Comprehensive genomic analysis in metastatic pancreatic ductal adenocarcinoma (PDAC).

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 285-285
Author(s):  
Hui-Li Wong ◽  
Martin Jones ◽  
Peter Eirew ◽  
Joanna Karasinska ◽  
Kasmintan A Schrader ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
De Novo ◽  
Expression Patterns ◽  
Genomic Analysis ◽  
Ductal Adenocarcinoma ◽  
Tumor Biopsy ◽  
Significant Difference ◽  
Gene Expression Signatures

285 Background: In the absence of defined tumor molecular subtypes and validated predictive markers, PDAC has been largely treated as a single disease. Recent studies of molecular subtyping in PDAC reveal a complex mutational landscape with data suggesting the presence of genomic and gene expression signatures that may have prognostic and therapeutic significance. These studies predominantly focused on resected PDAC and lack data on metastatic tumors. We aim to explore the clinical utility of whole genome sequencing (WGS) and transcriptome analysis from metastatic biopsy samples in patients (pts) with advanced PDAC. Methods: Pts with incurable advanced cancers undergo tumor biopsy for in-depth WGS and RNA sequencing (RNASeq) as part of an ongoing prospective study (NCT02155621). Comprehensive bioinformatics analysis is performed to identify somatic cancer aberrations, gene expression changes and cellular pathway abnormalities. Here we describe clinical and molecular data on the subset of pts with advanced PDAC. Results: Sixteen PDAC pts have been enrolled; median age 59 years, 8 males (50%), 10 with de novo metastases (63%). Full WGS and RNASeq were completed in 11 pts (1 failed biopsy, 4 had insufficient tumor). KRAS codon 12 and TP53 mutations were present in all but one pt. CDKN2A and SMAD4 were also frequently altered (7 and 4 pts respectively). Gene expression analysis for classical and basal subtypes similar to those recently described (PMID 26343385) identified 3 and 6 pts with classical and basal expression patterns respectively, and 2 pts with mixed expression. Overall survival (OS) was significantly worse for the basal subtype vs all others (median OS 7 vs. 13.9 months (ms), p = 0.017). When separated into 3 subtypes a significant difference was still noted (median OS 7 ms in basal, 19.2 ms in classical and 11.8 ms in mixed subtype, p = 0.032). Conclusions: WGS analysis demonstrated a similar mutation pattern to that described in resectable PDAC, with no novel actionable mutations identified. Gene expression analysis demonstrated the presence of distinct gene expression signatures significantly associated with outcome, despite small pt numbers. These results need to be validated prospectively in larger cohorts. Clinical trial information: NCT02155621.

Microarray Classification of Myelodysplastic Syndrome (MDS) Identifies Subgroups with Distinct Clinical Outcomes.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2426-2426
Author(s):  
Ken I. Mills ◽  
Alex Kohlmann ◽  
Mickey Williams ◽  
Wei-Min Liu ◽  
Rachel Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Cell Signalling ◽  
Bioinformatic Analysis ◽  
Initial Study ◽  
Outcome Data ◽  
Kaplan Meier ◽  
Significant Difference ◽  
Gene Expression Signatures ◽  
Microarray Classification

Abstract The MILE (Microarray Innovations in LEukemia) study has previously shown that gene expression signatures associated with initial leukaemia classifier (LCver7) give an overall cross-validation accuracy of >95% for distinct sub-classes of pediatric and adult leukemias. However, only 50% of the 174 MDS samples in the whole-genome microarray analysis (Stage 1) of the MILE study were correctly identified; the remainder showed AML-like or non-leukemia-like gene profiles. An external morphological review (DB & HL) according to FAB and WHO criteria, of the 174 slides was performed independently (blind) which resulted in 6 samples being reclassified as AML and 4 non-leukemia cases excluded from the study. A recently improved, hierarchical based algorithm correctly identified 100% of the confirmed MDS cases. In this study, using LCver7, the confirmed 164 samples had 50% MDS classifications (Class 17), 23.8% non-leukemia classifications (Class 18), and 22.6% AML classifications (Classes 13 or 14) with the remaining 3.7% having a classification tie between 2 or 3 Classes (due to low confidence). No 5q- syndrome patients had an AML call, whilst 68.3% of RAEB2 patients had an AML classification and none were Class 18. Similarly, 95.6% of Low IPSS patients were classified as Class 17 or 18, whilst all patients (n=5) with High IPSS had an AML call. The classification was independent of blast cells: 10.2% of Class 18 calls had >5% blasts; 28.2% of AML-like cases had <5% blasts. Outcome data (132 MDS patients) was correlated with Class: significant difference (p<0.028, (Kaplan-Meier)) was seen in overall survival; with p <0.004 if AML (Classes 13 & 14) was compared to “non AML” (Classes 17 & 18). Statistically significant differences were seen for time to transformation to AML between the classes (p<0.0001) and between AML and “non AML” (p<0.00007, Kaplan-Meier)) with a probability of transformation of 44% at 18 months for the AML group compared to <8% for the “non-AML” group. A further linear classifier has been used to discriminate patients who transform to AML within 18 months (poor prognosis) with patients with no transformation after >60 months (good prognostic group). Bioinformatic analysis of molecular mapped functions and canonical pathways showed that cell signalling processes were over-represented when comparing de novo AML (n=204) with MDS, from the MILE study, whilst signal transduction pathways were deregulated when comparing non-leukemia samples (n=71) with MDS. Similar pathways and functions were also deregulated when comparing the correctly classified MDS with Class 17 call against MDS with Class 18 call and MDS with AML Classes 13 or 14 calls. In conclusion, the use of microarrays within the initial study, solely intended for diagnostic purposes, has now evolved towards a position in which novel prognostic value may be gained from distinct gene expression signatures. This has also resulted in a better molecular understanding of the progression from non-leukemia, through MDS into full blown AML.

