scholarly journals Identification of Ovarian Cancer Gene Expression Patterns Associated with Disease Progression and Mortality

2018 ◽  
Author(s):  
Md. Ali Hossain ◽  
Sheikh Muhammad Saiful Islam ◽  
Julian Quinn ◽  
Fazlul Huq ◽  
Mohammad Ali Moni
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Multivariate Analysis ◽  
Mrna Expression ◽  
Patient Survival ◽  
Expression Patterns ◽  
Univariate Analysis ◽  
Cancer Site ◽  
Clinical Variables ◽  
Risk Of Death

Ovarian cancer (OC) is a common cause of death from cancer among women worldwide, so there is a pressing need to identify factors influencing mortality. Much OC patient clinical data is now publically accessible (including patient age, cancer site stage and subtype), as are large datasets of OC gene transcription profiles. These have enabled studies correlating OC patient survival with clinical variables and with gene expression but it is not well understood how these two aspects interact to influence mortality. To study this we integrated clinical and tissue transcriptome data from the same patients available from the Broad Institute Cancer Genome Atlas (TCGA) portal. We investigated OC mRNA expression levels (relative to normal patient tissue) of 26 genes already strongly implicated in OC, assessed how their expression in OC tissue predicts patient survival then employed Cox Proportional Hazard regression models to analyse both clinical factors and transcriptomic information to determine relative risk of death associated with each factor. Multivariate analysis of combined data (clinical and gene mRNA expression) found age, ovary tumour site and cancer stage IB significantly correlated with patient survival. Univariate analysis also confirmed significant differences in patient survival time when altered transcription levels of KLK6, CD36, MEF2C and SCGB2A1 were evident, while multivariate analysis that considered the 26 genes simultaneously revealed a significant relationship of mortality with KLK6, CD36 and E2F1 genes. However, analysis that considered all 26 genes with clinical variables together identified WFDC2, E2F1, BRCA1, KLK6, SCGB2A1 and SLPI genes as independently related to mortality in OC. This indicated that the latter genes affect OC patient survival, i.e., provided mechanistic and predictive information in addition to that of the clinical traits and provide strong evidence that these genes are critical markers of processes that underlie OC progression and mortality.

scholarly journals Protein Expression Patterns in ovarian cancer cells Associated with Monofunctional Platinums Treatment

2019 ◽  
Author(s):  
Laila Arzuman ◽  
Mohammad Ali Moni ◽  
Philip Beale ◽  
Jun Q. Yu ◽  
Mark Molloy ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Patient Survival ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Ovarian Cancer Cells ◽  
Altered Expression ◽  
Expression Levels ◽  
Risk Of Death ◽  
Platinum Based Chemotherapy ◽  
Resistant Cells

ABSTRACTPlatinum drugs cisplatin and carboplatin, given in combination with paclitaxel, constitute the standard chemotherapy against ovarian cancer (OC). Oc chemoresistance is a major obstacle to effective treatment, but knowledge of the mechanisms that underlie it remains incomplete. We thus sought to discover key proteins associated with platinum resistance by comparing A2780 OC cells with A2780cisR cells (resistant cells derived from the A2780 line) to identify proteins with markedly altered expression levels in the resistant cells. We also determined which proteins in these cells had altered expression in response to treatment with either designed monofunctional platinum alone or a combination with cisplatin with selected phytochemical therapeutic agents.We thus performed proteomic analysis using 2D-gel electrophoresis A2780 and A2780cisR to identify proteins with differential expression; these were eluted and analysed by mass spectrometry to identify them. A total of 122 proteins were found to be differentially expressed between A2780 and A2780cisR cell lines in the absence of any drug treatment. Among them, levels of 27 proteins in A2780cisR cell line were further altered (up-or down-regulated) in response to one or more of the drug treatments. We then investigated primary OC tissue RNA expression levels (compared to l ovarian tissue) of genes coding for these candidate 27 proteins using publically available datasets (The Cancer Genome Atlas). We assessed how expression of these genes in OC tissue associates with patient survival using Cox Proportional Hazard (PH) regression models to determine relative risk of death associated with each factor. Our Cox PH regression-based machine learning method confirmed a significant relationship of mortality with altered expression of ARHGDIA, CCT6A and HISTIH4F genes. This indicated that these genes affect OC patient survival, i.e., provided mechanistic evidence, in addition to that of the clinical traits, that these genes may be critical mediators of the processes that underlie OC progression and mortality.Thus, we identified differentially expressed proteins that are implicated in platinum-based chemotherapy resistance mechanisms which may serve as resistance biomarkers. These drug resistance associated proteins may also serve as potential OC therapeutic targets whose blockade may enhance the effectiveness of platinum based drugs.

