scholarly journals Higher Expression of SPP1 Predicts Poorer Survival Outcomes in Head and Neck Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Tongwu Bie ◽  
Xuewen Zhang
Keyword(s):  
Head And Neck ◽  
Prognostic Biomarker ◽  
The Cancer Genome Atlas ◽  
Biological Processes ◽  
Clinical Genetic ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Biological Methods ◽  
Secreted Phosphoprotein 1

Secreted phosphoprotein 1 (SPP1) participated in various biological processes in many cancers, including immune response, tumor progression, and prognosis. However, SPP1 in head and neck squamous cell carcinoma (HNSCC) remains unknown. Clinical-genetic data of HNSCC were obtained from The Cancer Genome Atlas (TCGA) database. The differential expression of SPP1 in HNSCC tissues and adjacent normal tissues was quantified by bioinformatics methods and verified by western blot and other differential biological methods. We concluded that SPP1 is significantly upregulated in tumor tissues and can become a prognostic biomarker for HNSCC.

scholarly journals Elevated ZNF703 Protein Expression Is an Independent Unfavorable Prognostic Factor for Survival of the Patients with Head and Neck Squamous Cell Carcinoma

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hang Yang ◽  
Wen-Qi Jiang ◽  
Ye Cao ◽  
Yong-An Sun ◽  
Jing Wei ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Head And Neck ◽  
Squamous Cell ◽  
The Cancer Genome Atlas ◽  
Cancer Center ◽  
Protein Overexpression ◽  
Prognostic Effect ◽  
Tumor Tissues ◽  
Cancer Genome Atlas

Aim. Data from The Cancer Genome Atlas (TCGA) show that the ZNF703 gene amplifies and overexpresses in head and neck squamous cell carcinomas (HNSCC). However, the clinical relevance of this observation in HNSCC is unclear. The purpose of this study was to clarify the expression of ZNF703 protein and its prognostic effect on HNSCC.Methods. Two hundred ten HNSCC patients from Sun Yat-Sen University Cancer Center with complete survival follow-up were included in this study. Tumor samples from primary sites were collected. The expression of the ZNF703 protein was tested by immunohistochemistry (IHC).Results. The high expression of ZNF703 in HNSCC tumor tissues was significantly higher than that of the matched noncancerous tissues (48.6% versus 11.6%,P<0.001). ZNF703 overexpression was correlated with tumor position (laryngeal carcinoma) and recurrence (allP<0.05). Multivariate analysis revealed that ZNF703 protein overexpression was an independent prognostic factor (P=0.022, hazard ratio = 1.635, 95% CI 1.073–2.493) in HNSCC patients.Conclusion. ZNF703 overexpression is associated with adverse prognosis in HNSCC, which might be a novel biomarker of HNSCC.

scholarly journals Comprehensive analysis of PD-L1 expression, tumor-infiltrating lymphocytes, and tumor microenvironment in LUAD: differences between Asians and Caucasians

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Fenglong Bie ◽  
He Tian ◽  
Nan Sun ◽  
Ruochuan Zang ◽  
Moyan Zhang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Tumor Infiltrating Lymphocytes ◽  
The Cancer Genome Atlas ◽  
Normal Tissues ◽  
Asian Patients ◽  
Expression Of Genes ◽  
Tumor Tissues ◽  
Significant Difference ◽  
Cancer Genome Atlas ◽  
Infiltrating Lymphocytes

Abstract Backgrounds The characteristics of programmed cell death protein-1 (PD-L1) expression, tumor-infiltrating lymphocytes (TILs), and tumor microenvironment (TME) in lung adenocarcinoma (LUAD) patients are closely related to immunotherapy, and there are differences between Asians and Caucasians. Methods Acquire the transcriptome data of the Cancer Genome Atlas and Chinese LUAD patients. R software was used to analyze the differential expression of genes, prognosis, and gene function. Use CIBERSORT for TIL-related analysis and ESTIMATE for TME-related analysis. Results The expression of PD-L1 in tumor tissues of Caucasian LUAD patients was lower than that in normal tissues, while there was no significant difference in Asians. There was no statistical difference between PD-L1 expression and prognosis. The composition of TILs between Caucasian and Asian LUAD patients was quite different. There was no correlation between TILs and prognosis in Caucasians. However, the higher content of resting mast cells indicated a better prognosis in Asians. The Caucasian patients with higher immune and estimate scores had a better prognosis (p = 0.021, p = 0.025). However, the Asian patients with a higher estimate score had a worse prognosis (p = 0.024). The high expression of COL5A2 (p = 0.046, p = 0.027) and NOX4 (p = 0.020, p = 0.019) were both associated with the poor prognosis in Caucasians and Asians. Conclusion There are many differences in the characteristics of PD-L1 expression, TILs, and TME between Caucasian and Asian LUAD patients. This provides a certain hint for the selection of specific immunotherapy strategies separately for Caucasian and Asian LUAD patients.

