ABSTRACT: Gene expression data from Agilent-014850 4x44K human expression array for CRPC Prostate Cancer study with Xenograph data. RNA was isolated using the mirVana total RNA protocol (part #AM1560, Ambion, Austin, TX). RNA integrity was verified using a 2100 Bioanalyzer (part #G2938A) with nano chips (parts #5067-15101 and #G4411B; Agilent Technologies, Alto, CA). RNA concentrations were determined using a Nanodrop spectrophotometer (Thermo Scientific, Wilmington, DE). Tumor messenger RNA expression was assessed using a human whole-genome oligo TMA kit from Agilent (prod #G4112F) according to the manufacturer’s protocol and as described previously. In the Characteristics field, we have the notation like "Pt Dxed in 2001; hormone Tx; chemo Tx 2002; HRPC by 2002". That means the patient was admitted in 2001, did hormone and chemo treatment in 2002, and HRPC 2002. They are standard prostate cancer treatments.
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<pre>Optimal control of mixed immunotherapy and chemotherapy of tumors
Lisette Depillis, K. R. Fister , W. Gu, Tiffany Head, Kenny Maples, Todd Neal, Anand Murugan and Kenji Kozai
Abstract
We investigate a mathematical population model of tumor-immune interactions. Thepopulations involved are tumor cells, specific and non-specific immune cells, and con-centrations of therapeutic treatments. We establish the existence of an optimal con-trol for this model and provide necessary conditions for the optimal control triple forsimultaneous application of chemotherapy, tumor infiltrating lymphocyte (TIL) ther-apy, and interleukin-2 (IL-2) treatment. We discuss numerical results for the combina-tion of the chemo-immunotherapy regimens. We find that the qualitative nature of ourresults indicates that chemotherapy is the dominant intervention with TIL interactingin a complementary fashion with the chemotherapy. However, within the optimal con-trol context, the interleukin-2 treatment does not become activated for the estimatedparameter ranges.
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
Project description:The hypoxia response contributes to radio and chemo-resistance in cancer cells. Our previous work has shown that the nitric oxide donating non-steroidal anti-inflammatory drug (NO-NSAID) NO-sulindac is a potent inhibitor of the hypoxia response in prostate cancer cells and leads to increased susceptibilty to radiation. In this study we used microarrays to investigated the global impact of NO-sulindac on the hypoxia response in prostate cancer cells with a view to determining the mechanism of action. PC3 hormone-insensitive prostate cancer cells were grown under normoxic or hypoxic conditions and treated with NO-sulindac, unnitrated sulindac or vehicle control. Global gene expression in response to treatment was examined using microarrays and the bioconductor software suite. Gene set enrichment analysis (GSEA), Gene ontology (GO) analysis and pathway analysis were used to examine the biological impact of treatments.
Project description:Both in situ synthesized long oligo arrays from Agilent Technologies and short oligo arrays from Affymetrix were used to measure differential gene expression in RNA samples generated from human neuroblastoma cells treated with vehicle (EtOH, 0.01%) and tert-butylhydroquinone (tBHQ, 10µM) for 24h. For Affymetrix technology, RNAs from vehicle or tBHQ treated groups were analyzed separately. There are three replicates (GSM 11865, 11866, 11858, 11857, 11870, and 11871) which represent the RNA preps harvested at three different time (April 17, 2001, March 15, 2001, and Feb 21, 2001). For Agilent arrays, amplified cRNAs generated from vehicle or tBHQ treated groups were labeled with cy3 or cy5 and were competitively hybridized with Hu 1A oligo arrays. The RNA prep used for Agilent array analysis was not the same as the one used for Affymetrix array analysis. Finally, three replicates (GSM 11828, 11831 and 11835) were generated. Keywords: parallel sample
Project description:This is a mathematical describing the interaction between the prostate adenocarcinoma tumor environment, the prostate specific antigen (PSA) produced by hormone-dependent and hormone-independent tumor cells, respectively, and the level of androgens.
Project description:Both in situ synthesized long oligo arrays from Agilent Technologies and short oligo arrays from Affymetrix were used to meausre differential gene expression in RNA samples generated from human neural stem cells treated with vehicle (EtOH, 0.01%) and tert-butylhydroquinone (tBHQ, 20µM) for 24h. For Affymetrix technology, RNAs from vehicle or tBHQ treated groups were analyzed separately. There are three replicates (GSM 11755, 11756, 11780, 11781, 11782, and 11783) which represent the RNA preps harvested at three different time (Jan 16, 2002, Jan 24, 2002, and Feb 20, 2002). For Agilent arrays, amplified cRNAs generated from vehicle or tBHQ treated groups were labeled with cy3 or cy5 and were competitively hybridized with Hu 1A oligo arrays. The same RNA preps used for Affymetrix array analysis were also used for Agilent array analysis. Finally, three replicates (GSM 11803, 11804 and 11809) were generated. Keywords: parallel sample
Project description:RNA was extracted from the frozen prostate tumours or tissues of P1 prostate tumours (n=3), CP1 prostate tumours (n=3) and CP2 prostate tumours (n=4). RNA quality of RNA extracted was evaluated by RNA integrity number (RIN>7.3), calculated using an Agilent 2100 Bioanalyzer (Agilent Technologies) with the Agilent RNA 6000 Nano Kit.
Project description:Chemo-resistance is the major cause of death in advanced prostate cancer (PCa), especially in metastatic PCa (mPCa). However, the molecular mechanisms behind chemo-resistance of PCa have not been clarified so far. Here we found GADD45B was significantly low expressed in metastasis PCa and it could promote chemotherapy sensitivity. So we further constructed GADD45B overexpressed cell line to investigate the possible mechanism.
Project description:Here, we characterize RIPK3-dependent transcriptional responses in cortical neurons following infection with neurotropic flaviviruses. Neurons were infected with either Zika virus (ZIKV) strain MR766 at an MOI of 0.1, West Nile virus (WNV) strain TX 2002-HC at an MOI of 0.001, or a saline mock solution. Neurons were derived from mice lacking RIPK3 expression (Ripk3-/-) or wildtype controls. These studies revealed a number of antiviral genes whose upregulation following viral infection is absent in neurons lacking RIPK3, a subset of which were validated using qRT-PCR.