High SPAG5 Expression Is Associated With Oncological Features in Endometrial Carcinoma

Abstract Sperm-associated Antigen 5 (SPAG5, also called astrin) is a mitotic spindle protein. SPAG5 has emerged as a promising biomarker and therapeutic target in a variety of cancers. However, its expression and role in endometrial cancer (EC) remain to be studied. Using multi-omic authoritative datasets from the TCGA and CPTAC studies, we characterized theexpression, regulation of SPAG5 and its association with clinicopathological and molecular features in EC. SPAG5 was observed to be overexpressed in tumor tissues compared to controls and receiver operating characteristic analysis suggested that its mRNA levels are an excellent predictor of tumor presence (AUC>0.98). SPAG5 overexpression was associated with serous histology and The Cancer Genome Atlas (TCGA) defined molecular subtypes. Analysis of DNA methylation levels at SPAG5 genomic regions exhibiting negative correlation to SPAG5 expression. Further, SPAG5 expression was associated with copy number gain in EC. Univariate and multivariate survival analysis revealed that higher SPAG5 expression was independently associated with poor patient outcomes in EC. Additionally, gene set enrichment analysis of SPAG5 correlated genes revealed its association with numerous oncological pathways which suggest its critical involvement in this malignancy.

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CSIG-03. RECONCILING TUMOR HETEROGENEITY IN GLIOBLASTOMA USING A PATHWAY-BASED APPROACH

Neuro-Oncology ◽

10.1093/neuonc/noaa215.115 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii28-ii28

Author(s):

Alvaro Alvarado ◽

Kaleab Tessema ◽

Kunal Patel ◽

Riki Kawaguchi ◽

Richard Everson ◽

...

Keyword(s):

Cell Cycle ◽

Patient Survival ◽

Molecular Subtype ◽

Gene List ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Molecular Architecture ◽

Survival Pathways ◽

Cancer Genome Atlas

Abstract Despite efforts to gain a deeper understanding of its molecular architecture, glioblastoma (GBM) remains uniformly fatal. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has yielded little progress towards extending patient survival. In particular, the great phenotypic heterogeneity of GBM – both inter and intratumorally – has hindered therapeutic efforts. To this end, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. Gene set enrichment analysis (GSEA) was applied to gene expression data and used to provide an overview of each sample that can be compared to other samples by generating sample clusters based on overall patterns of enrichment. The Cancer Genome Atlas (TCGA) samples were clustered using the canonical and oncogenic signatures and in both cases the clustering was distinct from the molecular subtype previously reported and clusters were informative of patient survival. We also analyzed single cell RNA sequencing datasets and uniformly found two clusters of cells enriched for cell cycle regulation and survival pathways. We have validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity when E2F1, out top target, was silenced and when treated with fulvestrant and calcitriol, which were identified as potential drugs targeting this genelist. Conversely, no changes were observed in samples not enriched for this gene list. Finally, we interrogated spatial heterogeneity and found higher enrichment of the proliferative signature in contrast enhancing compared with non-enhancing regions. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

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High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.752974 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qiming Wang ◽

Yan Cai ◽

Xuewen Fu ◽

Liang Chen

Keyword(s):

Cervical Cancer ◽

Poor Prognosis ◽

Biological Significance ◽

Enrichment Analysis ◽

Hpv Infection ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Protein Protein Interaction ◽

Cervical Cancer Cells ◽

Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

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Opposite Roles of BAP1 in Overall Survival of Uveal Melanoma and Cutaneous Melanoma

Journal of Clinical Medicine ◽

10.3390/jcm9020411 ◽

2020 ◽

Vol 9 (2) ◽

pp. 411 ◽

Cited By ~ 2

Author(s):

Feng Liu-Smith ◽

Yunxia Lu

Keyword(s):

