scholarly journals Systematic identification of genes with a cancer-testis expression pattern in 19 cancer types

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Cheng Wang ◽  
Yayun Gu ◽  
Kai Zhang ◽  
Kaipeng Xie ◽  
Meng Zhu ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Cancer Types ◽  
Systematic Identification ◽  
Cancer Testis

scholarly journals Systematic identification of long non-coding RNAs with cancer-testis expression patterns in 14 cancer types

Oncotarget ◽  
2017 ◽  
Vol 8 (55) ◽  
pp. 94769-94779 ◽  
Author(s):  
Na Qin ◽  
Cheng Wang ◽  
Qun Lu ◽  
Zijian Ma ◽  
Juncheng Dai ◽  
...  
Keyword(s):  
Expression Patterns ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Systematic Identification ◽  
Cancer Testis

scholarly journals Transporter associated with antigen processing 1 (TAP1) expression and prognostic analysis in breast, lung, liver, and ovarian cancer

2021 ◽  
Author(s):  
Anika Tabassum ◽  
Md. Nazmus Samdani ◽  
Tarak Chandra Dhali ◽  
Rahat Alam ◽  
Foysal Ahammad ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Cancer Progression ◽  
Antigen Processing ◽  
Human Cancer ◽  
Analytical Data ◽  
Significant Negative Correlation ◽  
Cancer Tissue ◽  
Human Cancer Cell Lines ◽  
Prognostic Analysis ◽  
Cancer Types

Abstract Transporter associated with antigen processing 1 (TAP1) is a transporter protein that represent tumor antigen in the MHC I or HLA complex. Any defect in the TAP1 gene resulting in inadequate tumor tracking. TAP1 influences multidrug resistance (MDR) in human cancer cell lines and hinders the treatment during chemotherapeutic. The association of TAP1 in cancer progression remains mostly unknown and further study of the gene in relation with cancer need to conduct. Thus, the study has designed to analyze the association between the TAP1 with cancer by computationally. The expression pattern of the gene has determined by using ONCOMINE, GENT2, and GEPIA2 online platforms. The protein level of TAP1 was examined by the help of Human Protein Atlas. Samples with different clinical outcomes were investigated to evaluate the expression and promoter methylation in cancer vs. normal tissues by using UALCAN server. The copy number alteration, mutation frequency, and expression level of the gene in different cancer were analyzed by using cBioPortal server. The PrognoScan and KM plotter platforms were used to perform the survival analysis and represented graphically. Additionally, pathway and gene ontology (GO) features correlated to the TAP1 gene were analyzed and presented by bar charts. After arranging the data in a single panel like correlating expression to prognosis, mutational and alterations characteristic, and pathways analysis, we observed some interesting insights that emphasized the importance of the gene in cancer progression. The study found the relationship between the TAP1 expression pattern and prognosis in different cancer tissues and shows how TAP1 affects the clinical characteristics. The analytical data presented in the study is vital to learn about the effect of TAP1 in tumor tissue, where previously studies showing contradicting expression of TAP1 in cancer tissue. The analyzed data can also be utilized further to evade the threats against chemotherapy. Overall, the study provided a new aspect to consider the role of TAP1 gene in cancer progression and survival status. Key messages • This study demonstrated, for the first time, a correlation between the TAP1 gene and tumor progression. • An upregulation of TAP1 mRNA was demonstrated in various cancer types. • This study reported a significant negative correlation for TAP1 gene expression and the survival rate in different cancer types.

scholarly journals Pan-cancer systematic identification of lncRNAs associated with cancer prognosis

2018 ◽  
Author(s):  
Matthew H. Ung ◽  
Evelien Schaafsma ◽  
Daniel E. Mattox ◽  
George L. Wang ◽  
Chao Cheng
Keyword(s):  
Drug Targets ◽  
Patient Survival ◽  
Cancer Prognosis ◽  
Rna Seq ◽  
Non Coding Rna ◽  
Cancer Types ◽  
Microarray Studies ◽  
Systematic Identification ◽  
Pan Cancer ◽  
Novel Associations

AbstractThe “dark matter” of the genome harbors several non-coding RNA species including IncRNAs, which have been implicated in neoplasias but remain understudied. RNA-seq has provided deep insights into the nature of lncRNAs in cancer but current RNA-seq data are rarely accompanied by longitudinal patient survival information. In contrast, a plethora of microarray studies have collected these clinical metadata that can be leveraged to identify novel associations between gene expression and clinical phenotypes. In this study, we developed an analysis framework that computationally integrates RNA-seq and microarray data to systematically screen 9,463 lncRNAs for association with mortality risk across 20 cancer types. In total, we identified a comprehensive list of associations between lncRNAs and patient survival and demonstrate that these prognostic lncRNAs are under selective pressure and may be functional. Our results provide valuable insights that facilitate further exploration of lncRNAs and their potential as cancer biomarkers and drug targets.

scholarly journals Systematic identification of dysregulated lncRNAs associated with platinum-based chemotherapy response across 11 cancer types

