scholarly journals Evaluation of connectivity map shows limited reproducibility in drug repositioning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nathaniel Lim ◽  
Paul Pavlidis
Keyword(s):  
Success Rate ◽  
Cell Line ◽  
Differential Expression ◽  
Drug Repositioning ◽  
False Positives ◽  
Data Driven ◽  
Connectivity Map ◽  
Expression Levels ◽  
Compound Concentration

AbstractThe Connectivity Map (CMap) is a popular resource designed for data-driven drug repositioning using a large transcriptomic compendium. However, evaluations of its performance are limited. We used two iterations of CMap (CMap 1 and 2) to assess their comparability and reliability. We queried CMap 2 with CMap 1-derived signatures, expecting CMap 2 would highly prioritize the queried compounds; the success rate was 17%. Analysis of previously published prioritizations yielded similar results. Low recall is caused by low differential expression (DE) reproducibility both between CMaps and within each CMap. DE strength was predictive of reproducibility, and is influenced by compound concentration and cell-line responsiveness. Reproducibility of CMap 2 sample expression levels was also lower than expected. We attempted to identify the “better” CMap by comparison with a third dataset, but they were mutually discordant. Our findings have implications for CMap usage and we suggest steps for investigators to limit false positives.

scholarly journals Evaluation of Connectivity Map shows limited reproducibility in drug repositioning

2019 ◽  
Author(s):  
Nathaniel Lim ◽  
Paul Pavlidis
Keyword(s):  
Success Rate ◽  
Cell Line ◽  
Differential Expression ◽  
Drug Repositioning ◽  
False Positives ◽  
Data Driven ◽  
Connectivity Map ◽  
Expression Levels ◽  
Compound Concentration

SummaryThe Connectivity Map (CMap) is a popular resource designed for data-driven drug repositioning using a large transcriptomic compendium. However, evaluations of its performance are limited. We used two iterations of CMap (CMap 1 and 2) to assess their comparability and reliability. We queried CMap 2 with CMap 1-derived signatures, expecting CMap 2 would highly prioritize the queried compounds; success rate was 17%. Analysis of previously published prioritizations yielded similar results. Low recall is caused by low differential expression (DE) reproducibility both between CMaps and within each CMap. DE strength was predictive of reproducibility, and is influenced by compound concentration and cell-line responsiveness. Reproducibility of CMap 2 sample expression levels was also lower than expected. We attempted to identify the “better” CMap by comparison with a third dataset, but they were mutually discordant. Our findings have implications for CMap usage and we suggest steps for investigators to limit false positives.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Enhancing Anti-Tumoral Potential of CD-NHF by Modulating PI3K/Akt Axis in U87 Ex Vivo Glioma Model

2021 ◽  
Vol 22 (8) ◽  
pp. 3873
Author(s):  
Gabriel Luta ◽  
Mihail Butura ◽  
Adrian Tiron ◽  
Crina E. Tiron
Keyword(s):  
Cell Line ◽  
Ex Vivo ◽  
Glioma Cells ◽  
In Vitro Study ◽  
Immunofluorescent Staining ◽  
Expression Levels ◽  
Disease Diagnostics ◽  
Phosphorylated Akt ◽  
Significant Impairment

Background: In the latest years, there has been an increased interest in nanomaterials that may provide promising novel approaches to disease diagnostics and therapeutics. Our previous results demonstrated that Carbon-dots prepared from N-hydroxyphthalimide (CD-NHF) exhibited anti-tumoral activity on several cancer cell lines such as MDA-MB-231, A375, A549, and RPMI8226, while U87 glioma tumor cells were unaffected. Gliomas represent one of the most common types of human primary brain tumors and are responsible for the majority of deaths. In the present in vitro study, we expand our previous investigation on CD-NHF in the U87 cell line by adding different drug combinations. Methods: Cell viability, migration, invasion, and immunofluorescent staining of key molecular pathways have been assessed after various treatments with CD-NHF and/or K252A and AKTVIII inhibitors in the U87 cell line. Results: Association of an inhibitor strongly potentiates the anti-tumoral properties of CD-NHF identified by significant impairment of migration, invasion, and expression levels of phosphorylated Akt, p70S6Kinase, or by decreasing expression levels of Bcl-2, IL-6, STAT3, and Slug. Conclusions: Using simultaneously reduced doses of both CD-NHF and an inhibitor in order to reduce side effects, the viability and invasiveness of U87 glioma cells were significantly impaired.

