scholarly journals Pan-cancer analysis combined with experiments predicts CTHRC1 as a therapeutic target for human cancers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dazhao Peng ◽  
Cheng Wei ◽  
Xiaoyang Zhang ◽  
Shenghui Li ◽  
Hao Liang ◽  
...  
Keyword(s):  
Cell Lines ◽  
Therapeutic Target ◽  
Immune Cell ◽  
Single Gene ◽  
Wnt Signaling Pathway ◽  
Disease Process ◽  
Genetic Alterations ◽  
Human Cancers ◽  
And Function ◽  
Pan Cancer

Abstract Background The function of collagen triple helix repeat containing 1 (CTHRC1) as an oncogene has been reported in a growing number of publications. Bioinformatics methods represent a beneficial approach to examine the mechanism and function of the CTHRC1 gene in the disease process of cancers from a pan-cancer perspective. Methods In this study, using the online databases UCSC, NCBI, HPA, TIMER2, Oncomine, GEPIA, UALCAN, cBioPortal, COSMIC, MEXPRESS, STRING, CCLE, LinkedOmics, GTEx, TCGA, CGGA, and SangerBox, we focused on the relationship between CTHRC1 and tumorigenesis, progression, methylation, immunity, and prognosis. qPCR was used to detect CTHRC1 expression in glioma tissues and cell lines. Results The pan-cancer analysis showed that CTHRC1 was overexpressed in most tumors, and a significant correlation was observed between CTHRC1 expression and the prognosis of patients with cancer. CTHRC1 genetic alterations occur in diverse tumors and are associated with tumor progression. Levels of CTHRC1 promoter methylation were decreased in most cancer tissues compared with normal tissues. In addition, CTHRC1 coordinated the activity of ICP genes through diverse signal transduction pathways, was also associated with immune cell infiltration and the tumor microenvironment, and potentially represented a promising immunotherapy target. We identified CTHRC1-related genes across cancers using the GEPIA2 tool. The single-gene GO analysis of CTHRC1 across cancers showed that it was involved in some signaling pathways and biological processes, such as the Wnt signaling pathway, cell migration, and positive regulation of protein binding. The expression and function of CTHRC1 were also further verified in glioma tissues and cell lines. Conclusions CTHRC1 is overexpressed in various cancer types and functions as an important oncogene that may promote tumorigenesis and development through different mechanisms. CTHRC1 may represent an important therapeutic target for human cancers.

Oncogenetic Function and Prognostic Value of DNA Topoisomerase II Alpha (TOP2A) in Human Malignances: A Pan-Cancer Analysis

2021 ◽  
Author(s):  
Fulai Zhao ◽  
Junli Chang ◽  
Wenyi Wang ◽  
Xingyuan Sun ◽  
Xiaoping Ma ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Topoisomerase Ii ◽  
Immune Cell ◽  
Wnt Signaling Pathway ◽  
Topoisomerase Ii Alpha ◽  
Dna Topoisomerase ◽  
Human Cancers ◽  
Go Enrichment ◽  
Comprehensive Knowledge ◽  
Pan Cancer

Abstract Increasing studies have revealed significant associations between TOP2A with oncogenesis and prognosis of human cancers; however, pan-cancer analysis has not been reported. Here, we explored the potential carcinogenic function, the association with clinical outcomes of TOP2A in 33 different human cancers. The results showed that TOP2A was amplified in 32 investigated cancers; TOP2A expression was significantly associated with metastasis of six different cancers, and significantly associated with the survivals of patients in ten different cancers; TOP2A encoded protein was obviously upregulated in five available cancers; phosphorylated TOP2A protein at S1106 was significantly upregulated in all six available cancers. Moreover, TOP2A expression was found to be associated with the cancer-associated immune cell infiltration, including fibroblasts, Tregs and macrophages. In addition, Kyoto encyclopedia of genes and genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses revealed a most significant association between TOP2A with Wnt signaling pathway, and DNA conformation change. This work provides a comprehensive knowledge of TOP2A in different cancers, including carcinogenic function, prognostic values for metastasis and clinical outcomes.

scholarly journals Pan-cancer analysis reveals TAp63-regulated oncogenic lncRNAs that promote cancer progression through AKT activation

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Marco Napoli ◽  
Xiaobo Li ◽  
Hayley D. Ackerman ◽  
Avani A. Deshpande ◽  
Ivan Barannikov ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Tumour Progression ◽  
Genetic Alterations ◽  
Mammary Adenocarcinoma ◽  
Akt Pathway ◽  
Metastasis Suppressor ◽  
P53 Family ◽  
Akt Activation ◽  
Human Cancers ◽  
Pan Cancer