Overall Survival ◽

Uveal Melanoma ◽

Cutaneous Melanoma ◽

Cox Regression ◽

Enrichment Analysis ◽

Copy Number Variations ◽

The Cancer Genome Atlas ◽

Small Subset ◽

Mrna Levels ◽

Cancer Genome Atlas

Background: BRCA1-Associated Protein 1 (BAP1) germline mutations predispose individuals to cancers, including uveal melanoma (UM) and cutaneous melanoma (CM). BAP1 loss is common in UM and is associated with a worse prognosis. BAP1 loss is rare in CM and the outcome is unclear. Methods: UM and CM data was retrieved from The Cancer Genome Atlas (TCGA) database. Cox regression model was performed to examine whether BAP1 mRNA levels or copy number variations were associated with overall survival (OS). Results: BAP1-low mRNA predicted a poor OS in UM (HR = 9.57, 95% CI: 2.82, 32.5) but a contrasting better OS in CM (HR = 0.73, 95% CI: 0.56, 0.95). These results remained unchanged after adjusting for sex, age, and stage in UM and CM, or after adjusting for ulceration or Breslow depth in CM. Additionally, low BAP1 mRNA predicted a better OS in CM patients older than 50 years but not in younger patients. Co-expression and enrichment analysis revealed differential genes and mutations that were correlated with BAP1 expression levels in UM and CM tumors. Conclusions: Low BAP1 mRNA was significantly associated with a better OS in CM patients, in sharp contrast to UM. High BAP1 expression in CM was significantly associated with over-expressed CDK1, BCL2, and KIT at the protein level which may explain the poor OS in this sub-group of patients. Function of BAP1 was largely different in CM and UM despite of a small subset of shared co-expressed genes.

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Mind Bomb 1 Promotes Pancreatic Cancer Proliferation by Activating β-Catenin Signaling

Journal of Nanoscience and Nanotechnology ◽

10.1166/jnn.2020.18755 ◽

2020 ◽

Vol 20 (12) ◽

pp. 7276-7282

Author(s):

Xiao Fu ◽

Neng Tang ◽

Weiqi Xie ◽

Liang Mao ◽

Yudong Qiu

Keyword(s):

Pancreatic Cancer ◽

Cancer Metastasis ◽

Mrna Level ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Pancreatic Tumors ◽

Mrna Levels ◽

Cancer Proliferation

Mind bomb 1 (MIB1), an E3 ligase, plays a vital role in chemo-resistance and cancer metastasis. According to The Cancer Genome Atlas (TCGA), MIB1 gene is preferentially amplified in pancreatic cancer. Copy number alterations in MIB1 gene are associated with worse survival. Gene Expression Omnibus (GEO) also showed that pancreatic cancer with high mRNA level of MIB1 tend to be more resistant to gemcitabine and higher mRNA levels of MIB1 are found in pancreatic tumors compared with adjacent normal tissues. MIB1 knockdown (KD) in Panc-1 and HPAF2 cell lines significantly inhibit proliferation and colony formation of pancreatic cancer. The gene set enrichment analysis (GSEA) has also showed that β-catenin is the downstream of MIB1. Western blot analysis showed that total and active β-catenin levels are decreased in MIB1 KD cells. β-catenin inhibitor also inhibits proliferation of Panc-1 and HPAF2 cells. We in this study implanted HPAF2 scramble and MIB1 KD cells orthotopically in athymic nude mice. Gemcitabine was used to treat the mice. Results revealed that after MIB1 KD HPAF2 cells were more sensitive to gemcitabine. In conclusion, we demonstrated that MIB1 promotes pancreatic cancer proliferation through activating β-catenin signaling. MIB1 may thus be a therapeutic target in pancreatic cancer therapy.

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A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme

Frontiers in Genetics ◽

10.3389/fgene.2020.604655 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ming Gao ◽

Xinzhuang Wang ◽

Dayong Han ◽

Enzhou Lu ◽

Jian Zhang ◽

...

Keyword(s):

Glioblastoma Multiforme ◽

Immune Cell ◽

Area Under The Curve ◽

Principal Component ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Non Coding Rna ◽

Cancer Genome Atlas ◽

The Central Nervous System

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system. As biomedicine advances, the researcher has found the development of GBM is closely related to immunity. In this study, we evaluated the GBM tumor immunoreactivity and defined the Immune-High (IH) and Immune-Low (IL) immunophenotypes using transcriptome data from 144 tumors profiled by The Cancer Genome Atlas (TCGA) project based on the single-sample gene set enrichment analysis (ssGSEA) of five immune expression signatures (IFN-γ response, macrophages, lymphocyte infiltration, TGF-β response, and wound healing). Next, we identified six immunophenotype-related long non-coding RNA biomarkers (im-lncRNAs, USP30-AS1, HCP5, PSMB8-AS1, AL133264.2, LINC01684, and LINC01506) by employing a machine learning computational framework combining minimum redundancy maximum relevance algorithm (mRMR) and random forest model. Moreover, the expression level of identified im-lncRNAs was converted into an im-lncScore using the normalized principal component analysis. The im-lncScore showed a promising performance for distinguishing the GBM immunophenotypes with an area under the curve (AUC) of 0.928. Furthermore, the im-lncRNAs were also closely associated with the levels of tumor immune cell infiltration in GBM. In summary, the im-lncRNA signature had important clinical implications for tumor immunophenotyping and guiding immunotherapy in glioblastoma patients in future.

