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GSE135068
Homo sapiens
12 Downloadable Samples
Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
Previously, we identified Ras homologous A (RHOA) as a major signalling hub in gastric cancer (GC), the third-most common cause of cancer death in the world, prompting us to rationally design an efficacious inhibitor of this oncogenic GTPase. Here, based on that previous work, we extend those computational analyses, and in silico modeling approaches, to further pharmacologically optimize anti-RHOA hydrazide derivatives for greater anti-GC potency. Two of these, JK-136 and JK-139, potently inhibited cell viability and migration/invasion of GC cell lines, and mouse xenografts, diversely expressing RHOA. Moreover, JK-136’s binding affinity for RHOA was >140-fold greater than Rhosin, a nonclinical RHOA inhibitor. Network analysis of JK-136/139-associated transcriptomes showed different functional contexts, compared to those following treatment with Rhosin. We strongly assert that identifying and targeting oncogenic signalling hubs, such as RHOA, represents an emerging strategy for the design, characterization, and translation of new antineoplastics, against gastric and other cancers.
Publication Title
Rational design of small molecule RHOA inhibitors for gastric cancer.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 2 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
Develop the 17-AAG resistance human lung cancer cell line and used microarrays to observe the gene alternnation
Publication Title
No associated publication
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 217 Downloadable Samples
- Illumina HumanHT-12 V3.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
No associated publication
Sample Metadata Fields
Sex, Age, Specimen part, Subject
View Samples- Homo sapiens
- 144 Downloadable Samples
- Illumina HumanHT-12 V4.0 expression beadchip
Description
While we and others have uncovered and validated several genomic predictors for metastatic recurrences, a molecular or genomic predictor that can reliably identify high-risk patients for late de novo recurrence has not been firmly established. We analyzed previously reported gene expression data from human livers that underwent partial hepatectomy or transplantation, which were representative physiological conditions that trigger liver regeneration signals. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 hepatocellular carcinoma (HCC) patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for recurrence of HCC after surgery.
Publication Title
Genomic predictors for recurrence patterns of hepatocellular carcinoma: model derivation and validation.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 118 Downloadable Samples
- Illumina human-6 v2.0 expression beadchip
Description
Despite continual efforts to rationalize a prognostic stratification of patients with esophageal adenocarcinoma (EAC) before treatment, current staging system only shows limited success owing to the lack of molecular and genetic markers that reflect prognostic features of the tumor. To develop molecular predictors of prognosis, we used systems-level characterization of tumor transcriptome. Using DNA microarray, genome-wide gene expression profiling was performed on 75 biopsy samples from patients with untreated EAC. Various statistical and informatical methods were applied to gene expression data to identify potential biomarkers associated with prognosis. Potential marker genes were validated in an independent cohort using quantitiative RT-PCR to measure gene expression. Distinct subgroups of EAC were uncovered by systems-level characterization of tumor transcriptome. We also identified a six-gene expression signature that could be used to predict overall survival (OS) of EAC patients. In particular, expression of SPARC and SPP1 was a strong independent predictor of OS, and a combined gene expression signature with these two genes was associated with prognosis (P < 0.024), even when all relevant pathological variables were considered together in multivariate Cox hazard regression analysis. Our findings suggest that molecular features reflected in gene expression signatures may dictate the prognosis of EAC patients, and these gene expression signatures can be used to predict the likelihood of prognosis at the time of diagnosis and before treatment.
Publication Title
Prognostic biomarkers for esophageal adenocarcinoma identified by analysis of tumor transcriptome.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 109 Downloadable Samples
Illumina HumanHT-12 V3.0 expression beadchip
Description
Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from gastric cancer patients and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis and response to adjuvant chemotherapy.
Publication Title
No associated publication
Sample Metadata Fields
Sex, Age, Specimen part, Subject
View Samples- Homo sapiens
- 108 Downloadable Samples
- Illumina HumanHT-12 V3.0 expression beadchip
Description
Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from gastric cancer patients and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis and response to adjuvant chemotherapy.
Publication Title
No associated publication
Sample Metadata Fields
Sex, Age, Specimen part, Subject
View Samples- Mus musculus, Homo sapiens
- 49 Downloadable Samples
- Illumina human-6 v2.0 expression beadchip
Description
To test gene expression changes of human cancer cells and mouse surrounding tissue cells during tumor progression, 4 different types of cancer cells (MDA-MB231Br3, PC14Br4, KM12M, A375SM) were injected into mouse brain, skin and orthotopic sites. RNAs containing human cancer cells and mouse surrounding tissue cells were extracted and hybridized into human and mouse arrays at the same times and it revealed the brain microenvironment induced complete reprogramming of metasized cancer cells, resulting in a gain of neuronal cell characteristic , mimicking neurogenesis during development.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 90 Downloadable Samples
- Illumina HumanWG-6 v3.0 expression beadchip
Description
Despite continual efforts to establish pre-operative prognostic model of gastric cancer by using clinical and pathological parameters, a staging system that reliably separates patients with early and advanced gastric cancer into homogeneous groups with respect to prognosis does not exist. With use of microarray and quantitative RT-PCR technologies, we exploited series of experiments in combination with complementary data analyses on tumor specimens from 161 gastric cancer patients. Various statistical analyses were applied to gene expression data to uncover subgroups of gastric cancer, to identify potential biomarkers associated with prognosis, and to construct molecular predictor of risk from identified prognostic biomarkers.Two subgroups of gastric cancer with strong association with prognosis were uncovered. The robustness of prognostic gene expression signature was validated in independent patient cohort with use of support vector machines prediction model. For easy translation of our finding to clinics, we develop scoring system based on expression of six genes that can predict the likelihood of recurrence after curative resection of tumors. In multivariate analysis, our novel risk score was an independent predictor of recurrence (P=0.004) in cohort of 96 patients, and its robustness was validated in two other independent cohorts. We identified novel prognostic subgroups of gastric cancer that are distinctive in gene expression patterns. Six-gene signature and risk score derived from them has been validated for predicting the likelihood of survival at diagnosis.
Publication Title
Gene expression signature-based prognostic risk score in gastric cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 88 Downloadable Samples
- Illumina HumanHT-12 V4.0 expression beadchip
Description
CTNNB1 is the most frequently mutated gene in hepatocellular carcinoma (HCC). However, its clinical relevance remains controversial. We determined an evolutionarily conserved -catenin signature by comparative analysis of gene expression data from human HCC and a mouse model (GSE43628). We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for prognosis of HCC after surgery.
Publication Title
Activating CAR and β-catenin induces uncontrolled liver growth and tumorigenesis.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage
View Samples