SCLC-CellMiner: A Resource for Small Cell Lung Cancer Cell Line Genomics and Pharmacology Based on Genomic Signatures.
Algorithms
Cell Line, Tumor
DNA Methylation
/ genetics
Data Mining
/ methods
Epigenesis, Genetic
/ genetics
Epigenomics
/ methods
Epithelial-Mesenchymal Transition
/ genetics
Gene Expression Regulation, Neoplastic
/ genetics
Genomics
/ methods
Humans
Lung Neoplasms
/ genetics
Pharmacological and Toxicological Phenomena
Reproducibility of Results
Small Cell Lung Carcinoma
/ genetics
Software
Transcription Factors
/ genetics
PARP
SLFN11
STING
Schlafen
genomics
immune checkpoints
mutations
native immune response
neuroendocrine tumors
replication
Journal
Cell reports
ISSN: 2211-1247
Titre abrégé: Cell Rep
Pays: United States
ID NLM: 101573691
Informations de publication
Date de publication:
20 10 2020
20 10 2020
Historique:
received:
25
02
2020
revised:
06
08
2020
accepted:
30
09
2020
entrez:
21
10
2020
pubmed:
22
10
2020
medline:
21
10
2021
Statut:
ppublish
Résumé
CellMiner-SCLC (https://discover.nci.nih.gov/SclcCellMinerCDB/) integrates drug sensitivity and genomic data, including high-resolution methylome and transcriptome from 118 patient-derived small cell lung cancer (SCLC) cell lines, providing a resource for research into this "recalcitrant cancer." We demonstrate the reproducibility and stability of data from multiple sources and validate the SCLC consensus nomenclature on the basis of expression of master transcription factors NEUROD1, ASCL1, POU2F3, and YAP1. Our analyses reveal transcription networks linking SCLC subtypes with MYC and its paralogs and the NOTCH and HIPPO pathways. SCLC subsets express specific surface markers, providing potential opportunities for antibody-based targeted therapies. YAP1-driven SCLCs are notable for differential expression of the NOTCH pathway, epithelial-mesenchymal transition (EMT), and antigen-presenting machinery (APM) genes and sensitivity to mTOR and AKT inhibitors. These analyses provide insights into SCLC biology and a framework for future investigations into subtype-specific SCLC vulnerabilities.
Identifiants
pubmed: 33086069
pii: S2211-1247(20)31285-7
doi: 10.1016/j.celrep.2020.108296
pmc: PMC7643325
mid: NIHMS1639626
pii:
doi:
Substances chimiques
Transcription Factors
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
108296Subventions
Organisme : Intramural NIH HHS
ID : ZIA BC011091
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA213274
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIC BC011622
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIC BC011499
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIC BC011509
Pays : United States
Organisme : Intramural NIH HHS
ID : Z01 BC006150
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA070907
Pays : United States
Organisme : CCR NIH HHS
ID : HHSN261200800001C
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261200800001E
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA213338
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIC BC011475
Pays : United States
Informations de copyright
Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Interests The authors declare no competing interests.
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