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CXCL5 Has Potential to Be a Marker for Hepatocellular Carcinoma Prognosis and Was Correlating With Immune Infiltrates

Frontiers in Oncology ◽

10.3389/fonc.2021.637023 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yuan Nie ◽

Mei-chun Jiang ◽

Cong Liu ◽

Qi Liu ◽

Xuan Zhu

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Hospital Data ◽

Gene Set Enrichment ◽

Local Hospital ◽

High Expression Group ◽

Cancer Genome Atlas

BackgroundsTumor microenvironment (TME) plays a crucial role in the initiation and progression of Hepatocellular Carcinoma (HCC), especially immune infiltrates. However, there is still a challenge in understanding the modulation of the immune and stromal components in TME, especially TME related genes.MethodsThe proportion of tumor-infiltrating immune cells (TICs) and the immune and stromal scores in 374 HCC patients from The Cancer Genome Atlas (TCGA) database were determined using CIBERSORT and ESTIMATE computational methods. The final screened genes were confirmed by the PPI network and univariate Cox regression of the differentially expressed genes based on different immune or stromal scores. The correlation between the expression levels of the final gene interactions and the clinical characteristics was based on TCGA database and local hospital data. Gene set enrichment analysis (GSEA) and the effect of CXCL5 expression on TICs were conducted.ResultsThere were correlations between the expression of CXCL5 and survival of HCC patients and TMN classification both in TCGA database and local hospital data. The immune-related activities were enriched in the high-expression group; however, the metabolic pathways were enriched in the low-expression group. The result of CIBERSORT analyzing had indicated that CXCL5 expression were correlated with the proportion of NK cells activated, macrophages M0, Mast cells resting, Neutrophils.ConclusionsCXCL5 was a potential prognostic marker for HCC and provides clues regarding immune infiltrates, which offers extra insight for therapeutics of HCC, however, more independent cohorts and functional experiments of CXCL5 are warranted.

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Construction of a CXC Chemokine-Based Prediction Model for the Prognosis of Colon Cancer

BioMed Research International ◽

10.1155/2020/6107865 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Kaisheng Liu ◽

Minshan Lai ◽

Shaoxiang Wang ◽

Kai Zheng ◽

Shouxia Xie ◽

...

Keyword(s):

Gene Expression ◽

Colon Cancer ◽

Overall Survival ◽

Prediction Model ◽

Enrichment Analysis ◽

Forecast Model ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Characteristic Analysis ◽

Incidence And Mortality

Colon cancer is the third most common cancer, with a high incidence and mortality. Construction of a specific and sensitive prediction model for prognosis is urgently needed. In this study, profiles of patients with colon cancer with clinical and gene expression data were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA). CXC chemokines in patients with colon cancer were investigated by differential expression gene analysis, overall survival analysis, receiver operating characteristic analysis, gene set enrichment analysis (GSEA), and weighted gene coexpression network analysis. CXCL1, CXCL2, CXCL3, and CXCL11 were upregulated in patients with colon cancer and significantly correlated with prognosis. The area under curve (AUC) of the multigene forecast model of CXCL1, CXCL11, CXCL2, and CXCL3 was 0.705 in the GSE41258 dataset and 0.624 in TCGA. The prediction model was constructed using the risk score of the multigene model and three clinicopathological risk factors and exhibited 92.6% and 91.8% accuracy in predicting 3-year and 5-year overall survival of patients with colon cancer, respectively. In addition, by GSEA, expression of CXCL1, CXCL11, CXCL2, and CXCL3 was correlated with several signaling pathways, including NOD-like receptor, oxidative phosphorylation, mTORC1, interferon-gamma response, and IL6/JAK/STAT3 pathways. Patients with colon cancer will benefit from this prediction model for prognosis, and this will pave the way to improve the survival rate and optimize treatment for colon cancer.

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Prognostic Biomarker SYK and its Correlation with Immune Infiltrates in Glioma

10.21203/rs.3.rs-839283/v1 ◽

2021 ◽

Author(s):

Pei Liu ◽

Jiamin Guo ◽

Xiaoxiao Xu ◽

Haixin Sun ◽

Zheng Gong

Keyword(s):

Development Process ◽

Prognostic Biomarker ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Ppi Network ◽

Glioma Patient ◽

Gene Set Enrichment ◽

Protein Protein Interaction ◽

Cancer Genome Atlas

Abstract Background: Tumor microenvironment (TME) has great effects on the development process of glioma, and we sought to identify effective prognostic factors by analyzing data from patients with glioma. In this paper, CIBERSORT and ESTIMATE calculations were employed to figure up the ratio of tumor-infiltrating immune cells (TICs) and the quantity of immune and stromal components in 698 glioma dates from The Cancer Genome Atlas (TCGA) database. In addition, differentially expressed genes (DEGs) were studied by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single genes associated with prognosis were identified by PPI network and COX combined analysis. Results: Immune and stromal scores of TME were significantly correlated with glioma patient survival. Through protein–protein interaction (PPI) network and regression analysis of COX, we finally determined that SYK was the best prognostic factor for patients with glioma. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis were also employed, with the former showed that high-expression SYK group’s genes are principally enriched immune-related activities and the latter revealed that SYK expression was positively associated with T cells CD4 memory resting and Monocytes. All the above experimental analyses provided the theoretical basis for the biological prediction of SYK.Conclusions: SYK contributes to immune predictors in glioma patients by facilitating the shift of TME from immune dominance to metabolic activity, which provides promising insights into the treatment of glioma.

