Copy number variation and expression of CT-genes in patients with colorectal cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16104-e16104
Author(s):  
Yuriy A. Gevorkyan ◽  
Denis S. Kutilin ◽  
Oleg I. Kit ◽  
Natalya V. Soldatkina ◽  
Dmitry A. Kharagezov ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Copy Number ◽  
Tumor Tissue ◽  
Malignant Tumors ◽  
Regulation Of Gene Expression ◽  
Rank Correlation ◽  
Normal Colon ◽  
Aberrant Expression ◽  
Spearman’S Rank Correlation

e16104 Background: Cancer-testis antigens (CTAs) can be used for immunotherapeutic approaches and early detection of malignant tumors. Despite numerous studies of CTA expression in various tumors, including colon tumors, the mechanisms of transcriptional activity regulation in colorectal cancer (CRC) remain poorly studied. One of the possible mechanisms of regulation of gene expression is a change in their copy number (CNV). The aim of the study was to analyze the changes in the copy number and expression of CT-genes in patients with CRC. Methods: Tumor and normal colon tissues of 81 patients were used in the study. DNA was isolated by phenol-chloroform extraction. RNA was isolated by the Chomczynski&Sacchi method (2006). The REVERTA-L reagent kit was used for the cDNA synthesis. Determination of expression and copy number of 16 CT genes ( MAGE-A1, -A2, -A3, -A4, MAGE-B1, -B2, GAGE-1, -3, -4, MAGEC1, BAGE, XAGE3, NYESO1, SSX2, SCP1, PRAME1) was performed using the Real-Time qPCR method (reference genes - GAPDH and GUSB). Differences were evaluated using the Mann-Whitney test, correlation analysis - using Spearman's rank correlation coefficient (r). Results: An analysis of CT-gene expression and CNV in tumor and normal colon tissues (n = 81) revealed a statistically significant (p < 0.05) difference between these parameters in tumor tissue relative to normal one: for MAGEB1 an increase of 2.0 and 2.7 times, GAGE3 an increase of 2.0 and 2.5 times, GAGE4 decreased by 5.0 and 6.8 times, BAGE decreased by 2.4 and 1.7 times, SSX2 increased by 1.8 and 2.1 times, SCP1 increased copy number by 4.4 times and PRAME1 increased expression and copy number by 2.9 and 2.3 times, respectively. When comparing CNV and expression of 16 CT genes, a positive correlation was observed (r = 0.875). Conclusions: Thus, the aberrant expression of MAGEB1, GAGE3, GAGE4, BAGE, SSX2 and PRAME1 found in the tumor tissue of CRC patients depends on the copy number of these CT-genes.

scholarly journals Promising Advances in LINC01116 Related to Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Yating Xu ◽  
Xiao Yu ◽  
Menggang Zhang ◽  
Qingyuan Zheng ◽  
Zongzong Sun ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gastric Cancer ◽  
Lung Cancer ◽  
Cancer Colorectal ◽  
Malignant Tumors ◽  
Biological Processes ◽  
Aberrant Expression ◽  
Protein Coding ◽  
Future Studies ◽  
Non Coding Rnas

Long non-coding RNAs (lncRNAs) are RNAs with a length of no less than 200 nucleotides that are not translated into proteins. Accumulating evidence indicates that lncRNAs are pivotal regulators of biological processes in several diseases, particularly in several malignant tumors. Long intergenic non-protein coding RNA 1116 (LINC01116) is a lncRNA, whose aberrant expression is correlated with a variety of cancers, including lung cancer, gastric cancer, colorectal cancer, glioma, and osteosarcoma. LINC01116 plays a crucial role in facilitating cell proliferation, invasion, migration, and apoptosis. In addition, numerous studies have recently suggested that LINC01116 has emerged as a novel biomarker for prognosis and therapy in malignant tumors. Consequently, we summarize the clinical significance of LINC01116 associated with biological processes in various tumors and provide a hopeful orientation to guide clinical treatment of various cancers in future studies.

scholarly journals Genotype-Based Gene Expression in Colon Tissue—Prediction Accuracy and Relationship with the Prognosis of Colorectal Cancer Patients

2020 ◽  
Vol 21 (21) ◽  
pp. 8150
Author(s):  
Heike Deutelmoser ◽  
Justo Lorenzo Bermejo ◽  
Axel Benner ◽  
Korbinian Weigl ◽  
Hanla A. Park ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Prediction Accuracy ◽  
Inverse Association ◽  
Normal Colon ◽  
Colon Tissue ◽  
Normal Colon Tissue ◽  
Study Population ◽  
The Uk ◽  
Colorectal Cancer Patients

