scholarly journals MEX3A and MEX3B as Potential Prognostic Indicators in Stomach Adenocarcinoma

2021 ◽  
Author(s):  
Junwei Zou ◽  
Yong Huang ◽  
Zhaoying Wu ◽  
Hao Xie ◽  
Rongsheng Wang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Rna Splicing ◽  
Rna Binding ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma ◽  
Tumor Pathogenesis ◽  
Kaplan Meier Plotter

Abstract Stomach adenocarcinoma(STAD) is one of the deadliest cancers in the world. The expression levels of family members of mex-3 RNA that bound MEX3A (member A) and MEX3B (member B) were high expressions in different cancers and interconnected to deficient prognosis. The present research assessed the potential regarding the expression of MEX3A and MEX3B in STAD by analysing the facts of STAD (viz. The Cancer Genome Atlas). TCGA, MEX3A and MEX3B in the cancers were analyzed using TIMER2.0, Kaplan Meier Plotter, and cBioPortal. The data was visualized using version 4.0.3 of R. We found MEX3A and MEX3B had various expressions regarding major cancer and relevant common tissues. Especially, high expression of MEX3A and MEX3B had relationships with the OS (namely overall survival) with deficiency and RFS (viz. relapse-free survival) concerning STAD. The expressions of MEX3B had correlations to T stage with P being 0.012 and to the race with P being 0.049. MEX3B was highly expressed in T3 and T4 stages, and was highly expressed in the white race. MEX3A mutation had a better survival without diseases, with P being 0.0205. However, the situation was different with non-overall survival, with P being 0.194, in comparison with the patients who did not have MEX3A change. MEX3A and MEX3B on tumor pathogenesis might be related to "RNA splicing" and "spliceosomal complex" and "single-stranded RNA binding". We further investigated the association between MEX3A and MEX3B and immune cells. The mast cells of the most connections to MEX3A (R=-0.300, P<0.001) and the NK cells were positively correlation with MEX3B (R=0.590, P<0.001). It showed that they might be potential prognostic molecular biomarkers in patients with STAD.

scholarly journals Bioinformatics Analysis and Insights for The Role of COMMD7 in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Xuehui Peng ◽  
Yonggang He ◽  
Xiaobing Huang ◽  
Nan You ◽  
Huiying Gu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Bioinformatics Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Research Progress ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Kaplan Meier Plotter

Abstract Background: The tumorigenesis and development of hepatocellular carcinoma (HCC) is a process involving multiple factors. The COMMDs family proteins were reported to play important roles in various disease and cancers including HCC. We previously found COMMD7 acted as a HCC-promotion factor; however, further understanding on COMMD7 was needed. We conducted these bioinformatics analysis for the purpose of comprehensive understanding of the functional role of COMMD7 in HCC.Methods: The bioinformatics analysis of COMMD7 were launched by online platforms including KEGG, GEPIA, cBioportal, Gene Ontology and The Kaplan-Meier plotter. Data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were downloaded, and the data analysis and processing were conducted by RStudio (version 1.3.959) software.Results: The expression profile results of COMMD7 in TCGA and GTEx database suggested that COMMD7 expressed highly in liver tumor tissues and positively related with poorer prognosis (p<0.01); COMMD7 also contributed to the early development of HCC as its higher expression resulted in progression from stage I to stage III (p<0.01). Based on our previous studies, COMMD7 may target NF-κB signaling and CXCL10 to enhance the proliferation of hepatoma cells so that promoting the development of HCC. Conclusions：This study updates the current studies about the newly recognized roles of COMMD7 in the progression of HCC, summarizing the research progress and prospects of COMMD7 comprehensively, offering an outlook for the future investigation and targeted therapy of HCC.

scholarly journals Bacterial Diversity Correlates with Overall Survival in Cancers of the Head and Neck, Liver, and Stomach

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5659
Author(s):  
Rebecca M. Rodriguez ◽  
Mark Menor ◽  
Brenda Y. Hernandez ◽  
Youping Deng ◽  
Vedbar S. Khadka
Keyword(s):  
Overall Survival ◽  
Head And Neck ◽  
Diversity Index ◽  
Single Agent ◽  
Response To Therapy ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma ◽  
Liver Hepatocellular Carcinoma ◽  
The Impact

