Deficiency of 15-LOX-1 Induces Radioresistance through Downregulation of MacroH2A2 in Colorectal Cancer

Despite the importance of radiation therapy, there are few radiation-related markers available for use in clinical practice. A larger catalog of such biomarkers is required to help clinicians decide when radiotherapy should be replaced with a patient-specific treatment. Arachidonate 15-lipoxygenase (15-LOX-1) enzyme is involved in polyunsaturated fatty acid metabolism. When colorectal cancer (CRC) cells were exposed to radiation, 15-LOX-1 was upregulated. To verify whether 15-LOX-1 protects against or induces DNA damage, we irradiated sh15-LOX-1 stable cells. We found that low 15-LOX-1 is correlated with radioresistance in CRC cells. These data suggest that the presence of 15-LOX-1 can be used as a marker for radiation-induced DNA damage. Consistent with this observation, gene-set-enrichment analysis based on microarray experiments showed that UV_RESPONSE was decreased in sh15-LOX-1 cells compared to shCon cells. Moreover, we discovered that the expression of the histone H2A variant macroH2A2 was sevenfold lower in sh15-LOX-1 cells. Overall, our findings present mechanistic evidence that macroH2A2 is transcriptionally regulated by 15-LOX-1 and suppresses the DNA damage response in irradiated cells by delaying H2AX activation.

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Radiation-induced DNA damage response and resistance in colorectal cancer stem-like cells

International Journal of Radiation Biology ◽

10.1080/09553002.2019.1580401 ◽

2019 ◽

Vol 95 (6) ◽

pp. 667-679 ◽

Cited By ~ 9

Author(s):

Kumari Anuja ◽

Amit Roy Chowdhury ◽

Arka Saha ◽

Souvick Roy ◽

Arabinda Kumar Rath ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Damage ◽

Dna Damage Response ◽

Damage Response ◽

Radiation Induced

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Identification of a Hypoxia - Related lncRNA Signature For The Prognosis of Colorectal Cancer

10.21203/rs.3.rs-757504/v1 ◽

2021 ◽

Author(s):

HUA HUANG ◽

Shanshan Xu ◽

Youran Li ◽

Yunfei Gu ◽

Lijiang Ji

Keyword(s):

Colorectal Cancer ◽

Roc Analysis ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Receptor Interaction ◽

Prognostic Signature ◽

Gene Set Enrichment ◽

Gene Set

Abstract Background: Colorectal cancer (CRC), the commonly seen malignancy, ranks the 3rd place among the causes of cancer-associated mortality. As suggested by more and more studies, long coding RNAs (lncRNAs) have been considered as prognostic biomarkers for CRC. But the significance of hypoxic lncRNAs in predicting CRC prognosis remains unclear.Methods: The gene expressed profiles for CRC cases were obtained based on the Cancer Genome Atlas (TCGA) and applied to estimate the hypoxia score using a single-sample gene set enrichment analysis (ssGSEA) algorithm. Overall survival (OS) of high- and low-hypoxia score group was analyzed by the Kaplan–Meier (KM) plot. To identify differentially expressed lncRNAs (DELs) between two hypoxia score groups, this study carried out differential expression analysis, and then further integrated with the DELs between controls and CRC patients to generate the hypoxia-related lncRNAs for CRC. Besides, prognostic lncRNAs were screened by the univariate Cox regression, which were later utilized for constructing the prognosis nomogram for CRC by adopting the least absolute shrinkage and selection operator (LASSO) algorithm. In addition, both accuracy and specificity of the constructed prognostic signature were detected through the receiver operating characteristic (ROC) analysis. Moreover, our constructed prognosis signature also was validated in the internal testing test. This study operated gene set enrichment analysis (GSEA) for exploring potential biological functions associated with the prognostic signature. Finally, the ceRNA network of the prognostic lncRNAs was constructed.Results: Among 2299 hypoxia-related lncRNAs of CRC in total, LINC00327, LINC00163, LINC00174, SYNPR-AS1, and MIR31HG were identified as prognostic lncRNAs by the univariate Cox regression, and adopted for constructing the prognosis signature for CRC. ROC analysis showed the predictive power and accuracy of the prognostic signature. Additionally, the GSEA revealed that ECM-receptor interaction, PI3K-Akt pathway, phagosome, and Hippo pathway were mostly associated with the high-risk group. 352 miRNAs-mRNAs pairs and 177 lncRNAs-miRNAs were predicted.Conclusion: To conclude , we identified 5 hypoxia-related lncRNAs to establish an accurate prognostic signature for CRC, providing important prognostic markers and therapeutic target.

