Consensus gene expression analysis to identify key hallmarks of cancer in malignant melanoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e21045-e21045
Author(s):  
Emma O'Connor ◽  
Eileen E. Parkes ◽  
Leeona Galligan ◽  
James Bradford ◽  
Shauna Lambe ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Gene Expression Analysis ◽  
Epithelial Mesenchymal Transition ◽  
Software Tool ◽  
Rna Seq ◽  
Combination Therapies ◽  
Hallmarks Of Cancer ◽  
Mesenchymal Transition ◽  
Melanoma Patients

e21045 Background: Traditionally gene expression signatures (GES) are used individually to classify patients into subgroups. Signatures targeting the same biology are often developed independently and may not classify identically. We developed the claraT software tool that uses consensus between multiple published GES categorised by the Hallmarks of Cancer (Hanahan & Weinberg, 2011) to classify cancers. As metastatic melanoma represents poor prognostic disease (5-yr survival 15-20%), we applied claraT to the TCGA melanoma dataset to identify targetable biologies, validated in a cohort of melanoma patients treated with Ipilimumab. Methods: TCGA RNA-seq data ( n= 472) was analysed using the claraT platform including GES for immune ( n= 14), angiogenesis ( n= 9) and epithelial-mesenchymal transition (EMT) ( n= 12) Hallmarks. Samples were clustered for the combined and individual Hallmarks. Median progression-free (PFS) and overall-survival (OS) differences were analysed across identified subgroups. Analysis was validated in an Ipilimumab treated melanoma dataset ( n= 42) (Van Allen, 2015). Results: Clustering the combined Hallmarks identified 4 subgroups in the TCGA cohort: 1) Immune active, 2) Immune-EMT active, 3) EMT-Angiogenesis active, 4) All inactive. Groups 1&2 had significantly improved OS compared to Groups 3&4 (HR = 0.50, p< 0.0001). Clustering using single Hallmarks revealed that immune-positive tumours had significantly improved OS (HR = 0.53, p< 0.0001) compared to immune-negative tumours. Angiogenesis-negative tumours displayed improved PFS (HR = 0.73, p= 0.03) and OS (HR = 0.53, p <0.0001) compared to angiogenesis-negative tumours. Interestingly the EMT Hallmark was not found to be individually prognostic. When validated in the Ipilimumab treated dataset, patients classified as immune-positive had improved OS (HR = 0.357, p= 0.010) when compared to immune-negative. Similar trends were also observed for angiogenesis and EMT Hallmarks. Conclusions: This study demonstrates how simultaneous analysis of multiple GES ( n= 35 in this study) can identify robust biologies through consensus expression. This platform may have value in the identification of reliable biomarkers for clinical trials and could inform how combination therapies targeting key biologies may be used in cancer treatment.

MET overexpression as a hallmark of the epithelial-mesenchymal transition (EMT) phenotype in colorectal cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 3529-3529 ◽  
Author(s):  
Kanwal Pratap Singh Raghav ◽  
Hesham M. Amin ◽  
Wenting Wang ◽  
Ganiraju C. Manyam ◽  
Bradley Broom ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Overall Survival ◽  
Protein Expression ◽  
Protein Gene ◽  
Epithelial Mesenchymal Transition ◽  
Mesenchymal Transition ◽  
Gene Signatures ◽  
Protein Levels ◽  
Emt Markers