scholarly journals A Comprehensive Survey of Immune Cytolytic Activity-Associated Gene Co-Expression Networks across 17 Tumor and Normal Tissue Types

Cancers ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 307
Author(s):  
Tian Tian ◽  
Ji Wan ◽  
Yan Han ◽  
Haoran Liu ◽  
Feng Gao ◽  
...  
Keyword(s):  
Cytolytic Activity ◽  
The Cancer Genome Atlas ◽  
Immune Activity ◽  
Multiple Tumor ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Comprehensive Survey ◽  
Cancer Genome Atlas ◽  
Normal Networks ◽  
Tumor Types

Cytolytic immune activity in solid tissue can be quantified by transcript levels of two genes, GZMA and PRF1, which is named the CYT score. A previous study has investigated the molecular and genetic properties of tumors associated CYT, but a systematic exploration of how co-expression networks across different tumors are shaped by anti-tumor immunity is lacking. Here, we examined the connectivity and biological themes of CYT-associated modules in gene co-expression networks of 14 tumor and 3 matched normal tissues constructed from the RNA-Seq data of the “The Cancer Genome Atlas” project. We first found that tumors networks have more diverse CYT-correlated modules than normal networks. We next identified and investigated tissue-specific CYT-associated modules across 14 tumor types. Finally, a common CYT-associated network across 14 tumor types was constructed. Two common modules have mixed signs of correlation with CYT in different tumors. Given the tumors and normal tissues surveyed, our study presents a systematic view of the regulation of cytolytic immune activity across multiple tumor tissues.

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 DNASE1L3 as a Novel Diagnostic and Prognostic Biomarker for Lung Adenocarcinoma Based on Data Mining

2021 ◽  
Vol 12 ◽  
Author(s):  
Jianlin Chen ◽  
Junping Ding ◽  
Wenjie Huang ◽  
Lin Sun ◽  
Jinping Chen ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Biomarker ◽  
Function Analysis ◽  
Mrna Level ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Diagnostic Efficiency ◽  
Protein Levels ◽  
Normal Tissues

Previous researches have highlighted that low-expressing deoxyribonuclease1-like 3 (DNASE1L3) may play a role as a potential prognostic biomarker in several cancers. However, the diagnosis and prognosis roles of DNASE1L3 gene in lung adenocarcinoma (LUAD) remain largely unknown. This research aimed to explore the diagnosis value, prognostic value, and potential oncogenic roles of DNASE1L3 in LUAD. We performed bioinformatics analysis on LUAD datasets downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analyzed with various online databases. We found that both the mRNA and protein levels of DNASE1L3 in patients with LUAD were noticeably lower than that in normal tissues. Low DNASE1L3 expression was significantly associated with higher pathological stages, T stages, and poor prognosis in LUAD cohorts. Multivariate analysis revealed that DNASE1L3 was an independent factor affecting overall survival (HR = 0.680, p = 0.027). Moreover, decreased DNASE1L3 showed strong diagnostic efficiency for LUAD. Results indicated that the mRNA level of DNASE1L3 was positively correlated with the infiltration of various immune cells, immune checkpoints in LUAD, especially with some m6A methylation regulators. In addition, enrichment function analysis revealed that the co-expressed genes may participate in the process of intercellular signal transduction and transmission. GSEA indicated that DNASE1L3 was positively related to G protein-coupled receptor ligand biding (NES = 1.738; P adjust = 0.044; FDR = 0.033) and G alpha (i) signaling events (NES = 1.635; P adjust = 0.044; FDR = 0.033). Our results demonstrated that decreased DNASE1L3 may serve as a novel diagnostic and prognostic biomarker associating with immune infiltrates in lung adenocarcinoma.