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Organoids Are Limited in Modeling the Colon Adenoma–Carcinoma Sequence

Cells ◽

10.3390/cells10030488 ◽

2021 ◽

Vol 10 (3) ◽

pp. 488

Author(s):

Yoshihisa Tokumaru ◽

Masanori Oshi ◽

Ankit Patel ◽

Wanqing Tian ◽

Li Yan ◽

...

Keyword(s):

Colorectal Cancer ◽

Immune Response ◽

Immune Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Related Gene ◽

Gene Set Enrichment ◽

Colon Adenoma ◽

Tissue Samples ◽

Gene Sets

The colon adenoma–carcinoma sequence is a multistep genomic-altering process that occurs during colorectal cancer (CRC) carcinogenesis. Organoids are now commonly used to model both non-cancerous and cancerous tissue. This study aims to investigate how well organoids mimic tissues in the adenoma–carcinoma sequence by comparing their transcriptomes. A total of 234 tissue samples (48 adenomas and 186 CRC) and 60 organoid samples (15 adenomas and 45 CRC) were analyzed. We found that cell-proliferation-related gene sets were consistently enriched in both CRC tissues and organoids compared to adenoma tissues and organoids by gene set enrichment analysis (GSEA). None of the known pathways in the colon adenoma–carcinoma sequence were consistently enriched in CRC organoids. There was no enrichment of the tumor microenvironment-related gene sets in CRC organoids. CRC tissues enriched immune-response-related gene sets, whereas CRC organoids did not. The proportions of infiltrating immune cells were different between tissues and organoids, whereas there was no difference between cancer and adenoma organoids. The amounts of cancer stem cells and progenitor cells were not different between CRC and adenoma organoids, whereas a difference was noted between CRC and adenoma tissues. In conclusion, we demonstrated that organoids model only part of the adenoma–carcinoma sequence and should be used with caution after considering their limitations.

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Phospholipase C Isozymes Are Deregulated in Colorectal Cancer – Insights Gained from Gene Set Enrichment Analysis of the Transcriptome

PLoS ONE ◽

10.1371/journal.pone.0024419 ◽

2011 ◽

Vol 6 (9) ◽

pp. e24419 ◽

Cited By ~ 34

Author(s):

Stine A. Danielsen ◽

Lina Cekaite ◽

Trude H. Ågesen ◽

Anita Sveen ◽

Arild Nesbakken ◽

...

Keyword(s):

Colorectal Cancer ◽

Phospholipase C ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set

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Gene set enrichment analysis: A genome-wide expression profile-based strategy for discovering functional microRNA–disease relationships

Journal of International Medical Research ◽

10.1177/0300060517693719 ◽

2017 ◽

Vol 46 (2) ◽

pp. 596-611 ◽

Cited By ~ 3

Author(s):

Yin Ni ◽

Caiyun Song ◽

Shuqing Jin ◽

Zhoufeng Chen ◽

Ming Ni ◽

...

Keyword(s):

Colorectal Cancer ◽

Pattern Matching ◽

Expression Profile ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Genome Wide ◽

A Genome ◽

Matching Strategy ◽

Genome Wide Expression

Objective To explore stable and functional microRNA (miRNA)–disease relationships using a genome-wide expression profile pattern matching strategy. Methods We applied the ranked microarray pattern matching strategy Gene Set Enrichment Analysis to identify miRNA permutations with similar expression patterns to diseases. We also used quantitative reverse transcription PCR to validate the predicted expression levels of miRNAs in three diseases: inflammatory bowel disease (IBD), oesophageal cancer, and colorectal cancer. Results We found that hsa-miR-200 c was upregulated more than 40-fold in oesophageal cancer. The expression of miR-16 and miR-124 was not consistently upregulated in IBD or colorectal cancer. Conclusions Our results suggest that this expression profile matching strategy can be used to identify functional miRNA–disease relationships.

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Identification of a Hypoxia-Related LncRNA Signature for the Prognosis of Colorectal Cancer

10.21203/rs.3.rs-757504/v2 ◽

2021 ◽

Author(s):

Hua Huang ◽

Mingjia Gu ◽

Shanshan Xu ◽

Youran Li ◽

Yunfei Gu ◽

...

