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| Status |
Public on May 15, 2024 |
| Title |
Drug Repurposing Using Molecular Network Analysis Identifies Janus Kinase as Targetable Driver in Necrobiosis Lipoidica |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Drug repurposing is an attractive strategy for therapy development, particularly in rare diseases where traditional drug development approaches may be challenging due to high cost and small numbers of patients. Here we used a novel drug identification and repurposing pipeline to identify candidate targetable drivers of disease and corresponding therapies through application of causal reasoning using a combination of open-access resources and transcriptomics data. We optimized our approach on psoriasis as a disease model, demonstrating the ability to identify known and novel molecular drivers of psoriasis and link them to current and emerging therapies. Application of our approach to a cohort of tissue samples of necrobiosis lipoidica, an unrelated, rare, and to date molecularly poorly characterized cutaneous inflammatory disorder, identified a unique set of upstream regulators, particularly highlighting the role of IFNG and the JAK-STAT pathway as a likely driver of disease pathogenesis and linked it to JAK inhibitors as potential therapy. Analysis of an independent cohort of NL samples validated these findings with the overall agreement of drug matched upstream regulators above 96%. These data highlight utility of our approach in rare diseases and offer a novel opportunity for drug discovery in other rare diseases in dermatology and beyond.
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| Overall design |
we analyzed 17 histologically typical, archival formalin-fixed paraffin-embedded (FFPE) lesions and 5 control tissues. Whole transcriptome analysis was performed, identifying 3,857 differentially expressed genes with 2,471 genes upregulated and 1,386 genes downregulated in NL (|Log2FC|>1, p<0.05).
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| Contributor(s) |
Hughes AN, Li X, Lehman JS, Nelson SA, DiCaudo DJ, Mudapphati R, Hwang A, Kechter J, Pittelkow MR, Mangold AR, Sekulic A |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
May 09, 2024 |
| Last update date |
May 15, 2024 |
| Contact name |
Tao Ma |
| E-mail(s) |
Ma.Tao@mayo.edu
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| Organization name |
Mayo Clinic
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| Street address |
200 1st ST SW
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| City |
Rochester |
| State/province |
MN |
| ZIP/Postal code |
55905 |
| Country |
USA |
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| Platforms (1) |
| GPL20301 |
Illumina HiSeq 4000 (Homo sapiens) |
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| Samples (22)
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| GSM8260669 |
SNR_48, control |
| GSM8260670 |
SNR_49, control |
| GSM8260671 |
SNR_01, NL disease sample |
| GSM8260672 |
SNR_02, NL disease sample |
| GSM8260673 |
SNR_03, NL disease sample |
| GSM8260674 |
SNR_04, NL disease sample |
| GSM8260675 |
SNR_13, NL disease sample |
| GSM8260676 |
SNR_14, NL disease sample |
| GSM8260677 |
SNR_24, NL disease sample |
| GSM8260678 |
SNR_29, NL disease sample |
| GSM8260679 |
SNR_32, NL disease sample |
| GSM8260680 |
SNR_36, NL disease sample |
| GSM8260681 |
SNR_37, NL disease sample |
| GSM8260682 |
SNR_38, NL disease sample |
| GSM8260683 |
SNR_39, NL disease sample |
| GSM8260684 |
SNR_40, NL disease sample |
| GSM8260685 |
SNR_41, NL disease sample |
| GSM8260686 |
SNR_42, NL disease sample |
| GSM8260687 |
SNR_46, NL disease sample |
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| Relations |
| BioProject |
PRJNA1109817 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE267132_merged_gene_count_fpkm_by_gene.tsv.gz |
7.6 Mb |
(ftp)(http) |
TSV |
SRA Run Selector |
| Raw data are available in SRA |
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