LBH589, a Novel Deacetylase Inhibitor (DACi), Treatment of Patients with Cutaneous T-Cell Lymphoma (CTCL). Skin Gene Expression Profiles in the First 24 Hours Related to Clinical Response Following Therapy.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2715-2715 ◽  
Author(s):  
Miles Prince ◽  
D.J. George ◽  
R. Johnstone ◽  
C. McCormack ◽  
L. Ellis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Gene Expression Patterns ◽  
Functional Categories ◽  
Patient Response ◽  
Individual Gene ◽  
Tumor Gene Expression ◽  
Tumor Gene

Abstract Background: LBH589 is a novel DACi in Phase I trials. Pre-clinical studies have demonstrated that DACi alter gene expression and other DACi have induced disease regression in CTCL. Indeed, CTCL is an ideal disease to assess variation in tumor gene expression over time following drug administration. In this study we evaluated the safety and activity of LBH589 in CTCL and examined changes in tumor gene expression in the first 24 hours following oral LBH589. Methods: Pts with advanced-stage CTCL, who had progressed following prior systemic therapy were entered into the oral DLT dose level 30 mg M,W,F cohort (n=1), the subsequent MTD dose level 20 mg M,W, F weekly (n=9). LBH589 was continued until disease progression or unacceptable toxicity. Intensive cardiac monitoring was performed. Six pts had 3 mm punch biopsies from CTCL-involved skin lesions at 0, 4, 8 and 24 h after administration, which were subjected to gene expression profiling using Affymetrix U133 plus 2.0 GeneChips with 47,000 probesets. Alteration in gene expression patterns was confirmed by QRT-PCR of selected genes. Individual gene expression analysis is underway, utilizing set enrichment analysis to elucidate the functional categories which correlate with degree of patient response. Results: 10 pts are currently evaluable for response. 2 of the pts attained a complete response (CR), 4 attained a partial response (PR), 1 achieved stable disease (SD) with ongoing improvement, and 2 progressed on treatment (PD). (RR = 6/10; 60%). Microarray data on 5 pts demonstrated distinct gene expression response profiles between pts. Individual gene expression within patient tumors varied over the timepoints in the first 24 hours following treatment. To demonstrate effects of LBH589 as an epigenetic modulator, global changes in gene expression patterns in responding versus progressing patients have been delineated. In addition, functional categories of genes which correlate with degree of patient response have been identified. Conclusions: LBH589 induces CR’s in CTCL pts. Preliminary microarray analysis of tumor samples have identified distinct gene expression profiles.

scholarly journals Biological Insights into Chemotherapy Resistance in Ovarian Cancer

2019 ◽  
Vol 20 (9) ◽  
pp. 2131 ◽  
Author(s):  
Michelle A. Glasgow ◽  
Peter Argenta ◽  
Juan E. Abrahante ◽  
Mihir Shetty ◽  
Shobhana Talukdar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Chemotherapy Resistance ◽  
Gene Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Before And After ◽  
Tumor Gene Expression ◽  
Tumor Gene

The majority of patients with high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy; however, most will develop chemotherapy resistance. Gene signatures may change with the development of chemotherapy resistance in this population, which is important as it may lead to tailored therapies. The objective of this study was to compare tumor gene expression profiles in patients before and after treatment with neoadjuvant chemotherapy (NACT). Tumor samples were collected from six patients diagnosed with HGSOC before and after administration of NACT. RNA extraction and whole transcriptome sequencing was performed. Differential gene expression, hierarchical clustering, gene set enrichment analysis, and pathway analysis were examined in all of the samples. Tumor samples clustered based on exposure to chemotherapy as opposed to patient source. Pre-NACT samples were enriched for multiple pathways involving cell cycle growth. Post-NACT samples were enriched for drug transport and peroxisome pathways. Molecular subtypes based on the pre-NACT sample (differentiated, mesenchymal, proliferative and immunoreactive) changed in four patients after administration of NACT. Multiple changes in tumor gene expression profiles after exposure to NACT were identified from this pilot study and warrant further attention as they may indicate early changes in the development of chemotherapy resistance.