Colorectal cancer (CRC) survival has environmental and inherited components. The expression of specific genes can be inferred based on individual genotypes—so called expression quantitative trait loci. In this study, we used the PrediXcan method to predict gene expression in normal colon tissue using individual genotype data from 91 CRC patients and examined the correlation ρ between predicted and measured gene expression levels. Out of 5434 predicted genes, 58% showed a negative ρ value and only 16% presented a ρ higher than 0.10. We subsequently investigated the association between genotype-based gene expression in colon tissue for genes with ρ > 0.10 and survival of 4436 CRC patients. We identified an inverse association between the predicted expression of ARID3B and CRC-specific survival for patients with a body mass index greater than or equal to 30 kg/m2 (HR (hazard ratio) = 0.66 for an expression higher vs. lower than the median, p = 0.005). This association was validated using genotype and clinical data from the UK Biobank (HR = 0.74, p = 0.04). In addition to the identification of ARID3B expression in normal colon tissue as a candidate prognostic biomarker for obese CRC patients, our study illustrates the challenges of genotype-based prediction of gene expression, and the advantage of reassessing the prediction accuracy in a subset of the study population using measured gene expression data.

DNA copy number alterations, gene expression changes and disease-free survival in patients with colorectal cancer: a 10 year follow-up

2016 ◽  
Vol 39 (6) ◽  
pp. 545-558 ◽  
Author(s):  
Elisabetta Bigagli ◽  
Carlotta De Filippo ◽  
Cinzia Castagnini ◽  
Simona Toti ◽  
Francesco Acquadro ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Copy Number ◽  
Disease Free Survival ◽  
Copy Number Alterations ◽  
Dna Copy Number ◽  
Free Survival ◽  
Dna Copy Number Alterations ◽  
Disease Free

scholarly journals MKL-1 regulates the stem cell marker. CD44 in breast cancer cells

2019 ◽  
Vol 78 ◽  
pp. 01002
Author(s):  
Zhou-Tong Dai ◽  
Ao Yao ◽  
Yuan Xiang ◽  
Jia Peng Li ◽  
Wei Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Malignant Tumors ◽  
Regulation Of Gene Expression ◽  
Gene Promoter ◽  
Expression Regulation ◽  
Stem Cell Marker ◽  
Luciferase Reporter ◽  
Regulation Mechanism ◽  
Luciferase Reporter Gene ◽  
Factors Affecting

CD44, cluster of differentiation 44 is a typical marker of stem cells. At present, it has been found that CD44 is prevalent in various human malignant tumors, but its expression regulation mechanism is still not clear. The initiation of gene expression, the modification of RNA levels, and the regulation of protein levels are the main factors affecting the expression level of genes, and the most critical one is the regulation of gene expression by signaling pathways. Up to now, there has been no report on the role of MKL-1 in the cloning of the cd44 promoter. Therefore, this study intends to clone the cd44 gene promoter, construct its luciferase reporter gene vector, transfect the MKL-1 overexpression vector, and analyze how it affects transcriptional activity, in order to further study the expression regulation of cd44. The mechanism provides a powerful tool in the future.

HOXA9 Is a Novel Therapeutic Target in Multiple Myeloma.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 832-832 ◽  
Author(s):  
Michael A Chapman ◽  
Jean-Philippe Brunet ◽  
Jonathan J Keats ◽  
Angela Baker ◽  
Mazhar Adli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Histone Modification ◽  
Cell Lines ◽  
Therapeutic Target ◽  
Copy Number ◽  
Conflicts Of Interest ◽  
Specific Expression ◽  
Aberrant Expression ◽  
High Level

