrence-free survival (RFS) in the in silico training (AUC = 0.73 and 0.69, respectively) and one independent in silico validation cohort (AUC = 0.69 and 0.74, respectively). This five-gene signature demonstrated significant associations with poor OS in independent clinical validation cohorts of colon cancer (CC) patients (AUC = 0.82). Intriguingly, a risk stratification model comprising of the five-gene signature together with TNM stage and gender status achieved an even superior AUC of 0.89 in the clinical cohorts. On the other hand, the circulating mRNA expression of the upregulated four-gene signature achieved a robust AUC = 0.83 with high sensitivity and specificity as a diagnosis marker in plasma from CRC patients. We have identified a novel, five-gene signature as an independent predictor of OS, which in combination with TNM stage and gender offers an easy-to-translate and facile assay for the personalized risk-assessment in CRC patients.

scholarly journals A Novel Five-gene Signature Predicts Overall Survival in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhigang Wang ◽  
Leyu Pan ◽  
Deliang Guo ◽  
Xiaofeng Luo ◽  
Jie Tang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Signature ◽  
Tnm Stage ◽  
Time Dependent ◽  
Quantitative Real Time Pcr ◽  
Cox Regression Analysis ◽  
Normal Tissues

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common challenges for public health worldwide. Due to its complex molecular and great heterogeneity, the effectiveness of existing HCC risk prediction models is unsatisfactory. Hence, more accurate prognostic models are pressingly needed. Materials and methods: Differentially expressed mRNAs (DEMs) between HCC and normal tissues were identified after downloading GSE1450 from gene omnibus (GEO) database. We randomly divided all patients into training and testing sets. Univariate Cox regression, lasso Cox regression and multivariable Cox regression analysis were used to constructed the prognostic gene signature in training set. Our study utilized Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis with clinical information, nomogram and decision curve analysis (DCA) to evaluate the predictive ability for overall survival of the novel gene signature in training, testing and whole sets. We also validated the prognostic capacity of the five-gene signature in an external validation set. The information of mutation of each gene was explored on cBioPortal online website. We performed gene set enrichment analysis (GSEA) to explore underlying mechanisms in the high and low risk group. Finally, quantitative real-time PCR was conducted to validate the expression tendency between 12 paired HCC and adjacent normal tissues. Results: Our study constructed a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2 and CCL19) for predicting overall survival of HCC. Time-dependent ROC curve indicated admirable ability in survival prediction in two datasets. Multivariable Cox regression analysis indicated that both this five-gene signature and TNM stage were two independent prognostic factors for overall survival of HCC patients. Combined with TNM stage clinical pathological parameters, the predictive capacity of nomogram had a decent improvement. The mutation of the five genes had no obvious variation. Plenty pathways were enriched by GSEA, including cell cycle and various metabolism. Furthermore, the mRNA levels of these five genes had significantly different expressions between HCC tissues and adjacent normal tissues by quantitative real-time PCR. Conclusions: A five-gene prognostic model and nomogram were constructed and validated for predicting prognostic of HCC patients. And the five-gene risk score with TNM stage models might help various HCC patients to customize individual therapies.

scholarly journals Systematic Profiling of Invasion-related Genes Signature Predicts Prognostic Features and Identificates Molecular Subtypes of Lung Adenocarcinoma

2021 ◽  
Author(s):  
Ping Yu ◽  
Linlin Tong ◽  
Yujia Song ◽  
Hui Qu ◽  
Ying Chen
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Molecular Subtypes ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Cox Analysis

Abstract Background: Due to the high heterogeneity of lung adenocarcinoma (LUAD), molecular subtype based on gene expression profiles is of great significance for diagnosis, and prognosis prediction in patients with LUAD.Methods: Invasion-related genes were obtained from the CancerSEA database, and LUAD expression profiles were downloaded from The Cancer Genome Atlas. The ConsensusClusterPlus was used to obtain molecular subtypes based on invasion-related genes. The limma software package was used to identify differentially expressed genes (DEGs). A multi-gene risk model was constructed by Lasso-Cox analysis. A nomogram was also constructed based on risk scores and meaningful clinical features.Results: 3 subtypes (C1, C2, C3) based on the expression of invasion-related genes were obtained. C3 had the worst prognosis. A total of 669 DEGs were identified among the subtypes. Pathway enrichment analysis results showed that the DEGs were mainly enriched in the cell cycle, DNA replication, the p53 signaling pathway, and other tumor-related pathways. A 5-gene signature (KRT6A, MELTF, IRX5, MS4A1, CRTAC1) was identified by using Lasso-Cox analysis. The training, validation, and external independent cohorts proved that the model was robust and had better prediction ability than other lung cancer models. The gene expression results showed that the expression levels of MS4A1 and KRT6A in tumor tissues were higher than in normal tissues, while CRTAC1 expression in tumor tissues was lower than in normal tissues. At the same time, the 5 genes were significantly expressed in pan-cancer immune subtypes. Gene set enrichment analysis showed that MS4A1, KRT6A, and CRAT1 genes were both enriched in the HALLMARK_IL2_STAT5_SIGNALING pathway, and IRX5 and MELTF gene were both enriched in the HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION pathway. Conclusion: The 5-gene signature prognostic stratification system based on invasion-related genes could be used to assess prognostic risk in patients with LUAD.