scholarly journals CancerLivER: a database of liver cancer gene expression resources and biomarkers

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Harpreet Kaur ◽  
Sherry Bhalla ◽  
Dilraj Kaur ◽  
Gajendra PS Raghava
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Full Potential ◽  
Individual Gene ◽  
Comprehensive Information ◽  
Tremendous Amount ◽  
Disease Specific

Abstract Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

171 THE EFFECT OF TRICHOSTATIN A ON THE DEVELOPMENT AND THE GLOBAL GENE EXPRESSION PATTERNS IN MOUSE EMBRYOS DEVELOPING IN VITRO

2008 ◽  
Vol 20 (1) ◽  
pp. 165
Author(s):  
X. S. Cui ◽  
X. Y. Li ◽  
T. Kim ◽  
N.-H. Kim
Keyword(s):  
Gene Expression ◽  
Trichostatin A ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Mouse Embryos ◽  
Differentially Expressed ◽  
Gene Expression Patterns ◽  
Cell Stage

Trichostatin A (TSA) is an inhibitor of histone deacetylase and is able to alter gene expression patterns by interfering with the removal of acetyl groups from histones. The aim of this study was to determine the effect of TSA treatment on the development and gene expression patterns of mouse zygotes developing in vitro. The addition of 100 nm TSA to the culture medium did not affect the cleavage of mouse embryos (TSA treatment, 148/150 (99%) v. control, 107/107 (100%)); however, embryos that were treated with TSA arrested at the 2-cell stage (145/148, 98%). We estimated the number of nuclei in control and TSA-treated embryos by propidium iodide staining, taking into account the presence of any cells with two or more nuclei. At 62–63 h post-hCG stimulation, control zygotes had developed to the 4-cell stage and exhibited one nucleus in each blastomere, indicative of normal development. In contrast, we observed tetraploid nuclei in at least one blastomere in 20.8% (11/53) of the embryos that had been treated with TSA. At 28–29 h post-hCG stimulation (metaphase of the 1-cell stage), there was no difference in the mitotic index (as determined by analyzing the microtubule configuration) in the TSA group compared to the control group. At the 2-cell stage, however, we did not observe mitotic spindles and metaphase chromatin in embryos in the TSA treatment group compared to the controls. Interestingly, when embryos were cultured in TSA-free medium from 35 h post-hCG stimulation (S- or early G2-phase of the 2-cell stage) onward, almost all of them (47/50) developed to the blastocyst stage. In contrast, when embryos were cultured in TSA-free medium from 42 h post-hCG stimulation (middle G2-phase of the 2-cell stage) onward, they did not develop to the 4-cell stage. We used Illumina microarray technology to analyze the gene expression profiles in control and TSA-treated late 2-cell-stage embryos. Applied Biosystems Expression System software was used to extract assay signals and assay signal-to-noise ratio values from the microarray images. Our data showed that 897 genes were significantly (P < 0.05; 2-sample t-test) up- or down-regulated by TSA treatment compared to controls. Analysis using the PANTHER classification system (https://panther.appliedbiosystems.com) revealed that the 575 genes that were differentially expressed in the TSA group compared to the control were classified as being associated with putative biological processes or molecular function. Overall, in terms of putative biological processes, more nucleoside, nucleotide, and nucleic acid metabolism, protein metabolism and modification, signal transduction, developmental process, and cell cycle genes were differentially expressed between the TSA and control groups. In terms of putative molecular function, more nucleic acid-binding transcription factor and transferase genes were differentially expressed between the groups. The results collectively suggest that inhibition of histone acetylation in mouse embryos affects gene expression profiles at the time of zygotic genome activation, and this subsequently affects further development.

scholarly journals Tumor diversity and the trade-off between universal cancer tasks