Abstract Abstract 832 We hypothesized that new therapeutic targets for multiple myeloma (MM) could be discovered through the integrative computational analysis of genomic data. Accordingly, we generated gene expression profiling and copy number data on 250 clinically-annotated MM patient samples. Utilizing an outlier statistical approach, we identified HOXA9 as the top candidate gene for further investigation. HOXA9 expression was particularly high in patients lacking canonical MM chromosomal translocations, and allele-specific expression analysis suggested that this overexpression was mono-allelic. Indeed, focal copy number amplifications at the HOXA locus were observed in some patients. Outlier HOXA9 expression was further validated in both a collection of 52 MM cell lines and 414 primary patient samples previously described. To further verify the aberrant expression of HOXA9 in MM, we performed quantitative RT-PCR, which confirmed expression in all MM patients and cell lines tested, with high-level expression in a subset. To further investigate the mechanism of aberrant HOXA9 expression, we interrogated the pattern of histone modification at the HOXA locus because HOXA gene expression is particularly regulated by such chromatin marks. Accordingly, immunoprecipitation studies showed an aberrantly low level of histone 3 lysine 27 trimethylation marks (H3K27me3) at the HOXA9 locus. H3K27me3 modification is normally associated with silencing of HOXA9 in normal B-cell development. As such, it appears likely that the aberrant expression of HOXA9 in MM is due at least in part to defects in histone modification at this locus. To determine the functional consequences of HOXA9 expression in MM, we performed RNAi-mediated knock-down experiments in MM cell lines. Seven independent HOXA9 shRNAs that diminished HOXA9 expression resulted in growth inhibition of 12/14 MM cell lines tested. Taken together, these experiments indicate that HOXA9 is essential for survival of MM cells, and that the mechanism of HOXA9 expression relates to aberrant histone modification at the HOXA9 locus. The data thus suggest that HOXA9 is an attractive new therapeutic target for MM. Disclosures: No relevant conflicts of interest to declare.

A pooled analysis of the secondary resection for colorectal cancer liver metastases: Comparison of bevacizumab (Bmab) and anti-EGFRs.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 610-610
Author(s):  
Wataru Ichikawa ◽  
Yu Sunakawa ◽  
Hirofumi Nakayama ◽  
Toshikazu Ikusue ◽  
Toshikado Kaneta ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastases ◽  
Rank Correlation ◽  
Positive Association ◽  
Pooled Analysis ◽  
Clear Correlation ◽  
Colorectal Cancer Liver Metastases ◽  
Spearman’S Rank Correlation ◽  
Secondary Resection ◽  
Spearman’S Rank Correlation Coefficient

610 Background: Systemic chemotherapies can convert irresectable liver metastases (LM) to resectable in some cases of metastatic colorectal cancer (mCRC). Secondary surgical resection is now considered to be a worthwhile therapeutic aim in mCRC with LM. There is a clear correlation between radiological response and secondary resection rate (SRR) (Jones RP et al. Eur J Cancer 2014). However, it remains unclear which monoclonal antibodies contribute the improvement of SRR, Bmab or anti-EGFRs. Methods: We performed a systematic review of literature published between Jan 1998 and Aug 2015 to analyze the relationship between SRR and antibodies in mCRC treated with 1st-line chemotherapy. Phase II or III trials which obtained the information of response rate (RR) and resection of LM were included in this analysis. The RR, SRR, and R0 SRR were compared between Bmab- and anti-EGFR (cetuximab or panitumumab)-containing regimen groups using Mann–Whitney U test. The correlation between RR and R0 SRR was assessed by Spearman's rank correlation coefficient. Results: A total of 40 studies were enrolled: 33 treatment arms from 16 trials for liver-limited disease (LLD) and 31 arms from 24 trials for non-LLD. The result is shown below. No difference was observed in SRR and R0 SRR between Bmab and anti-EGFR groups. In addition, a preliminary analysis showed that RR had significantly positive association with R0 SRR in anti-EGFR group (R2 0.74, P=0.027 for non-LLD; R2 0.88, P=0.018 for LLD) but not in Bmab group (P=0.27 for non-LLD, P=0.12 for LLD). Conclusions: The SRR and R0 SRR were comparable between Bmab and anti-EGFRs, even in mCRC with LLD, while RR correlated with R0 SSR in anti-EGFRs but not in Bmab. These findings warrant validation in ongoing trials to compare the targeted-agents. [Table: see text]

Regulation of gene expression by DNA methylation with cytotoxic T lymphocytes evaluation in consensus molecular subtypes of colorectal cancer.

2020 ◽  
Vol 38 (5_suppl) ◽  
pp. 25-25
Author(s):  
Yuanyuan Shen ◽  
Justin Hummel ◽  
Isabel Cristina Trindade ◽  
Christos Papageorgiou ◽  
Chi-Ren Shyu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Epigenetic Modification ◽  
Pearson Correlation ◽  
Critical Role ◽  
Regulation Of Gene Expression ◽  
The Cancer Genome Atlas ◽  
Highly Correlated