Expression Patterns of Nrf2 and Keap1 in Ovarian Cancer Cells and their Prognostic Role in Disease Recurrence and Patient Survival

2017 ◽  
Vol 27 (3) ◽  
pp. 412-419 ◽  
Author(s):  
Hye-yon Cho ◽  
Kidong Kim ◽  
Yong-Beom Kim ◽  
Haeryoung Kim ◽  
Jae Hong No
Keyword(s):  
Ovarian Cancer ◽  
Cancer Cells ◽  
Patient Survival ◽  
Expression Patterns ◽  
Disease Recurrence ◽  
Ovarian Cancer Cells ◽  
Prognostic Role

scholarly journals Early Response of CD8+ T Cells in COVID-19 Patients

2021 ◽  
Vol 11 (12) ◽  
pp. 1291
Author(s):  
Deni Ramljak ◽  
Martina Vukoja ◽  
Marina Curlin ◽  
Katarina Vukojevic ◽  
Maja Barbaric ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
Mrna Expression ◽  
Cd8 T Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Effector Memory ◽  
Healthy Controls ◽  
Ifn Γ

Healthy and controlled immune response in COVID-19 is crucial for mild forms of the disease. Although CD8+ T cells play important role in this response, there is still a lack of studies showing the gene expression profiles in those cells at the beginning of the disease as potential predictors of more severe forms after the first week. We investigated a proportion of different subpopulations of CD8+ T cells and their gene expression patterns for cytotoxic proteins (perforin-1 (PRF1), granulysin (GNLY), granzyme B (GZMB), granzyme A (GZMA), granzyme K (GZMK)), cytokine interferon-γ (IFN-γ), and apoptotic protein Fas ligand (FASL) in CD8+ T cells from peripheral blood in first weeks of SARS-CoV-2 infection. Sixteen COVID-19 patients and nine healthy controls were included. The absolute counts of total lymphocytes (p = 0.007), CD3+ (p = 0.05), and CD8+ T cells (p = 0.01) in COVID-19 patients were significantly decreased compared to healthy controls. In COVID-19 patients in CD8+ T cell compartment, we observed lower frequency effector memory 1 (EM1) (p = 0.06) and effector memory 4 (EM4) (p < 0.001) CD8+ T cells. Higher mRNA expression of PRF1 (p = 0.05) and lower mRNA expression of FASL (p = 0.05) at the fifth day of the disease were found in COVID-19 patients compared to healthy controls. mRNA expression of PRF1 (p < 0.001) and IFN-γ (p < 0.001) was significantly downregulated in the first week of disease in COVID-19 patients who progressed to moderate and severe forms after the first week, compared to patients with mild symptoms during the entire disease course. GZMK (p < 0.01) and FASL (p < 0.01) mRNA expression was downregulated in all COVID-19 patients compared to healthy controls. Our results can lead to a better understanding of the inappropriate immune response of CD8+ T cells in SARS-CoV2 with the faster progression of the disease.

scholarly journals How to Manage Synchronous Endometrial and Ovarian Cancer Patients?