3529 Background: Epithelial-mesenchymal transition (EMT) has been identified as a dominant molecular subtype of colorectal cancer (CRC). This EMT phenotype as recognized by complex gene signatures is prognostic and associated with chemoresistance, but a biomarker for EMT suitable for clinical utilization has not yet been validated. The purpose of this study was to compare MET protein expression with protein/gene expression of EMT markers and to evaluate its impact on overall survival (OS). Methods: We performed an exploratory analysis of 139 untreated primary CRC samples using data from The Cancer Genome Atlas. Protein and gene expressions were measured using reverse-phase protein array (RPPA) and RNA-sequencing, respectively. MET high/overexpressed group was defined by protein level in the highest quartile. Mann-Whitney U-test and Spearman rank correlation was used to determine association between MET protein expression and protein/gene expression of EMT markers and EMT gene signature scores. Regression tree method and Kaplan-Meier estimates were used to assess overall survival (OS). Results: The MET protein distribution is right skewed, demonstrating a unique population of MET high expressing tumors (P < 0.01). Colon tumors had higher MET protein levels compared to rectal tumors (P < 0.01). MET overexpression was associated with decreased OS (HR 2.92; 95% CI: 1.45 - 5.92). MET protein expression correlated strongly with protein expressions of SLUG (transcription factor for EMT) (r = 0.6) and ERCC1 (a marker for oxaliplatin chemo-resistance) (r = 0.6) (P < 0.01). Higher MET protein levels were associated with higher gene expression of 28 EMT markers including AXL, VIM, ZEB1, ZEB2, FGF1, TGFB1I1 and MMP11 (P < 0.05). Higher MET protein levels were also associated with higher gene scores derived from three published EMT gene signatures (P < 0.05). MET protein expression did not correlate with MET gene expression (r = 0.16). Conclusions: Increased MET protein expression strongly correlates with a molecular EMT phenotype and poor survival in patients with CRC. MET protein expression may be used as a surrogate biomarker to represent and select for this unique molecular subset of CRC driven by EMT biology.

scholarly journals Comprehensive discovery of subsample gene expression components by information explanation: therapeutic implications in cancer

2016 ◽  
Author(s):  
Shirley Pepke ◽  
Greg Ver Steeg
Keyword(s):  
Gene Expression ◽  
Drug Targets ◽  
De Novo ◽  
Epithelial Mesenchymal Transition ◽  
Learning Algorithm ◽  
Gene Clusters ◽  
Rna Seq ◽  
Latent Factors ◽  
Mesenchymal Transition ◽  
Therapeutic Implications

BackgroundDe novoinference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations (co-expression) that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem.MethodsIn this work we adapt a recently developed machine learning algorithm, CorEx, that efficiently optimizes over multivariate mutual information for sensitive detection of complex gene relationships. The algorithm can be iteratively applied to generate a hierarchy of latent factors. Patients are stratified relative to each factor and combinatoric survival analyses are performed and interpreted in the context of biological function annotations and protein network interactions that might be utilized to match patients to multiple therapies.ResultsAnalysis of ovarian tumor RNA-seq samples demonstrates the algorithm's power to infer well over one hundred biologically interpretable gene cohorts, several times more than standard methods such as hierarchical clustering and k-means. The CorEx factor hierarchy is also informative, with related but distinct gene clusters grouped by upper nodes. Some latent factors correlate with patient survival, including one for a pathway connected with the epithelial-mesenchymal transition in breast cancer that is regulated by a potentially druggable microRNA. Further, combinations of factors lead to a synergistic survival advantage in some cases.ConclusionsIn contrast to studies that attempt to partition patients into a small number of subtypes (typically 4 or fewer) for treatment purposes, our approach utilizes subgroup information for combinatoric transcriptional phenotyping. Considering only the 66 gene expression groups that are both found to have significant Gene Ontology enrichment and are small enough to indicate specific drug targets implies a computational phenotype for ovarian cancer that allows for 366possible patient profiles, enabling truly personalized treatment. The findings here demonstrate a new technique that sheds light on the complexity of gene expression dependencies in tumors and could eventually enable the use of patient RNA-seq profiles for selection of personalized and effective cancer treatments.

scholarly journals DNA Methylation Changes in Endometrium and Correlation with Gene Expression During Ovarian Hyper-stimulation

2020 ◽  
Author(s):  
Bo Sun ◽  
Yujia Ma ◽  
Fang Wang ◽  
Linli Hu ◽  
Shanjun Dai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Detrimental Effect ◽  
Epithelial Mesenchymal Transition ◽  
Progesterone Receptors ◽  
Endometrial Receptivity ◽  
Rna Seq ◽  
Normal Cycle ◽  
Mesenchymal Transition ◽  
Cycle Group