25 Background: Low cytotoxic T lymphocyte (CTLs) infiltration in colorectal cancer (CRC) tumors is a challenge to treatment with immune checkpoint inhibitors. Consensus molecular subtypes (CMS) classify patients based on tumor attributes, and CMS1 patients include the majority of patients with high CTL infiltration and “inflamed” tumors. Epigenetic modification plays a critical role in gene expression and therapy resistance. Therefore, in this study we compared DNA methylation, gene expression, and CTL infiltration of CMS1 patients to other CMS groups to determine targets for improving immunotherapy in CRC. Methods: RNA-seq (n = 511) and DNA methylation (n = 316) from The Cancer Genome Atlas databases were used to determine gene expression and methylation profiles based on CMSs. CMS1 was used as a reference and compared to other subtypes (CMS2-4). Microenvironment Cell Populations- counter (MCPcounter) was used to determine tumor CTL infiltration. Genes with significantly different expression (p < 0.01, LogFC≥|1.5|) and difference of mean methylation β value ≥|0.25| were integrated for Pearson correlation coefficient analysis with MCPcounter score (r > |0.7|). Results: Comparing CMS1 and CMS2, ARHGAP9, TBX21, and LAG3 were differentially methylated and correlated with CTL scores. ARHGAP9 and TBX21 were decreased and hypomethylated in CMS2. Comparing CMS1 and CMS3, ARHGAP9, TBX21, FMNL1, HLA-DPB1, and STX11 were downregulated in CMS3 and highly correlated with CTL scores. ARHGAP9, FMNL1, HLA-DPB1, and STX11 were hypomethylated in CMS3 and TBX21 was methylated in both, but had a higher methylation ratio in CMS1. Comparing CMS1 and CMS4, TBX21 was the only gene downregulated, hypomethylated, and highly correlated with CTL scores in CMS4 patients. Conclusions: We found six genes differentially expressed, differentially methylated, and highly correlated with CTL infiltration when comparing CMS1 to other CMS groups. Specifically, TBX21 was the only gene highly correlated with CTL scores with differential gene expression and methylation in CMS2-4 when compared to CMS1. Thus, T-bet may be a critical regulator of T cell responses in CRC.

Misregulation of the Dependence Receptor DCC and its Upstream lincRNA, LOC100287225, in Colorectal Cancer

2015 ◽  
Vol 103 (1) ◽  
pp. 40-43 ◽  
Author(s):  
Mina Kazemzadeh ◽  
Reza Safaralizadeh ◽  
Mohammad Ali HosseinPour feizi ◽  
Mohammad Hossein Somi ◽  
Behrooz Shokoohi
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Regulation Of Gene Expression ◽  
Cellular Processes ◽  
Qrt Pcr ◽  
Cis Regulation ◽  
Tumor Tissues ◽  
Non Coding Rnas ◽  
Colorectal Cancer Patients ◽  
Dependence Receptor

Background Long non-coding RNAs (lncRNAs), a class of regulatory RNAs, play a major role in various cellular processes. Long intergenic non-coding RNAs (lincRNAs), a subclass of lncRNAs, are involved in the trans- and cis-regulation of gene expression. In the case of cis-regulation, by recruiting chromatin-modifying complexes, lincRNAs influence adjacent gene expression. Methods We used quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) to evaluate the coexpression of LOC100287225, a lincRNA, and DCC, one of its adjacent genes that is often decreased in colorectal cancer, in pairs of tumor and adjacent tumor-free tissues of 30 colorectal cancer patients. Results The qRT-PCR results revealed the misregulation of these genes during tumorigenesis. Their relative expression levels were significantly lower in tumor tissues than adjacent tumor-free tissues. However, the analysis found no significant correlation between reduced expression of these genes. Conclusions Our study demonstrated the concurrent misregulation of DCC and LOC100287225 in colorectal cancer.

scholarly journals scMontage: Fast and Robust Gene Expression Similarity Search for Massive Single-cell Data

2020 ◽  
Author(s):  
Tomoya Mori ◽  
Naila Shinwari ◽  
Wataru Fujibuchi
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Similarity Search ◽  
Rank Correlation ◽  
Cell Types ◽  
Specific Information ◽  
Link Type ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Additional Cell

AbstractSingle-cell RNA-seq (scRNA-seq) analysis is widely used to characterize cell types or detect heterogeneity of cell states at much higher resolutions than ever before. Here we introduce scMontage (https://scmontage.stemcellinformatics.org), a gene expression similarity search server dedicated to scRNA-seq data, which can rapidly compare a query with thousands of samples within a few seconds. The scMontage search is based on Spearman’s rank correlation coefficient and its robustness is ensured by introducing Fisher’s Z-transformation and Z-test. Furthermore, search results are linked to a human cell database SHOGoiN (http://shogoin.stemcellinformatics.org), which enable users to fast access to additional cell-type specific information. The scMontage is available not only as a web server but also as a stand-alone application for user’s own data, and thus it enhances the reliability and throughput of cell analysis and helps users gain new insights into their research.

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