APLN: A potential novel biomarker for cervical cancer

Apelin (APLN) is recently demonstrated a direct association with many malignant diseases. However, its effects on cervical cancer remain unclear. This study therefore aims to evaluate the association between APLN expression and cervical cancer using publicly available data from The Cancer Genome Atlas (TCGA). The Pearson χ2 test and Fish exact test, as well as logistic regression, were used to evaluate the relationship between clinicopathological factors in cervical cancer and the expression of APLN. Additionally, the Cox regression and Kaplan-Meier methods were conducted to analyze the Overall Survival (OS) of cervical cancer patients in TCGA. Finally, gene set enrichment analysis (GSEA) was performed to establish its biological functions. High expression of APLN in cervical cancer was significantly associated with a more advanced clinical stage (OR = 1.91 (1.21–3.05) for Stage II, Stage III, and Stage IV vs Stage I, p = 0.006). Additionally, it was associated with poor outcome after primary therapy (OR = 2.14 (1.03–4.59) for Progressive Disease (PD), Stable Disease (SD), and Partial Response (PR) vs Complete Remission (CR), p = 0.045) and high histologic grade (OR = 1.67 (1.03–2.72) for G3 and G4 vs G1 and G2, p = 0.037). Moreover, multivariate analysis showed that high expression of APLN was associated with a shorter OS. GSEA demonstrated that six KEGG pathways, including PPAR signaling, ECM-receptor interaction, focal adhesion, MAPK signaling, TGF-beta signaling, and Gap junction pathways were differentially enriched in the high expression APLN phenotype. The recent study suggests that APLN plays an important role in the progression of cervical cancer and might be a promising prognostic biomarker of the disease.

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Upregulation of GNPNAT1 Predicts Poor Prognosis and Correlates With Immune Infiltration in Lung Adenocarcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.605754 ◽

2021 ◽

Vol 8 ◽

Author(s):

Wenting Liu ◽

Kaiting Jiang ◽

Jingya Wang ◽

Ting Mei ◽

Min Zhao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Signaling Pathways ◽

Poor Prognosis ◽

Cox Regression ◽

Clinical Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Cox Regression Analysis ◽

Normal Tissues

BackgroundGlucosamine 6-phosphate N-acetyltransferase (GNPNAT1) is a key enzyme in the hexosamine biosynthetic pathway (HBP), which functions as promoting proliferation in some tumors, yet its potential biological function and mechanism in lung adenocarcinoma (LUAD) have not been explored.MethodsThe mRNA differential expression of GNPNAT1 in LUAD and normal tissues was analyzed using the Cancer Genome Atlas (TCGA) database and validated by real-time PCR. The clinical value of GNPNAT1 in LUAD was investigated based on the data from the TCGA database. Then, immunohistochemistry (IHC) of GNPNAT1 was applied to verify the expression and clinical significance in LUAD from the protein level. The relationship between GNPNAT1 and epigenetics was explored using the cBioPortal database, and the miRNAs regulating GNPNAT1 were found using the miRNA database. The association between GNPNAT1 expression and tumor-infiltrating immune cells in LUAD was observed through the Tumor IMmune Estimation Resource (TIMER). Finally, Gene set enrichment analysis (GSEA) was used to explore the biological signaling pathways involved in GNPNAT1 in LUAD.ResultsGNPNAT1 was upregulated in LUAD compared with normal tissues, which was verified through qRT-PCR in different cell lines (P < 0.05), and associated with patients’ clinical stage, tumor size, and lymphatic metastasis status (all P < 0.01). Kaplan–Meier (KM) analysis suggested that patients with upregulated GNPNAT1 had a relatively poor prognosis (P < 0.0001). Furthermore, multivariate Cox regression analysis indicated that GNPNAT1 was an independent prognostic factor for LUAD (OS, TCGA dataset: HR = 1.028, 95% CI: 1.013–1.044, P < 0.001; OS, validation set: HR = 1.313, 95% CI: 1.130–1.526, P < 0.001). GNPNAT1 overexpression was correlated with DNA copy amplification (P < 0.0001), low DNA methylation (R = −0.52, P < 0.0001), and downregulation of hsa-miR-30d-3p (R = −0.17, P < 0.001). GNPNAT1 expression was linked to B cells (R = −0.304, P < 0.0001), CD4+T cells (R = −0.218, P < 0.0001), and dendritic cells (R = −0.137, P = 0.002). Eventually, GSEA showed that the signaling pathways of the cell cycle, ubiquitin-mediated proteolysis, mismatch repair and p53 were enriched in the GNPNAT1 overexpression group.ConclusionGNPNAT1 may be a potential prognostic biomarker and novel target for intervention in LUAD.