Abstract Persistent supraphysiological serum estradiol (E2) levels during controlled ovarian hyper-stimulation (COH) have a detrimental effect on endometrial receptivity. In this study, we explored RNA expression and DNA methylation profiles from patients’ endometrium. The patients were divided into two groups: the COH cycle (n=3, hCG+7) group and normal cycle group (n=3, LH+5). Quantitative RT-PCR was used to validate the expression of selected differentially expressed genes (DEGs). Comparing natural and stimulated endometrium transcriptome profiles revealed 640 DEGs, with a > 2-fold change (FC) and p < 0.01. The DEGs were reported to be involved in endometrial receptivity and epithelial-mesenchymal transition (EMT). The expression of IGFBP-1, MMP9, FGF9, LIF, WNT4, HAND2, and immune system-related genes were significantly up-regulated. By clustering and KEGG pathway analysis, molecules and pathways associated with endometrial receptivity (PI3K-Akt signaling pathway) were identified. DNA methylation was partially correlated to gene expression. In conclusion, RNA-seq COH affected endometrial receptivity and EMT/MET process by accelerated the decidualization process and broken the balance of estrogen and progesterone receptors expression. However, this was not associated with changes in DNA methylation.

scholarly journals ETV4 plays a role on the primary events during the adenoma-adenocarcinoma progression in colorectal cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Aline Simoneti Fonseca ◽  
Anelisa Ramão ◽  
Matheus Carvalho Bürger ◽  
Jorge Estefano Santana de Souza ◽  
Dalila Lucíola Zanette ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Dna Sequencing ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Epithelial Mesenchymal Transition ◽  
Sequencing Analysis ◽  
Microarray Gene Expression ◽  
Mesenchymal Transition ◽  
Paired Samples

Abstract Background Colorectal cancer (CRC) is one of the most common cancers worldwide; it is the fourth leading cause of death in the world and the third in Brazil. Mutations in the APC, DCC, KRAS and TP53 genes have been associated with the progression of sporadic CRC, occurring at defined pathological stages of the tumor progression and consequently modulating several genes in the corresponding signaling pathways. Therefore, the identification of gene signatures that occur at each stage during the CRC progression is critical and can present an impact on the diagnosis and prognosis of the patient. In this study, our main goal was to determine these signatures, by evaluating the gene expression of paired colorectal adenoma and adenocarcinoma samples to identify novel genetic markers in association to the adenoma-adenocarcinoma stage transition. Methods Ten paired adenoma and adenocarcinoma colorectal samples were subjected to microarray gene expression analysis. In addition, mutations in APC, KRAS and TP53 genes were investigated by DNA sequencing in paired samples of adenoma, adenocarcinoma, normal tissue, and peripheral blood from ten patients. Results Gene expression analysis revealed a signature of 689 differentially expressed genes (DEG) (fold-change> 2, p< 0.05), between the adenoma and adenocarcinoma paired samples analyzed. Gene pathway analysis using the 689 DEG identified important cancer pathways such as remodeling of the extracellular matrix and epithelial-mesenchymal transition. Among these DEG, the ETV4 stood out as one of the most expressed in the adenocarcinoma samples, further confirmed in the adenocarcinoma set of samples from the TCGA database. Subsequent in vitro siRNA assays against ETV4 resulted in the decrease of cell proliferation, colony formation and cell migration in the HT29 and SW480 colorectal cell lines. DNA sequencing analysis revealed KRAS and TP53 gene pathogenic mutations, exclusively in the adenocarcinomas samples. Conclusion Our study identified a set of genes with high potential to be used as biomarkers in CRC, with a special emphasis on the ETV4 gene, which demonstrated involvement in proliferation and migration.

scholarly journals A novel prognostic model based on epithelial-mesenchymal transition-related genes predicts patient survival in gastric cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wanting Song ◽  
Yi Bai ◽  
Jialin Zhu ◽  
Fanxin Zeng ◽  
Chunmeng Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Risk Model ◽  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Critical Function ◽  
Mesenchymal Transition ◽  
Patient Prognosis

Abstract Background Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. Methods Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. Results Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. Conclusions We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.

scholarly journals Combination of subtherapeutic anti-TNF dose with dasatinib restores clinical and molecular arthritogenic profiles better than standard anti-TNF treatment