Abstract The most frequent genetic alterations across multiple human cancers are mutations in TP53 and the activation of the PI3K/AKT pathway, two events crucial for cancer progression. Mutations in TP53 lead to the inhibition of the tumour and metastasis suppressor TAp63, a p53 family member. By performing a mouse-human cross species analysis between the TAp63 metastatic mammary adenocarcinoma mouse model and models of human breast cancer progression, we identified two TAp63-regulated oncogenic lncRNAs, TROLL-2 and TROLL-3. Further, using a pan-cancer analysis of human cancers and multiple mouse models of tumour progression, we revealed that these two lncRNAs induce the activation of AKT to promote cancer progression by regulating the nuclear to cytoplasmic translocation of their effector, WDR26, via the shuttling protein NOLC1. Our data provide preclinical rationale for the implementation of these lncRNAs and WDR26 as therapeutic targets for the treatment of human tumours dependent upon mutant TP53 and/or the PI3K/AKT pathway.

scholarly journals Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2927 ◽  
Author(s):  
Linh Nguyen ◽  
Cuong C Dang ◽  
Pedro J. Ballester
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cell Line ◽  
Cell Lines ◽  
Gene Expression Data ◽  
Single Gene ◽  
Cancer Cell Line ◽  
Expression Data ◽  
Gene Markers ◽  
Pan Cancer

Background:Selected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data.Methods:Here we present this systematic comparison using Random Forest (RF) classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than K-fold cross-validation.Results and Discussion:Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug). Regarding overall classification performance, about two thirds of the drugs are better predicted by multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG.Conclusions:We now know that this type of models can predictin vitrotumour response to these drugs. These models can thus be further investigated onin vivotumour models.

scholarly journals Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data

2016 ◽  
Author(s):  
Linh C. Nguyen ◽  
Cuong C. Dang ◽  
Pedro J. Ballester
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cell Line ◽  
Cell Lines ◽  
Gene Expression Data ◽  
Single Gene ◽  
Cancer Cell Line ◽  
Expression Data ◽  
Gene Markers ◽  
Pan Cancer

AbstractSelected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data.Here we present this systematic comparison using Random Forest (RF) classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than K-fold cross-validation. Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug). Regarding overall classification performance, about two thirds of the drugs are better predicted by multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG.

scholarly journals Pan-cancer characterization of GDF15 as a potential prognosis and immunological biomarker

2021 ◽  
Author(s):  
Xiaolei Li ◽  
Qian Huai ◽  
Cheng Zhu ◽  
Yishan Du ◽  
Fang Ma ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cellular Proliferation ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Loss Of Function ◽  
Comprehensive Overview ◽  
Immune Infiltration ◽  
Functional Mechanisms ◽  
Pan Cancer

Abstract Background Growth/differentiation factor 15 (GDF15) is a member of the TGF-b superfamily whose expression is increased in response to cellular stress and disease. Although emerging cell-or animal-based evidence supports the relationship between GDF15 and cancers, systematic pan-cancer analysis of GDF15 remains unavailable. Thus, we aimed to explore the prognostic and immunological roles of GDF15 across different types of tumors. Methods A comprehensive analysis of GDF15 in 33 types of cancer was performed based on the TCGA database. This involved an analysis of mRNA expression profiles, genetic alterations, methylation, prognostic values, immune infiltration analysis, potential biological pathways. Moreover, both the gain and loss of function strategies were used to assess the function of GDF15 in cell lines of hepatocellular carcinoma (HCC). Results GDF15 is highly expressed in most types of cancers, and there is a significant correlation between the expression of GDF15 and the prognosis of cancer patients. We have observed that GDF15 promotes the proliferation and invasion of HCC cell lines. Subsequently, methylation analyses suggested that high GDF15 expression likely resulted from hypomethylation, and immune infiltration analysis showed that GDF15 may have an impact on the changes in the tumor microenvironment. Moreover, enrichment analysis revealed that TGF-beta signaling and metabolism pathways were involved in the functional mechanisms of GDF15. Conclusions Our unpresented pan-cancer analysis of GDF15 offers a relatively comprehensive overview of the oncogenic roles of GDF15 in multiple human cancers. GDF15 may prompt HCC cellular proliferation, invasion and metastasis. All of these provides solid basement and will promote more advanced understanding the role of GDF15 in tumorigenesis and development from the perspective of clinical tumor samples and cells.

