Unveiling Prognostics Biomarkers of Tyrosine Metabolism Reprogramming in Liver Cancer by Cross-platform Gene Expression Analyses

AbstractTyrosine is mainly degraded in the liver by a series of enzymatic reactions. Abnormal expression of the tyrosine catabolic enzyme tyrosine aminotransferase (TAT) has been reported in patients with hepatocellular carcinoma (HCC). Despite this, aberration in tyrosine metabolism has not been investigated in cancer development. In this work, we conduct comprehensive cross-platform study to obtain foundation for discoveries of potential therapeutics and preventative biomarkers of HCC. We explore data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine and Kaplan Meier plotter (KM plotter) and performed integrated analyses to evaluate the clinical significance and prognostic values of the tyrosine catabolic genes in HCC. We find that five tyrosine catabolic enzymes are downregulated in HCC compared to normal liver at mRNA and protein level. Moreover, low expression of these enzymes correlates with poorer survival in patients with HCC. Notably, we identify pathways and upstream regulators that might involve in tyrosine catabolic reprogramming and further drive HCC development. In total, our results underscore tyrosine metabolism alteration in HCC and lay foundation for incorporating these pathway components in therapeutics and preventative strategies.

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OSmfs: An Online Interactive Tool to Evaluate Prognostic Markers for Myxofibrosarcoma

Genes ◽

10.3390/genes11121523 ◽

2020 ◽

Vol 11 (12) ◽

pp. 1523

Author(s):

Huimin Li ◽

Longxiang Xie ◽

Qiang Wang ◽

Yifang Dang ◽

Xiaoxiao Sun ◽

...

Keyword(s):

Gene Expression ◽

Poor Prognosis ◽

Analysis Data ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Prognostic Biomarkers ◽

Rank Test ◽

Web Tool ◽

Kaplan Meier ◽

Cox Analysis

Myxofibrosarcoma is a complex genetic disease with poor prognosis. However, more effective biomarkers that forebode poor prognosis in Myxofibrosarcoma remain to be determined. Herein, utilizing gene expression profiling data and clinical follow-up data of Myxofibrosarcoma cases in three independent cohorts with a total of 128 Myxofibrosarcoma samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we constructed an easy-to-use web tool, named Online consensus Survival analysis for Myxofibrosarcoma (OSmfs) to analyze the prognostic value of certain genes. Through retrieving the database, users generate a Kaplan–Meier plot with log-rank test and hazard ratio (HR) to assess prognostic-related genes or discover novel Myxofibrosarcoma prognostic biomarkers. The effectiveness and availability of OSmfs were validated using genes in ever reports predicting the prognosis of Myxofibrosarcoma patients. Furthermore, utilizing the cox analysis data and transcriptome data establishing OSmfs, seven genes were selected and considered as more potentially prognostic biomarkers through overlapping and ROC analysis. In conclusion, OSmfs is a promising web tool to evaluate the prognostic potency and reliability of genes in Myxofibrosarcoma, which may significantly contribute to the enrichment of novelly potential prognostic biomarkers and therapeutic targets for Myxofibrosarcoma.

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Identification and Validation of a Novel Immune-Related Four-lncRNA Signature for Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.639254 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jixin Wang ◽

Xiangjun Yin ◽

Yin-Qiang Zhang ◽

Xuming Ji

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Lasso Regression ◽

Kaplan Meier

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer, the prognosis of patients with which is associated with both lncRNAs and cancer immunity. In this study, we collected gene expression data of 585 LUAD patients from The Cancer Genome Atlas (TCGA) database and 605 subjects from the Gene Expression Omnibus (GEO) database. LUAD patients were divided into high and low immune-cell-infiltrated groups according to the single sample gene set enrichment analysis (ssGSEA) algorithm to identify differentially expressed genes (DEGs). Based on the 49 immune-related DE lncRNAs, a four-lncRNA prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) regression, univariate Cox regression, and stepwise multivariate Cox regression in sequence. Kaplan–Meier curve, ROC analysis, and the testing GEO datasets verified the effectiveness of the signature in predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression suggested that the signature was an independent prognostic factor. The correlation analysis revealed that the infiltration immune cell subtypes were related to these lncRNAs.