One in five cancers is attributed to infectious agents, and the extent of the impact on the initiation, progression, and disease outcomes may be underestimated. Infection-associated cancers are commonly attributed to viral, and to a lesser extent, parasitic and bacterial etiologies. There is growing evidence that microbial community variation rather than a single agent can influence cancer development, progression, response to therapy, and outcome. We evaluated microbial sequences from a subset of infection-associated cancers—namely, head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and stomach adenocarcinoma (STAD) from The Cancer Genome Atlas (TCGA). A total of 470 paired tumor and adjacent normal samples were analyzed. In STAD, concurrent presence of EBV and Selemonas sputigena with a high diversity index were associated with poorer survival (HR: 2.23, 95% CI 1.26–3.94, p = 0.006 and HR: 2.31, 95%CI 1.1–4.9, p = 0.03, respectively). In LIHC, lower microbial diversity was associated with poorer overall survival (HR: 2.57, 95%CI: 1.2, 5.5, p = 0.14). Bacterial within-sample diversity correlates with overall survival in infection-associated cancers in a subset of TCGA cohorts.

scholarly journals Bioinformatics analysis reveals the ceRNA co-expression network in tumor microenvironment and prognostic biomarkers in Sarcomas

2020 ◽  
Author(s):  
Dandan Zou ◽  
Yang Wang ◽  
Meng Wang ◽  
Bo Zhao ◽  
Fei Hu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bioinformatics Analysis ◽  
Immune Therapy ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Tumor Microenviroment ◽  
Prognostic Prediction

Abstract Background Sarcomas (SARCs) are rare, heterogeneous mesenchymal neoplasia. To understand the tumor microenviroment (TME) and identify potential biomarkers for prognosis that associated with TME of SARCs might provide effective clues for immune therapy. Methods We evaluated the immune scores and stromal scores by using the RNA sequencing dataset of SARCs patients from The Cancer Genome Atlas (TCGA) database and the ESTIMATE algorithm. Then the differentially expressed mRNAs (DEGs), miRNAs (DEMs) and lncRNAs (DELs) were filtered after comparing the two high- and low- scores groups. Next, based on these DERNAs, we established a competing endogenous RNA (ceRNA) network and explored the prognostic roles of biomarkers involved in the network with the help of bioinformatics analysis. Results High immune scores were significantly associated with favorable overall survival of SARCs patients. Next, a total of 328 DEGs, 18 DEMs and 67 DELs that commonly regulated in the immune and stromal scores groups were obtained. And for the DEGs, some of the Gene Ontology (GO) terms and pathways were mainly associated with immune processes. A ceRNA network were constructed with 142 nodes and 424 edges, in which hsa-miR-9-5p, hsa-miR-490-3p, hsa-miR-133a-3p, hsa-miR-133b and hsa-miR-129-5p were the top 5 nodes. Additionally, the protein-protein Interaction (PPI) network identified MMP9, TYROBP, CSF1, CXCR4, FBN1, FLNA, PDGFRB, CYBB, FCGR3A and MYH11 as hub nodes with considerable importance that functioned in the network. Finally, the Kaplan-Meier survival analysis demonstrated that 9 mRNAs (APOL1, EFEMP1, LYZ, MEDAG, MYH11, RARRES1, TNFAIP2, TNFSF10 and ZNF385A), 2 miRNAs (hsa-miR-9-5p and hsa-miR-183-5p) and 3 lncRNAs (CTD-2228K2.7, HOTAIRM1 and NCF1C) were closely associated with the overall survival of SARCs patients. Conclusions Taken together, our study confirmed that the prognosis value of immune scores for SARCs patients, also we identified a list of TME-related biomarkers which might contribute to prognostic prediction and help improve the efficacy of immune therapy.

Prognostic and diagnostic roles of prolyl 4-hydroxylase subunit α members in breast cancer

2021 ◽  
Author(s):  
Mingjie Li ◽  
Qianyun Wang ◽  
Qinqin Zheng ◽  
Lin Wu ◽  
Bin Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Stage ◽  
Univariate Analysis ◽  
The Cancer Genome Atlas ◽  
Poor Survival ◽  
Free Survival ◽  
Kaplan Meier ◽  
Human Protein Atlas ◽  
Cancer Genome Atlas ◽  
Kaplan Meier Plotter

Aim: We aimed to evaluate the diagnostic and prognostic values of P4HAs in breast cancer (BC) patients. Materials & methods: Kaplan–Meier plotter was used to evaluate the prognostic values of P4HAs and correlations between their expression and clinical characteristics were assessed based on The Cancer Genome Atlas and the Human Protein Atlas. Results: The current study showed that P4HAs were highly expressed in BC patients with clinical stage I compared with nontumor control and elevated P4HAs were correlated with poor survival outcomes. Subtypes analysis revealed that P4HA1 and P4HA2 were most expressed in HER2+ subtypes patients. Univariate analysis displayed that elevated P4HA1 and P4HA3 correlated with unfavorable recurrence-free survival in mutated TP53 patients. Conclusion: This study indicated the diagnostic and prognostic roles of P4HAs members and broadened the biomarker fields of early diagnosis and prognostic monitoring of BC patients.