scholarly journals Targeting UCP2 Suppresses the FAK Signaling and Progression of Human Head and Neck Cancer Cells

2020 ◽  
pp. 1-8
Author(s):  
Yunfeng Zhao ◽  
Cherie Ann Nathan ◽  
Chunjing Zhang ◽  
Hongyan Du ◽  
Manikandan Panchatcharam ◽  
...  
Keyword(s):  
Head And Neck ◽  
Cancer Cells ◽  
Cancer Progression ◽  
Uncoupling Protein ◽  
Human Head ◽  
Atp Production ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Lactate Formation

Background: New adjuvant therapies for human head and neck (H&N) cancer to improve the quality of life of the patients are in great demand. Our early studies have demonstrated that uncoupling protein 2 (UCP2) is upregulated in the tumor tissues of H&N cancer compared to the adjacent normal tissues; however, the role of UCP2 in H&N cancer has not been studied. Objective: In this manuscript, we aim to examine whether UCP2 contributes to H&N cancer progression in vitro. Methods: We generated UCP2 stable knockdown H&N cancer cells and detected the effects of UCP2 inhibition on cell proliferation, migration, invasion, 3D spheroid formation, and the sensitivity to a chemodrug treatment. Results: Knockdown of UCP2 suppressed the progression of H&N cancer in vitro, which might be mediated via the following mechanism: 1) increased the G1 phase whereas decreased the S phase of the cell cycle, which could be mediated by suppression of the G1/S regulators including CDK4/6 and cyclin D1. 2) Decreased mitochondrial oxygen consumption, ATP production, and lactate formation, which is consistent with the downregulation of c-Myc. 3) FAK may serve as the upstream signaling molecule, and its action was mediated by Akt and ERK. Conclusions: Our studies first demonstrate that targeting UCP2 may suppress H&N cancer progression in vitro.

scholarly journals Deciphering N6-Methyladenosine-Related Genes Signature to Predict Survival in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jie Zhu ◽  
Min Wang ◽  
Daixing Hu
Keyword(s):  
Lung Adenocarcinoma ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Lasso Regression ◽  
Gene Expressions ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Selection Operator ◽  
Cox Analysis

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Among these, lung adenocarcinoma (LUAD) accounts for most cases. Due to the improvement of precision medicine based on molecular characterization, the treatment of LUAD underwent significant changes. With these changes, the prognosis of LUAD becomes diverse. N6-methyladenosine (m6A) is the most predominant modification in mRNAs, which has been a research hotspot in the field of oncology. Nevertheless, little has been studied to reveal the correlations between the m6A-related genes and prognosis in LUAD. Thus, we conducted a comprehensive analysis of m6A-related gene expressions in LUAD patients based on The Cancer Genome Atlas (TCGA) database by revealing their relationship with prognosis. Different expressions of the m6A-related genes in tumor tissues and non-tumor tissues were confirmed. Furthermore, their relationship with prognosis was studied via Consensus Clustering Analysis, Principal Components Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) Regression. Based on the above analyses, a m6A-based signature to predict the overall survival (OS) in LUAD was successfully established. Among the 479 cases, we found that most of the m6A-related genes were differentially expressed between tumor and non-tumor tissues. Six genes, HNRNPC, METTL3, YTHDC2, KIAA1429, ALKBH5, and YTHDF1 were screened to build a risk scoring signature, which is strongly related to the clinical features pathological stages (p<0.05), M stages (p<0.05), T stages (p < 0.05), gender (p=0.04), and survival outcome (p=0.02). Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor, revealing that the m6A-related genes signature has great predictive value. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database.

scholarly journals The Gasdermin E gene Potential as a Pan-Cancer Biomarker, While Discriminating between Different Tumor Types

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1810 ◽  
Author(s):  
Joe Ibrahim ◽  
Ken Op de Beeck ◽  
Erik Fransen ◽  
Marc Peeters ◽  
Guy Van Camp
Keyword(s):  
The Cancer Genome Atlas ◽  
Tumor Type ◽  
E Gene ◽  
Normal Tissues ◽  
Incidence And Mortality ◽  
Cancer Genome Atlas ◽  
Cancer Setting ◽  
Tumor Types ◽  
Methylation Patterns ◽  
Pan Cancer

