The Diagnostic Value of Arginase-1, FTCD, and MOC-31 Expression in Early Detection of Hepatocellular Carcinoma (HCC) and in Differentiation Between HCC and Metastatic Adenocarcinoma to the Liver

Labib, O. H.; Harb, Ola A.; Khalil, Osama H; Baiomy, Taha A.; Gertallah, Loay M.; Ahmed, Rham Z.

doi:10.1007/s12029-019-00211-2

Cited by 18 publications

(15 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, it serves as a useful diagnostic biomarker for distinguishing early stage HCC from benign tumors [ 53 ]. Moreover, most hepatocellular and metastatic cancers are diagnosed by examining the combined expression of arginase 1 + FTCD + MOC 31 [ 54 ]. In addition, FTCD has also been found to correlate with drug sensitivity to methotrexate chemotherapy [ 55 ].…”

Section: Discussionmentioning

confidence: 99%

Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

Wang

et al. 2021

Cancer Cell Int

View full text Add to dashboard Cite

Background The aim of this study was to construct a model based on the prognostic features associated with epithelial–mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma (HCC) cells. Methods EMT-associated genes were identified, and their molecular subtypes were determined by consistent clustering analysis. The differentially expressed genes (DEGs) among the molecular subtypes were ascertained using the limma package and they were subjected to functional enrichment analysis. The immune cell scores of the molecular subtypes were evaluated using ESTIMATE, MCPcounter, and GSCA packages of R. A multi-gene prognostic model was constructed using lasso regression, and the immunotherapeutic effects of the model were analyzed using the Imvigor210 cohort. In addition, immunohistochemical analysis was performed on a cohort of HCC tissue to validate gene expression. Results Based on the 59 EMT-associated genes identified, the 365—liver hepatocellular carcinoma (LIHC) samples were divided into two subtypes, C1 and C2. The C1 subtype mostly showed poor prognosis, had higher immune scores compared to the C2 subtype, and showed greater correlation with pathways of tumor progression. A four-gene signature construct was fabricated based on the 1130 DEGs among the subtypes. The construct was highly robust and showed stable predictive efficacy when validated using datasets from different platforms (HCCDB18 and GSE14520). Additionally, compared to currently existing models, our model demonstrated better performance. The results of the immunotherapy cohort showed that patients in the low-risk group have a better immune response, leading to a better patient’s prognosis. Immunohistochemical analysis revealed that the expression levels of the FTCD, PON1, and TMEM45A were significantly over-expressed in 41 normal samples compared to HCC samples, while that of the G6PD was significantly over-expressed in cancerous tissues. Conclusions The four-gene signature construct fabricated based on the EMT-associated genes provides valuable information to further study the pathogenesis and clinical management of HCC.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

Wang

et al. 2021

Cancer Cell Int

View full text Add to dashboard Cite

show abstract

“…Moreover, CD138 was markedly higher in hepatocellular carcinoma as compared to cholangiocellular carcinoma of the liver. However, other antibodies as, for example, arginase or BSEP are better separators of these tumor entities [63][64][65].…”

mentioning

confidence: 99%

Prevalence of Syndecan-1 (CD138) Expression in Different Kinds of Human Tumors and Normal Tissues