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Construction of a Pseudogene‐associated ceRNA Network and Identification of Prognostic Pseudogene Biomarkers for Colorectal Cancer

10.21203/rs.3.rs-620279/v1 ◽

2021 ◽

Author(s):

Zhuoqi Li ◽

Jing Zhou ◽

Liankun Gu ◽

Baozhen Zhang

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Cox Regression ◽

Expression Profiles ◽

Colon Adenocarcinoma ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Cox Regression Analysis ◽

Cerna Network ◽

Kaplan Meier

Abstract Colorectal cancer (CRC) is one of the most common and deadly malignant carcinomas. Many long noncoding RNAs (lncRNA) have been reported to play an important role in the tumorigenesis of CRC by interacting with miRNAs and influencing the expression of some mRNAs through a competing endogenous RNA (ceRNA) network. Pseudogenes are one kind of lncRNA and can act as RNA sponges for miRNAs and regulate gene expression via ceRNA networks, but there are few studies about pseudogenes in CRC. In this study, total of 31 differentially expressed (DE) pseudogenes, 17 DE miRNAs and 152 DE mRNAs were identified by analyzing the expression profiles of colon adenocarcinoma (COAD) obtained from The Cancer Genome Atlas (TCGA). And a ceRNA network was constructed based on these RNAs. Kaplan–Meier analysis showed that 7 pseudogenes, 4 miRNAs and 30 mRNAs were significantly associated with overall survival. Then multivariate Cox regression analysis on the ceRNA-related DE pseudogenes was performed and a 5-pseudogene signature with the greatest prognostic value for CRC was identified. What’s more, the results were validated by the Gene Expression Omnibus (GEO) database, and quantitative real‐time PCR (qRT‐PCR) in 113 pairs of CRC tissues. In conclusion, this study provides a pseudogene-associated ceRNA network and 7 prognostic pseudogene biomarkers, and a 5-pseudogene prognostic risk signature that may be useful to predict the survival of CRC patients.

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Prognostic Values of Stabilin-2 in Hepatocellular Carcinoma

10.21203/rs.3.rs-27280/v1 ◽

2020 ◽

Author(s):

Zhicheng Du ◽

Pengfei Zhu ◽

Long Yu ◽

Kunlun Chen ◽

Janwen Ye ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Survival Time ◽

Cox Regression ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Primary Malignancy ◽

Diagnosis And Prognosis ◽

Kaplan Meier ◽

Potential Biomarker

Abstract Background: Hepatocellular carcinoma (HCC) is the primary malignancy of the liver. However, biomarkers for early HCC diagnosis are not available. Stabilin (STAB) proteins are scavenger receptors involved in apoptosis and clearance of hyaluronic acid .The role of STAB in HCC has not been previously explored; therefore, the aim of this study was to assess whether STAB gene expression can be used as a novel HCC biomarker.Materials and Methods: Data on 370 HCC patients in the Cancer Genome Atlas database and 221 patients in the Gene Expression Comprehensive Database were retrieved and analyzed. Kaplan–Meier analysis and Cox regression model were used to calculate median survival time using hazard ratio (HR) and 95% confidence interval (CI). Results: The Gene Expression Omnibus dataset showed that high Stabilin-2（STAB2） expression implies longer overall survival (HR after correction = 0.541; 95% CI, 0.339–0.865; p = 0.0182, after correction p = 0.010) and longer recurrence-free survival time (adjusted HR = 0.554; 95% CI, 0.376-0.816; p = 0.0085, adjusted p = 0.003). Conclusions: STAB2 is a potential biomarker for the diagnosis and prognosis of HCC.

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Novel Epigenetic Eight-Gene Signature Predictive of Poor Prognosis and MSI-Like Phenotype in Human Metastatic Colorectal Carcinomas

Cancers ◽

10.3390/cancers13010158 ◽

2021 ◽

Vol 13 (1) ◽

pp. 158

Author(s):

Valentina Condelli ◽

Giovanni Calice ◽

Alessandra Cassano ◽

Michele Basso ◽

Maria Grazia Rodriquenz ◽

...