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Angiogenesis-Related Gene Expression Signatures Predicting Prognosis in Gastric Cancer Patients

Cancers ◽

10.3390/cancers12123685 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3685

Author(s):

Haoyu Ren ◽

Jiang Zhu ◽

Haochen Yu ◽

Alexandr Bazhin ◽

Christoph Westphalen ◽

...

Keyword(s):

Gastric Cancer ◽

Risk Score ◽

Cox Regression ◽

Clinical Stage ◽

External Validation ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Related Gene ◽

Angiogenesis Related Gene

Increasing evidence indicates that angiogenesis is crucial in the development and progression of gastric cancer (GC). This study aimed to develop a prognostic relevant angiogenesis-related gene (ARG) signature and a nomogram. The expression profile of the 36 ARGs and clinical information of 372 GC patients were extracted from The Cancer Genome Atlas (TCGA). Consensus clustering was applied to divide patients into clusters 1 and 2. Least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to identify the survival related ARGs and establish prognostic gene signatures, respectively. The Asian Cancer Research Group (ACRG) (n = 300) was used for external validation. Risk score of ARG signatures was calculated, and a prognostic nomogram was developed. Gene set enrichment analysis of the ARG model risk score was performed. Cluster 2 patients had more advanced clinical stage and shorter survival rates. ARG signatures carried prognostic relevance in both cohorts. Moreover, ARG-risk score was proved as an independent prognostic factor. The predictive value of the nomogram incorporating the risk score and clinicopathological features was superior to tumor, lymph node, metastasis (TNM) staging. The high-risk score group was associated with several cancer and metastasis-related pathways. The present study suggests that ARG-based nomogram could serve as effective prognostic biomarkers and allow a more precise risk stratification.

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INHBB Is a Novel Prognostic Biomarker Associated with Cancer-Promoting Pathways in Colorectal Cancer

BioMed Research International ◽

10.1155/2020/6909672 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Jinpeng Yuan ◽

Aosi Xie ◽

Qiangjian Cao ◽

Xinxin Li ◽

Juntian Chen

Keyword(s):

Colorectal Cancer ◽

Signaling Pathways ◽

Signaling Pathway ◽

Transforming Growth Factor ◽

Cox Regression ◽

Prognostic Biomarker ◽

Disease Free Survival ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Receptor Interaction

Background. Inhibin subunit beta B (INHBB) is a protein-coding gene that participated in the synthesis of the transforming growth factor-β (TGF-β) family members. The study is aimed at exploring the clinical significance of INHBB in patients with colorectal cancer (CRC) by bioinformatics analysis. Methods. Real-time PCR and analyses of Oncomine, Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) databases were utilized to evaluate the INHBB gene transcription level of colorectal cancer (CRC) tissue. We evaluated the INHBB methylation level and the relationship between expression and methylation levels of CpG islands in CRC tissue. The corresponding clinical data were obtained to further explore the association of INHBB with clinical and survival features. In addition, Gene Set Enrichment Analysis (GSEA) was performed to explore the gene ontology and signaling pathways of INHBB involved. Results. INHBB expression was elevated in CRC tissue. Although the promoter of INHBB was hypermethylated in CRC, methylation did not ultimately correlate with the expression of INHBB. Overexpression of INHBB was significantly and positively associated with invasion depth, distant metastasis, and TNM stage. Cox regression analyses and Kaplan-Meier survival analysis indicated that high expression of INHBB was correlated with worse overall survival (OS) and disease-free survival (DFS). GSEA showed that INHBB was closely correlated with 5 cancer-promoting signaling pathways including the Hedgehog signaling pathway, ECM receptor interaction, TGF-β signaling pathway, focal adhesion, and pathway in cancer. INHBB expression significantly promoted macrophage infiltration and inhibited memory T cell, mast cell, and dendritic cell infiltration. INHBB expression was positively correlated with stromal and immune scores of CRC samples. Conclusion. INHBB might be a potential prognostic biomarker and a novel therapeutic target for CRC.