scholarly journals Bioinformatics Analysis and Insights for the Role of COMMD7 in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Jing Li ◽  
Xuehui Peng ◽  
Yonggang He ◽  
Xiaobing Huang ◽  
Nan You ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Bioinformatics Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Research Progress ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Kaplan Meier Plotter

Abstract Background: The tumorigenesis and development of hepatocellular carcinoma (HCC) is a process involving multiple factors. The COMMDs family proteins were reported to play important roles in various disease and cancers including HCC. We previously found COMMD7 acted as a HCC-promotion factor; however, further understanding on COMMD7 was needed. We conducted these bioinformatics analysis for the purpose of comprehensive understanding of the functional role of COMMD7 in HCC.Methods: The bioinformatics analysis of COMMD7 were launched by online platforms including KEGG, GEPIA, cBioportal, Gene Ontology and The Kaplan-Meier plotter. Data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were downloaded, and the data analysis and processing were conducted by RStudio (version 1.3.959) software.Results: The expression profile results of COMMD7 in TCGA and GTEx database suggested that COMMD7 expressed highly in liver tumor tissues and positively related with poorer prognosis (p<0.01); COMMD7 also contributed to the early development of HCC as its higher expression resulted in progression from stage I to stage III (p<0.01). Based on our previous studies, COMMD7 may target NF-κB signaling and CXCL10 to enhance the proliferation of hepatoma cells so that promoting the development of HCC. Conclusions：This study updates the current studies about the newly recognized roles of COMMD7 in the progression of HCC, summarizing the research progress and prospects of COMMD7 comprehensively, offering an outlook for the future investigation and targeted therapy of HCC.

High KIF11 expression is associated with poor outcome of NSCLC

2021 ◽  
pp. 030089162098834
Author(s):  
Junhui Liu ◽  
Yubin Tian ◽  
Lei Yi ◽  
Zhaojia Gao ◽  
Ming Lou ◽  
...  
Keyword(s):  
Overall Survival ◽  
Multivariate Analysis ◽  
Tissue Microarrays ◽  
The Cancer Genome Atlas ◽  
Normal Lung ◽  
Clinicopathologic Characteristics ◽  
Poor Outcome ◽  
Kaplan Meier ◽  
Significant Difference ◽  
Cancer Genome Atlas

Purpose: To clarify the correlation between KIF11 (kinesin family member 11) and clinicopathologic characteristics of non-small cell lung cancer (NSCLC) and identify the prognostic value of KIF11 in patients with NSCLC. Methods: For investigating the expression of KIF11 in NSCLC, two tissue microarrays (TMAs: one contained 60 paired NSCLC tissues and paratumor tissues, the other contained 140 NSCLC tissues and 10 normal lung tissues) were constructed, stained, and scored. The Cancer Genome Atlas (TCGA) datasets were used to explore the differential expression level of KIF11 between NSCLC and paratumor. Kaplan-Meier survival curves were plotted and multivariate analysis were carried out. Results: The staining of KIF11 mainly distributed throughout the cytoplasm of tumor cells. Its expression was higher in NSCLC than paratumor cells, and similar results were obtained from TCGA datasets. We found that high expression of KIF11 had a significant correlation with lymph node metastases ( p = 0.024) and pathologic stage ( p = 0.018); that significant difference was not found in any other clinicopathologic characteristic. As univariate and multivariate analysis showed, KIF11 expression was significantly correlated with overall survival time of NSCLC ( p = 0.002, p = 0.025, respectively). High KIF11 expression was found to significantly associate with overall survival of stage II–III ( p = 0.001) and lung adenocarcinoma ( p = 0.036). Conclusion: High KIF11 expression predicts poor outcome in NSCLC. KIF11 is expected to be a viable prognostic biomarker for NSCLC.

scholarly journals Comprehensive Analysis of Aldehyde Dehydrogenases (ALDHs) and Its Significant Role in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Senbang Yao ◽  
Wenjun Chen ◽  
He Zuo ◽  
Ziran Bi ◽  
Xiuqing Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Oxidative Dna Damage ◽  
Tumor Grade ◽  
The Cancer Genome Atlas ◽  
Kaplan Meier ◽  
Human Protein Atlas ◽  
Cancer Genome Atlas ◽  
The Relationship ◽  
Kaplan Meier Plotter