scholarly journals INTS8 is a therapeutic target for intrahepatic cholangiocarcinoma via the integration of bioinformatics analysis and experimental validation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi Zhou ◽  
Li Ji ◽  
Xueying Shi ◽  
Dawei Deng ◽  
Fangyue Guo ◽  
...  
Keyword(s):  
Cell Lines ◽  
Intrahepatic Cholangiocarcinoma ◽  
Therapeutic Target ◽  
Primary Liver Cancer ◽  
Univariate Analysis ◽  
Dna Methyltransferases ◽  
The Cancer Genome Atlas ◽  
Mmr Genes ◽  
Pan Cancer

AbstractIntrahepatic cholangiocarcinoma (CHOL) remains a rare malignancy, ranking as the leading lethal primary liver cancer worldwide. However, the biological functions of integrator complex subunit 8 (INTS8) in CHOL remain unknown. Thus, this research aimed to explore the potential role of INTS8 as a novel diagnostic or therapeutic target in CHOL. Differentially expressed genes (DEGs) in two Gene Expression Omnibus (GEO) datasets were obtained by the “RRA” package in R software. The “maftools” package was used to visualize the CHOL mutation data from The Cancer Genome Atlas (TCGA) database. The expression of INTS8 was detected by performing quantitative reverse transcription-PCR (qRT-PCR) and immunohistochemistry in cell lines and human samples. The association between subtypes of tumour-infiltrating immune cells (TIICs) and INTS8 expression in CHOL was determined by using CIBERSORT tools. We evaluated the correlations between INTS8 expression and mismatch repair (MMR) genes and DNA methyltransferases (DNMTs) in pan-cancer analysis. Finally, the pan-cancer prognostic signature of INTS8 was identified by univariate analysis. We obtained the mutation landscapes of an RRA gene set in CHOL. The expression of INTS8 was upregulated in CHOL cell lines and human CHOL samples. Furthermore, INTS8 expression was closely associated with a distinct landscape of TIICs, MMR genes, and DNMTs in CHOL. In addition, the high INTS8 expression group presented significantly poor outcomes, including overall survival (OS), disease-specific survival (DSS) and disease-free interval (DFI) (p < 0.05) in pan-cancer. INTS8 contributes to the tumorigenesis and progression of CHOL. Our study highlights the significant role of INTS8 in CHOL and pan-cancers, providing a valuable molecular target for cancer research.

scholarly journals Current Insights and Future Prospects for Targeting IL-17 to Treat Patients With Systemic Lupus Erythematosus

2021 ◽  
Vol 11 ◽  
Author(s):  
Tomohiro Koga ◽  
Kunihiro Ichinose ◽  
Atsushi Kawakami ◽  
George C. Tsokos
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Therapeutic Target ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Ex Vivo ◽  
Systemic Lupus ◽  
Promising Therapeutic Target ◽  
Attractive Therapeutic Target ◽  
And Function

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by immune cell abnormalities which lead to the production of autoantibodies and the deposition of immune complexes. Interleukin (IL)-17-producing cells play an important role in the pathogenesis of the disease, making them an attractive therapeutic target. Studies in lupus-prone mice and of ex vivo cells from patients with SLE humans have shown that IL-17 represents a promising therapeutic target. Here we review molecular mechanisms involved in IL-17 production and Th17 cell differentiation and function and an update on the role of IL-17 in autoimmune diseases and the expected usefulness for targeting IL-17 therapeutically.

IL-23 and IL-2 activation of STAT5 is required for optimal IL-22 production in ILC3s during colitis

2020 ◽  
Vol 5 (46) ◽  
pp. eaav1080 ◽  
Author(s):  
David Bauché ◽  
Barbara Joyce-Shaikh ◽  
Julie Fong ◽  
Alejandro V. Villarino ◽  
Karin S. Ku ◽  
...  
Keyword(s):  
Immune Cells ◽  
Interleukin 2 ◽  
Disease Process ◽  
Genetic Alterations ◽  
Lymphoid Cells ◽  
Nucleotide Polymorphisms ◽  
Stat Proteins ◽  
Increased Risk ◽  
Promoter Dna ◽  
And Function