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Jean Hausser ◽  
Pablo Szekely ◽  
Noam Bar ◽  
Anat Zimmer ◽  
Hila Sheftel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Data ◽  
Treatment Groups ◽  
Trade Offs ◽  
Multiple Tasks ◽  
Passenger Mutations ◽  
Tumor Gene Expression ◽  
Tumor Gene

AbstractRecent advances have enabled powerful methods to sort tumors into prognosis and treatment groups. We are still missing, however, a general theoretical framework to understand the vast diversity of tumor gene expression and mutations. Here we present a framework based on multi-task evolution theory, using the fact that tumors need to perform multiple tasks that contribute to their fitness. We find that trade-offs between tasks constrain tumor gene-expression to a continuum bounded by a polyhedron whose vertices are gene-expression profiles, each specializing in one task. We find five universal cancer tasks across tissue-types: cell-division, biomass and energy, lipogenesis, immune-interaction and invasion and tissue-remodeling. Tumors that specialize in a task are sensitive to drugs that interfere with this task. Driver, but not passenger, mutations tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a framework of tumor diversity grounded in evolutionary theory.

scholarly journals Effect of surgical procedures on prostate tumor gene expression profiles

2012 ◽  
Vol 14 (5) ◽  
pp. 708-714 ◽  
Author(s):  
Jie Li ◽  
Zhi-Hong Zhang ◽  
Chang-Jun Yin ◽  
Christian Pavlovich ◽  
Jun Luo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Surgical Procedures ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Prostate Tumor ◽  
Tumor Gene Expression ◽  
Tumor Gene

Categorization of gene expression subtypes in clear cell renal cell carcinoma with sarcomatoid features.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 519-519
Author(s):  
Shreyas Joshi ◽  
Suraj Peri ◽  
Eric A. Ross ◽  
Robert G. Uzzo ◽  
Alexander Kutikov ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Gene Expression Patterns ◽  
Cell Renal Cell Carcinoma

519 Background: Presence of sarcomatoid features in Renal Cell Carcinoma (sRCC) tumors signals aggressive clinical behavior and poor prognosis compared to Clear Cell Renal Cell Carcinoma (ccRCC). However, the underlying gene expression patterns of sRCC are poorly understood. We sought to categorize ccRCC and sRCC gene expression subtypes and compare survival outcomes, as well as evaluate whether sRCC gene expression patterns are similar to non-renal sarcomas. Methods: We identified 511 ccRCC cases, of which 36 had a sarcomatoid component from The Cancer Genome Atlas. Enrichment analysis was used to measure associations between gene expression signatures for soft tissue sarcomas and expression profiles of sRCC and ccRCC cases measured by RNA-Seq. The resulting scores were used to identify distinct patient groups using K-means clustering. Overall survival (OS) was evaluated by Kaplan-Meier, log rank, and Cox regression methods. Results: Our analysis identified 4 distinct clusters that differ in enrichment for soft-tissue sarcoma gene expression profiles. The clusters showed significantly different OS distributions (p-value<0.001 log rank). Most sRCC cases (69%) segregated into a single cluster with the worst prognosis. Among ccRCC cases, 57% of patients with higher levels of sarcoma signature enrichment were associated with a shorter OS, which is independent of tumor stage. 5-year/median OS survival estimates for ccRCC cases in the 4 clusters, by increasing levels of sarcoma profile enrichment, were 83%/NR, 75%/NR, 67%/90.9 mo, and 49%/56.7 mo. We also validated existence of these clusters in another sRCC cohort (Sircar 2015). Conclusions: We identified strong associations between sarcoma expression signatures and gene expression profiles of sRCC. We also found that 57% of morphologically non-sRCC cases demonstrate enrichment for sarcoma expression signatures, and these patients have worse OS than their non-sarcoma enriched ccRCC counterparts. The presence of sarcoma expression signatures has not been previously evaluated in RCC. These signatures portend poor survival and may be clinically actionable, as they describe unique subtypes of RCC that may not correspond to histologic characterization.

Sign in / Sign up

Export Citation Format

Share Document