Calreticulin is Differentially Expressed in Invasive Ductal Carcinoma: A Comparative Study

2019 ◽  
Vol 16 (2) ◽  
pp. 148-155
Author(s):  
Asma Tariq ◽  
Rana Muhammad Mateen ◽  
Iram Fatima ◽  
Muhammad Waheed Akhtar
Keyword(s):  
Invasive Ductal Carcinoma ◽  
Tumor Tissue ◽  
Ductal Carcinoma ◽  
Tissue Level ◽  
Differentially Expressed ◽  
Breast Cancer Patients ◽  
Two Dimensional Gel Electrophoresis ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Grade Ii

Objective: The aim of the present study was to build protein profiles of untreated breast cancer patients of invasive ductal carcinoma grade II at tissue level in Pakistani population and to compare 2-D profiles of breast tumor tissues with matched normal tissues in order to evaluate for variations of proteins among them. Materials & Methods: Breast tissue profiles were made after polytron tissue lysis and rehydrated proteins were further characterized by using two-dimensional gel electrophoresis. On the basis of isoelectric point (pI) and molecular weight, proteins were identified by online tool named Siena 2-D database and their identification was further confirmed by using MALDI-TOF. Results: Among identified spots, 10 proteins were found to be differentially expressed i.e.; COX5A, THIO, TCTP, HPT, SODC, PPIA, calreticulin (CRT), HBB, albumin and serotransferrin. For further investigation, CRT was selected. The level of CRT in tumors was found to be significantly higher than in normal group (p < 0.05). The increased expression of CRT level in tumor was statistically significant (p = 0.010) at a 95% confidence level (p < 0.05) as analyzed by Mann-Whitney. CRT was found distinctly expressed in high amount in tumor tissue as compared to their matched normal tissues. Conclusion: It has been concluded that CRT expression could discriminate between normal tissue and tumor tissue so it might serve as a possible candidate for future studies in cancer diagnostic markers.

scholarly journals Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Feng Jiang ◽  
Chuyan Wu ◽  
Ming Wang ◽  
Ke Wei ◽  
Jimei Wang
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Single Gene ◽  
Prediction Method ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Cox Models ◽  
Normal Tissues ◽  
Predictive Risk

AbstractOne of the most frequently identified tumors and a contributing cause of death in women is breast cancer (BC). Many biomarkers associated with survival and prognosis were identified in previous studies through database mining. Nevertheless, the predictive capabilities of single-gene biomarkers are not accurate enough. Genetic signatures can be an enhanced prediction method. This research analyzed data from The Cancer Genome Atlas (TCGA) for the detection of a new genetic signature to predict BC prognosis. Profiling of mRNA expression was carried out in samples of patients with TCGA BC (n = 1222). Gene set enrichment research has been undertaken to classify gene sets that vary greatly between BC tissues and normal tissues. Cox models for additive hazards regression were used to classify genes that were strongly linked to overall survival. A subsequent Cox regression multivariate analysis was used to construct a predictive risk parameter model. Kaplan–Meier survival predictions and log-rank validation have been used to verify the value of risk prediction parameters. Seven genes (PGK1, CACNA1H, IL13RA1, SDC1, AK3, NUP43, SDC3) correlated with glycolysis were shown to be strongly linked to overall survival. Depending on the 7-gene-signature, 1222 BC patients were classified into subgroups of high/low-risk. Certain variables have not impaired the prognostic potential of the seven-gene signature. A seven-gene signature correlated with cellular glycolysis was developed to predict the survival of BC patients. The results include insight into cellular glycolysis mechanisms and the detection of patients with poor BC prognosis.