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Comprehensive Analysis of Immune Correlation of KIF20A in Pan-cancer

10.21203/rs.3.rs-127486/v1 ◽

2020 ◽

Author(s):

Xiao-Han Cui ◽

Qiu-Ju Peng ◽

Peng Gao ◽

Xu-Dong Zhang ◽

Ren-Zhi Li ◽

...

Keyword(s):

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Immune Checkpoints ◽

Rna Seq ◽

Gene Set Enrichment ◽

Related Information ◽

Common Causes ◽

Cancer Genome Atlas ◽

Pan Cancer

Abstract Background: Cancer is one of the most common causes of death, and the morbidity and mortality are gradually increasing in the world. KIF20A plays an important role in tumors, but its immune relevance in pan-cancer needs to be further studied.Methods: KIF20A-related information was download from The Cancer Genome Atlas (TCGA). Collecting RNA-seq data is fragments per kilobase million (FPKM) style data. The ESTIMATE algorithm was used for estimating the stromal and immune scores for 33 tumors. Then, we analyzed the correlation between KIF20A in pan-cancer and immune checkpoints and performed gene set enrichment analysis (GSEA) analysis on the co-expressed genes of KIF20A in pan-cancer.Results: We have confirmed that the expression of KIF20A has a intensive correlation with prognosis in 33 kinds of tumors. Its expression of KIF20A was related to a variety of immune cells and immune checkpoints. Based on the results of GSEA for further analysis, in multiple tumors, KIF20A is related to immune-related pathways.Conclusion: We have demonstrated that KIF20A played an important role in pan-cancer and could affect the occurrence or development of a variety of tumors. Moreover, KIF20A was related to immunity, and KIF20A- related immune research in pan-cancer also needs to be further demonstrate.

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Tumor mutational burden predicts survival in patients with low-grade gliomas expressing mutated IDH1

Neuro-Oncology Advances ◽

10.1093/noajnl/vdaa042 ◽

2020 ◽

Vol 2 (1) ◽

Cited By ~ 2

Author(s):

Mahmoud S Alghamri ◽

Rohit Thalla ◽

Ruthvik P Avvari ◽

Ali Dabaja ◽

Ayman Taher ◽

...

Keyword(s):

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Low Grade ◽

Low Grade Gliomas ◽

Mutational Burden ◽

Gene Sets ◽

Tumor Mutational Burden ◽

Cancer Genome Atlas ◽

Gene Ontologies

Abstract Background Gliomas are the most common primary brain tumors. High-Grade Gliomas have a median survival (MS) of 18 months, while Low-Grade Gliomas (LGGs) have an MS of approximately 7.3 years. Seventy-six percent of patients with LGG express mutated isocitrate dehydrogenase (mIDH) enzyme. Survival of these patients ranges from 1 to 15 years, and tumor mutational burden ranges from 0.28 to 3.85 somatic mutations/megabase per tumor. We tested the hypothesis that the tumor mutational burden would predict the survival of patients with tumors bearing mIDH. Methods We analyzed the effect of tumor mutational burden on patients’ survival using clinical and genomic data of 1199 glioma patients from The Cancer Genome Atlas and validated our results using the Glioma Longitudinal AnalySiS consortium. Results High tumor mutational burden negatively correlates with the survival of patients with LGG harboring mIDH (P = .005). This effect was significant for both Oligodendroglioma (LGG-mIDH-O; MS = 2379 vs 4459 days in high vs low, respectively; P = .005) and Astrocytoma (LGG-mIDH-A; MS = 2286 vs 4412 days in high vs low respectively; P = .005). There was no differential representation of frequently mutated genes (eg, TP53, ATRX, CIC, and FUBP) in either group. Gene set enrichment analysis revealed an enrichment in Gene Ontologies related to cell cycle, DNA-damage response in high versus low tumor mutational burden. Finally, we identified 6 gene sets that predict survival for LGG-mIDH-A and LGG-mIDH-O. Conclusions we demonstrate that tumor mutational burden is a powerful, robust, and clinically relevant prognostic factor of MS in mIDH patients.

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