2021 ◽  
Author(s):  
wonkyo shin ◽  
Sang-yoon Park ◽  
Sokbom Kang ◽  
Myongcheol Lim ◽  
Sang-Soo Seo
Keyword(s):  
Ovarian Cancer ◽  
Multivariate Analysis ◽  
Metastatic Cancer ◽  
Univariate Analysis ◽  
Influential Factors ◽  
Factors Affecting ◽  
Gynecology And Obstetrics ◽  
Aortic Lymph Node ◽  
Risk Patients ◽  
The Difference

Abstract Backgrounds: We aimed to evaluate the prognosis in patients with synchronous endometrial and ovarian cancer (SEOC) by comparing the differences between double primary cancer (DPC) and metastatic cancer (MC). Methods: The medical records of 47 patients diagnosed synchronously with endometrial and ovarian cancer between January 2006 and December 2018 were retrospectively reviewed. Twenty-eight and 19 patients were diagnosed with DPC and MC, respectively. Demographics, recurrence-free survival (RFS), and 5-year overall survival (OS) were compared. The clinical factors affecting survival were evaluated using univariate and multivariate analyses.Results: The demographics were not different between both groups. Endometrioid histology and the International Federation of Gynecology and Obstetrics grade were higher in the MC group than in the DPC group (42.1% vs. 10.7 %; P=0.018, P=0.002, respectively). The ratio of post-operative adjuvant therapy was not different in both groups. Recurrence occurred in five patients with DPC and seven with MC. The difference in RFS was not significantly different (P=0.131) but the OS was different between both groups (P = 0.020). Histology and para-aortic lymph node metastasis were associated wtih RFS in univariate analysis, but no difference was found in multivariate analysis.Conclusions: Although DPC patients had longer OS, multivariate analysis did not identify any influential factors. Focus should be placed on defining the appropriate adjuvant treatment for high-risk patients, which will improve prognosis, rather than on discriminating between DPC and MC.

scholarly journals Protein structure-based gene expression signatures

2020 ◽  
Author(s):  
R. Rahman ◽  
Y. Xiong ◽  
J. G. C. van Hasselt ◽  
J. Hansen ◽  
E. A. Sobie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Structure ◽  
Mrna Expression ◽  
Expression Patterns ◽  
Drug Effects ◽  
Tissue Expression ◽  
Structural Features ◽  
Biological Phenomena ◽  
Gene Expression Signatures ◽  
Cellular Phenotypes

AbstractGene expression signatures (GES) connect phenotypes to mRNA expression patterns, providing a powerful approach to define cellular identity, function, and the effects of perturbations. However, the use of GES has suffered from vague assessment criteria and limited reproducibility. The structure of proteins defines the functional capability of genes, and hence, we hypothesized that enrichment of structural features could be a generalizable representation of gene sets. We derive structural gene expression signatures (sGES) using features from various levels of protein structure (e.g. domain, fold) encoded by the transcribed genes in GES, to describe cellular phenotypes. Comprehensive analyses of data from the Genotype-Tissue Expression Project (GTEx), ARCHS4, and mRNA expression of drug effects on cardiomyocytes show that structural GES (sGES) are useful for identifying robust signatures of biological phenomena. sGES also enables the characterization of signatures across experimental platforms, facilitates the interoperability of expression datasets, and can describe drug action on cells.

scholarly journals Prognostic value of kallikrein-related peptidase 7 (KLK7) mRNA expression in advanced high-grade serous ovarian cancer

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Weiwei Gong ◽  
Yueyang Liu ◽  
Eleftherios P. Diamandis ◽  
Marion Kiechle ◽  
Holger Bronger ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Mrna Expression ◽  
Protein Level ◽  
Multivariate Analyses ◽  
Expression Patterns ◽  
Mrna Levels ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Expression Levels ◽  
Mrna Expression Levels