The RAV12 Monoclonal Antibody Recognizes the N-Linked Glycotope RAAG12: Expression in Human Normal and Tumor Tissues

2009 ◽  
Vol 133 (9) ◽  
pp. 1403-1412
Author(s):  
Suzanne K. Coberly ◽  
Francine Z. Chen ◽  
Mark P. Armanini ◽  
Yan Chen ◽  
Peter F. Young ◽  
...  
Keyword(s):  
Monoclonal Antibody ◽  
Antigen Expression ◽  
Subcellular Location ◽  
Carbohydrate Antigen ◽  
Cytoplasmic Staining ◽  
Safety Issues ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Associated Proteins

Abstract Context.—RAAG12 is a primate-restricted N-linked carbohydrate antigen present on multiple membrane-associated proteins. RAAG12 is recognized by the RAV12 monoclonal antibody. RAV12 binds to RAAG12-expressing gastrointestinal adenocarcinomas, modifies growth factor-mediated signaling, induces oncotic cell death in vitro, and has antitumor activity toward gastrointestinal tumor xenografts. Objective.—To determine the expression pattern of RAAG12 in normal and tumor tissue to identify indications for clinical study and potential safety issues. Design.—Immunohistochemistry of 36 normal human tissues and a broad range of tumor tissues to profile RAAG12 expression. Results.—More than 90% of colon, gastric, and pancreatic adenocarcinomas expressed RAAG12, and expression was uniform in most samples. Expression of RAAG12 at lower frequency and/or uniformity was observed in other cancers, including esophageal, ovarian, liver, breast, and prostate carcinomas and adenocarcinomas. Similar RAAG12 expression was observed between primary and metastatic colon adenocarcinomas. No staining was seen on cardiovascular, endocrine, neuromuscular, hematopoietic, or nervous system tissue from non–tumor-bearing individuals. RAAG12 was expressed on mucosal and glandular/ductal epithelium. The gastrointestinal tract mucosa and pancreatic/biliary ducts displayed the most uniform reactivity. RAAG12 exhibited differential subcellular localization in these normal, compared with tumor, tissues. Normal polarized epithelia primarily displayed apical membrane and cytoplasmic staining, whereas tumors exhibited whole membrane staining that increased with decreasing differentiation. Conclusions.—High expression of RAAG12 on tumors of gastrointestinal origin suggests these cancers are appropriate targets for RAV12 therapy. Differential subcellular location of RAAG12 on normal epithelia may limit accessibility of RAV12 to the subset of normal tissues that exhibit antigen expression.

TOXOHORMONE IN BACTERIA-FREE TUMORS

1966 ◽  
Vol 44 (8) ◽  
pp. 1069-1087 ◽  
Author(s):  
J. C. Nixon ◽  
B. Zinman
Keyword(s):  
Gel Filtration ◽  
Human Kidney ◽  
Metastatic Carcinoma ◽  
Exchange Chromatography ◽  
Human Spleen ◽  
Normal Tissues ◽  
Highly Active ◽  
Normal Human Kidney ◽  
Tumor Tissues ◽  
Normal Human

Toxohormone was extracted from bacteria-free human tumors and normal tissues, and assayed for activity by measuring the decrease in serum iron levels of rats 12 hours after injection of the extracts. In contrast with the findings of others, the results of the present study demonstrated that active toxohormone could be isolated from bacteria-free tumor tissues. Bacteria-free normal human kidney and spleen also yielded active toxohormone extracts, whereas extracts of normal human- and rat-skeletal muscle and rat liver had no activity.Four active toxohormone extracts were purified by ion-exchange chromatography followed by gel filtration. Human leukemic spleen, metastatic carcinoma of the cecum, and normal human spleen and kidney yielded several highly active purified fractions.

scholarly journals Identification of key genes related to macrophage infiltration in gastric cancer based on WGCNA

2020 ◽  
Author(s):  
Haiyan Chen ◽  
Cangang Zhang ◽  
Shuai Cao ◽  
Meng Cao ◽  
Nana Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Immune Cell ◽  
Accurate Diagnosis ◽  
Marker Genes ◽  
Hub Genes ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
New Strategy ◽  
Tumor Environment ◽  
Advanced Stages