Due to the elevated rates of incidence and mortality of cancer, early and accurate detection is crucial for achieving optimal treatment. Molecular biomarkers remain important screening and detection tools, especially in light of novel blood-based assays. DNA methylation in cancer has been linked to tumorigenesis, but its value as a biomarker has not been fully explored. In this study, we have investigated the methylation patterns of the Gasdermin E gene across 14 different tumor types using The Cancer Genome Atlas (TCGA) methylation data (N = 6502). We were able to identify six CpG sites that could effectively distinguish tumors from normal samples in a pan-cancer setting (AUC = 0.86). This combination of pan-cancer biomarkers was validated in six independent datasets (AUC = 0.84–0.97). Moreover, we tested 74,613 different combinations of six CpG probes, where we identified tumor-specific signatures that could differentiate one tumor type versus all the others (AUC = 0.79–0.98). In all, methylation patterns exhibited great variation between cancer and normal tissues, but were also tumor specific. Our analyses highlight that a Gasdermin E methylation biomarker assay, not only has the potential for being a methylation-specific pan-cancer detection marker, but it also possesses the capacity to discriminate between different types of tumors.

scholarly journals ExonSkipDB: functional annotation of exon skipping event in human

2019 ◽  
Author(s):  
Pora Kim ◽  
Mengyuan Yang ◽  
Ke Yiya ◽  
Weiling Zhao ◽  
Xiaobo Zhou
Keyword(s):  
Functional Annotation ◽  
Exon Skipping ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Multiple Cancer ◽  
Annotation Database ◽  
Reading Frame ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
Functional Features

AbstractExon skipping (ES) is reported to be the most common alternative splicing event due to loss of functional domains/sites or shifting of the open reading frame (ORF), leading to a variety of human diseases and considered therapeutic targets. To date, systematic and intensive annotations of ES events based on the skipped exon units in cancer and normal tissues are not available. Here, we built ExonSkipDB, the ES annotation database available at https://ccsm.uth.edu/ExonSkipDB/, aiming to provide a resource and reference for functional annotation of ES events in multiple cancer and tissues to identify therapeutically targetable genes in individual exon units. We collected 14 272 genes that have 90 616 and 89 845 ES events across 33 cancer types and 31 normal tissues from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). For the ES events, we performed multiple functional annotations. These include ORF assignment of exon skipped transcript, studies of lost protein functional features due to ES events, and studies of exon skipping events associated with mutations and methylations based on multi-omics evidence. ExonSkipDB will be a unique resource for cancer and drug research communities to identify therapeutically targetable exon skipping events.

scholarly journals Downregulated SPINK4 is associated with poor survival in colorectal cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiaojie Wang ◽  
Qian Yu ◽  
Waleed M. Ghareeb ◽  
Yiyi Zhang ◽  
Xingrong Lu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Expression Data ◽  
Poor Survival ◽  
Protein Levels ◽  
Normal Tissues ◽  
Human Protein Atlas ◽  
Cancer Genome Atlas ◽  
Independent Indicator

Abstract Background SPINK4 is known as a gastrointestinal peptide in the gastrointestinal tract and is abundantly expressed in human goblet cells. The clinical significance of SPINK4 in colorectal cancer (CRC) is largely unknown. Methods We retrieved the expression data of 1168 CRC patients from 3 Gene Expression Omnibus (GEO) datasets (GSE24551, GSE39582, GSE32323) and The Cancer Genome Atlas (TCGA) to compare the expression level of SPINK4 between CRC tissues and normal colorectal tissues and to evaluate its value in predicting the survival of CRC patients. At the protein level, these results were further confirmed by data mining in the Human Protein Atlas and by immunohistochemical staining of samples from 81 CRC cases in our own center. Results SPINK4 expression was downregulated in CRC compared with that in normal tissues, and decreased SPINK4 expression at both the mRNA and protein levels was associated with poor prognosis in CRC patients from all 3 GEO datasets, the TCGA database and our cohort. Additionally, lower SPINK4 expression was significantly related to higher TNM stage. Moreover, in multivariate regression, SPINK4 was confirmed as an independent indicator of poor survival in CRC patients in all databases and in our own cohort. Conclusions We concluded that reduced expression of SPINK4 relates to poor survival in CRC, functioning as a novel indicator.

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