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Comprehensive Analysis of the Immune Effect of TGFβ1 in Colorectal Adenocarcinoma:A TGFβ1-related Prognostic Model of Tumor Microenvironment

10.21203/rs.3.rs-477295/v1 ◽

2021 ◽

Author(s):

Yucheng Qian ◽

Lina Zhang ◽

Jihang Wen ◽

Yanxia Mei ◽

Jingsun Wei ◽

...

Keyword(s):

Tumor Microenvironment ◽

Survival Data ◽

Prognostic Model ◽

Immune Cell ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Immune Checkpoints ◽

Cox Regression Analysis

Abstract ColorColorectal cancer is one of the most common cancer worldwide. Recently, tumor microenvironment (TME), especially its remoulding , is thought to control the colorectal cancer genesis and progression. In this study, we use ESTIMATEscore to make out the proportion of immune and stromal components in colorectal adenocarcinoma (CRA) samples from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were found by COX regression analysis and protein-protein interaction (PPI) network, among which TGFβ1 was supposed to be a prognosis factor and tumor environment indicator. Continuous analysis showed that TGFβ1 expression is positively correlated with lymph node metastasis (N stage) but negatively correlated with survival. Gene Set Enrichment Analysis (GSEA) revealed that the genes of the high-expression TGFβ1 group were mainly enriched in immune-related activities. Cluster analysis divided the samples into 2 subgroups. 24 HLA-related genes and 8 immune checkpoint genes were found upregulated in the high immunity group as well as TGFβ1, which suggests the possibility of novel therapies targeting immune checkpoints combined with TGFβ1. Tumor-infiltrating immune cell (TIC) profile of CRA patients was described by CIBERSORT analysis. Further analysis showed that the infiltration of Tregs and Neutrophils were positively correlated with TGFβ1 high expression. Then 3 TGFβ1-related genes were picked out to construct a prognostic model, which matches the survival data well.

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MYD88 Is a Potential Prognostic Gene and Immune Signature of Tumor Microenvironment for Gliomas

Frontiers in Oncology ◽

10.3389/fonc.2021.654388 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qinglong Guo ◽

Xing Xiao ◽

Jinsen Zhang

Keyword(s):

Tumor Microenvironment ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Who Grade ◽

Cox Regression Analysis ◽

Clinical Cases

PurposeTo explore the profiles of immune and stromal components of the tumor microenvironment (TME) and their related key genes in gliomas.MethodsWe applied bioinformatic techniques to identify the core gene that participated in the regulation of the TME of the gliomas. And immunohistochemistry staining was used to calculate the gene expressions in clinical cases.ResultsThe CIBERSORT and ESTIMATE were used to figure out the composition of TME in 698 glioma cases from The Cancer Genome Atlas (TCGA) database. Differential expression analysis identified 2103 genes between the high and the low-score group. Then the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, univariate Cox regression analysis, and protein–protein interaction (PPI) network construction were conducted based on these genes. MYD88 was identified as the key gene by the combination univariate Cox and PPI analysis. Furthermore, MYD88 expression was significantly associated with the overall survival and WHO grade of glioma patients. The genes in the high-expression MYD88 group were mainly in immune-related pathways in the Gene Set Enrichment Analysis (GSEA). We found that macrophage M2 accounted for the largest portion with an average of 27.6% in the glioma TIICs and was associated with high expression of MYD88. The results were verified in CGGA database and clinical cases in our hospital. Furthermore, we also found the MYD88 expression was higher in IDH1 wild types. The methylation rate was lower in high grade gliomas.ConclusionMYD88 had predictive prognostic value in glioma patients by influencing TIICs dysregulation especially the M2-type macrophages.

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Increased expression of homeobox 5 predicts poor prognosis: A potential therapeutic target for glioma

10.21203/rs.3.rs-376213/v1 ◽

2021 ◽

Author(s):

Chengran Xu ◽

Jinhai Huang ◽

Yi Yang ◽

Lun Li ◽

Guangyu Li

Keyword(s):

Cox Regression ◽

Homeobox Gene ◽

Enrichment Analysis ◽

Tissue Expression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Who Grade ◽