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Lydia Ntari ◽  
Christoforos Nikolaou ◽  
Ksanthi Kranidioti ◽  
Dimitra Papadopoulou ◽  
Eleni Christodoulou-Vafeiadou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Therapeutic Effect ◽  
Expression Analysis ◽  
Mode Of Action ◽  
Gene Expression Analysis ◽  
Kinase Inhibitors ◽  
High Dose ◽  
Dependent Manner ◽  
Combination Therapies ◽  
Number Of Patients

Abstract Background New medications for Rheumatoid Arthritis (RA) have emerged in the last decades, including Disease Modifying Antirheumatic Drugs (DMARDs) and biologics. However, there is no known cure, since a significant proportion of patients remain or become non-responders to current therapies. The development of new mode-of-action treatment schemes involving combination therapies could prove successful for the treatment of a greater number of RA patients. Methods We investigated the effect of the Tyrosine Kinase inhibitors (TKIs) dasatinib and bosutinib, on the human TNF-dependent Tg197 arthritis mouse model. The inhibitors were administered either as a monotherapy or in combination with a subtherapeutic dose of anti-hTNF biologics and their therapeutic effect was assessed clinically, histopathologically as well as via gene expression analysis and was compared to that of an efficient TNF monotherapy. Results Dasatinib and, to a lesser extent, bosutinib inhibited the production of TNF and proinflammatory chemokines from arthritogenic synovial fibroblasts. Dasatinib, but not bosutinib, also ameliorated significantly and in a dose-dependent manner both the clinical and histopathological signs of Tg197 arthritis. Combination of dasatinib with a subtherapeutic dose of anti-hTNF biologic agents, resulted in a synergistic inhibitory effect abolishing all arthritis symptoms. Gene expression analysis of whole joint tissue of Tg197 mice revealed that the combination of dasatinib with a low subtherapeutic dose of Infliximab most efficiently restores the pathogenic gene expression profile to that of the healthy state compared to either treatment administered as a monotherapy. Conclusion Our findings show that dasatinib exhibits a therapeutic effect in TNF-driven arthritis and can act in synergy with a subtherapeutic anti-hTNF dose to effectively treat the clinical and histopathological signs of the pathology. The combination of dasatinib and anti-hTNF exhibits a distinct mode of action in restoring the arthritogenic gene signature to that of a healthy profile. Potential clinical applications of combination therapies with kinase inhibitors and anti-TNF agents may provide an interesting alternative to high-dose anti-hTNF monotherapy and increase the number of patients responding to treatment.

scholarly journals Pancreatic Cancers with High Grade Tumor Budding Exhibit Hallmarks of Diminished Anti-Tumor Immunity

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1090
Author(s):  
Hassan Sadozai ◽  
Animesh Acharjee ◽  
Thomas Gruber ◽  
Beat Gloor ◽  
Eva Karamitopoulou
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Disease Progression ◽  
Immune Escape ◽  
Epithelial Mesenchymal Transition ◽  
Tumor Budding ◽  
Ductal Adenocarcinoma ◽  
Low Grade ◽  
High Grade ◽  
Mesenchymal Transition

Tumor budding is associated with epithelial-mesenchymal transition and diminished survival in a number of cancer types including pancreatic ductal adenocarcinoma (PDAC). In this study, we dissect the immune landscapes of patients with high grade versus low grade tumor budding to determine the features associated with immune escape and disease progression in pancreatic cancer. We performed immunohistochemistry-based quantification of tumor-infiltrating leukocytes and tumor bud assessment in a cohort of n = 111 PDAC patients in a tissue microarray (TMA) format. Patients were divided based on the ITBCC categories of tumor budding as Low Grade (LG: categories 1 and 2) and High Grade (HG: category 3). Tumor budding numbers and tumor budding grade demonstrated a significant association with diminished overall survival (OS). HG cases exhibit notably reduced densities of stromal (S) and intratumoral (IT) T cells. HG cases also display lower M1 macrophages (S) and increased M2 macrophages (IT). These findings were validated using gene expression data from TCGA. A published tumor budding gene signature demonstrated a significant association with diminished survival in PDAC patients in TCGA. Immune-related gene expression revealed an immunosuppressive TME in PDAC cases with high expression of the budding signature. Our findings highlight a number of immune features that permit an improved understanding of disease progression and EMT in pancreatic cancer.

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