Gene Expression Levels Of Imatinib Transporters and Molecular Response To Imatinib Therapy In Chronic Myeloid Leukemia Patients

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4959-4959
Author(s):  
Hemant Malhotra ◽  
Pratibha Sharma ◽  
Shipra Bhargava ◽  
Bharti Malhotra ◽  
Madhu Kumar
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Conflicts Of Interest ◽  
Imatinib Therapy ◽  
Molecular Response ◽  
Transcript Expression ◽  
Analysis Study ◽  
Expression Levels ◽  
Significant Difference

Abstract Imatinib mesylate (IM) is the standard first-line treatment for most CML patients. After an initial response, approximately 30 to 40% patients develop resistance to the drug. Various mechanisms of resistance to Imatinib therapy have been identified. One of the mechanisms proposed is varying expression levels of the drug transporters. In the present study, we determined the relative expression levels of Imatinib transporter genes (hOCT1, ABCB1, ABCG2) in CML patients by quantitative real time polymerase chain reaction (qRT-PCR) and correlated these levels with molecular response. One hundred and ten CML patients were considered for gene expression analysis study for hOCT1 gene and eighty seven CML patients were considered for gene expression analysis study for ABCB1 and ABCG2 genes. CML patients who were on IM therapy for more than 2 years were divided into two groups: Responders: patients who achieve a Complete Molecular response (CMR) or a Major Molecular Response (MMR) [bcr/abl: abl ratio <1% as assessed by RQ-PCR] and Non-responders: those without CMR or MMR (bcr/abl: abl ratio =/> 1% as assessed by RQ-PCR). The relative transcript expression levels of the three genes were compared between responders and non-responders. No significant difference in the expression levels of hOCT1, ABCB1 and ABCG2 was found between the two categories - responders versus non-responders (p value > 0.05). The median transcript expression levels of hOCT1, ABCB1 and ABCG2 genes in responders were 30.63, 10.14 and 0.59 versus 40.13, 8.34 and 0.53 in non-responders, respectively. We conclude that, in our study, the mRNA expression levels of IM transporter genes did no correlate with molecular response in CML patients. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Evidence of the Complexity of Gene Expression Analysis in Fish Wild Populations

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Mbaye Tine
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Expression Patterns ◽  
Cell Volume Regulation ◽  
Mitogen Activated Protein Kinase ◽  
Wild Populations ◽  
Natural Habitats ◽  
Evolutionary Forces

The present work examines the induction of theband 3 anion transport protein,mitogen-activated protein kinase, andlactate dehydrogenase, respectively related to osmolyte transport, cell volume regulation, and energy production in the gills of two tilapia strains exposed to either freshwater or hypersaline water. Overall, genes showed similar expression patterns between strains. However, a wild population survey across a range of natural habitats and salinities did not reveal the expected patterns. Although significant, the correlations between gene expression and salinity were slightly ambiguous and did not show any link with phenotypic differences in life history traits previously reported between the same populations. The differential expression was also not associated with the population genetic structure inferred from neutral markers. The results suggest that the differential expression observed is not the result of evolutionary forces such as genetic drift or adaptation by natural selection. Instead, it can be speculated that genes responded to various abiotic and biotic stressors, including factors intrinsic to animals. This study provides clear evidence of the complexity of gene expression analysis in wild populations and shows that more attention needs to be paid when selecting candidates as potential biomarkers for monitoring adaptive responses to a specific environmental perturbation.

scholarly journals Rapid parallel adaptation despite gene flow in silent crickets

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xiao Zhang ◽  
Jack G. Rayner ◽  
Mark Blaxter ◽  
Nathan W. Bailey
Keyword(s):  
Gene Expression ◽  
Gene Flow ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
De Novo ◽  
Parallel Evolution ◽  
De Novo Mutation ◽  
Genome Scans ◽  
Wing Structures ◽  
In The Wild