AbstractOxidative DNA damage is closely related to the occurrence and progression of cancer. Oxidative stress plays an important role in alcohol-induced hepatocellular carcinoma (HCC). Aldehyde dehydrogenase (ALDH) is a family of enzymes that plays an essential role in the reducing oxidative damage. However, how ALDHs family affects alcohol-related HCC remains obscure. We aimed to explore the correlation between the differential expression of ALDHs in patients with HCC and pathological features, as well as the relationship between ALDHs and prognosis, and finally analyze the possible mechanism of ALDHs in targeted therapy of HCC. The data of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. This research explored the expression and prognostic values of ALDHs in HCC using Oncomine, UALCAN, Human Protein Atlas, cBioPortal, Kaplan–Meier plotter, GeneMANIA, Tumor Immune Estimation Resource, GEPIA databases, and WebGestalt. Low mRNA and protein expressions of ALDHs were found to be significantly associated with tumor grade and clinical cancer stages in HCC patients. In particular, the loss of ALDH expression is more obvious in Asians, and its effect on prognosis is far more significant than that in the White race. Our findings play an important role in the study of prognostic markers and anti-liver cancer therapeutic targets for the members of the ALDHs family, especially in patients with liver cancer in Asia.

scholarly journals TRIM27 interacts with Iκbα to promote the growth of human renal cancer cells through regulating the NF-κB pathway

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chengwu Xiao ◽  
Wei Zhang ◽  
Meimian Hua ◽  
Huan Chen ◽  
Bin Yang ◽  
...  
Keyword(s):  
Cell Lines ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Mrna Levels ◽  
Loss Of Function ◽  
Protein Levels ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Abstract Background The tripartite motif (TRIM) family proteins exhibit oncogenic roles in various cancers. The roles of TRIM27, a member of the TRIM super family, in renal cell carcinoma (RCC) remained unexplored. In the current study, we aimed to investigate the clinical impact and roles of TRIM27 in the development of RCC. Methods The mRNA levels of TRIM27 and Kaplan–Meier survival of RCC were analyzed from The Cancer Genome Atlas database. Real-time PCR and Western blotting were used to measure the mRNA and protein levels of TRIM27 both in vivo and in vitro. siRNA and TRIM27 were exogenously overexpressed in RCC cell lines to manipulate TRIM27 expression. Results We discovered that TRIM27 was elevated in RCC patients, and the expression of TRIM27 was closely correlated with poor prognosis. The loss of function and gain of function results illustrated that TRIM27 promotes cell proliferation and inhibits apoptosis in RCC cell lines. Furthermore, TRIM27 expression was positively associated with NF-κB expression in patients with RCC. Blocking the activity of NF-κB attenuated the TRIM27-mediated enhancement of proliferation and inhibition of apoptosis. TRIM27 directly interacted with Iκbα, an inhibitor of NF-κB, to promote its ubiquitination, and the inhibitory effects of TRIM27 on Iκbα led to NF-κB activation. Conclusions Our results suggest that TRIM27 exhibits an oncogenic role in RCC by regulating NF-κB signaling. TRIM27 serves as a specific prognostic indicator for RCC, and strategies targeting the suppression of TRIM27 function may shed light on future therapeutic approaches.

scholarly journals Deep Learning for Automatic Subclassification of Gastric Carcinoma Using Whole-Slide Histopathology Images

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3811
Author(s):  
Hyun-Jong Jang ◽  
In-Hye Song ◽  
Sung-Hak Lee
Keyword(s):  
Deep Learning ◽  
Relative Proportion ◽  
The Cancer Genome Atlas ◽  
Cancer Tissue ◽  
Mucinous Tumor ◽  
Receiver Operating Characteristic Curves ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma ◽  
Tumor Types

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

scholarly journals Predicted CD4+ T cell infiltration levels could indicate better overall survival in sarcoma patients

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098153
Author(s):  
Qing Bi ◽  
Yang Liu ◽  
Tao Yuan ◽  
Huizhen Wang ◽  
Bin Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
T Cell ◽  
Survival Data ◽  
Tumor Infiltrating Lymphocytes ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
T Cell Infiltration ◽  
Whole Exome ◽  
Cancer Genome Atlas ◽  
Infiltrating Lymphocytes

Objective The role of tumor-infiltrating lymphocytes (TILs) has not yet been characterized in sarcomas. The aim of this bioinformatics study was to explore the effect of TILs on sarcoma survival and genome alterations. Methods Whole-exome sequencing, transcriptome sequencing, and survival data of sarcoma were obtained from The Cancer Genome Atlas. Immune infiltration scores were calculated using the Tumor Immune Estimation Resource. Potential associations between abundance of infiltrating TILs and survival or genome alterations were examined. Results Levels of CD4+ T cell infiltration were associated with overall survival of patients with pan-sarcomas, and higher CD4+ T cell infiltration levels were associated with better survival. Somatic copy number alterations, rather than mutations, were found to correlate with CD4+ T cell infiltration levels. Conclusions This data mining study indicated that CD4+ T cell infiltration levels predicted from RNA sequencing could predict sarcoma prognosis, and higher levels of CD4+ T cells infiltration indicated a better chance of survival.

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