Abstract Background High-grade serous ovarian cancer (HGSOC) is the most common and lethal subtype of ovarian cancer. A growing body of evidence suggests tumor-supporting roles of several members of the kallikrein-related peptidase (KLK) family, including KLK5 and KLK7, in this cancer subtype. In normal physiology, KLK5 and KLK7 are the major proteases involved in skin desquamation. Moreover, in several cancer types KLK5 and KLK7 co-expression has been observed. Recently, we have shown that elevated KLK5 mRNA levels are associated with an unfavorable prognosis in HGSOC. Therefore, the aim of this study was to investigate the clinical significance of KLK7 mRNA expression and to explore its relation to KLK5 levels in HGSOC. Methods mRNA expression levels of KLK7 were quantified by qPCR in a well-characterized patient cohort afflicted with advanced high-grade serous ovarian cancer (FIGO III/IV, n = 139). Previously determined KLK5 mRNA as well as KLK5 and KLK7 antigen concentrations were used to evaluate the relationship between the expression patterns of both factors on the mRNA as well as protein level in tumor tissue of HGSOC patients. Results There were strong, significant positive correlations between KLK5 and KLK7 both at the mRNA and the protein level, suggesting coordinate expression of these proteases in HGSOC. In univariate analyses, elevated KLK7 levels as well as the combination of KLK5 + KLK7 (high and/or high versus low/low) were significantly associated with worse progression-free survival (PFS). High mRNA expression levels of KLK7 and the combination of KLK5 and KLK7 showed a trend towards significance for overall survival (OS). In multivariate analyses, KLK7 mRNA expression represented an unfavorable, statistically significant independent predictor for PFS and OS. Conclusions The findings imply that both increased KLK5 and KLK7 mRNA expression levels represent unfavorable prognostic biomarkers in advanced high-grade serous ovarian cancer, whereby multivariate analyses indicate that KLK7 mRNA exhibits a stronger predictive value as compared to KLK5 mRNA and the combination of KLK5 and KLK7.

scholarly journals Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock

2020 ◽  
Vol 9 (5) ◽  
pp. 1276
Author(s):  
Pedro Martínez-Paz ◽  
Marta Aragón-Camino ◽  
Esther Gómez-Sánchez ◽  
Mario Lorenzo-López ◽  
Estefanía Gómez-Pesquera ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Mortality Risk ◽  
Validation Cohort ◽  
Expression Patterns ◽  
Gene Expression Signature ◽  
Mrna Levels ◽  
Characteristic Analysis ◽  
Discovery Cohort ◽  
Risk Of Death

Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores.

Correlation of messenger RNA expression patterns of ERCC1, TS, EGFR, and VEGFR2 with KRAS and BRAF mutational status in advanced colorectal cancer: Implications for targeted therapies.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 383-383
Author(s):  
Martin K. H. Maus ◽  
Craig Stephens ◽  
Stephanie H. Astrow ◽  
Peter Philipp Grimminger ◽  
Dongyun Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Mrna Expression ◽  
Advanced Colorectal Cancer ◽  
Expression Patterns ◽  
Mrna Levels ◽  
Expression Levels ◽  
Mutational Status ◽  
Mrna Expression Levels ◽  
Gene Expression Levels

383 Background: Gene expression levels of ERCC1, TS, EGFR and VEGFR2 may have predictive value for the personalized use of standard chemotherapeutics as well as agents targeting the EGFR and VEGF pathways and the efficacy of EGFR directed monoclonal antibodies like panitumumab and cetuximab has been confirmed to be dependent on wt KRAS and wt BRAF in patients with advanced colorectal cancer. We investigated the correlations between KRAS/BRAF mutational status and the mRNA expression levels of these genes. Methods: Formalin-fixed paraffin-embedded tumor specimens from 600 patients with advanced colorectal adenocarcinoma were microdissected and DNA and RNA was extracted. Specifically designed primers and probes were used to detect 7 different base substitutions in codon 12 and 13 of KRAS, V600E mutations in BRAF and the expression levels of ERCC1, TS, EGFR and VEGFR2 by RT-PCR. Results: Mt KRAS tumors had significantly lower TS and EGFR gene expression levels compared with wt KRAS (p<0,001), whereas mt BRAF tumors showed significantly increased TS and EGFR mRNA levels compared to wt BRAF (p<0,001). Mt BRAF tumors showed significantly higher mRNA levels than mt KRAS tumors (p<0,001). ERCC1 and VEGFR2 mRNA levels were significantly down-regulated in mt KRAS specimen (p<0,001), but showed no significant correlation with BRAF mutational status. Conclusions: KRAS and BRAF mutations are associated with opposite mRNA expression levels for TS and EGFR. Recently, resistance to BRAF inhibition in mt BRAF colorectal tumors has been shown in preclinical models to be associated with up-regulation of EGFR. Our data suggests that BRAF mutants are associated with high EGFR levels at the time of diagnosis, and not necessarily part of an acquired mechanism of resistance. Significantly lower mRNA expression levels of VEGFR2 in mt KRAS tumors may explain lower response to angiogenesis inhibition seen in the TML study.

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