Keyword(s):

Gene Expression ◽

Poor Prognosis ◽

Cpg Island ◽

Colon Adenocarcinoma ◽

Gene Signature ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Cpg Island Methylator Phenotype ◽

Prognostic Information ◽

Global Methylation

Epigenetics is involved in tumor progression and drug resistance in human colorectal carcinoma (CRC). This study addressed the hypothesis that the DNA methylation profiling may predict the clinical behavior of metastatic CRCs (mCRCs). The global methylation profile of two human mCRC subgroups with significantly different outcome was analyzed and compared with gene expression and methylation data from The Cancer Genome Atlas COlon ADenocarcinoma (TCGA COAD) and the NCBI GENE expression Omnibus repository (GEO) GSE48684 mCRCs datasets to identify a prognostic signature of functionally methylated genes. A novel epigenetic signature of eight hypermethylated genes was characterized that was able to identify mCRCs with poor prognosis, which had a CpG-island methylator phenotype (CIMP)-high and microsatellite instability (MSI)-like phenotype. Interestingly, methylation events were enriched in genes located on the q-arm of chromosomes 13 and 20, two chromosomal regions with gain/loss alterations associated with adenoma-to-carcinoma progression. Finally, the expression of the eight-genes signature and MSI-enriching genes was confirmed in oxaliplatin- and irinotecan-resistant CRC cell lines. These data reveal that the hypermethylation of specific genes may provide prognostic information that is able to identify a subgroup of mCRCs with poor prognosis.

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Functions and clinical significance of KLRG1 in the development of lung adenocarcinoma and immunotherapy

BMC Cancer ◽

10.1186/s12885-021-08510-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiaodong Yang ◽

Yuexin Zheng ◽

Zhihai Han ◽

Xiliang Zhang

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Lung Adenocarcinoma ◽

Molecular Mechanisms ◽

Killer Cell ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Normal Lung ◽

Using Data ◽

Low Expression

Abstract Background As a marker of differentiation, Killer cell lectin like receptor G1 (KLRG1) plays an inhibitory role in human NK cells and T cells. However, its clinical role remains inexplicit. This work intended to investigate the predictive ability of KLRG1 on the efficacy of immune-checkpoint inhibitor in the treatment of lung adenocarcinoma (LUAD), as well as contribute to the possible molecular mechanisms of KLRG1 on LUAD development. Methods Using data from the Gene Expression Omnibus, the Cancer Genome Atlas and the Genotype-Tissue Expression, we compared the expression of KLRG1 and its related genes Bruton tyrosine kinase (BTK), C-C motif chemokine receptor 2 (CCR2), Scm polycomb group protein like 4 (SCML4) in LUAD and normal lung tissues. We also established stable LUAD cell lines with KLRG1 gene knockdown and investigated the effect of KLRG1 knockdown on tumor cell proliferation. We further studied the prognostic value of the four factors in terms of overall survival (OS) in LUAD. Using data from the Gene Expression Omnibus, we further investigated the expression of KLRG1 in the patients with different responses after immunotherapy. Results The expression of KLRG1, BTK, CCR2 and SCML4 was significantly downregulated in LUAD tissues compared to normal controls. Knockdown of KLRG1 promoted the proliferation of A549 and H1299 tumor cells. And low expression of these four factors was associated with unfavorable overall survival in patients with LUAD. Furthermore, low expression of KLRG1 also correlated with poor responses to immunotherapy in LUAD patients. Conclusion Based on these findings, we inferred that KLRG1 had significant correlation with immunotherapy response. Meanwhile, KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD.

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Decision theory for precision therapy of breast cancer

Scientific Reports ◽

10.1038/s41598-021-82418-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Michael Kenn ◽

Dan Cacsire Castillo-Tong ◽

Christian F. Singer ◽

Rudolf Karch ◽

Michael Cibena ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Decision Theory ◽

Data Science ◽

Gene Expression Omnibus ◽

Hormone Receptor Status ◽

Breast Cancer Patients ◽

Receptor Status ◽

Kaplan Meier ◽

Precision Therapy

AbstractCorrectly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.