Keyword(s):

Colorectal Cancer ◽

Roc Analysis ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Receptor Interaction ◽

Prognostic Signature ◽

Gene Set Enrichment ◽

Gene Set

Abstract Background:Colorectal cancer (CRC), the commonly seen malignancy, ranks 3rd place among the causes of cancer-associated mortality. As suggested by more and more studies, long non-coding RNAs (lncRNAs)have been considered as prognostic biomarkers for CRC. But the significance of hypoxic lncRNAs in predicting CRC prognosis remains unclear.Methods:The gene expressed profiles for CRC cases were obtained based on the Cancer Genome Atlas (TCGA) and applied to estimate the hypoxia score using a single-sample gene set enrichment analysis (ssGSEA) algorithm. Overall survival (OS) of the high- and low-hypoxia score group was analyzed by the Kaplan–Meier (KM) plot. To identify differentially expressed lncRNAs (DELs) between two hypoxia score groups, this study carried out differential expression analysis, and then further integrated with the DELs between controls and CRC patients to generate the hypoxia-related lncRNAs for CRC. Besides, prognostic lncRNAs were screened by the univariate Cox regression, which was later utilized for constructing the prognosis nomogram for CRC by adopting the least absolute shrinkage and selection operator (LASSO) algorithm. In addition, both accuracy and specificity of the constructed prognostic signature were detected through the receiver operating characteristic (ROC) analysis. Moreover, our constructed prognosis signature also was validated in the internal testing test. This study operated gene set enrichment analysis (GSEA) for exploring potential biological functions associated with the prognostic signature. Finally, the ceRNA network of the prognostic lncRNAs was constructed.Results:Among 2299 hypoxia-related lncRNAs of CRC in total, LINC00327, LINC00163, LINC00174, SYNPR-AS1, and MIR31HG were identified as prognostic lncRNAs by the univariate Cox regression and adopted for constructing the prognosis signature for CRC. ROC analysis showed the predictive power and accuracy of the prognostic signature. Additionally, the GSEA revealed that ECM-receptor interaction, PI3K-Akt pathway, phagosome, and Hippo pathway were mostly associated with the high-risk group. 352 miRNAs-mRNAs pairs and 177 lncRNAs-miRNAs were predicted.Conclusion:To conclude, we identified 5 hypoxia-related lncRNAs to establish an accurate prognostic signature for CRC, providing important prognostic markers and therapeutic targets.

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Screening of DNA Damage Repair Genes Involved in the Prognosis of Triple-Negative Breast Cancer Patients Based on Bioinformatics

10.21203/rs.3.rs-594124/v1 ◽

2021 ◽

Author(s):

Nan Wang ◽

Yuanting Gu ◽

Jiangrui Chi ◽

Xinwei Liu ◽

Youyi Xiong ◽

...

Keyword(s):

Breast Cancer ◽

Dna Damage ◽

Regulatory Network ◽

Prognostic Model ◽

Triple Negative ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Regression Analyses ◽

Gene Set Enrichment

Abstract Background: Triple-negative breast cancer (TNBC) is a special subtype of breast cancer with poor prognosis. DNA damage response (DDR) is one of the hallmarks of this cancer. However, the association of DDR genes with the prognosis of TNBC is still unclear.Methods: We identified differentially expressed genes (DEGs) between normal and TNBC samples from The Cancer Genome Atlas (TCGA). DDR genes were obtained from the Molecular Signatures Database (MSigDB) through six DDR gene sets. We then overlapped the DEGs with DDR genes. Based on univariate and LASSO Cox regression analyses, a prognostic model was constructed to predict overall survival (OS). Kaplan–Meier (K–M) analysis and receiver operating characteristic (ROC) curve were used to assess the performance of the prognostic model. Cox regression analysis was applied to identify independent prognostic factors in TNBC. The prognostic model was validated using an independent dataset. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by using gene set enrichment analysis (GSEA). Single-sample gene set enrichment analysis (ssGSEA) was employed to estimate immune cells related to this prognostic model. Finally, we constructed a transcriptional factor (TF) network and a competing endogenous RNA (ceRNA) regulatory network.Results: 23 differentially expressed DDR genes were detected between TNBC and normal samples. The six-gene prognostic model we developed was shown to be related to OS in TNBC using univariate and LASSO Cox regression analyses. By drawing ROC curve and KM curve, we determined the effectiveness of the risk model. The prognostic value of the six-gene prognostic model was further validated using the GSE58812 dataset. The GSEA analysis indicated that the genes in the high-risk group were mainly correlated with leukocyte migration, cytokine interaction with cytokine receptors, oxidative phosphorylation, autoimmune diseases, and coagulation cascade. The mutation data revealed that the mutation frequency of the two groups was the same, while the mutated genes were different. The gene-TF regulatory network showed that Replication Factor C subunit 4 (RFC4) occupied the dominant position.Conclusion: We identified six gene markers related to DDR, which can predict prognosis and serve as an independent biomarker for TNBC patients.