Forecast Efficiency ◽

Genome Atlas

Abstract Background: The homeobox gene 5 (HOXB5) encodes a transcription factor that regulates the central nervous system embryonic development. Of note, its expression pattern and prognostic role in glioma remain unelucidated. This study aimed to identify the relationship between HOXB5 and glioma by investigating the HOXB5 expression data from the The Cancer Genome Atlas (TCGA) and The Genotype Tissue Expression (GTEx) databases and validating the obtained data using the Chinese Glioma Genome Atlas (CGGA) database. Kaplan-Meier and univariate cox regression analyses were performed to assess the prognostic value of HOXB5. The key functions and signaling pathways of HOXB5 were analyzed using GSEA and GSVA. Immune infiltration was calculated using Microenvironment Cell Populations-counter (MCP-counter), single-sample Gene Set Enrichment Analysis (ssGSEA), and ESTIMATE algorithms.Result: HOXB5 expression was elevated in glioma tissues. The increased levels of HOXB5 were significantly correlated with a higher WHO grade and aggressive cancer phenotypes. HOXB5 overexpression represented a risk factor that was associated with shorter overall survival (OS) while exhibiting a moderate forecast efficiency in most clinical subgroups. These results were validated using the CGGA and Rembrandt datasets. Furthermore, the functional analysis showed enrichment of angiogenesis, the IL6/JAK-STAT3 pathway, and inflammatory response in the tissues that showed high expression of HOXB5. Lastly, the high expression of HOXB5 was associated with enrichment of Tregs and MDSCs, and HOXB5 expression was shown to play a role in several immune checkpoint genes.Conclusions: HOXB5 may serve as a predictive factor of glioma malignancy and prognostic status and represents potential as a molecular treatment candidate.

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High expression of PIMREG predicts poor survival outcomes and is correlated with immune infiltrates in lung adenocarcinoma

PeerJ ◽

10.7717/peerj.11697 ◽

2021 ◽

Vol 9 ◽

pp. e11697

Author(s):

Feng Jiang ◽

Min Liang ◽

Xiaolu Huang ◽

Wenjing Shi ◽

Yumin Wang

Keyword(s):

Prognostic Value ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Gene Set Enrichment ◽

Gene Set ◽

Kaplan Meier ◽

Cancer Genome Atlas

Background PIMREG is upregulated in multiple cancer types. However, the potential role of PIMREG in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to explore its clinical significance in LUAD. Methods Using the Cancer Genome Atlas (TCGA) databases, we obtained 513 samples of LUAD and 59 normal samples from the Cancer Genome Atlas (TCGA) databases to analyze the relationship between PIMREG and LUAD. We used t and Chi-square tests to evaluate the level of expression of PIMREG and its clinical implication in LUAD. The prognostic value of PIMREG in LUAD was identified through the Kaplan–Meier method, Cox regression analysis, and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to screen biological pathways and analyze the correlation of the immune infiltrating level with the expression of PIMREG in LUAD. Results PIMREG was highly expressed in patients with LUAD. Specifically, the level of PIMREG gradually increased from pathological stage I to IV. Further, we validated the higher expression of PIMREG expressed in LUAD cell lines. Moreover, PIMREG had a high diagnostic value, with an -AUC of 0.955. Kaplan–Meier survival and Cox regression analyses revealed that the high expression of PIMREG was independently associated with poor clinical outcomes. In our prognostic nomogram, the expression of PIMREG implied a significant prognostic value. Gene set enrichment analysis (GSEA) identified that the high expression PIMREG phenotype was involved in the mitotic cell cycle, mRNA splicing, DNA repair, Rho GTPase signaling, TP53 transcriptional regulation, and translation pathways. Next, we also explored the correlation of PIMREG and tumor-immune interactions and found a negative correlation between PIMREG and the immune infiltrating level of T cells, macrophages, B cells, dendritic cells (DCs) , and CD8+ T cells in LUAD. Conclusions High levels of PIMREG correlated with poor prognosis and immune infiltrates in LUAD.

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CLEC10A is a Potential Prognostic Biomarker and Immune Regulator of Tumor Microenvironment in Breast Cancer

10.21203/rs.3.rs-295872/v1 ◽

2021 ◽

Author(s):

Jincheng He ◽

Lei Jiang ◽

Jun Wang ◽

Guangtao Min ◽

Xiangwen Wang ◽

...