AbstractGene flow is predicted to impede parallel adaptation via de novo mutation, because it can introduce pre-existing adaptive alleles from population to population. We test this using Hawaiian crickets (Teleogryllus oceanicus) in which ‘flatwing’ males that lack sound-producing wing structures recently arose and spread under selection from an acoustically-orienting parasitoid. Morphometric and genetic comparisons identify distinct flatwing phenotypes in populations on three islands, localized to different loci. Nevertheless, we detect strong, recent and ongoing gene flow among the populations. Using genome scans and gene expression analysis we find that parallel evolution of flatwing on different islands is associated with shared genomic hotspots of adaptation that contain the gene doublesex, but the form of selection differs among islands and corresponds to known flatwing demographics in the wild. We thus show how parallel adaptation can occur on contemporary timescales despite gene flow, indicating that it could be less constrained than previously appreciated.

scholarly journals gEAR: gene Expression Analysis Resource portal for community-driven, multi-omic data exploration

2020 ◽  
Author(s):  
Joshua Orvis ◽  
Brian Gottfried ◽  
Jayaram Kancherla ◽  
Ricky S. Adkins ◽  
Yang Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
De Novo ◽  
Marker Gene ◽  
Rna Seq ◽  
Data Types ◽  
Multiple Species ◽  
User Friendly ◽  
The Brain

ABSTRACTThe gEAR portal (gene Expression Analysis Resource, umgear.org) is an open access community-driven tool for multi-omic and multi-species data visualization, analysis and sharing. The gEAR supports visualization of multiple RNA-seq data types (bulk, sorted, single cell/nucleus) and epigenomics data, from multiple species, time points and tissues in a single-page, user-friendly browsable format. An integrated scRNA-seq workbench provides access to raw data of scRNA-seq datasets for de novo analysis, as well as marker-gene and cluster comparisons of pre-assigned clusters. Users can upload, view, analyze and privately share their own data in the context of previously published datasets. Short, permanent URLs can be generated for dissemination of individual or collections of datasets in published manuscripts. While the gEAR is currently curated for auditory research with over 90 high-value datasets organized in thematic profiles, the gEAR also supports the BRAIN initiative (via nemoanalytics.org) and is easily adaptable for other research domains.

2 Intrafollicular injection of asprosin in water buffaloes and the potential role of FBN1 mRNA and asprosin in follicular function

2021 ◽  
Vol 33 (2) ◽  
pp. 108
Author(s):  
E. R. Maylem ◽  
L. Spicer ◽  
E. Atabay ◽  
E. Atabay ◽  
I. Batalha ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Mrna Abundance ◽  
Follicular Growth ◽  
Significant Difference ◽  
Follicle Size ◽  
Phosphate Buffered Saline

Fibrillin-1 (FBN1) functions as a structural protein in the ovary, whereas the role of its protein product asprosin remains unknown. Both proteins are encoded by the FBN1 gene; when it is cleaved at the C-terminal end, asprosin is produced. Asprosin acts as an orexigenic hormone and is associated with various metabolic parameters and sex related hormones in women. One goal of this research was to quantify FBN1 and the presumed asprosin receptor, olfactory receptor family 4 subfamily M member 1 (OR4M1) mRNA in water buffalo granulosa cells (GC) and correlate them to aromatase (CYP19A1) gene expression. A second goal was to determine the effect of asprosin on follicular growth invivo. In Experiment 1, ovaries were collected from a local slaughterhouse, GC from small (&lt;6mm) and large (6–13mm) follicles were aspirated, RNA was extracted, and gene expression analysis conducted. In Experiment 2, an intrafollicular injection of asprosin (6μL of asprosin in 194μL of phosphate-buffered saline; to achieve 20ng mL−1) or vehicle (200μL of phosphate-buffered saline; Controls) was given via the ovarian stroma below the dominant follicle of synchronized cows (n=5/group) 1 day after injection of prostaglandin F2α, and follicle sizes were measured daily via transrectal ultrasonography until the day of ovulation. Means were compared using t-test for gene expression analysis, and Pearson correlation coefficients calculated among FBN1, OR4M1, and CYP19A1 gene expression. A repeated-measures ANOVA was used to determine the effect of asprosin on follicle size and growth rate of follicles. In Experiment 1, FBN1 mRNA abundance was 7.51-fold greater in GC of small than large follicles (P&lt;0.05). There was no significant difference in the OR4M1 (57.83±39.89 vs. 38.98±4.86) or CYP19A1 (11.46±3.72 vs. 8.27±4.81) mRNA abundance between the 2 sizes of follicles (P&gt;0.10). Abundance of CYP19A1 mRNA was positively correlated with FBN1 (r=0.55, P&lt;0.05) and OR4M1 mRNA (r=0.50, P&lt;0.05). In Experiment 2, there was a treatment×day interaction (P&lt;0.10) for follicle size and growth rate of follicles. Cows treated with asprosin had a higher growth rate from Day 1 to 2 (1.09±0.39 to 2.37±0.32 mm/day) than placebo cows (1.74±0.55 to 1.05±0.61 mm/day) after injection. Most of the follicles from both treatment groups ovulated 3 days post injection. These findings suggest that FBN1 (and thus asprosin) are present in buffalo GC and may be developmentally expressed. Also, asprosin may induce follicular growth when given invivo. Whether these proteins directly regulate aromatase expression, and therefore oestradiol production, during follicle development will require further study.

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