Fig 1.
The GSLHC workflow.
Fig 2.
Hierarchical clustering of CMap instances less dominated by cell-type when clustering is based on gene-set/tag enrichment scores.
Dendrograms are hierarchical clustering of CMap instances based on gene expression (A) and tag enrichment score (B). Colors in color bar below dendogram respectively represent the cell lines SKMEL5 (red), PC3 (green), MCF7 (blue), and HL60 (purple). For each instance top-300 genes or tags with the top-300 expression log-ratios or ES scores were selected for clustering based on Pearson distance metric and average linkage.
Table 1.
Cell-type effects are eliminated in hierarchical clustering based gene-set enrichment.
Fig 3.
Two-way hierarchical clustering heatmep of 1309 CMap perturbagens shows higher contrast when clustering is based on gene-set/tag enrichment scores.
Two-way hierarchical clustering heatmaps were generated based on Pearson distance metric and average linkage using, for each CMap perturbagen: (A) normalized enrichment scores (NESs) of 4,884 tags from MSigDB, and (B) log-ratios for expression levels of the top-4884 high-variance genes. Color code: on red, positive NES or log-ratio; green, black, NES or log ratio ~0; green, negative NES or log-ratio.
Fig 4.
Separation of two drugs among all instances involving the drug pair is done better using gene-set/tag enrichment scores.
Quality of separation is determined by F-scores for hierarchical clusters, constructed using tag enrichment scores and log-ratios for gene expressions, respectively, of all instances involving the drug pair. (A) Two clusters for the drug-pair valproic acid and trichostatin A; cluster based on gene expression, cluster on left, and on tag, cluster on right. Two-color bar indicates drug classification. (B) Ranking by F-scores of ~20,000 drug-pairs from the CMap development batch on HG-U133A platform involving 407 drugs and 674 chips; black, gene expression and red, tag.
Fig 5.
Same-target drug-pairs correlate better when evaluated by gene-set/tag enrichment scores.
Figure plots correlation of same-target drug pair evaluated by tag enrichment score (ES) versus that evaluated by gene expression. Drug targets were those given by TTD database. In the tag approach, each drug, or CMap perturbagen, was represented by the ESs of 4884 MSigDB tags. In the gene expression case, each drug was represented by the set of top-4884 high variance genes. The three red dots are from the three pairs formed by the three drugs, vorinostat, valproic acid, and trichostatin A, all targeting the histone deacetylase (HDAC) protein.
Fig 6.
GSLHC finds novel HDAC inhibitors.
The three know HDAC inhibitors valproic acid, trichostatin A, and vorinostat, are all significantly enriched by 597 tags with permutation p< 0.005; these 597 tags were used in a new heatmap in the GSLHC protocol. (A) A sub-heatmap including the three HDAC inhibitors and all neighbors with correlation > 0.9. (B) Detail of the drug cluster associated with the sub-heatmap. The two drugs rifabutin and scriptaid in the cluster, not previously known as HDAC inhibitors, has literature support as having inhibition functions on HDAC proteins. (C) Detail of the tag cluster with the sub-heatmap shows several functions known to be related to HDAC inhibitor activities.
Fig 7.
GSLHC identifies 0175029–0000 as a novel cyclin-dependent kinase inhibitor (CDKi).
(A) A correlation > 0.9 sub-heatmap including the compound 0175029–0000 of unknown function from a GSLHC-generated heatmap based on the ES of 1080 tags significantly enriched in 0175029–0000 with permutation p< 0.005. (B) Detail of the drug cluster associated with the sub-heatmap. According to the TTD database, GW-8510, alsterpaullone, and H-7 (red asterisk) CDK inhibitors, and doxorubicin, camptothecin, azacitidine, mitoxantrone, and ellipticine (blue asterisk) are DNA topoisomerase inhibitors. All have anti-tumor activities. (C) Detail of the tag cluster with the sub-heatmap shows functions known to be related to the inhibition activities of cell cycle.
Fig 8.
GSLHC identifies CP-863187 as a potential antibiotic.
(A) A correlation > 0.9 sub-heatmap including the compound CP-863187 of unknown function from a GSLHC-generated heatmap based on the ES of 36 tags significantly enriched in CP-863187 with permutation p< 0.005. (B) Detail of the drug cluster associated with the sub-heatmap. According to TTD database, piperacillin, dapsone, tocainide, ampicillin, sulfadimethoxine, metronidazole (red asterisk) are antibiotics, betulinic acid and isoflupredone (blue asterisk) are anti-inflammatory agents, and benzocaine (green asterisk) is an anesthetic. (C) Detail of the tag cluster with the sub-heatmap shows functions known to block the formation of bacteria cell wall by inhibition of integrin signaling pathway.
Table 2.
Putative molecular target and pharmacology obtained from application of GSLHC on CMap perturbagens without known indication.