Genomics ◽  
2020 ◽  
Vol 112 (2) ◽  
pp. 1214-1222 ◽  
Author(s):  
Yanjiao Zhu ◽  
Yichuan Zhao ◽  
Siyao Dong ◽  
Lu Liu ◽  
Lin Tai ◽  
...  
Keyword(s):  
Chemotherapy Response ◽  
Platinum Based Chemotherapy ◽  
Cancer Types ◽  
Systematic Identification

Cancer/Testis Antigen CT45 Is Frequently Expressed in Hodgkin’s Lymphoma and Associated with Nodular Sclerosis Subtype and Advanced Disease.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 4591-4591 ◽  
Author(s):  
Alexander Claviez ◽  
Christine Mauz-Körholz ◽  
Hans-Jürgen Heidebrecht ◽  
Günther Schellong ◽  
Dieter Körholz ◽  
...  
Keyword(s):  
Children And Adolescents ◽  
Expression Pattern ◽  
Hodgkin’S Lymphoma ◽  
Advanced Disease ◽  
Hodgkin's Lymphoma ◽  
Histological Subtypes ◽  
Free Survival ◽  
Nodular Sclerosis ◽  
Ct Antigen ◽  
Cancer Testis

Abstract Cancer/testis (CT) antigens are members of a large tumor-associated protein family of increasing interest because of their diagnostic and possible therapeutic implications. Only few studies have investigated CT antigen expression in Hodgkin’s lymphoma (HL) so far. Recently, immunopurification of a 25/22-kDa antigen and sequencing revealed a peptide of 14 amino acids, which corresponds to the gene product of the newly described gene family MGC27005, located on chromosome Xq26.3, now termed CT45. The antigen shows a CT antigen-like expression pattern in human tissues and is detectable by the monoclonal antibody Ki-A10 generated after immunization of mice with HL-derived cell line L428. In this study, the expression pattern of CT45 in a large number of patients with HL included in subsequent pediatric multicenter treatment protocols of the GPOH was analyzed. Immunohistochemical results of Ki-A10 staining were correlated with histological subtype, immunophenotype, clinical data and outcome. In total, 1124 children and adolescents with HL diagnosed between 1978 and 2004 were studied. Median age of the patients was 13.7 years (range, 2.2 to 19.5) and 637 patients 02(57%) were male. Classical HL (cHL) was diagnosed in 988 patients (88%) and nodular lymphocyte predominant HL (NLPHL) was seen in 136 patients (12%). The group of cHL included 683 cases of nodular sclerosis HL (NSHL), 280 cases of mixed cellularity HL (MCHL), ten cases of lymphocyte-rich cHL (LRCHL), seven cases of lymphocyte-depleted HL (LDHL) and eight cases without subclassification. Nuclear CT45 expression was found in 526 cases (47%) with striking differences among histological subtypes and unrelated to CD30, CD20 and latent EBV infection. In NLPHL, 15% of cases scored CT45 positive in contrast to 51% of cases in cHL (p<.001). Within cHL, 58% of cases with NSHL were CT45 positive compared to 36% of cases with MCHL (p<.001). Aggressive histological variants of cHL (NSHL Bennett 2, LDHL) stained positive for CT45 in 62% of cases in comparison to 49% of other subtypes (p=.002). CT45 expression was associated with stage (p<.001), presence of B symptoms (p=.026), extranodal disease (p=.009) and allocation to treatment group (TG, p<.001). Fewer patients from TG1 (localized disease) were CT45 positive than patients from TG2/3 (intermediate and advanced disease; 38% vs. 53%, p<.001). With a median follow-up of 5.6 years, 97% of patients are alive. No significant differences were observed for overall survival, failure-free survival and event-free survival with respect to CT45 status. CT45 expression, which is restricted to neoplastic cells in HL, is found in a significant number of children and adolescents with HL, especially in cases of NSHL, aggressive histological subtypes and advanced disease. Due to effective polychemotherapy with or without low-dose radiotherapy, CT45 status did not emerge as an adverse prognostic factor in children and adolescents with HL in this series.

scholarly journals The Cancer/Testis Antigens of SSX4, MAGE-A3, and CTAG2 Are Attractive Targets for Cancer Immunotherapy in Korean Patients with Multiple Myeloma

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 5757-5757
Author(s):  
Nu-Ri Choi ◽  
Sung-Hoon Jung ◽  
Hyun-Ju Lee ◽  
Manh-Cuong Vo ◽  
My-Dung Hoang ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cancer Immunotherapy ◽  
Expression Pattern ◽  
Light Chain ◽  
Plasma Cells ◽  
Quantitative Polymerase Chain Reaction ◽  
Fold Increase ◽  
Korean Patients ◽  
Cancer Testis Antigens ◽  
Cancer Testis