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Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

Current Bioinformatics ◽

10.2174/1574893615999200608125427 ◽

2020 ◽

Vol 15 ◽

Author(s):

Wei Han ◽

Dongchen Lu ◽

Chonggao Wang ◽

Mengdi Cui ◽

Kai Lu

Keyword(s):

Papillary Thyroid Carcinoma ◽

Thyroid Carcinoma ◽

Differential Expression Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Integrated Analysis ◽

Papillary Thyroid ◽

Gene Set Enrichment ◽

Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

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Placental Transcriptome Adaptations to Maternal Nutrient Restriction in Sheep

International Journal of Molecular Sciences ◽

10.3390/ijms22147654 ◽

2021 ◽

Vol 22 (14) ◽

pp. 7654

Author(s):

Chelsie B. Steinhauser ◽

Colleen A. Lambo ◽

Katharine Askelson ◽

Gregory W. Burns ◽

Susanta K. Behura ◽

...

Keyword(s):

Mhc Class Ii ◽

Killer Cell ◽

National Research Council ◽

Enrichment Analysis ◽

Nutrient Utilization ◽

Gene Set Enrichment Analysis ◽

Nutrient Restriction ◽

Placental Development ◽

Gene Set Enrichment ◽

Pregnant Sheep

Placental development is modified in response to maternal nutrient restriction (NR), resulting in a spectrum of fetal growth rates. Pregnant sheep carrying singleton fetuses and fed either 100% (n = 8) or 50% (NR; n = 28) of their National Research Council (NRC) recommended intake from days 35–135 of pregnancy were used to elucidate placentome transcriptome alterations at both day 70 and day 135. NR fetuses were further designated into upper (NR NonSGA; n = 7) and lower quartiles (NR SGA; n = 7) based on day 135 fetal weight. At day 70 of pregnancy, there were 22 genes dysregulated between NR SGA and 100% NRC placentomes, 27 genes between NR NonSGA and 100% NRC placentomes, and 22 genes between NR SGA and NR NonSGA placentomes. These genes mediated molecular functions such as MHC class II protein binding, signaling receptor binding, and cytokine activity. Gene set enrichment analysis (GSEA) revealed significant overrepresentation of genes for natural-killer-cell-mediated cytotoxicity in NR SGA compared to 100% NRC placentomes, and alterations in nutrient utilization pathways between NR SGA and NR NonSGA placentomes at day 70. Results identify novel factors associated with impaired function in SGA placentomes and potential for placentomes from NR NonSGA pregnancies to adapt to nutritional hardship.

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Cancer-associated fibroblasts promote the survival of irradiated nasopharyngeal carcinoma cells via the NF-κB pathway

Journal of Experimental & Clinical Cancer Research ◽

10.1186/s13046-021-01878-x ◽

2021 ◽

Vol 40 (1) ◽

Cited By ~ 1

Author(s):

Weiqiang Huang ◽

Longshan Zhang ◽

Mi Yang ◽

Xixi Wu ◽

Xiaoqing Wang ◽

...

Keyword(s):

Dna Damage ◽

Nasopharyngeal Carcinoma ◽

Enrichment Analysis ◽

Underlying Mechanism ◽

Gene Set Enrichment Analysis ◽

Cancer Associated Fibroblasts ◽

Western Blot Assay ◽

Damage Level ◽

Radiation Resistant

Abstract Background Irradiation has emerged as a valid tool for nasopharyngeal carcinoma (NPC) in situ treatment; however, NPC derived from tissues treated with irradiation is a main cause cancer-related death. The purpose of this study is to uncover the underlying mechanism regarding tumor growth after irradiation and provided potential therapeutic strategy. Methods Fibroblasts were extracted from fresh NPC tissue and normal nasopharyngeal mucosa. Immunohistochemistry was conducted to measure the expression of α-SMA and FAP. Cytokines were detected by protein array chip and identified by real-time PCR. CCK-8 assay was used to detect cell proliferation. Radiation-resistant (IRR) 5-8F cell line was established and colony assay was performed to evaluate tumor cell growth after irradiation. Signaling pathways were acquired via gene set enrichment analysis (GSEA). Comet assay and γ-H2AX foci assay were used to measure DNA damage level. Protein expression was detected by western blot assay. In vivo experiment was performed subcutaneously. Results We found that radiation-resistant NPC tissues were constantly infiltrated with a greater number of cancer-associated fibroblasts (CAFs) compared to radiosensitive NPC tissues. Further research revealed that CAFs induced the formation of radioresistance and promoted NPC cell survival following irradiation via the IL-8/NF-κB pathway to reduce irradiation-induced DNA damage. Treatment with Tranilast, a CAF inhibitor, restricted the survival of CAF-induced NPC cells and attenuated the of radioresistance properties. Conclusions Together, these data demonstrate that CAFs can promote the survival of irradiated NPC cells via the NF-κB pathway and induce radioresistance that can be interrupted by Tranilast, suggesting the potential value of Tranilast in sensitizing NPC cells to irradiation.

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