Keyword(s):

Breast Cancer ◽

T Cells ◽

B Cells ◽

Tumor Microenvironment ◽

Immune Cells ◽

Cox Regression ◽

Clinical Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cox Regression Analysis

Abstract The communication between tumor cells and immune cells influences the ecology of the tumor microenvironment in breast cancer, as well as the disease progression and clinical outcome. The aim of this study was to investigate the prognostic value of the immunomodulatory factor CLEC10A in breast cancer. We applied the CIBERSORT and ESTIMATE calculation methods to calculate the proportion of tumor-infiltrating immune cells (TICs) and the amount of immune and stromal components in 1053 BRCA cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were analyzed by COX regression analysis and protein-protein interaction (PPI) network construction. Then, CLEC10A was identified as a prognostic factor by the intersection analysis of univariate COX and PPI. Further analysis revealed that CLEC10A expression was negatively correlated with the clinical pathologic characteristics (age, clinical stage) and positively correlated with survival of BRCA patients. Gene set enrichment analysis (GSEA) showed that genes in the high CLEC10A expression group were mainly enriched in immune-related activities. Genes in the low CLEC10A expression group were enriched in biochemical functions. CIBERSORT analysis of the proportion of TICs revealed that Macrophages M1, B cells memory, B cells naive, T cells CD4+ memory activated, T cells CD8+, and T cells gamma delta were positively correlated with CLEC10A expression, and Macrophages M0, Macrophages M2, Neutrophils, and NK cells resting were positively correlated with CLEC10A expression was negatively correlated, suggesting that CLEC10A may be an important factor in the immune regulation of the tumor microenvironment, especially in mediating the anti-tumor immune response of tumor-infiltrating immune cells at the tumor initiation stage. Therefore, CLEC10A expression may contribute to the prognosis of BRCA patients and provide a new idea for the immunotherapy of BRCA.

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ARID1A Upregulation Predicts Poor Survival in Patients with Liver Cancer

10.21203/rs.3.rs-166724/v1 ◽

2021 ◽

Author(s):

Feng Jiang ◽

Ke Wei ◽

Ming Wang ◽

Chuyan Wu

Keyword(s):

Overall Survival ◽

Liver Cancer ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Diagnosis And Prognosis ◽

Kaplan Meier ◽

Erbb Signaling

Abstract Objective: ARID1A has been identified as a possible biomarker for certain cancers. There is, however, some debate regarding its function in liver cancer. Methods: Associations between clinical variables and ARID1A were evaluated. Cox and Kaplan – Meier analysis were used to examine clinicalopathological factors linked to overall survival of patients with liver cancer. Gene Set Enrichment Analysis (GSEA) was conducted using the dataset of the Cancer Genome Atlas. Results: High expression of ARID1A was correlated with the gender and tumor topography (T) diagnosis of liver cancer. Patients with elevated ARID1A expression had poorer prognosis than those with low ARID1A expression. The study also showed that ARID1A was an independent risk factor for overall survival. GSEA established pathways involved in ERBB signaling, cancer, insulin signaling, mTOR signaling, MAPK signaling, VEGF signaling, Ubiquitin signaling, and Wnt signaling as differentially enriched in ARID1A-high expression liver cancer. Conclusion: ARID1A has been shown to be expressed at high rates of liver cancer and to represent a possible independent molecular marker for diagnosis and prognosis of liver cancer.

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ARID1A Upregulation Predicts Poor Survival in Patients With Liver Cancer

10.21203/rs.3.rs-146505/v1 ◽

2021 ◽

Author(s):

Feng Jiang ◽

Ke Wei ◽

Ming Wang ◽

Chuyan Wu

Keyword(s):

Overall Survival ◽

Liver Cancer ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Diagnosis And Prognosis ◽

Kaplan Meier ◽

Erbb Signaling

Abstract Objective: ARID1A has been identified as a possible biomarker for certain cancers. There is, however, some debate regarding its function in liver cancer. Methods: Associations between clinical variables and ARID1A were evaluated. Cox and Kaplan – Meier analysis were used to examine clinical pathological factors linked to overall survival of patients with liver cancer. Gene set enrichment analysis (GSEA) was conducted using the dataset of the cancer genome atlas(TCGA). Results: High expression of ARID1A was correlated with the gender and tumor topography (T) diagnosis of liver cancer. Patients with elevated ARID1A expression had poorer prognosis than those with low ARID1A expression. The study also showed that ARID1A was an independent risk factor for overall survival. GSEA established pathways involved in ERBB signaling, cancer, insulin signaling, mTOR signaling, MAPK signaling, VEGF signaling, Ubiquitin signaling, and Wnt signaling as differentially enriched in ARID1A-high expression liver cancer. Conclusion: ARID1A has been shown to be expressed at high rates of liver cancer and to represent a possible independent molecular marker for diagnosis and prognosis of liver cancer.

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