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 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

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 Maintenance of Head and Neck Tumor Gene Expression Profiles upon Lymph Node Metastasis

2006 ◽  
Vol 66 (23) ◽  
pp. 11110-11114 ◽  
Author(s):  
Paul Roepman ◽  
Alike de Jager ◽  
Marian J.A. Groot Koerkamp ◽  
J. Alain Kummer ◽  
Piet J. Slootweg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Head And Neck ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Head And Neck Tumor ◽  
Node Metastasis ◽  
Tumor Gene Expression ◽  
Tumor Gene

scholarly journals Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations

2018 ◽  
Author(s):  
Jean Hausser ◽  
Pablo Szekely ◽  
Noam Bar ◽  
Anat Zimmer ◽  
Hila Sheftel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Diversity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Data ◽  
The Body ◽  
Driver Mutations ◽  
Passenger Mutations ◽  
Tumor Gene Expression ◽  
Tumor Gene

AbstractRecent advances have led to an appreciation of the vast molecular diversity of cancer. Detailed data has enabled powerful methods to sort tumors into groups with benefits for prognosis and treatment. We are still missing, however, a general theoretical framework to understand the diversity of tumor gene-expression and mutations. To address this, we present a framework based on multi-task evolution theory, using the fact that tumors evolve in the body, and that tumors are faced with multiple tasks that contribute to their fitness. In accordance with the theory, we find that tradeoff between tasks constrains tumor gene-expression to a continuum bounded by a polyhedron. The vertices of the polyhedron are gene-expression profiles each specializing in one task, allowing the tasks to be identified. We find five universal cancer tasks across tissue-types: cell-division, biomass & energy, lipogenesis, immune-interaction and invasion & tissue remodeling. Tumors whose gene-expression lies close to a vertex are task specialists. We find evidence that such specialists are more sensitive to drugs that interfere with this task. We find that driver mutations, but not passenger mutations, tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a theoretically-based framework for understanding tumor diversity.

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