scholarly journals Extracellular Matrix Proteins Expression Profiling in Chemoresistant Variants of the A2780 Ovarian Cancer Cell Line

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Radosław Januchowski ◽  
Piotr Zawierucha ◽  
Marcin Ruciński ◽  
Michał Nowicki ◽  
Maciej Zabel
Keyword(s):  
Ovarian Cancer ◽  
Extracellular Matrix ◽  
Drug Resistance ◽  
Cell Line ◽  
Cancer Cell ◽  
Ovarian Cancer Cell ◽  
Ovarian Cancer Cell Line ◽  
Cancer Cell Line ◽  
Altered Expression ◽  
Expression Levels

Ovarian cancer is the leading cause of death among gynaecological malignancies. Extracellular matrix (ECM) can affect drug resistance by preventing the penetration of the drug into cancer cells and increased resistance to apoptosis. This study demonstrates alterations in the expression levels of ECM components and related genes in cisplatin-, doxorubicin-, topotecan-, and paclitaxel-resistant variants of the A2780 ovarian cancer cell line. Affymetrix Gene Chip Human Genome Array Strips were used for hybridisations. The genes that had altered expression levels in drug-resistant sublines were selected and filtered by scatter plots. The genes that were up- or downregulated more than fivefold were selected and listed. Among the investigated genes, 28 genes were upregulated, 10 genes were downregulated, and two genes were down- or upregulated depending on the cell line. Between upregulated genes 12 were upregulated very significantly—over 20-fold. These genes included COL1A2, COL12A1, COL21A1, LOX, TGFBI, LAMB1, EFEMP1, GPC3, SDC2, MGP, MMP3, and TIMP3. Four genes were very significantly downregulated: COL11A1, LAMA2, GPC6, and LUM. The expression profiles of investigated genes provide a preliminary insight into the relationship between drug resistance and the expression of ECM components. Identifying correlations between investigated genes and drug resistance will require further analysis.

Correlation of expression levels of P-glycoprotein with resistance to adriamycin in a renal adenocarcinoma cell line

1997 ◽  
Vol 25 (6) ◽  
pp. 407-412
Author(s):  
S. Kawamoto ◽  
T. Deguchi ◽  
S. Nezasa ◽  
S. Yamada ◽  
M. Okano ◽  
...  
Keyword(s):  
Cell Line ◽  
Adenocarcinoma Cell Line ◽  
Adenocarcinoma Cell ◽  
Expression Levels ◽  
Renal Adenocarcinoma ◽  
P Glycoprotein

Characterization of Alternatively Spliced Isoforms of MUC4 and ADAM12 Genes in a Metastatic Colorectal Cancer Cell Line Model

2021 ◽  
Author(s):  
Saleh Althenayyan ◽  
Mohammed H AlMuhanna ◽  
Abdulkareem Al Abdulrahman ◽  
Bandar Alghanem ◽  
Suliman A. Alsagaby ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Cell Line ◽  
Differential Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Colorectal Cancer Cell ◽  
Line Model ◽  
Cell Line Model ◽  
Alternatively Spliced

Colorectal cancer prognosis get worse with advancement of disease into metastatic stage. There is a pertinent need to develop prognostic biomarkers that can be used for personalized and precision medicine. Alternative splicing provides an insight into understanding of changes at isoform expression level which may not be evident at gene level. In this direction, we utilized our prior knowledge about significant alternatively spliced genes and chose ADAM12 and MUC4 for further characterization in a metastatic cell line model. These genes were found to be good prognostic indicators in The Cancer Genome Atlas database. We studied the gene organization and designed primers to specifically amplify a group of isoforms. Differential expression of these group of isoforms was observed in normal, primary and metastatic colorectal cancer cell lines. We further validated the results using sanger sequencing. Isoform expression was found to respond to the 5-fluorouracil treatment. RNAseq analysis of the cell lines further validated the differential expression of gene isoforms. Successful detection of ADAM12 and MUC4 in cell lysates varied according to the antibody used which may reflect differential expression of isoforms. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their probable used as prognostic or predictive biomarkers.

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