Abstract Introduction: Cancer/testis antigens (CTAs) are an attractive target for cancer immunotherapy because of a tumor-restricted expression and remarkable immunogenicity. Several CTAs have been used as a source of tumor antigen in dendritic cell therapy against multiple myeloma (MM), but there was no report the CTAs in Asian patients with MM. In this study, we evaluate the expression of 10 CTAs on malignant plasma cells of bone marrow in 18 Korean patients with relapsed or refractory MM. Materials and methods: Eighteen patients with relapsed or refractory MM were classified as four categories according to paraprotein subtypes: IgG (n=7), IgA (n=5), light chain-lambda (n=3), and light chain-kappa (n=3). The expression pattern of 10 CTAs, including NY-ESO-1, SSX2, SSX4, SSX5, MAGE-A3, MAGE-C1, MAGE-C2, BAGE2, CTAG2, and SPA7, was studied by real-time quantitative polymerase chain reaction in CD138+ cells of BM mononuclear cells (MNCs) obtained from MM patients. In addition, we compared it with expression pattern of CTAs in the MNCs from healthy normal donors and the CD138- cells of BM MNCs from MM patients as controls. Results: In CD138+ cells of BM MNCs from the patients, five CTAs, including SSX2, SSX4, MAGE-A3, MAGEC2, and CTAG2, showed high frequency and overall 5.4 to 63.9 fold increase expression in the quantitative mRNA survey compared to MNCs from healthy donors and CD138- cells of BM MNCs from patients. Expression pattern of 5 CTAs was slightly different by paraprotein subtypes: IgA subtype - SSX4 (17.1 fold increase), MAGE-A3 (11.0 fold increase), and CTAG2 (5.9 fold increase); IgG subtype - CTAG2 (63.9 fold increase), SSX4 (40.2 fold increase), and MAGE-A3 (39.9 fold increase); lambda light chain subtype - CTAG2 (42.4 fold increase), SSX4 (29.0 fold increase), and MAGE-A3 (24.4 fold increase); kappa light chain subtype - SSX2 (6.4 fold increase), MAGE-C2 (6.2 fold increase), MAGE-A3 (5.4 fold increase), and SSX4 (5.4 fold increase). Conclusion: This study suggests that three CTAs, such as SSX4, MAGE-A3, and CTAG2, highly expressed on malignant plasma cells are potentially promising targets for cancer immunotherapy in Korean patients with relapsed or refractory MM. Disclosures No relevant conflicts of interest to declare.

scholarly journals Pan-cancer systematic identification of lncRNAs associated with cancer prognosis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8797 ◽  
Author(s):  
Matthew Ung ◽  
Evelien Schaafsma ◽  
Daniel Mattox ◽  
George L. Wang ◽  
Chao Cheng
Keyword(s):  
Drug Targets ◽  
Patient Survival ◽  
Cancer Prognosis ◽  
Rna Seq ◽  
Non Coding Rna ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Microarray Studies ◽  
Systematic Identification ◽  
Pan Cancer

Background The “dark matter” of the genome harbors several non-coding RNA species including Long non-coding RNAs (lncRNAs), which have been implicated in neoplasia but remain understudied. RNA-seq has provided deep insights into the nature of lncRNAs in cancer but current RNA-seq data are rarely accompanied by longitudinal patient survival information. In contrast, a plethora of microarray studies have collected these clinical metadata that can be leveraged to identify novel associations between gene expression and clinical phenotypes. Methods In this study, we developed an analysis framework that computationally integrates RNA-seq and microarray data to systematically screen 9,463 lncRNAs for association with mortality risk across 20 cancer types. Results In total, we identified a comprehensive list of associations between lncRNAs and patient survival and demonstrate that these prognostic lncRNAs are under selective pressure and may be functional. Our results provide valuable insights that facilitate further exploration of lncRNAs and their potential as cancer biomarkers and drug targets.

scholarly journals Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms

2019 ◽  
Vol 20 (9) ◽  
pp. 2185 ◽  
Author(s):  
Xiaoyong Pan ◽  
Lei Chen ◽  
Kai-Yan Feng ◽  
Xiao-Hua Hu ◽  
Yu-Hang Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Expression Pattern ◽  
Learning Algorithms ◽  
Expression Patterns ◽  
Feature Selection Method ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Feature List ◽  
Cancer Types

Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNAs can both participate in the regulation of methylation and pseudouridylation and regulate the expression pattern of their host genes. This research investigated the expression pattern of snoRNAs in eight major cancer types in TCGA via several machine learning algorithms. The expression levels of snoRNAs were first analyzed by a powerful feature selection method, Monte Carlo feature selection (MCFS). A feature list and some informative features were accessed. Then, the incremental feature selection (IFS) was applied to the feature list to extract optimal features/snoRNAs, which can make the support vector machine (SVM) yield best performance. The discriminative snoRNAs included HBII-52-14, HBII-336, SNORD123, HBII-85-29, HBII-420, U3, HBI-43, SNORD116, SNORA73B, SCARNA4, HBII-85-20, etc., on which the SVM can provide a Matthew’s correlation coefficient (MCC) of 0.881 for predicting these eight cancer types. On the other hand, the informative features were fed into the Johnson reducer and repeated incremental pruning to produce error reduction (RIPPER) algorithms to generate classification rules, which can clearly show different snoRNAs expression patterns in different cancer types. The analysis results indicated that extracted discriminative snoRNAs can be important for identifying cancer samples in different types and the expression pattern of snoRNAs in different cancer types can be partly uncovered by quantitative recognition rules.

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