We derived a transcriptional signature of oncogenic KRAS by using the KF508 murine pancreatic ductal cell line with an inducible Lox-Stop-Lox (LSL) cassette in front of the KRASG12D oncogene to regulate transcription. This dataset allowed us to study the differential expression profile after oncogenic KRAS induction in mouse.
Master Regulators of Oncogenic KRAS Response in Pancreatic Cancer: An Integrative Network Biology Analysis.
Cell line, Treatment
View SamplesChronic obstructive pulmonary disease (COPD) is a known risk factor for developing lung cancer suggesting that the COPD stroma contains factors supporting tumorigenesis. Since cancer initiation is complex we used a multi-omic approach to identify gene expression patterns that distinguish COPD stroma in patients with or without lung cancer. We obtained lung tissue from patients with COPD and lung cancer (tumor and adjacent non-malignant tissue) and those with COPD without lung cancer for proteomic and mRNA (cytoplasmic and polyribosomal) profiling. We used the joint and individual variation explained (JIVE) method to integrate and analysis across the three datasets. JIVE identified eight latent patterns that robustly distinguished and separated the three groups of tissue samples. Predictive variables that associated with the tumor, compared to adjacent stroma, were mainly represented in the transcriptomic data, whereas, predictive variables associated with adjacent tissue compared to controls was represented at the translatomic level. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis revealed extracellular matrix (ECM) and PI3K-Akt signaling pathways as important signals in the pre-malignant stroma. COPD stroma adjacent to lung cancer is unique and differs from non-malignant COPD tissue and is distinguished by the extracellular matrix and PI3K-Akt signaling pathways. Overall design: Polysome-profiling of lung tumor, adjacent non-cancerous lung stroma tissue samples from the same patient compared to patients without lung cancer across a range of forced expiratory volume in one second (FEV1)
Multi-omic molecular profiling of lung cancer in COPD.
Specimen part, Subject
View SamplesChronic obstructive pulmonary disease (COPD) is an independent risk factor for lung cancer, but the underlying molecular mechanisms are unknown. We hypothesized that lung stromal cells activate pathological gene expression programs supporting oncogenesis. To identify molecular mechanisms operating in the lung stroma that support development of lung cancer. Study subjects included patients with- or without- lung cancer across a spectrum of lung function. We conducted multi-omics analysis of non-malignant lung tissue to quantify the transcriptome, translatome and proteome. Cancer-associated gene expression changes predominantly manifested as alterations in the efficiency of mRNA translation modulating protein levels in the absence of corresponding changes in mRNA levels. The molecular mechanisms driving these cancer-associated translation programs differed based on lung function. In subjects with normal to mildly impaired lung-function, the mammalian target of rapamycin (mTOR) pathway served as an upstream driver; whereas in severe airflow obstruction, pathways downstream of pathological extracellular matrix (ECM) emerged. Consistent with a role during cancer initiation, both the mTOR and ECM gene expression programs paralleled activation of previously identified pro-cancer secretomes. Furthermore, in situ examination of lung tissue documented that stromal fibroblasts express cancer-associated proteins from the two pro-cancer secretomes including IL6 in mild or no airflow obstruction and BMP1 in severe airflow obstruction. Two distinct stromal gene expression programs promoting cancer initiation are activated in lung cancer patients depending on lung function. Our work has implications both for screening strategies and personalized approaches to cancer treatment. Overall design: Polysome-profiling of non-cancerous lung stroma tissue samples from patients with or without lung cancer across a range of forced expiratory volume in one second (FEV1)
Distinct Cancer-Promoting Stromal Gene Expression Depending on Lung Function.
Specimen part, Subject
View SamplesGenome-wide association studies have identified a locus within the second intron of the FGFR2 gene that is consistently the most strongly associated with estrogen receptor-poisive breast cancer risk. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Previously, a systems biology approach was adopted to elucidate the regulatory networks operating in MCF-7 breast cancer cells in order to examine the role of FGFR2 in mediating risk. Here, the same approach has been employed using a number of different estrogen receptor-positive breast cancer cell lines in order to see if the previous findings are reproducible and consistent in estrogen receptor-positive disease.
Regulators of genetic risk of breast cancer identified by integrative network analysis.
Specimen part, Cell line, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Master regulators of FGFR2 signalling and breast cancer risk.
Specimen part, Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Cell line
View SamplesGenome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways
Master regulators of FGFR2 signalling and breast cancer risk.
Specimen part
View SamplesAlthough corticosteroids remain a mainstay of therapy for UC, a meta-regression of cohort studies in acute severe ulcerative colitis (UC) showed that 29% of patients fail corticosteroid therapy and require escalation of medical management or colectomy.
Gene expression changes associated with resistance to intravenous corticosteroid therapy in children with severe ulcerative colitis.
Specimen part
View Samples