et al. 2019

View full text Add to dashboard Cite

Syndecan-1 (CD138) is a transmembrane proteoglycan known to be expressed in various normal and malignant tissues. It is of interest because of a possible prognostic role of differential expression in tumors and its role as a target for indatuximab, a monoclonal antibody coupled with a cytotoxic agent. To comprehensively analyze CD138 in normal and neoplastic tissues, we used tissue microarrays (TMAs) for analyzing immunohistochemically detectable CD138 expression in 2,518 tissue samples from 85 different tumor entities and 76 different normal tissue types. The data showed that CD138 expression is abundant in tumors. At least an occasional weak CD138 immunostaining could be detected in 71 of 82 (87%) different tumor types, and 58 entities (71%) had at least one tumor with a strong positivity. In normal tissues, a particularly strong expression was found in normal squamous epithelium of various organs, goblet and columnar cells of the gastrointestinal tract, and in hepatocytes. The highly standardized analysis of most human cancer types resulted in a ranking order of tumors according to the frequency and levels of CD138 expression. CD138 immunostaining was highest in squamous cell carcinomas such as from the esophagus (100%), cervix uteri (79.5%), lung (85.7%), vagina (89.7%) or vulva (73.3%), and in invasive urothelial cancer (76.2%). In adenocarcinomas, CD138 was also high in lung (82.9%) and colorectal cancer (85.3%) but often lower in pancreas (73.3%), stomach (54.2% in intestinal type), or prostate carcinomas (16.3%). CD138 expression was usually low or absent in germ cell tumors, sarcomas, endocrine tumors including thyroid cancer, and neuroendocrine tumors. In summary, the preferential expression in squamous cell carcinomas of various sites makes these cancers prime targets for anti-CD138 treatments once these might become available. Abundant expression in many different normal tissues might pose obstacles to exploiting CD138 as a therapeutic target, however.

show abstract

“…Some studies have authenticated that iron metabolism relatedgenes SLC11A1, ASNS, SLC6A3, and FTCD may be involved in the regulation of tumorgenesis (46)(47)(48)(49). But the value of these genes in the occurrence of ccRCC and its underlying mechanism needs to be further explored.…”

Section: Discussionmentioning

confidence: 99%

The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma

Mou

Zhang

et al. 2020

Front. Oncol.

View full text Add to dashboard Cite

Background: Clear cell renal cell carcinoma (ccRCC) is characteristics of resistance to chemotherapy and radiotherapy. The prognosis of ccRCC was dismay with immense diversity. Iron metabolism disturbance is a common phenomenon in ccRCC. The purpose of our study is to identify and validate the candidate prognostic gene signature of iron metabolism and methylation closely related to the poor prognosis of ccRCC through comprehensive bioinformatics analysis in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Methods: The prognostic iron metabolism-related genes were screened according to the overlapping differentially expressed genes (DEGs) from the TCGA database. We built a prognostic model using risk score method to predict OS, each ccRCC patient's risk score was calculated, and the resulting score can divide these patients into two categories according to the cut-point risk score. The prognostic significance of the hub genes was further evaluated with the Kaplan-Meier (KM) survival and Receiver Operating Characteristic (ROC) curve analysis. Univariate and multivariate Cox regression analysis was implemented to evaluate the impact of each variable on OS. Furthermore, the prediction power of the 25 gene signatures has been validated using an independent ccRCC cohort from the GEO database. The Gene Set Enrichment Analysis (GSEA) identified the characteristics of hub related oncogenes. Finally, we utilize Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the co-expression network based on these DEGs. Results: In this study, we identified and validated 25 iron metabolism-related and methylated genes as the prognostic signatures, which differentiated ccRCC patients into high and low risk subgroups. The KM analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 25 gene signatures could largely predict OS and DFS for 1, 3, and 5 years in patients with ccRCC. Mou et al. Iron Metabolism Gene Predicts Prognosis in ccRCC Conclusions: Taken together, we identified the key iron metabolism-related and methylated genes for ccRCC through a comprehensive bioinformatics analysis. This study provides a reliable and robust gene signature for the prognostic predictor of ccRCC patients and maybe provides a promising treatment strategy for this lethal disease.

show abstract

The Diagnostic Value of Arginase-1, FTCD, and MOC-31 Expression in Early Detection of Hepatocellular Carcinoma (HCC) and in Differentiation Between HCC and Metastatic Adenocarcinoma to the Liver

Cited by 18 publications

References 31 publications

Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

Prevalence of Syndecan-1 (CD138) Expression in Different Kinds of Human Tumors and Normal Tissues

The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma

Contact Info

Product

Resources

About