This SuperSeries is composed of the SubSeries listed below.
Modeling a lethal prostate cancer variant with small-cell carcinoma features.
Specimen part, Disease
View SamplesPurpose: Small-cell prostate carcinoma (SCPC) morphology predicts for a distinct clinical behavior, resistance to androgen ablation, and frequent but short responses to chemotherapy. The model systems we report reflect the biology of the human disease and can be used to improve our understanding of SCPC and to develop new therapeutic strategies for it.
Modeling a lethal prostate cancer variant with small-cell carcinoma features.
Specimen part
View SamplesTo study the immune response of the prostate tumor tissues after the leuprolide acetate plus ipilimumab, we compared the gene expression of 6 post-therapy with 3 pre-therapy samples. We identified 690 differential expressed genes (DEGs). Pathway analysis showed that these genes are associated with critical immune pathways such as CTLA4 signaling, antigen presenting etc.
VISTA is an inhibitory immune checkpoint that is increased after ipilimumab therapy in patients with prostate cancer.
Specimen part
View SamplesAnalysis of enzalutamide- and/or olaparib-responsive gene expression in prostate cancer cells. The hypothesis tested in the present study was that enzalutamide influences the expression of genes that are involved in important bioprocesses in prostate cance rcells, including DNA damage response genes and this effect may synergize with poly(ADP-ribose) polymerase inhibitor olaparib in cytotoxicity to prstate cancer cells.
Androgen receptor inhibitor-induced "BRCAness" and PARP inhibition are synthetically lethal for castration-resistant prostate cancer.
Disease, Disease stage, Cell line, Treatment
View SamplesSingle cells from Ptenpc-/-Smad4pc-/-mTmG+ prostate tumors were isolated into single cells which were FACS-sorted for GFP+ and Tomato+ cells and RNA was purified with TRIzol (Life Technologies).
Targeting YAP-Dependent MDSC Infiltration Impairs Tumor Progression.
No sample metadata fields
View SamplesGlioblastoma multiforme is the most lethal form of glioma with an overall survival at 5 years nearly null, which mainly results from acquired resistance to therapies. Large scale sequencing studies on human cancer biopsies defined IRE1alpha as the fifth most oncogenic mutated kinase in human cancer. IRE1alpha is a major component of the Unfolded Protein Response signaling and increasing evidence suggests that it is a central player in GBM development.
Dual IRE1 RNase functions dictate glioblastoma development.
Specimen part, Cell line
View SamplesMale Wistar rats weighing 90-120 g were acclimatized for one week and fed standard laboratory chow, at which time the animals were divided into two groups. Animals were then pair-fed for 8 weeks a regular laboratory chow and water ad libitum or Lieber-DeCarli diet (36% calories from ethanol). Control animals received the iso-caloric amount of dextrose to replace ethanol. After 8 weeks of differential feeding rats were euthanized, the pancreas immediately dissected and stored at -80?C until RNA isolation. RNA expression was analyzed using Affymetrix RAE230A gene chips
Long-term ethanol consumption alters pancreatic gene expression in rats: a possible connection to pancreatic injury.
No sample metadata fields
View SamplesGlobal mRNA expression was compared between stable and progressive IPF using bronchoalveolar lavage derived mesenchymal stromal cells
Developmental Reprogramming in Mesenchymal Stromal Cells of Human Subjects with Idiopathic Pulmonary Fibrosis.
Specimen part, Disease
View SamplesThis SuperSeries is composed of the SubSeries listed below.
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.
Age, Specimen part, Disease, Disease stage
View SamplesWe demonstrate a promising approach to identify robust molecular markers for targeted treatment of acute myeloid leukemia. We show that our method outperforms several state-of-the-art approaches in identifying molecular markers replicated in validation data and predicting drug sensitivity accurately.
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.
Age, Specimen part, Disease, Disease stage
View Samples