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BART Cancer: a web resource for transcriptional regulators in cancer genomes

NAR Cancer ◽

10.1093/narcan/zcab011 ◽

2021 ◽

Vol 3 (1) ◽

Author(s):

Zachary V Thomas ◽

Zhenjia Wang ◽

Chongzhi Zang

Keyword(s):

Gene Expression ◽

Cancer Research ◽

Computational Prediction ◽

Transcriptional Regulators ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Regulation Of Transcription ◽

Data Resource ◽

Web Resource ◽

Cancer Types

Abstract Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10000 gene expression profiling RNA-seq datasets from TCGA with over 7000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.

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Development and validation of a 13-m6a related lncRNA prognostic signature for lung adenocarcinoma

10.21203/rs.3.rs-771653/v1 ◽

2021 ◽

Author(s):

Pingfan Wu ◽

Xiaowen Zhao ◽

Ling Xue ◽

Xiaojing Yang ◽

Yuxiang Shi ◽

...

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Treatment Strategies ◽

Risk Groups ◽

Gene Expression Omnibus ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Prognostic Signature ◽

P53 Signaling ◽

Selection Operator

Abstract Considerable evidence suggests that N6-methyladenosine (m6A) is involved in the regulation of long non-coding RNA (lncRNA), whichparticipates in the occurrence, development and prognosis of tumorscancerBut the relationship between m6A regulators-related lncRNA (mRlncRNA) and lung adenocarcinoma (LUAD) remains unclear. This study aims to determine a feature based on mRlncRNA for prognostic evaluation of LUAD patients. By integrating the gene expression data of LUAD and normal samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, the m6A gene and mRlncRNA with imbalanced expression were screened out. Then we used the least absolute shrinkage and selection operator (LASSO) to obtain the 13-lncRNA prognostic signature in the TCGA training cohort. Patients were divided into two risk groups based on the risk score of lncRNAs characteristics, and their overall survival (OS) was significantly different. The predictive power of this signature was verified in TCGA testing cohort and entire TCGA cohort. These landmark lncRNAs were involved in several biologiocal processes and pathways related to cell cycle, DNA replication, P53 signaling pathway and mismatch repair. Besides, the high-risk group was low-response to cisplatin, while high-response to mitomycin, docetaxel and immunotherapy. In conclusion, we identified a 13-mRlncRNA model associated with prognosis and treatment sensitivity in LUAD, which may provide clues about the influence of m6A on lncRNA in LUAD and promote the further improvement of LUAD individualized treatment strategies.

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SMC4, CCNB1 and CKS1B as potential targets and new critical biomarkers for the prognosis of human bladder cancer

10.21203/rs.3.rs-595148/v1 ◽

2021 ◽

Author(s):

Hongpeng Fang ◽

Zhansen Huang ◽

Xianzi Zeng ◽

Jiaming Wan ◽

Jieying Wu ◽

...

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Transcriptional Level ◽

Hub Genes ◽

Kaplan Meier ◽

High Form

Abstract Background As a common malignant cancer of the urinary system, the precise molecular mechanisms of bladder cancer remain to be illuminated. The purpose of this study was to identify core genes with prognostic value as potential oncogenes for the diagnosis, prognosis or novel therapeutic targets of bladder cancer. Methods The gene expression profiles GSE3167 and GSE7476 were available from the Gene Expression Omnibus (GEO) database. Next, PPI network was built to filter the hub gene through the STRING database and Cytoscape software and GEPIA and Kaplan-Meier plotter were implemented. Frequency and type of hub genes and sub groups analysis were performed in cBioportal and ULCAN database. Finally,We used RT-qPCR to confirm our results. Results Totally, 251 DEGs were excavated from two datasets in our study. We only founded high expression of SMC4, TYMS, CCNB1, CKS1B, NUSAP1 and KPNA2 was associated with worse outcomes in bladder cancer patients and no matter from the type of mutation or at the transcriptional level of hub genes, the tumor showed a high form of expression. However, only the expression of SMC4,CCNB1and CKS1B remained changed between the cancer and the normal samples in our results of RT-qPCR. Conclusion In conclusion,These findings indicate that the SMC4,CCNB1 and CKS1B may serve as critical biomarkers in the development and poor prognosis.

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