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pmid:33531976

Identification of novel biomarkers and candidate small-molecule drugs in cutaneous melanoma by comprehensive gene microarrays analysis.

Jilei Ma · Xin Cai · Li Kang · Songfeng Chen · Hongjian Liu

Journal of Cancer · 2021 doi:10.7150/jca.49702

Paper

complete

Experiment

complete

Data

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Analysis

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:33531976
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science-record
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sha256:c291a5a4a22236a79bb9456a4ea776607dc15241e1063aef5de114289325e86f
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created_at
2026-11-01T15:41:24Z
updated_at
2026-11-01T22:03:01Z
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paper object · 10 fields
state
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title
Identification of novel biomarkers and candidate small-molecule drugs in cutaneous melanoma by comprehensive gene microarrays analysis.
doi
10.7150/jca.49702
pmid
33531976
authors array · 5 items
[0]
Jilei Ma
[1]
Xin Cai
[2]
Li Kang
[3]
Songfeng Chen
[4]
Hongjian Liu
journal
Journal of Cancer
year
2021
abstract
Background: Melanoma is a pernicious skin cancer with high aggressiveness. This study aimed to identify potential novel biomarkers associated with the prognosis and pathogenesis of cutaneous melanoma and to explore new targeted drugs for melanoma. Methods: Two Gene Expression Omnibus (GEO) microarray datasets, GSE3189 and GSE7553 were combined to analyze the differentially expressed genes (DEGs). To better understand the DEGs in the melanoma pathogenesis, we performed gene enrichment analyses and established a protein-protein interaction network (PPI). The survival analyses for key genes were conducted based on the GEPIA platform. Finally, we mined the CMap database to explore potential small-molecule drugs to target the obtained DEGs. Results: In short, we identified 500 DEGs between cutaneous melanoma samples and normal samples. The PPI network was established with 349 nodes and 1251 edges. Signaling pathway analysis showed that these genes play a vital role in ECM-receptor interactions, the PPAR signaling pathway and pathways in cancer. Eight DEGs with a relatively high degree of connectivity (CDC45, CENPF, DTL, FANCI, GINS2, HJURP, TPX2 and TRIP13) were selected as hub-genes that remarkably correlated to a poor survival rate. Based on 500 DEGs, 20 small-molecule drugs that potentially target genes with abnormal expression in cutaneous melanoma were obtained from the CMap database. Among these compounds, we found that menadione has the greatest therapeutic value for melanoma. Conclusions: In conclusion, we identified the 8 candidate biomarkers and potential key signaling pathways in cutaneous melanoma through comprehensive microarray analyses. The identified candidate drugs have provided several directive significances for the synthesis medicine for melanoma.
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GSE3189 was based on platform GPL96 and included 52 samples, containing 45 tumor samples and 7 normal samples.
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sections[3] "Gene Microarray Data" paragraph 2
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GSE3189 was based on platform GPL96 and included 52 samples, containing 45 tumor samples and 7 normal samples.
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title
Novel genes associated with malignant melanoma but not benign melanocytic lesions
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title
Gene Expression Patterns Involved in the Malignant Transformation and Progression of Metastatic Melanoma
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Clinical properties of cutaneous melanoma patients
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Gene Microarray Data
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Table 1
caption
Clinical properties of cutaneous melanoma patients
rows array · 5 items
[0] array · 10 items
[0]
[1]
GEO ID
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[3]
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[4]
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[7]
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[8]
adjuvant chemotherapy
[9]
Stage(I/II/III/IV)
[1] array · 10 items
[0]
Melanoma Samples
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GSE3189
[2]
GPL96
[3]
45
[4]
39
[5]
66.63± 15.78
[6]
21/24
[7]
12/33
[8]
45
[9]
2/7/14/22
[2] array · 9 items
[0]
GSE7553
[1]
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[2]
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[3]
47
[4]
72.03 ± 26.37
[5]
35/19
[6]
6/48
[7]
54
[8]
0/2/14/38
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7
[4]
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[5]
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[6]
3/4
[7]
NA
[8]
NA
[9]
NA
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[0]
GSE7553
[1]
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[3]
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62.35 ± 16.50
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[6]
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[7]
NA
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NA
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Functional and pathway enrichment analysis of the overlap DEGs
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10
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Enrichment analyses
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Table 2
caption
Functional and pathway enrichment analysis of the overlap DEGs
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[1]
Term
[2]
P value
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7.23E-11
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3.99E-08
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2.35E-05
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1.14E-04
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GO:0005200~structural constituent of cytoskeleton
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3.01E-04
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0.001161
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0.003447
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List of the 20 most significant small molecule drugs that can reverse the tumoral status of melanoma.
structure object · 5 fields
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PMC7847648
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13
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Potential small-molecule drugs identification
row_count
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Table 3
caption
List of the 20 most significant small molecule drugs that can reverse the tumoral status of melanoma.
rows array · 21 items
[0] array · 3 items
[0]
Cmap name
[1]
Enrichment score
[2]
P value
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[0]
menadione
[1]
-0.954
[2]
0.00453
[2] array · 3 items
[0]
1,4-chrysenequinone
[1]
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[2]
0.00545
[3] array · 3 items
[0]
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[1]
-0.938
[2]
0.00799
[4] array · 3 items
[0]
piperlongumine
[1]
-0.856
[2]
0.04151
[5] array · 3 items
[0]
difenidol
[1]
-0.845
[2]
0.00747
[6] array · 3 items
[0]
Y-27632
[1]
-0.835
[2]
0.05432
[7] array · 3 items
[0]
imipenem
[1]
-0.814
[2]
0.00219
[8] array · 3 items
[0]
quinostatin
[1]
-0.8
[2]
0.07859
[9] array · 3 items
[0]
etomidate
[1]
-0.784
[2]
0.02063
[10] array · 3 items
[0]
bezafibrate
[1]
-0.76
[2]
0.00684
[11] array · 3 items
[0]
flunarizine
[1]
-0.751
[2]
0.00774
[12] array · 3 items
[0]
omeprazole
[1]
-0.748
[2]
0.00808
[13] array · 3 items
[0]
camptothecin
[1]
-0.747
[2]
0.03295
[14] array · 3 items
[0]
5248896
[1]
-0.745
[2]
0.12913