Abstract Background: Gastric cancer (GC) is rampant around the world. Most of the GC cases are detected in advanced stages with poor prognosis. The identification of marker genes for early diagnosis is of great significance. Studying the tumor environment is helpful to acknowledge the process of tumorigenesis, development, and metastasis.Methods: In GEO, 22 kinds of immune cell infiltration were calculated by CIBERSORT. Macrophages were discovered remarkably infiltrated higher in GC compared with normal tissues. WGCNA was utilized to construct the network and then identify key modules and genes related to macrophages in TCGA.Results: Finally, 18 hub genes were verified. In the PPI bar chart, the top 3 genes were chosen as hub genes involved in most pathways. On the TIMER and THPA websites, it is verified that the expression levels of CYBB, CD86 and C3AR1 genes in tumor tissues were higher than those in normal tissues.Conclusion: These genes may work as biomarkers or targets for accurate diagnosis and treatment of GC in the future. Our findings may be a new strategy for the treatment of GC.

scholarly journals The Expression of miR-513c and miR-3163 was Downregulated in Tumor Tissues Compared with Margin Tissues of Patients With Breast Cancer

2020 ◽  
Author(s):  
Soheila Delgir ◽  
Khandan Ilkhani ◽  
Asma Safi ◽  
Farhad Seif ◽  
Milad Bastami ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
In Silico ◽  
In Silico Analysis ◽  
Glutamine Metabolism ◽  
Expression Level ◽  
P Value ◽  
Biological Processes ◽  
Tumor Tissues ◽  
Silico Analysis

Abstract Background Breast cancer (BC) is the most common invasive cancer with different subtypes that its metabolism is unique compared with normal cells. Glutamine is considered a critical nutrition for tumor cell growth and therefore, targeting glutamine metabolism, especially Glutaminase, which catalyzed the conversion of glutamine to glutamate can be beneficial to design anti-cancer agents. Recently, evidence has shown that miRNAs with short length and single strand properties play a significant role in regulating the genes related to glutamine metabolism and may control the development of cancer.Methods Since, in-silico analysis confirmed that miR-513c and miR-3163 might be involved in glutamine metabolism, the expression level of these two miRNAs was evaluated in eighty BC tissues and margin tissues. The data were analyzed to evaluate the correlation between expression level of these miRNAs and patient’s characteristics such as abortion history, family history, and age. Furthermore, in-silico analysis was applied to predict the potential biological processes and molecular pathways of miR-513c and miR-3163 based on its gene targets.Results In-silico studies revealed the top categories of biological processes and pathways that play a critical role in cancer development were target genes for miR-513c and miR-3163. The current study showed that miR-513c (P-value = 0.02062 and fold change= -2.3801) and miR-3163 (P-value = 0.02034 and fold change= -2.3792) were downregulated in tumor tissues compared to margin tissues. Furthermore, the subgroup studies did not show any substantial relationship between expression levels of these two miRNAs and factors such as age, family history cancer, and abortion.Conclusion Based on our data, miR-513c and miR-3163 may be offered as a potential diagnosis and therapeutic targets for patients with BC.

scholarly journals Interleukin 37 Expression was Negatively Associated with Pathological Grading in Human Gliomas

2021 ◽  
Author(s):  
Sheng Liu ◽  
Ying Ba ◽  
Chenglong Li ◽  
Mengyang Xing ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Survival Time ◽  
Grade Level ◽  
Brain Injuries ◽  
Control Group ◽  
Normal Brain ◽  
Normal Tissues ◽  
Pathological Type ◽  
Tumor Tissues ◽  
Clinicopathologic Factors ◽  
Immunohistochemical Techniques

Abstract Background: Little is known about the roles of interleukin 37 (IL-37), a newly identified cytokine, in the pathogenesis of cancer. In this study, we aimed to determine the expression of IL-37 in gliomas with different pathological grades and evaluated its effects on survival. Methods: Ninety-five participants with different pathological grades of glioma were included in this study, which were classified into grade I-II (n=27), grade III (n=30), and grade IV (n=38). Ten normal brain tissues that were resected for intracranial decompression after traumatic brain injuries served as control group. The expression of IL-37 mRNA and protein in glioma tissues was determined using Real-time PCR and immunohistochemical techniques. The association between IL-37 expression and various clinicopathologic factors was evaluated. Results: IL-37 mRNA was expressed in normal tissues and tumor tissues, and the expression of IL-37 in tumor tissues were significantly higher than normal brain tissue (p<0.05). IL-37 expression showed decline with the increase of grade level. The expression of IL-37 was significantly lower in glioma tissues of a high malignancy compared with the glioma tissues of a low malignancy. Patients with low IL-37 expression showed a shorter survival time. Conclusions: Low IL-37 expression was negatively correlated with pathological grade, rather than pathological type. Low IL-37 was positively correlated with survival time. Thus, IL-37 maybe plays an inhibitory role in glioma progression.

Sign in / Sign up

Export Citation Format

Share Document