Signal transducer and activator of transcription (STAT) proteins have critical roles in the development and function of immune cells. STAT signaling is often dysregulated in patients with inflammatory bowel disease (IBD), suggesting the importance of STAT regulation during the disease process. Moreover, genetic alterations in STAT3 and STAT5 (e.g., deletions, mutations, and single-nucleotide polymorphisms) are associated with an increased risk for IBD. In this study, we elucidated the precise roles of STAT5 signaling in group 3 innate lymphoid cells (ILC3s), a key subset of immune cells involved in the maintenance of gut barrier integrity. We show that mice lacking either STAT5a or STAT5b are more susceptible to Citrobacter rodentium–mediated colitis and that interleukin-2 (IL-2)– and IL-23–induced STAT5 drives IL-22 production in both mouse and human colonic lamina propria ILC3s. Mechanistically, IL-23 induces a STAT3-STAT5 complex that binds IL-22 promoter DNA elements in ILC3s. Our data suggest that STAT5a/b signaling in ILC3s maintains gut epithelial integrity during pathogen-induced intestinal disease.

scholarly journals Discovery of Latent Drivers from Double Mutations in Pan-Cancer Data Reveal their Clinical Impact

2021 ◽  
Author(s):  
Bengi Ruken Yavuz ◽  
Chung-Jung Tsai ◽  
Ruth Nussinov ◽  
Nurcan Tuncbag
Keyword(s):  
Cell Lines ◽  
Drug Response ◽  
Cancer Genomics ◽  
Single Gene ◽  
Clinical Information ◽  
Driver Mutations ◽  
Patient Specific ◽  
Cancer Data ◽  
Activated State ◽  
Pan Cancer

Transforming patient-specific molecular data into clinical decisions is fundamental to personalized medicine. Despite massive advancements in cancer genomics, to date driver mutations whose frequencies are low, and their observable transformation potential is minor have escaped identification. Yet, when paired with other mutations in cis, such 'latent driver' mutations can drive cancer. Here, we discover potential 'latent driver' double mutations. We applied a statistical approach to identify significantly co-occurring mutations in the pan-cancer data of mutation profiles of ~80,000 tumor sequences from the TCGA and AACR GENIE databases. The components of same gene doublets were assessed as potential latent drivers. We merged the analysis of the significant double mutations with drug response data of cell lines and patient derived xenografts (PDXs). This allowed us to link the potential impact of double mutations to clinical information and discover signatures for some cancer types. Our comprehensive statistical analysis identified 228 same gene double mutations of which 113 mutations are cataloged as latent drivers. Oncogenic activation of a protein can be through either single or multiple independent mechanisms of action. Combinations of a driver mutation with either a driver, a weak driver, or a strong latent driver have the potential of a single gene leading to a fully activated state and high drug response rate. Tumor suppressors require higher mutational load to coincide with double mutations compared to oncogenes which implies their relative robustness to losing their functions. Evaluation of the response of cell lines and patient-derived xenograft data to drug treatment indicate that in certain genes double

scholarly journals Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of Dickkopf-1 (DKK1)

2021 ◽  
Vol 12 ◽  
Author(s):  
Shuang Gao ◽  
Ye Jin ◽  
Hongmei Zhang
Keyword(s):  
Wnt Signaling ◽  
Signaling Pathway ◽  
Immune Cell ◽  
Wnt Signaling Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Dickkopf 1 ◽  
Pan Cancer

WNT signaling pathway inhibitor Dickkopf-1 (DKK1) is related to cancer progression; however, its diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. In this study, multiple bioinformatic analyses were conducted to evaluate therapeutic value of DKK1 in human cancers. The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project served as data resources. The Wilcoxon rank test was performed to evaluate the expression difference of DKK1 between cancer tissues and normal tissues. A Kaplan-Meier curve and Cox regression were used for prognosis evaluation. Single-sample gene set enrichment analysis (ssGSEA) was used to evaluate the association of DKK1 expression with the immune cell infiltration. The potential function of DKK1 was explored by STRING and clusterProfiler. We found that the expression level of DKK1 is significantly different in different cancer types. Importantly, we demonstrated that DKK1 is an independent risk factor in ESCA, LUAD, MESO, and STAD. Further analysis revealed that DKK1 had a large effect on the immune cell infiltration and markers of certain immune cells, such as Th1 and Th2 cells. PPI network analysis and further pathway enrichment analysis indicated that DKK1 was mainly involved in the WNT signaling pathway. Our findings suggested that DKK1 might serve as a marker of prognosis for certain cancers by affecting the WNT signaling pathway and tumor immune microenvironment.

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