[15] array · 3 items
[0]
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[1]
-0.743
[2]
0.03463
[16] array · 3 items
[0]
alsterpaullone
[1]
-0.74
[2]
0.03591
[17] array · 3 items
[0]
medrysone
[1]
-0.738
[2]
0.00066
[18] array · 3 items
[0]
apigenin
[1]
-0.735
[2]
0.00985
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[0]
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[1]
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[2]
0.13957
[20] array · 3 items
[0]
dequalinium chloride
[1]
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[2]
0.01104
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asset:data:geo:GSE3189 licence not read
[2]
asset:data:geo:GSE7553 not downloaded
[3]
asset:data:geo:GSE7553 licence not read
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protein-protein interaction
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pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
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evidence object · 3 fields
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0.8
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high
quote
pathway enrichment
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complete
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capability_id
capability:computational_analysis
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assay_families array · 9 items
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[3]
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pca
[5]
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[6]
network_analysis
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gwas
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Automated Assays Laravel application and simulated adapters
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complete
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R1
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hierarchical_cluster
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: hierarchical.
capability object · 4 fields
tier
R1
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capability:computational_analysis
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owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
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[0]
GSE3189
[1]
GSE7553
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[0]
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GSE7553
statements array · 1 item
[0]
GSE3189 was based on platform GPL96 and included 52 samples, containing 45 tumor samples and 7 normal samples.
basis
The paper names GSE3189, GSE7553 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
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hierarchical_cluster
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source:pmid:33531976
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review object · 5 fields
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partial
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MiniMax-M3.1-Flash
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minimax
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minimax
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2026-10-31T18:26:39Z
independence
single_reader
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pmid:33531976
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paper
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pmid:33531976
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source:pmid:33531976
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manuscript
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PMID 33531976 full text
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dataset
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GEO GSE3189
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paper
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pmid:33531976
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PMID 33531976 full text
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data:geo:GSE3189
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dataset
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GEO GSE3189
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agent:corpus-assay-engine
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agent:minimax-reader
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agent:minimax-reader
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. Methods: Two Gene Expression Omnibus (GEO) microarray datasets, GSE3189 and GSE7553 were combined
[1]
in cutaneous melanoma through comprehensive microarray analyses. The identified candidate drugs hav
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paper_text_order:382
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33531976", "kind": "science-record", "revision": 8, "content_hash": "sha256:c291a5a4a22236a79bb9456a4ea776607dc15241e1063aef5de114289325e86f", "created_at": "2026-11-01T15:41:24Z", "updated_at": "2026-11-01T22:03:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of novel biomarkers and candidate small-molecule drugs in cutaneous melanoma by comprehensive gene microarrays analysis.", "doi": "10.7150/jca.49702", "pmid": "33531976", "authors": ["Jilei Ma", "Xin Cai", "Li Kang", "Songfeng Chen", "Hongjian Liu"], "journal": "Journal of Cancer", "year": 2021, "abstract": "Background: Melanoma is a pernicious skin cancer with high aggressiveness. This study aimed to identify potential novel biomarkers associated with the prognosis and pathogenesis of cutaneous melanoma and to explore new targeted drugs for melanoma. Methods: Two Gene Expression Omnibus (GEO) microarray datasets, GSE3189 and GSE7553 were combined to analyze the differentially expressed genes (DEGs). To better understand the DEGs in the melanoma pathogenesis, we performed gene enrichment analyses and established a protein-protein interaction network (PPI). The survival analyses for key genes were conducted based on the GEPIA platform. Finally, we mined the CMap database to explore potential small-molecule drugs to target the obtained DEGs. Results: In short, we identified 500 DEGs between cutaneous melanoma samples and normal samples. The PPI network was established with 349 nodes and 1251 edges. Signaling pathway analysis showed that these genes play a vital role in ECM-receptor interactions, the PPAR signaling pathway and pathways in cancer. Eight DEGs with a relatively high degree of connectivity (CDC45, CENPF, DTL, FANCI, GINS2, HJURP, TPX2 and TRIP13) were selected as hub-genes that remarkably correlated to a poor survival rate. Based on 500 DEGs, 20 small-molecule drugs that potentially target genes with abnormal expression in cutaneous melanoma were obtained from the CMap database. Among these compounds, we found that menadione has the greatest therapeutic value for melanoma. Conclusions: In conclusion, we identified the 8 candidate biomarkers and potential key signaling pathways in cutaneous melanoma through comprehensive microarray analyses. The identified candidate drugs have provided several directive significances for the synthesis medicine for melanoma.", "claims": [{"id": "claim-data-access", "statement": "GSE3189 was based on platform GPL96 and included 52 samples, containing 45 tumor samples and 7 normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33531976", "locator": "sections[3] \"Gene Microarray Data\" paragraph 2", "quote": "GSE3189 was based on platform GPL96 and included 52 samples, containing 45 tumor samples and 7 normal samples."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33531976"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE3189"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE3189"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33531976", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7150/jca.49702", "sha256": 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